HIGHER EDUCATION: Handbook of Theory and Research Volume XIX
Associate Editors William G. Tierney, University of Southern California (senior associate editor) Philip G. Altbach, Boston College (comparative and international) Alan E. Bayer, Virginia Polytechnic Institute and State University (faculty) Eric L. Dey, University of Michigan (students) David D. Dill, University of North Carolina at Chapel Hill (governance and planning) Corinna A. Ethington, The University of Memphis (research methodology) Carol E. Floyd, Education consultant (systems and organization) Yvonna S. Lincoln, Texas A&M University (social context) Michael B. Paulsen, University of New Orleans (finance and economics) Raymond P. Perry, University of Manitoba (curriculum and instruction)
HIGHER EDUCATION: Handbook of Theory and Research Volume XIX
Edited by
John C. Smart University of Memphis
Published under the sponsorship of The Association for Institutional Research (AIR) and The Association for the Study of Higher Education (ASHE)
KLUWER ACADEMIC PUBLISHERS NEW YORK, BOSTON, DORDRECHT, LONDON, MOSCOW
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TABLE OF CONTENTS
CONTRIBUTORS
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1. SERVICE THROUGH RESEARCH: MY LIFE IN HIGHER EDUCATION John A. Centra Syracuse University 2. THE OPPORTUNITY AGENDA: A REEXAMINATION OF POSTSECONDARY REWARD AND OPPORTUNITY Scott L. Thomas and Laura W. Perna University of Georgia and University of Maryland 3. A CULTURAL ANALYSIS OF SHARED GOVERNANCE: THE CHALLENGES AHEAD William G. Tierney University of Southern California 4. STATEWIDE COMMUNITY COLLEGE GOVERNANCE STRUCTURES: FACTORS THAT INFLUENCE AND ISSUES THAT TEST EFFECTIVENESS Cheryl D. Lovell and Catherine Trouth University of Denver 5. COMPUTING AND INTERPRETING EFFECT SIZES Crystal Reneé Hill and Bruce Thompson Texas A&M University 6. FOLLOW THE MONEY: THE CHANGING WORLD OF BUDGETING IN HIGHER EDUCATION William F. Lasher and Charlotte A. Sullivan The University of Texas at Austin 7. TUITION FEES IN EUROPE AND AUSTRALASIA: THEORY, TRENDS AND POLICIES Ben Jongbloed University of Twente
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TABLE OF CONTENTS 8. TOWARD MASSIFICATION: HIGHER EDUCATION DEVELOPMENT IN THE PEOPLE’S REPUBLIC OF CHINA SINCE 1949 Rui Yang Monash University 9. THEORY AND RESEARCH ON THE DEVELOPMENT OF MORAL REASONING AMONG COLLEGE STUDENTS Patricia M. King and Matthew J. Mayhew University of Michigan 10. FACULTY PROFESSIONAL DEVELOPMENT FOR THE 21ST CENTURY Christine A. Stanley Texas A&M University 11. DOCTORAL STUDENT ATTRITION AND PERSISTENCE: A META-SYNTHESIS OF RESEARCH Carolyn Richert Bair and Jennifer Grant Haworth University of Northern Iowa and Loyola University of Chicago
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CONTENTS OF PREVIOUS VOLUMES
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SUBJECT INDEX
545
AUTHOR INDEX
549
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CONTRIBUTORS
JOHN A. CENTRA is a Research Professor and Professor Emeritus at Syracuse University. He is currently directing a project to improve teaching at colleges and universities which uses an instrument he developed, The Inventory on the Scholarship of Teaching and Learning. For the past 38 years his career in higher education has included being a Research Psychologist at Educational Testing Service, and Chair of the Higher Education department at Syracuse University. His research interests have centered on how to improve the climate for learning and teaching at Colleges and universities, and related topics. The Student Instructional Report, which he developed in the early 1970s, has been used at hundreds of institutions; his books on determining faculty effectiveness have been used to help design faculty development and faculty personnel programs in higher education. He can be reached at
[email protected]. SCOTT L. THOMAS is Associate Professor of Higher Education at the Institute of Higher Education at the University of Georgia. His current research is on issues of access and stratification in higher education, with a focus on economic outcomes and indebtedness related to college quality and choice of major. His writings have examined topics in the areas of the sociology of education, labor economics, and student persistence. His work in these areas has appeared in journals including Sociology of Education, Economics of Education Review, Journal of Higher Education, and Research in Higher Education. His methodological work includes a recent book (coauthored with Ronald Heck), An Introduction to Multilevel Modeling Techniques, published by Erlbaum and Associates. LAURA W. PERNA is Assistant Professor of Higher Education in the Department of Education Policy and Leadership at the University of Maryland, College Park. Her research explores the individual and structural factors that limit the ability of women, racial/ethnic minorities, and individuals of lower socioeconomic status to realize the economic, political, and social opportunities that are associated with two aspects of higher education: access as a student and employment as a faculty member. Her research has been published as chapters in edited books, technical reports, and articles in such journals as Journal of Higher Education, Review of Higher Education, Research in Higher Education, Journal of College Student Development, and Journal of Student Financial Aid. WILLIAM G. TIERNEY is Wilbur Kieffer Professor of Higher Education and Director of the Center for Higher Education Policy Analysis at the University of Southern California. He has been President of the Academic Senate at USC, President of ASHE and Vice President of
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CONTRIBUTORS AERA. His research interests pertain to governance, faculty productivity, decision-making, organizational change, and issues of equity. He has been a Fulbright Scholar to Central America and Australia. His most recent book is Competing Conceptions of Academic Governance. He is currently at work on a book on “trust and academic work.” CHERYL D. LOVELL, Ph.D., is Associate Dean of the College of Education at the University of Denver and is Associate Professor of Higher Education. She has worked for the National Center for Higher Education Management Systems (NCHES) and at the State Higher Education Executive Officers (SHEEO). CATHERINE TROUTH is a doctoral student in higher education at the University of Denver. She has recently worked on policy projects with the Western Interstate Commission for Higher Education (WICHE) and the Education Commission of the States (ECS). BRUCE THOMPSON is Professor and Distinguished Research Scholar, Department of Educational Psychology, Texas A&M University, and Professor of Interdisciplinary Health Sciences at LSU Health Sciences Center. He is the editor of Educational and Psychological Measurement and of the series, Advances in Social Science Methodology, and past editor of two other journals. He is the author/editor of 9 books, 13 book chapters, 178 articles, 22 notes/ editorials, and 11 book reviews. His contributions have been especially influential in moving the field as regards greater emphasis on effect size reporting and interpretation, and promoting improved understanding of score reliability. CRYSTAL RENEÉ HILL graduated from Francis Marion University with a Master of Science Degree in Applied Psychology with a specialization on School Psychology. She is currently enrolled as a graduate student at Texas A&M University where she is pursuing a Ph.D. in School Psychology with specialization strands in Research Design and Child and Family. Her research interests include feeding disorders in children with developmental disabilities, behavioral analysis, children’s goal orientation, as well as achievement motivation. WILLIAM F. LASHER is Vice Provost at the University of Texas at Austin. He is also professor of educational administration and has served as the director of the UT Austin graduate program in Higher Education Administration. He teaches courses in Higher Education Economics and Finance Policy, Higher Education Legislative Issues, Higher Education Business Management, and Institutional Research and Planning. He has also served as Associate Dean of the College of Education, Associate Vice President for Budget and Institutional Studies, and Director of Institutional Studies, all at UT Austin. He is a Past President and Treasurer of the Association for Institutional Research. His work on higher education budgeting and finance has appeared in Higher Education: Handbook of Theory and Research and The Finance of Higher Education: Theory, Research, Policy and Practice by Paulsen and Smart. He holds a doctorate in higher education from the University of Michigan, a master’s degree in college student personnel from Indiana University, and a bachelor’s degree in psychology from the University of Rochester. CHARLOTTE A. SULLIVAN, Ph.D. in Higher Education Administration, is a Lecturer and Research Fellow at the University of Texas at Austin. She teachers courses in the History and Philosophy of Higher Education, and Higher Education Legislative Issues. Her research interests are in the area of educational policy. Her specific research activities have focused on the influence of political environments and leadership on state higher education systems. Previously, she has served at the Logan Wilson Fellow at the University of Texas at Austin and as a researcher for the Charles A. Dana Center, the University of Texas System and the Texas Higher Education Coordinating Board.
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CONTRIBUTORS BEN JONGBLOED holds a Master’s degree in Econometrics from the University of Groningen and a Ph.D. in Public Administration from the University of Twente. Since joining CHEPS (the Center for Higher Education Policy Studies, at the University of Twente) as a senior researcher in 1993, he has done research on a wide range of projects, mostly in the area of higher education economics. He has written extensively on topics such as funding methodologies, marketization, financial management, and per student costs. As a staff member of CHEPS he has been involved in commissioned research projects, training seminars and consultancies on the area of higher education policy and institutional management. DR. RUI YANG was an associate professor at a Chinese university before he commenced his Doctoral studies at the Comparative Education Research Centre, The University of Hong Kong in 1996. He received a Ph.D. from the University of Sydney in 2001. He has taught and researched in Guangdong, Hong Kong, New South Wales, Western Australia and Victoria. He is now a lecturer in comparative and international education at the Faculty of Education, Monash University. He has written extensively in the field of comparative higher education. His current interest is focused on globalization, internationalization and higher education reforms. His recent book Internationalisation of Higher Education in China: A Study of Guangzhou appeared with Routledge in 2002, as part of the series of East Asia: History, Politics, Sociology, Culture. PATRICIA M. KING is a Professor of Higher Education and Director of the Center for the Study of Higher and Postsecondary Education at the University of Michigan. She previously serves as Chair of the Higher Education and Student Affairs Program at Bowling Green State University, and Assistant Vice President for Student Services at Ohio State University. She is the author of numerous articles and book chapters on student learning and development, and is the coauthor (with Karen Strohm Kitchener) of Developing Reflective Judgement (1994). She was a founding editor of About Campus, and served as Executive Editor from 1995 to 2002. She has received the ACPA Contribution to Knowledge Award and NASPA’s Robert Shaffer Award. MATTHEW J. MAYHEW is a doctoral student in the Center for the Study of Higher and Postsecondary Education at the University of Michigan. His interests include research design, evaluation and assessment, and the development of moral reasoning and intercultural sensitivity in undergraduate students. CHRISTINE A. STANLEY is Associate Professor of Higher Education Administration in the Department of Educational Administration and Human Resource Development and Assistant Dean of Faculties at Texas A&M University. She is a Past President and Past Chair of the Diversity Commission of the Professional and Organizational Development (POD) Network in Higher Education. Her research areas are faculty development, multicultural faculty development, and college teaching. She is a recent co-editor of the text, Engaging Large Classes: Strategies and Techniques for College Faculty. She serves as the Senior Editor for the New Forums Press faculty development series. CAROLYN RICHERT BAIR, Ph.D., is Assistant Professor at the University of Northern Iowa in the Master of Arts in Education Program in Postsecondary Education: Student Affairs and in the Doctoral Program in Educational Leadership. She served in university administration for a number of years as a Vice President for Student Affairs and Dean of Students. Her research interests center around the experiences of graduate and professional students as well as undergraduate students in higher education. JENNIFER GRANT HAWORTH, Ph.D., is Associate Professor in the Higher Education graduate program at Loyola University Chicago. She has written extensively on the topics of
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CONTRIBUTORS doctoral and master’s education, program quality in higher education, and college students. She is currently serving as the principal investigator on a FIPSE-funded initiative on “Preparing Future Learning-Centered Community College Faculty,” and a Lilly Endowmentfunded three-year longitudinal investigation of how college students make meaning of and respond to the theme of vocation or call in their lives.
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1. SERVICE THROUGH RESEARCH: MY LIFE IN HIGHER EDUCATION John A. Centra Syracuse University
It’s odd to recall what kind of circumstances affect major decisions in our lives. In my case it was a book. Back in the early 1960s, when I was wrestling with the decision on what field of study to consider for doctoral work, I came across a copy of the newly published The American College (1962). The description of the studies completed in American higher education by Nevitt Sanford and other psychologists, sociologists, and social psychologists fascinated me. So too did the book’s plea that higher education should be a field of study in and of itself. The book and the plea helped me eventually to decide what I would do with my professional life, a life that began to expand at Michigan State University in the early 1960s and extended to Syracuse University in the 2000s. In this essay I would like to share what I consider to be important influences on my life and career, and then to provide some reflections on my own contributions to the field of higher education. Describing how and why I conducted some of my studies may, I hope, help students understand the process of doing research. Early in my graduate studies I came across a book about how sociologists work. The book was written by sociologists who described in some detail how they went about doing particular research studies. This essay follows that same approach in describing my own rationale and experiences in carrying out studies in higher education. During my 40 plus professional years my interests have shifted somewhat, although assessment and the use of assessment information to improve the climate for learning and teaching have always been at the core. My research agenda overlaps three noted researchers who preceded me in J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XIX, 1–42. ©2004 Kluwer Academic Publishers. Printed in The Netherlands.
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writing these autobiographical essays. Bob Pace was a pioneer in the study of college environments and I have tried to offer some new approaches in that area. Sandy Astin’s model for studying the impact of college on students was one that my colleagues and I applied several times, modifying it as needed. And Bill McKeachie provided a rich foundation in the evaluation and improvement of teaching that helped me identify worthwhile research directions. My own goal has always been to be pragmatic and to hope my findings would make a difference — in other words I have hoped that my research results would somehow be of service to someone in our colleges and universities. The field has changed over the past four decades, so I will offer my views on these changes. As with previous scholars in this series I will add some advice to young researchers. Perhaps this and the other essays in this series that John Smart so astutely inaugurated will have the same impact on young students that The American College had on me.
EARLY INFLUENCES: GENES AND GEOGRAPHY It seems to me that being born and raised in a small town in upstate New York had a lasting influence on me. The town was named after a Revolutionary War general, Nicholas Herkimer, who, we were taught, played a significant role in changing the course of the war at the battle of Oriskany. This view was hardly substantiated in my own readings later on in college as a history major, teaching me to question all such chauvinistic viewpoints. On the whole I cannot recall a bad teacher, but several good ones provided lasting lessons and memories. One seventh grade teacher used humor consistently in her science classes, something that made learning easy as well as enjoyable. As one example she taught the lesson that two things cannot be in the same place at the same time by sitting suddenly at one of the occupied desks, displacing a startled student onto the floor. The use of humor in teaching is certainly something I have come to value, though as research has shown, teachers can be effective in many ways; in fact, attempting humor when it may not be comfortable or natural can be counter-productive to a teacher. While small town values and personal friendships were formative, more important was a close and supportive family. My parents both emigrated from Italy at early ages, with English being their second language. Bedtime stories and help with homework were seldom options but my 2
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parents did set a good example for me with strong ethical behavior and hard work. My father seemed to be a taciturn man until I saw him talking in his native language with his friends and brothers, when he became animated and gregarious. My mother was very protective of her children, especially of me as her only son. Under her simple facade were a quick wit and a sense of fun that often caught people off guard. My father was a skilled carpenter and he settled in the town because it had one of the largest desk-making factories in the country. He worked there for 40 years, retired, and began collecting his company pension, only to find the company going bankrupt and wiping out the retirement fund. This weakness in the free enterprise system has been even more apparent in recent years, with thousands of people losing their savings when their companies folded. When I worked in the factory during summer vacations from college, he was deathly afraid that I might want to stay on. There was no fear of that — I had neither the skill nor the desire. In fact I always returned to college in the fall with a renewed desire to attend classes. In my senior year in high school I had no idea what I wanted to do. An older sister had graduated from nursing school, so my parents hoped I would go on to college. I had done well enough in high school and certainly wanted to go on but since my parents’ own education had stopped after grade school, I knew they could not advise me (nor did the high school offer much guidance). Many of my classmates did not go on to college until years later, if at all. I had thought of working a year or two to save money for a private college until I learned that I could get a BA degree from a state-supported college — the teachers college at Albany, which prepared secondary school teachers. At the time New York State was far behind most of the country in providing free higher education in a variety of fields, unless you lived in New York City where CUNY provided both choice and quality to students. Albany State turned out to be a good decision. Classes were small, much of the teaching was active and inspiring, and the majority of my classmates were motivated first generation college students who later went on to responsible positions in education (mainly), law, and medicine. My history/social studies major and math minor gave me a solid liberal arts background. I played varsity basketball each year, which undoubtedly took time from studying, but the lessons I learned in teamwork and leadership were well worth it. Later in my career, when reading about student development theories of personal, social, and academic growth during the college years, I was reminded of the in- and out-of class activities that 3
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contributed to my own development. When I returned to Albany a few years ago to receive an alumni achievement award, it was a very different institution; its Edward Durrell Stone designed buildings and towers contrasted with the brick buildings and Greek columns on the campus I attended. With 10 times as many students, it was no longer as cozy as it had been, but it now had a wide range of programs and degrees, and a growing national reputation. I joined a fraternity-like club that emphasized fellowship and service, and which was named after a college WWI hero. That service should be a major activity in life seemed like a worthy idea to me. I have remained in touch with many in the club and look forward to our reunion each year. Although the Korean War was winding down, military service was still a requirement in the mid-1950s and college graduates were not exempted. I joined the U.S. Coast Guard and was stationed in New York City for the better part of my stint. Our unit was responsible for port security, which included making sure an atomic bomb was not smuggled into the city on a ship. Ironically, that is still a concern some half a century later. Being exposed to the cultural life of the city — its plays, museums, galleries, sporting events, opera, and symphony — turned out to be a second liberal arts education. I fell in love with New York City and was doubly wounded when 9/11 happened. (There is hardly a year that my wife and I do not spend a few days enjoying the many diversions of New York City.) When my tour of duty was up, I decided to attend graduate school at Columbia University. Teachers College of Columbia had a master’s degree in personnel psychology, which appealed to me because it included measurement, psychology, and labor relations. Not knowing at that point whether I would go into industry or education, the degree seemed to offer both options. An interview with a major corporation following completion of my degree made my decision clear. I was asked what I thought the role of government should be with industry. The answer they sought left no doubt in my mind: laissez-faire. But that is not what I believed and it occurred to me at that moment that I should not start lying to myself. So instead of corporate life I entered the field of higher education, a decision I have never regretted. Joining the service right after college had a benefit I did not foresee: I received the Korean GI Bill before it expired in January 1955. It helped finance my master’s degree and later my doctoral work. My first positions following my masters work was as an admissions officer, first at Alfred University and then at Buffalo State College. I directed the office during my 4
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fifth year at Buffalo State, which at that time was the largest unit in the State University of New York system, admitting only one of every three applicants. Although I had been learning a great deal about higher education and student services, the work did not have the challenge I sought. (It was at this point that I discovered Sanford’s The American College.) I applied and was accepted at Michigan State University in their higher education/student personnel program. But before leaving Buffalo for East Lansing, I persuaded a pretty assistant professor of special education at Buffalo State to marry me. Nancy and I left Buffalo in late August with a U-Haul filled with personal belongings and wedding gifts, not knowing whether she would find a teaching position or I would be able to line up an assistantship. It was the start of a long and happy marriage, and a new career in higher education.
THE MICHIGAN STATE YEARS: INNOVATIONS IN THE MIDWEST Upon arriving at Michigan State my advisor informed me that a position had just opened up at the instructor level in the Office of Institutional Research (IR). The director, Paul Dressel, a man who was to become an important mentor in my life, offered me the position. Unlike some other IR offices at the time, and many today, the staff in the office at Michigan State conducted studies aimed at improving education at the University. Of course a couple of people worked on what was referred to as the nuts and bolts of IR — space utilization, student credit hour productivity, and the like. During my first year, while continuing with my doctoral course work, Dressel assigned me the task of studying voluntary student withdrawals from the University. The administration wanted to know why students left, what they were doing, and what their future plans were. The thought of designing a study to find answers to these questions truly excited me. Only one major study had been done at that point, at the U.S. Office of Education. Using their findings I designed a brief questionnaire that students could fill out in a couple of minutes and mail back easily. The return rate was phenomenal, about three-quarters of those contacted. Several of the findings were surprising and useful. First, about 20 percent of the population were not really dropouts but students off-campus for the semester in practice teaching or internships. While this was embarrassing to the registrar’s office, it did alleviate fears of excessive losses. Second, we found that a 5
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significant number of the students were merely taking the semester or year off and planned to return to the University. Such “stop-outs” had never been identified before. Finally, the reasons students gave for withdrawal fell into personal, social, and academic categories, which the University found useful. The findings actually fit the student withdrawal models that appeared in the literature a few years later, but because I did not have enough confidence in myself and what I had found, I failed to publish the study. I learned much later as an advisor that doctoral students are often reluctant to publish their dissertation findings, and need an extra push. Paul Dressel, who was at the time one of the most respected and published scholars of higher education, helped me to gain needed confidence by asking me to fill in for him in giving a presentation at the annual American Association for Higher Education (AAHE) conference. At that point I had been directing a study of student evaluations of teaching and he suggested that I discuss what I had been finding. Student evaluations were rarely being used by colleges at that time and the University decided to establish a program to discourage efforts by the student association to collect and publish ratings. After reviewing studies on the topic by Herman Remmers at Purdue, and by a few people at other institutions, I designed a rating form that became known as the Student Instructional Rating Report (SIRR). A unique feature of this form was that it could be machine-scored but also contained a tear-off portion that encouraged students to write comments. I shared with the 1965 AAHE conference audience what I had learned about student evaluations of teaching: that students could provide reliable and useful information not otherwise available, but there were still questions about validity. I returned to this issue after I went to Educational Testing Service (ETS). Another study I completed while on the IR staff at Michigan State was a survey of graduates of the School of Veterinary Medicine. While the major purpose was to learn something about what they were doing and their views about their program of study, the survey results provided evidence that the vast majority of women graduates, though small in number, were successfully practicing in the field, though at times with career interruptions. Prior to this, the predominant view was that the number of women admitted should be limited because the majority was professionally inactive. My very first journal publication was based on this study, titled the Women Veterinarian (1968, with Betty Guliani). At this point the women’s movement was just beginning to stir in the United States with the publication of Betty Friedan’s The Feminine Mystique. 6
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By this time I had finished my doctoral course work and comprehensive exams and was anxious to begin work on a dissertation. Paul Dressel provided me with a possibility. He shared a copy of Bob Pace’s manual for the College and University Environment Scales (CUES), which had just been published. Dressel’s view was that a modification of the scales might be useful in studying the sub-environments that exist in a large university; moreover, these sub-environments probably affected how students saw the total environment. I was quite enthusiastic about this topic so I identified each of the 10 colleges at Michigan State as separate sub-environments for my study. In addition, I realized that the residential groupings on campus were another set of sub-environments, expecting that the new “livinglearning” residence halls would be especially different. Dressel wisely advised me not to include the residences in my dissertation but rather to focus on the total university and college environments. I did indeed find very different sub-environments among the colleges though my predictions of how these units would affect student views of the university, based on assimilation theory, were not totally supported. My analysis of the residence hall environments revealed that the living-learning units contributed to a sense of community but did not enhance the scholarly climate as was intended. I gave papers at national conferences on both of these studies and published one as well. I was beginning to gain confidence as a researcher and my writing skills were improving. A non-credit graduate writing course had been especially helpful in getting me to use a more active voice in my writing. In addition, one of the other people in the office, Margaret Lorimer, used her skills as a former English teacher to advise me occasionally on my writing style. Michigan State University was an innovative and exciting place to be in the 1960s. John Hannah, the long-time president, had brought the University from a small agricultural institution (a “cow-college” as detractors said) to a member of the prestigious American Association of Universities. Change was taken for granted, and new ideas were readily given a trial. The IR office was important in gathering data and studying both old and new programs. Paul Dressel reminded me of my own father with his quiet, introspective manner; he was very supportive of me, as well as other members on his staff. As a mentor, he offered suggestions but gave me free reign to plan my projects. It was, in short, an ideal climate in which to learn and grow. The 1960s were also an opportune time to be starting out in higher education. Often referred to as the golden age of higher education, new colleges were opening weekly at the 2-year level, and experimental 4-year colleges and programs were 7
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fairly common. Students began demanding more of a voice in decisions that affected them on their campuses, including the curriculum and teaching quality. Just as students in other countries were often protesting national policies, American college students began demonstrating against the Vietnam War in the later 1960s and into the early 1970s. Major studies of student growth and development during the college years were underway, including a major longitudinal study at Michigan State directed by Dressel. Foundation and government grants were readily available for a variety of topics in higher education. It would be another decade before colleges had to tighten their belts and begin to retrench. Studying the college environment and the evaluation of teaching became areas I continued to pursue after leaving Michigan State. Upon receiving my doctorate I was offered a permanent position at the University, with a special assignment of evaluating the newly formed residential colleges. Michigan State was one of the first institutions to try to establish small colleges within the University that had a particular cross-disciplinary focus. I debated long and hard about staying on with this challenging opportunity but decided to return to the East, where our families resided. I accepted an offer as a research psychologist at ETS. My wife, 2-year old daughter Cathy, and I left East Lansing for Princeton in 1966, though I have often wondered what course my professional life would have taken had I stayed at MSU.
EDUCATIONAL TESTING SERVICE: A CAMPUS WITHOUT STUDENTS I went to the ETS thinking I would stay for 3 or 4 years and then return to a university setting. Instead, I stayed for 19 years. ETS was started in the late 1940s with the express purpose of making tests for college admissions so that selection could be based on merit rather than privilege. James Conant, Harvard’s president, was instrumental in establishing ETS along with others, especially Henry Chauncey, who became its first president. Chauncey led ETS until the late 1960s and died in 2002 at the age of 97; during his time research and service to constituents became important functions of the organization. The organization also had a family-like atmosphere, with an annual picnic and other functions. Each year it invited four or five national scholars to spend a week giving seminars on their work to the staff, helping to keep us stimulated and thinking. 8
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I was part of a higher education research group that, at various times, included Dick Peterson, Bob Linn, Rod Hartnett, Len Baird and Mary Jo Clark. With the exception of Peterson, all of us returned to universities sooner or later. Bob Linn was the statistician in the group and later became an expert on national assessment. Rod eventually went to Rutgers, Mary Jo to New Mexico Highlands, and Len to Ohio State where he became editor of the Journal of Higher Education. At the ETS western office, our colleagues were Pat Cross and Bud Warren. We have all remained friends over the years. Each of us had individual as well as collaborative projects funded by foundations, the government, or ETS programs. We often bounced ideas off each other and critiqued manuscripts in progress; it was an ideal setting that we referred to as our own Camelot. Several other groups were part of the research division including a guidance and counseling group that developed SIGI, which is a computerized interactive guidance and career-counseling program still widely used by colleges and universities. There were also some of the most renowned psychometricians and statisticians in the world (e.g., Fred Lord, Karl Joreskog), along with a large group of test developers and program directors. Developing and administering the Scholastic Aptitude Test (SAT), the Graduate Record Examination (GRE), and other tests were unquestionably the bread and butter of the organization. Located in a bucolic, campus-like setting just outside the town of Princeton, NJ, ETS was serene compared to the many turbulent college campuses at which student demonstrations and building take-overs were becoming common in the late 1960s. Dick Peterson of our group began documenting the student protest movement with surveys and campus reports. Rod Hartnett conducted an “antiestablishment” survey of college trustees that portrayed them as largely white, male and moneyed. During my years at ETS I was involved with many studies, but my two main subject areas were the evaluation and improvement of college instruction, and the college environment and its impact on students. Both built on what I had begun at Michigan State and both remained an interest even after I left ETS. My first project was a study of the utility of student ratings of teaching. These ratings were becoming increasingly used, largely for instructional improvement, but little was known as to whether they actually resulted in positive changes. The Esso (now Exxon) Foundation funded my proposal to do an experimental study that included five colleges that had never used student ratings for its faculties (Centra, 1973a,b,c). I developed 9
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a rating form that was administered at the mid-semester point in each class. On a random basis half of the teachers received their results (the feedback experimental group) and half did not (the control group). All teachers rated themselves on each item. At the end of the semester the rating form was administered again to the two groups and to a post-test only group. Over 400 teachers were studied, including a group that used the form just once a semester later. On the basis of equilibrium theory I had predicted that student ratings would produce changes in teachers who had rated themselves more favorably than their students had rated them. My regression analysis supported this prediction as well as the need for additional time to make changes, and for providing interpretations of the data for teachers. This study was important because it provided evidence that a student ratings program could help in altering teaching practices. To me it was a rare opportunity to use an experimental design in a study, which I found absolutely exhilarating. Looking through the statistical printouts for the results was like opening presents on Christmas Day. Also, for the first time I witnessed the importance of serendipity in research, that is, the good fortune to discover findings not planned for at the beginning of the study: extending the data collection to a second semester had not been part of the original proposal, but by doing so I discovered how teachers often needed more time to absorb the feedback from ratings and to make changes. It was the early 1970s and colleges were paying more attention to the quality of teaching and to their curricula, in many cases as a result of student demands. Increasingly, colleges were requesting that their faculties, particularly new faculty, collect student ratings in their courses. Rather than having each college or faculty member construct their own rating form, it seemed to me that a well-designed form backed by research could be a useful service to colleges. I thought the form I had developed for the Esso project, with some further development, could serve that purpose. While some of the ETS officers doubted the feasibility of my idea — they were, after all, familiar mainly with achievement testing — I was given a modest grant to begin the work. What followed was a rating form I named the Student Instructional Report (SIR), a variation of my Michigan State rating form title (Centra, 1972). Over the next 25 years, until I revised it in 1997, the SIR was used at hundreds of colleges and completed by millions of college students. It became quite profitable to ETS and I used some of the money they allotted to carry out a program of research on the instrument. In fact, I am sure what made the form acceptable to many college 10
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faculties were the research findings, particularly the validity study results. Another commercial form that became available to colleges shortly afterward was produced by a faculty development center at Kansas State University and given the acronym IDEA. SIR and IDEA became the most widely used student rating forms in the country over the years. The validity of student ratings was very much in question in the early 1970s. Did they have anything at all to do with teacher effectiveness or student learning? That was the question many faculty members and administrators asked. If a study could show that teachers who received high ratings also produced higher achievement scores for their students, that is, if I could show that students learned more from teachers they rated highly, then I would have strong evidence of validity. An opportunity to design that type of study arose when I heard of a university in Newfoundland where freshmen were enrolled in multiple section courses with a common final exam. I flew to St. Johns, Newfoundland’s capital, in the middle of winter and although the weather was frigid, the faculty and staff of Memorial University could not have been warmer and more cooperative. The University required all incoming students to take a common liberal arts core of five or six courses, and furthermore they assigned students to sections on a random basis. Even the questions on the final exams were unknown to those teaching the courses, so they had no opportunity to teach to the test. In short, it was an ideal experimental setting. The university agreed to administer the SIR in their classes and to provide me with the ratings and test scores; in return they received rating summaries for the classes and the results of the study. The correlations between ratings and achievement scores were generally positive, with the single global evaluation item correlating highest. I plotted the scores for 22 sections of psychology 101, in which the highest correlation was 0.63. The only sections of the course that fell off the regression line were taught by a teacher who, I learned, did not follow the syllabus faithfully, thus depriving his students of material for doing very well on the exam. Plotting the scores and finding out about the teachers involved enabled me to learn much more about the results than simply looking at the correlations (Centra, 1977). I discuss this study because it was one of the first that demonstrated the validity of student ratings with an experimental design and a criterion that faculty saw as critical; later studies replicated my findings, though few were able to control for as many extraneous variables (Cohen, 1981). Student ratings were increasingly being used in higher education through the 1980s and I believe this was for two reasons. First, colleges 11
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were searching for ways to evaluate teaching, not only to improve instruction but also to promote and award tenure to good teachers. Second, the evidence was mounting that students could provide reliable, valid, and useful information about effective teaching. Articles were regularly appearing in journals, which for the most part supported the use of the student ratings as one of several judgements about teachers. The authors of many of these articles formed a Special Interest Group (SIG) within the American Educational Research Association to meet and discuss their work at the annual conference. Among the people who were part of this SIG Faculty Evaluation and Development (SIGFED) early group and who were actively conducting research on student ratings and faculty evaluation were: Bill McKeachie, Ken Doyle, Bob Menges, Herb Marsh, Phil Abrami, Peter Cohen, Harry Murray, Ray Perry, John Ory, and Larry Braskamp. They were joined later by Mike Theall, Ken Feldman, Jennifer Franklin, and others. A count I made of articles on students’ ratings in the ERIC system in the mid-1980s indicated that over 2,000 had been published in the previous two decades, a number that has increased considerably since then. In 1979 I published Determining Faculty Effectiveness, which summarized not only what was known from research about the uses of student evaluations but also the value of colleague evaluations and self-assessments. Because personnel decisions about faculty were more frequently being challenged in the courts, I also included a chapter on legal considerations, strongly advising college officials to consult with attorneys when formulating personnel policies and when conflicts first arise. Another chapter discusses the assessment of research, advising, and public service, although it was four more years before I published a study on the relationship between research productivity and teaching effectiveness. The latter study demonstrated that there was essentially no correlation between the number of publications by faculty members and their teaching effectiveness as measured by student evaluations (Centra, 1983). This finding was confirmed by later studies, underscoring that good researchers are not necessarily good teachers, and vice versa. The accepted wisdom among many faculty members was that one could not be a good teacher without being a good researcher, a belief that is mistakenly held by a sizeable number in the profession today. The chapter in my 1979 book on self-assessments discussed whether a teacher’s self-ratings were of any value for either teaching improvement or personnel decisions. The five-college study I had conducted earlier in which I collected self-ratings from over 400 teachers helped shed light on 12
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this question. After comparing teacher self-ratings with student ratings, it was clear that most teachers had an inflated view of their effectiveness (Centra, 1973a). A poem by Robert Burns (To a Louse, 1786) summed it up thusly: Oh! wad some power the giftie gie us To see ourrsels as others see us! It was frae mony a blunder free us And foolish notion
But while their self-ratings were high in absolute terms, their relative strengths and weaknesses were in line with student views. My conclusion was that teacher self-ratings would be of little use to administrators who wanted to use them for making tenure or promotion decisions, but since teachers had some awareness of their weaknesses, their ratings could be useful to faculty developers and others. I discussed the importance of obtaining teacher self-reports or reflections on their teaching when making personnel decisions, and outlined what might be specifically included. A decade later, similar reports were called teaching portfolios, and promoted as an important new input into teacher evaluation. A study I completed at that time on the teaching portfolio indicated that for use in personnel decisions, reliable judgments needed to be made of the contents by administrators and colleagues, and the reliability varied depending on how colleagues were selected, whether work samples were included, and whether evaluators received training in procedures to be used (Centra, 1994). Among many faculties there was a strong opinion that student ratings were being emphasized too much on campuses. I offered this view in a conference paper titled “The Student as Godfather? The Impact of Student Ratings on Academia” (Centra, 1973b). After discussing the likely impact of the ratings on the various constituents in colleges, I concluded that I did not believe that they would have the type of influence of the Mario Puzo type of Godfather. Rather, I thought the evidence was that student ratings could play the more traditional and positive role of Godfather: providing guidance and direction. (The paper, later published in the Educational Researcher, produced many comments and even a few invitations to speak on campuses, illustrating the value of a catchy title.) For some faculty members and administrators the solution to giving less emphasis to student ratings was to have colleagues shoulder more of the evaluation burden. Why should they not play more of a role in helping 13
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each other improve their teaching? And why should they not take greater responsibility in judging teaching as they do for research for tenure and promotion? They should, of course, but as a study I conducted back in 1975 indicated, judgments should not be based on classroom visitations alone. Ratings colleagues made of each other’s teaching were exceedingly generous, even more so than student ratings, and they were not especially reliable (Centra, 1975). The AAHE (1995) decided to tackle the problems of colleague evaluations of teaching in the mid-1990s, and produced some very helpful materials for colleges. BACK TO STUDYING THE COLLEGE ENVIRONMENT The College Board, in addition to sponsoring the SAT, also produced the College Handbook, an annual publication with information about colleges for prospective applicants. The information consisted largely of facts and figures — enrollment, books in the library, student–faculty ratio, average SAT scores, and the like. What was needed, the Board decided, was more descriptive information about what the college was really like so that applicants could better decide whether it was the place for them. Students currently enrolled at the college would seem to be in the best position to provide those kinds of descriptions. Actually, providing college environmental information for prospective students had been a purpose of Bob Pace and George Stern’s earlier work with the College Characteristics Index. But what the Board wanted now was updated information from enrolled students, including what they did on campus as well as their perceptions of the academic and social life. I was given a grant by the College Board to develop an instrument and to collect such information. I named the instrument the Questionnaire on Student and College Characteristics (QSCC), and developed it by first interviewing enrolled college students about what they thought was important for a prospective student to know about their college. The questionnaire included students’ self-reports of their own interests and activities on campus along with how they viewed other students and the college. Over 200 colleges administered the questionnaire to samples of their juniors. We summarized the responses and returned the results to the colleges with the expectation that they would use the information to describe their environments in the next edition of the College Handbook. Few of the colleges did so and those that did only included positive statements based on questionnaire results. Probably this should not have been surprising; the colleges owned the data 14
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and they were interested largely in attracting applicants, not providing a balanced description of campus life that may have dissuaded viable applicants (Centra, 1971b). I did, however, suggest that information from the QSCC might be made available to prospective students as on-line computer data, but this idea was ahead of its time. Although the project did not fulfill its primary purpose, it did expand the methodology of assessing college environments by comparing three methods — students’ perceptions, student self-reports, and objective institutional data. I used a new statistical technique at the time, multimethod factor analysis, to examine the convergent and discriminate validity of the variables and methods. My findings indicated that there was a good deal of convergence among the different methods in assessing the college environment; for example, student perceptions of a college’s academic challenge coincided with the kinds of activities they participated in as well as a college’s selectivity and library holdings (Centra, 1972). I always suspected that student perceptions of their college environments were affected by not only internal variations (such as residence halls and students’ majors within large universities, as my dissertation indicated), but also by external factors. I found some proof for this when, in 1970, Bob Linn and I analyzed Pace’s CUES environment scales for a large number of colleges (Centra and Linn, 1970). ETS had been marketing the CUES instrument to colleges so the data were available for our analysis. Our findings suggested an external frame of reference on the Scholarship scale, on which northeastern college students downgraded the scholarly environment of their own institutions (relative to other predictors of scholarship such as SAT scores); these students seem to be comparing their colleges to the reputations of more prestigious colleges nearby. By contrast, midwestern and southern colleges had overpredicted scores on Scholarship, suggesting that their students’ frame of reference was not as limited, or at least very different from those in the northeast. Given this limitation of using student perceptions alone to measure institutional environments, including other methodologies was further justified. Bob Pace did in fact later develop a student “quality of effort” instrument that elicited students’ use of an institution’s facilities and opportunities, as well as their perceptions of general features of the environment (Pace, 1984). The QSCC and previous measures had relied primarily on students as reporters of the college environment. These views were clearly limited, excluding the many characteristics that distinguished colleges and made them vital. College faculty members and administrators, on the other 15
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hand, could provide a different and in many ways richer, description of their colleges, thereby providing better information for institutional selfstudy. With this in mind our higher education research group at ETS began a foundation-funded project to study college environments by including multiple reporters on what we came to call an institution’s vitality. It began with the question: What made a college vital? We asked this question of various experts and participants in higher education, through both discussion groups and open-ended surveys. Dick Peterson spearheaded this part of the project. We gathered some interesting perspectives, including that vital institutions are innovative, have a great deal of institutional esprit, are intellectually alive (in both teaching/learning and advancing knowledge), are democratically governed, have diverse student and faculty characteristics, and use self-study and planning to improve their effectiveness (Peterson, Centra, Hartnett, and Linn, 1970). Our next step was to list items that reflected the various dimensions of vitality. It was at this point that we realized that we needed a more neutral term than institutional vitality, and we agreed that institutional functioning would be appropriate. The resulting Institutional Functioning Inventory (IFI) consisted of 132 items yielding scores on 11 dimensions or scales. Faculty members and administrators could reply to all 132 items, while students and trustees could more appropriately reply to only half of the items. These multiple responses helped establish the validity of the scales and also made the instrument much more valuable in institutional self-study (Centra, 1971a). For example, I recall a small religiously affiliated college whose faculty IFI responses revealed very low morale and democratic governance on campus. When I pointed this out at a faculty meeting to administrators, who held opposite views, a useful discussion of why this might be true and what could done to alter the environment took place. The IFI continued to be used by hundreds of colleges in the 1970s for institutional self-study. And it was probably more useful in that respect than instruments that relied on student perceptions alone because of the dimensions it could tap and the likelihood that student views are often discounted by faculties. One caveat, however, is that faculty members are less likely to take the time to complete questionnaires unless they see an obvious use and payoff for themselves. HOW EVENTS OF THE TIMES INFLUENCED MY RESEARCH AGENDA The unrest of the 1960s led to some major changes that began to take place in the country in the 1970s. These included the women’s movement, 16
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the civil rights movement and, in higher education, a realization that student enrollments and money were becoming more limited. Each of these changes affected the particular studies I undertook in higher education at that time. Dire predictions of college enrollments for the 1980s by some agencies seemed extreme to me, so with the assistance of a College Board grant, I reviewed projections made by the National Center for Educational Statistics, the Carnegie Corporation, and various demographic scholars. After plotting these projections and considering their assumptions, including the known drop in the 18–21 age group, I concluded that a middle-ofthe road projection would be reasonable and certainly not as threatening as some had predicted (Centra, 1980). As it later turned out enrollments in the 1980s, while less dramatic than the 1960s, was not an insurmountable problem for most colleges, largely due to older students attending in greater numbers and more public aid for students. This was a totally new kind of study for me, with many uncertainties. Although it was worthwhile doing, I found that I was more comfortable studying variables I could more easily quantify and control statistically. A declining rate of growth in postsecondary education in the 1970s resulted in a decrease in faculty mobility. With fewer turnovers and less new blood, colleges could no longer depend on new staff to help keep them vital. Teaching-improvement programs and faculty-renewal efforts of various kinds became a common remedy for this steady-state condition. Little was known about the effectiveness of these efforts and so, with my second grant from the Esso foundation, I conducted a survey of the faculty development directors on each campus. About half of all postsecondary institutions appeared to have some kind of program for faculty. My findings described the activities of these programs, extending the work of Berquist and Phillips (1975) who had published the first primer for establishing faculty development programs. The respondents to my survey revealed a major shortcoming of their programs however: the faculty who really needed to improve were least likely to be involved in the development activities available to them, a serious fault that has proven difficult to remedy (Centra, 1978). This study taught me the importance of being parsimonious in producing results; that is, I reduced the lengthy list of activities, through factor analysis, to four groups that represented the major types of faculty development programs in existence at the time, a finding that was useful to colleges examining their options. The women’s movement was just beginning to pick up steam in the 1970s and pressure was mounting on graduate and professional schools to 17
HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX admit more women. The GRE Board, which oversaw the ETS development and administration of the GRE exam, decided that they needed more information about women who had attended graduate school so they funded my proposal to do a nationwide survey (Centra, 1974, 1975). The graduate deans at the universities wanted to know mainly the extent to which their women Ph.D. alumni actually used their advanced education and how they were using it. Nearly every university in the country cooperated in providing me with the names and addresses of men and women graduates in 1950, 1960, and 1968. I matched men and women by institution and field of study as well as by year of degree. Of the large sample contacted, 81 percent replied to the survey, an indication of the interest the study tapped among the Ph.D.s. I believe most graduate deans were surprised to find that only a small percentage of women had seldom made use of their graduate training and that three-quarters were employed full time (vs. 95 percent of the men). A small but significant number of women, probably 15–20 percent, were nevertheless on the periphery of the employment scene, either in a part-time or intermittent full-time capacity. The 1968 cohort was more actively involved in women’s rights and opportunities as were the older men in the sample, many of who were department chairs and full professors. The extent that women were employed, along with the evidence of their contributions in many fields, helped deans to support a more equitable basis for admissions to graduate and professional schools. In writing up this study I incorporated many of the written comments by women into the report to bring to life the quantitative information. (One disillusioned woman who thought she had sacrificed her professional career for family life said, “I was raped by the Ladies Home Journal.”) This was my first venture into any sort of qualitative methodology and I thought it made the final report much more readable yet did not misrepresent the data. While doing the study was very satisfying, I was dismayed by the comment of a woman colleague who questioned my motives, arguing that the study should have been done by a woman instead of me or, for that matter, any man. During the 4 years following Martin Luther King Jr.’s famous “I have a dream” speech in 1964 the number of African American students attending college increased by 85 percent, compared to an increase of 46 percent for all other students. Much of this long overdue increase had been at colleges that had traditionally enrolled predominantly white students. The question arose as to what kind of experience these minority students were having at these colleges, which were largely unfamiliar with their 18
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backgrounds and unprepared for them. I had an opportunity to shed light on this question in 1970 by using the data collected from the over 200 colleges that had used my Questionnaire on Student and College Characteristics. By comparing responses from black and white students from the same colleges, I was able to examine differences in their family backgrounds, future plans, involvement with various college activities, and how they viewed their college experiences. Some of the differences were not surprising: black students came from lower socioeconomic backgrounds and consequently needed to rely on scholarship and part-time work as sources of financial support. More unexpected was the extremely high proportion of black students planning to attend graduate or professional school (82 percent). As later studies confirmed, expanding minority student aspirations was not an issue, but preparing more of them for the academic work and financial aid would need to be addressed. My study also showed evidence of two cultures on the campuses, in which black and white students participated in different activities and viewed their experiences differently. Another study at the time described the climate at one college as two nations in which the two groups hardly talked to each other. These differences clearly seemed more extreme than the typical cliques that develop on most campuses, although over time it appears that more assimilation has taken place. My analysis of data collected for another purpose, while not exactly suited for addressing racial differences, still produced useful findings (Centra, 1970). STUDYING COLLEGE EFFECTS Higher education researchers have long been interested in the subject of college outcomes and differential college effects. Do some colleges have more impact on students, and if so, what characteristics of college might help explain the difference? Prior to the late 1960s, most college effects studies examined such student outcomes as attitudes, values, aspirations, assorted personality characteristics, vocational choice, and income. Ken Feldman and Ted Newcomb reviewed these studies very thoroughly in their Impact of Colleges on Students (1969). Sandy Astin conducted one of the first studies of college effects on student academic achievement. He pioneered the use of an input–output design in which freshmen SAT Verbal and Math scores at entrance to college were used as input or predictor variables, and senior GRE institutional scores in Social Science, Natural Science and Humanities, which colleges administered to all their seniors, 19
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were used as the output or performance variables. Astin concluded that such institutional resources as the ratio of library books to students, the proportion of faculty with a doctorate, and college income per student contributed little to student achievement (Astin, 1968). This finding was not only surprising but also suspect because it was based on a very limited sample. When the U.S. Office of Education asked some of us at ETS to verify Astin’s results by conducting a similar study with a larger sample, we were happy to do so. Certainly one of the advantages of being at ETS was having access to test scores that could be used in studying college effects. Of course we had to protect the identity of individuals and institutions but that was not a handicap. Our analysis indicated that college income per student and the proportion of faculty with doctorates did, to some extent, distinguish high achieving groups of colleges from low achieving groups (Rock, Centra, and Linn, 1970). Employing a larger sample plus using the college as the unit of analysis (rather than individual students) probably produced the more positive results. But while the institutional resources we identified were important for colleges, it was difficult to argue that those measures per se produced an effect on students. More likely, they are related to other features of the college environment that more directly influence student learning. A followup study we conducted identified one of those features. We found 27 colleges for which we had SAT and GRE institutional data along with environmental measures based on my QSCC. A factor analysis of the QSCC had identified a factor I named faculty–student interaction, which measured the extent that students feel that the faculty was interested in teaching and in students. Colleges with high scores on faculty–student interaction overachieved on the senior learning measures, indicating that students learn more if they feel that instructors are readily accessible, interested in teaching, and interested in students as individuals (Centra and Rock, 1971). While there were other findings, this was one of the first (if not the first) studies that demonstrated how important it was for faculty to interact with students both in and out of class. Clearly this was something that colleges could use to promote student learning. I was pleased to hear from a college dean who, after reading the study, invited me to discuss the findings with his faculty. Frequently researchers hear nothing about any impact their findings may have, at least in any direct way. My colleagues and I used test scores on several other occasions to investigate timely questions. The effectiveness of a black college education 20
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was one of these. Given the increasing enrollments of black students at predominantly white colleges in the 1960s and 1970s, critics were questioning the need for black colleges, at least those that appeared to be particularly weak in preparing students for future careers and in providing their students with a strong general education. Black college administrators countered by arguing that their students acquired more confidence and actually gained more knowledge than they would at a predominantly white college. There was of course no possibility of examining this assumption in a true experimental way, but we did have an opportunity to test it in a quasi-experimental way using the input–output design. We first identified predominantly white and black colleges with similar SAT freshmen scores. Both groups also had GRE institutional scores (senior scores in Social Science, Natural Science, and Humanities). We regressed the senior scores onto the freshman institutional averages for each of the colleges and then examined the regression lines. There was no clear superiority of either black or white colleges in learning gains. Black colleges were not doing any better than white colleges but neither were they doing any worse in their “value-added,” as some people referred to this college effect, borrowing the term from economics (Centra, Linn, and Parry, 1970). Over the years the difference between many black and white colleges has become less distinct as both have integrated their student enrollments. The question of which type of college has greater impact therefore has become mute. I do, however, recall consulting at a predominantly black college in the 1970s that would not have been in the study described above because of the poor quality of their students. Government grants for these so-called developing colleges were attempting to improve these colleges, though some critics questioned whether this could be done to any significant extent. Virtually all of the studies of college effects initially had looked at the total college as the primary unit of analysis, in spite of the fact that institutions generally represent little more than an administrative framework for a variety of separate, and often quite distinctive, divisions, departments, or other academic units. Given the importance of the department, especially in the influence it could be expected to have on student learning, it was critical to examine learning gains by departments. Rod Hartnett and I were able to do this by dipping into the extensive ETS database and again using an input–output design. Our output measures were senior scores on the advanced tests of the GRE and the major field tests that ETS made available to colleges that wanted to examine student knowledge at 21
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the department level. The GRE advanced tests were required for entrance to many graduate programs. Input measures were once again SAT V and M scores along with the students’ major field of study. We ran separate regression analysis for each of the two sets of output measures and found the results to be consistent. There were considerable differences between departments within most of the institutions, indicating that within each college there were strong and weak departments (in student learning gains). Studies of learning outcomes for total institutions have masked these important educational effects within colleges and universities (Hartnett and Centra, 1977). If the major purpose of college effects studies were to see which colleges do well in teaching general education, then using the entire institution would make sense. Otherwise, learning at the department level must be examined. When we published these findings, we received a letter from one of our idols in higher education, David Reisman. He congratulated us on our study and said that it was an important point to make. His letter meant a great deal to us because of his stature as a scholar in the field; too often colleagues in our field, as well as most other disciplines, fail to offer positive reactions to authors of studies. Many of the college impact studies we conducted at ETS were discussed in Pascarella and Terenzini’s How College Affects Students (1991). Their monumental review of research discussed questions such as what evidence is there that different colleges have a differential influence on student changes or development during college? And what evidence exists on effects of different experiences within the same institution? The data we had at ETS, especially the cognitive measures, allowed us to investigate these questions in ways that many others could not. SAT RESEARCH During my last year or so at ETS I had the opportunity to conduct a couple of studies on the SAT and to coordinate a validity review of other research on the test. The SAT, also known at various times as the Scholastic Aptitude Test and the Selective Admissions Test, was designed to be as curriculum free as possible. Unlike the ACT Achievement tests, which measure student knowledge in natural science, social science, mathematics, and English, the SAT verbal and mathematics scores are supposedly not affected by extensive academic course work. The claim that they measure aptitude for college and not high school offerings, would not put 22
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students from schools with a limited curriculum (e.g., rural schools) at a disadvantage, according to the rationale for their development. It’s unlikely, however, that any aptitude test for college would be totally curriculum free, and this was substantiated by the higher scores on the SAT that students received if they took more courses in math, languages, etc. The SAT and the ACT admissions tests do add to the prediction of first year college grades. They are not nearly as predictive as high school grades but when added to grade averages, they do bolster the prediction somewhat (Donlon, 1984). The reason is that they provide a common ruler, so to speak, to measure all students. Because high schools differ in their grading standards and quality, a 92 average from one school does not equal the same average from another school. In spite of improving prediction and in spite of the likelihood that they give students from less prestigious schools an opportunity to show their ability, admissions tests, and particularly the SAT, have been controversial. Critics have claimed that they discriminate against minority students and that test preparation courses, which are more likely to be taken by well-off students, give such students an unfair advantage. While minority students do score much lower on the SAT, the validity studies indicated that the prediction of their grades was of the same order as white students. The effect of SAT test preparation courses remains in question, although some well-designed studies have not shown sizeable gains in scores for students who take these short courses. Still, parents have been very willing to pay the fees for these courses since they may increase their child’s chances for admission to a prestigious college. Very likely students who learn test taking skills that they did not know (e.g., when to guess an answer) do improve their scores, as do students in lengthier courses aimed at reviewing relevant math formulas and skills. A few colleges, Bates being one of the first, stopped requiring the SAT for admissions, arguing that they would rather emphasize the high school record and more subjective measures. The University of California system, a onetime major user of the SAT, decided in 2002 to require the College Board Achievement tests instead. These achievement tests are based on knowledge acquired in high school courses and have been slightly better predictors of college grades than the SAT. Yet another attack on the SAT is from affirmative action proponents who would like them and other admissions tests disregarded. With all of these issues and others invariably present, it is clear that research on the utility and validity of the SAT needs to be ongoing. This research should be done by outside researchers as well as those at ETS to reduce the possibility of biased results. 23
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My two studies of the SAT investigated very different questions: Which scores should colleges use for students who take the SAT more than once (the highest, the most recent, or an average)? And how do students with various kinds of handicaps perform on the SAT and how valid were these scores? For the first study, my colleagues and I compared the validity coefficients of the different types of scores at 87 colleges. We concluded that colleges should use an average of V and M scores over the number of administrations, rather than the most recent or highest, which many colleges had been doing (Boldt, Centra and Courtney, 1986). Because students from higher income families were liklier to take the SAT more than once, they obviously had an advantage if highest scores were used by college admissions offices. Encouraging colleges to use an average instead, was therefore fairer as well as having better validity. I am not sure many colleges changed their admissions practices in view of our study even though it was made available to them as a College Board report. The second study of the SAT compared scores for handicapped students who had taken both a timed version of the test under standard conditions, as do all non-handicapped students, and an untimed version of the test. The SAT has been available in Braille, cassette, large-type, and regular type editions for students who are visually impaired, hearing impaired, physically impaired, or who have a learning disability. Most of the students who took both timed and untimed versions claimed learning disabilities, so it was this group that I studied to determine the extent examinees benefit from being given more time on the test. As might be expected, the extended time allowed learning disabled students to improve their scores on the SAT, with average gains of 30–38 points over timed administrations. The extended time obviously allowed handicapped students enough time to read and respond to many more test items than with a time limit. Increased time also produced increased scores, indicating that giving students as much time as needed reduced the effects of the examinee’s impairment. Had there not been a pattern of increasing gains, one might have concluded that examinees spent the extra time largely deliberating over questions they could not answer. A high correlation between timed and untimed students’ scores indicated that the relative standing of those students remained much the same over both conditions. These findings supported the rationale for giving handicapped students extra time on the SAT, an issue that has re-appeared in more recent years (Centra, 1986). Some people have argued that all students should have extra time on the SAT and other admission tests because students are allowed to vary 24
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their time in college in completing courses toward a degree. And then there is the argument put forth by Benjamin Bloom, Jack Carroll, and others that most students can learn just about anything if motivated and given enough time. LEAVING ETS During the 19 years I had spent at ETS the organization changed considerably, and since then it has changed even more. It had gone from a place that had many features of academe, at least in the research division, to a more corporate environment. Tenure had been used as a way of attracting researchers, but as time went on it was devalued because the officers claimed budget restrictions required more flexibility in dealing with the staff. It had always valued service to schools and colleges as part of its mission; the president who took charge as the century came to a close announced that service was not a prime purpose of the organization, profit was. That president was the first to come from the corporate ranks (Dupont); all previous ones had experience in various educational institutions. He raised additional concerns among outside critics when he began the practice of giving large bonuses to executives as incentives, explaining that the organization needed to do so to compete for staff with profitmaking corporations. As a non-profit organization, ETS receives certain tax benefits and over the years this status has been questioned by various writers. At a visit to ETS in 2003 I was surprised to see the motto, “At ETS Sales is Everybody’s Business,” prominently displayed. Indeed, ETS was no longer the organization I had once known. Still I have no regrets for the time I spent at ETS. I learned a great deal from my colleagues and various scholars invited there. In particular, my knowledge of research methodology and statistics increased far beyond graduate school training, and I was fortunate to have learned by applying methods in many different kinds of studies. Two more daughters had been added to our family, Liza and Joan, both teenagers in 1985 when I left ETS. Family life was very agreeable in our hometown of Pennington, New Jersey, a village only 4 miles from the ETS campus and a half-dozen miles from where Washington changed the course of the Revolutionary War by crossing the Delaware on Christmas Eve to surprise Hessian soldiers in Trenton. Pennington itself still had many historic homes and its schools and community activities made it an ideal place to raise children. We have life-long friends there and return at least once a year. Nancy, Cathy 25
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(then a sophomore at Dickinson College), Liza, Joan, and our golden retriever Christy, reluctantly agreed to leave and as an enticement we purchased a new contemporary house in Manlius, an up-scale suburb of Syracuse.
RETURN TO ACADEME: SYRACUSE UNIVERSITY I accepted the position of Professor and Chair of the Higher Education program at Syracuse University, an institution that had a long-established reputation for conducting studies in higher education. The University had a number of current and former faculty members who were researchers in higher education, including Bob Pace, George Stern, and Bob Diamond, who was then head of the Instructional Development office. Maurice Troyer, who had studied student values development during the college years, was once chair of the higher education program. Joan Stark had also been chair before leaving for the University of Michigan. When I arrived in 1985, the faculty consisted of Jack Honey, Sid Micek, and Jim Collins. Jack taught public policy in higher education but his interests were multidisciplinary, as evidenced by a book he later published on science, values, and the citizen. He drew on sociobiology, behavioral psychology, and anthropology in discussing how knowledge from science is the most reliable way to adapt to our environment (Honey, 1996). Sid left the program a year after I arrived to take a position in the University’s development office. Jim taught the student affairs sequence. A few years later we recruited John Braxton to join our faculty. John turned out to be an outstanding teacher and researcher in higher education. His interests in studying teaching and faculty issues overlapped my own somewhat, making him an excellent colleague. We were all sorry to see him leave but he had very good opportunity to chair the higher education program at Vanderbilt. The dean who interviewed me for the Syracuse University position was Burton Blatt, a man who was highly respected in his field of special education as well as by the faculty at the University. He impressed me with his questions and comments about studies I had conducted, and made assurances to me if I decided to accept an offer to join the faculty. Unfortunately he passed away after I accepted the position and before I arrived. His premature death was a setback for the School of Education but his assurances to me (e.g., tenure) did not turn out to be a problem. 26
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My experience at ETS proved to be an excellent background for teaching higher education courses and directing student dissertations. The various studies I had conducted and the knowledge of research design and statistics allowed me to include specific examples in teaching the doctoral research seminar, as well as a course we titled “Research on College Students,” and one on evaluation in higher education. While at ETS, I had also taught briefly as an adjunct in New York University’s Higher Education program. Although there were only three faculty members in the higher education program at Syracuse University, other faculty members taught courses that complemented our program; they also played important roles as dissertation members or readers. Among these were Joan Burstyn, a historian who taught the history of American higher education, Arthur Blumberg who taught K-12 administration and supervision courses, Philip Doughty who taught instructional design, Vince Tinto who studied student retention issues, and Alan Goldberg who taught counseling courses. Our program allowed students to have certain concentrations, such as evaluation and institutional research, teaching, administration, and student affairs. At its apex, the program enrolled 85 full- and part-time students, evenly split between masters and doctoral candidates. Some of the doctoral students were graduate assistants in our department who played critical roles in teaching selected courses and helping to conduct research. Most notable were Mardy Eimers, who went to the University of Missouri in their institutional research office, Sister Mary Salvaterra, later a Marymount University professor, Carol Van Der Karr, who went on to SUNY Cortland as head of the academic advising program, Ben Baez, later a professor of higher education at Georgia State University, and Noreen Gaubatz, who remained at SU as part of the Center for the Support of Teaching and Learning. Other doctoral students completed the program while retaining their full-time jobs and taking leaves to complete their residency. Several of these people wrote outstanding dissertations related to their positions, among them: Jim Boyle on alumni giving, George Miller on freshman student retention, and Mary McMann on women faculty. I found working with these and other doctoral students to be both stimulating and personally rewarding, something I had not anticipated. Another pleasant surprise was the freedom I had to pursue any line of research or writing I desired; no longer did I need funding and a “project job” to account for my time. There were other benefits in going Syracuse. Both of my younger daughters later took advantage of a tuition exchange or a remitted tuition 27
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program of the University that allowed them to attend college tuition-free, no small benefit given rising college costs. My wife Nancy was accepted to the doctoral program in Special Education Administration at the University, allowing her to resume a goal she had abandoned when we were married. She had received her master’s degree from SU and was later offered a fellowship to complete her doctorate, which she turned down to marry me and go to Michigan in 1963. Nancy’s dissertation topic turned out to be a qualitative study of a high school resource complex for special education students. The University had several faculty members who were expert in qualitative research and her dissertation chair had co-authored a widely used book on the topic (Bogdan and Biklen, 1982). I knew next to nothing about qualitative methodology at the time and I joked that I learned about it by sleeping with a qualitative researcher. Although most of my doctoral students used quantitative methods, my forte, eventually some used a qualitative approach and I came to recognize and respect good research that relied on interviews, case studies, and similar methods. Given my long-time interest in the evaluation and improvement of college teaching, I was asked, shortly after my arrival, to help put together a manual for the Syracuse University faculty and department chairs. The resulting monograph, A Guide to Evaluating Teaching for Promotion and Tenure, which I wrote with colleagues at the University, was published by the University and later made available through an outside publisher (Centra, Froh, Gray, Lambert and Diamond, 1987). We first identified characteristics of effective teaching and then suggested what techniques could be used to evaluate each one. Drawing on previous studies, we identified six characteristics: ● ● ● ● ● ●
good organization of subject matter and course, effective communication, knowledge of and enthusiasm for the subject and teaching, positive attitudes toward students, fairness in examinations and grading, flexibility in approaches to teaching.
We added a seventh characteristic that focused on the goal of effective teaching: Appropriate student learning outcomes. We thought this was probably the most important characteristic and proposed a definition stating that “effective teaching produces beneficial and purposeful student learning through the use of appropriate procedures.” We provided examples of how student learning and teaching might be assessed in order to 28
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make the monograph as user friendly as possible. While the monograph was used by some departments and colleges, we were disappointed that it had not been more widely adopted. At the time research productivity was the major if not the sole criteria for promotion or tenure at Syracuse University, as it was at most research universities. A few years later a new Chancellor, Kenneth Shaw, put emphasis on teaching effectiveness by proclaiming that Syracuse would become a “student-centered research university.” Naturally this phrase led to much discussion about what it meant, but there was increasing interest among the faculty in discussing and attending seminars on teaching. A new training program for teaching assistants was started and some departments established mentoring programs for new faculty members. A new office of undergraduate studies was established and the existing Center for Instructional Development (later the Center for the Support of Teaching and Learning) acquired additional responsibility. Eventually a better balance seemed to be established between research and teaching, with some faculty members being promoted, who were excellent teachers and only adequate researchers. Given my interest in studying teaching and how best to evaluate/improve it, the University became an ideal environment for me. An important advantage in being at a college or university is having the opportunity to take a sabbatical. I used a sabbatical semester in 1991 to write my second book on teaching and faculty evaluation, Reflective Faculty Evaluation, subtitled, Enhancing Teaching and Determining Faculty Effectiveness (1993). Given the vast amount of research during the previous decade on the evaluation and improvement of teaching, I thought it was necessary to update my 1979 book and to add my new thinking about college teaching. One of the questions I addressed was how and when does evaluation lead to the improvement of teaching. Based on the research evidence and my own observations, it seemed to me that truly significant improvement is likely to take place only if four conditions are fulfilled. The four conditions are first, that teachers must learn something new about their teaching performance through the evaluation (New knowledge). Second, they must value the information, which generally means they must have confidence in the source and in the evaluation process (Value). Third, teachers must understand how to make the changes called for (How to change). And finally, teachers must be motivated to make the changes (Motivation), either through extrinsic rewards or intrinsic satisfactions. The resulting acronym, NVHM, was not especially catchy but it did constitute a model for understanding when formative evaluation has maximum effect. 29
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For example, student evaluations are most effective when a teacher learns something useful from students, puts value in what they say, and knows how to make necessary changes. My study in 1973 on the effectiveness of student ratings in improving instruction, along with other studies, had supported several of the conditions in the model. Another feature of the book that I thought was especially useful was a chapter on guidelines for the proper use of student evaluations, which was based on research evidence (e.g., how many students are needed for a reliable course rating). The remainder of the book included chapters on how other sources of information (colleagues, teaching portfolios) may or may not fulfill conditions in the model. I thought the model was a useful way to look at formative evaluation of teaching, both for understanding how change takes place and in pointing to what additional studies were still needed (e.g., people seem to put more faith in the use of the portfolio than any studies had yet supported). In the book I also gave a brief history of teaching methodologies, pointing out that the lecture method is almost as dominant today in college teaching as it was during medieval times. While the lecture has its place, more active learning methods (e.g., collaborative learning, problemsolving, field experience) should be used if students are to attain higher levels of learning. I have often used the ancient Chinese proverb to illustrate the need for active learning: I hear and I forget I see and I remember I do and I understand
It seems to me that a teaching evaluation system should not encourage teachers to use only didactic teaching methods. How actively involved students were in learning and the level of student learning must also be emphasized. Unfortunately many evaluation forms and evaluators still focus on traditional methods of teaching. It is a matter of the proverbial tail wagging the dog: evaluation methods have dictated teaching methods. Studies of active learning and its potential benefits are definitely needed. One of my doctoral students, Brad Beran, and I designed a study to compare learning in straight lecture courses to learning in courses taught with more active learning techniques. The same course material was taught in each case. Brad videotaped the various courses and then wrote exam questions to test student knowledge of material during the class period (the test was administered unannounced at the next class session). 30
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We discovered a consistent decrease in retention of information in the lecture classes after the first 15 min or so. The same decrease did not occur in classes where active learning was used. We concluded that students’ attention spans begin to wane after about 15 min or so in the typical lecture (the time probably depends on the quality of the lecture), and that teachers needed to vary their presentations to take this into account or use active learning techniques throughout the class period. The study eventually became Brad’s dissertation. While a few other studies, using different designs, came to a similar conclusion, this line of research still needs further exploration. Pat Cross (1990) has encouraged faculty members to conduct “classroom research” as a practical alternative to traditional educational research; teachers who carry out classroom research are less concerned with statistical significance or detailed analysis than with reaching a better understanding of how students learn in their courses.
DEVELOPING SIR II In the mid-1990s ETS program directors contacted me to see if I was interested in updating the SIR, the student rating instrument that they had been selling to colleges since 1972. When I had developed it I thought it should be revised periodically as more became known about teaching and about students as evaluators. In the almost 25 years, much indeed had been learned. For one, emphasis had shifted to what students had learned and what contribution the teacher made to that learning. Secondly, the student’s role in learning was recognized as critical — their effort, their time on the task, and the like. And third, teachers were beginning to complement lecturing with some active learning approaches. All of these needed to be taken into account in a second generation SIR. In developing the new form, later called SIR II, I tried out new items that dealt with the three areas mentioned above. Fifty classes in 10 colleges provided responses to two experimental forms, each with a different response scale for students. One response format was a five point agree/disagree option, with a mid-point of neither agree or disagree. The second response format also used a five-point scale but without a neutral point. It ranged from “very effective” to “ineffective” in relation to instructional practices. Half of the students in each of the 50 classes, determined randomly, responded to each form. The analyses, which included traditional statistics and a Rasch Analysis, informed me of which items worked best 31
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and which needed some modifications. I had never used a Rasch Analysis before but found that it was especially helpful in examining response categories. In particular, it indicated that the effectiveness scale was the better scale, and that a neutral point on the agree/disagree scale was confusing to interpret. A neutral point is fairly common in rating scales, including student ratings, and I have never seen research results that questioned its use. The quasi-experimental nature of my data (two forms with the same items randomly responded to) was unusual and allowed a comparison of the two response scales, something that most studies have not been able to do (Centra, 1998). The final SIR II form emphasizes student learning in two ways. Students are asked to rate each practice as it contributed to their learning in the course, and a five-item scale measures course outcomes. Students also rate their effort and involvement in the course and can reply to various supplementary instructional active learning methods (e.g., assigned projects in which students work together). Perhaps because of these changes, SIR II has been widely adopted by many colleges since its development. SIR II has been made available through the higher education assessment program of ETS, whose program directors assured me that I could carry out a continuing series of studies with the instrument. The hundreds of colleges that have been using the instrument and the thousands of student responses over the years have allowed me to complete studies with a large database. Faculty members rightfully want to know about the validity and reliability of any rating form they use. Two studies I completed with the large SIR II data base provided answers to questions that are frequently asked about the validity of student ratings: Is there gender bias? And can instructors influence their ratings by giving higher grades and less coursework? Both of these studies are worth summarizing here because the results apply to student ratings generally as well as to the SIR II, and because of the methodology used. I examined the question of gender bias in ratings with Noreen Gaubatz, who used her collaboration in the study to satisfy the research apprenticeship requirement of her doctoral program. We looked at over 700 classes to compare how male and female students rated the same female and male instructors. Previous studies had been inconsistent or inconclusive, most likely due to shortcomings in their design. Our MANOVA results of mean differences, which took into account academic disciplines as well as interactions among the variables, indicated some gender preferences, particularly in female students rating women teachers. But by also 32
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considering effect size, we concluded that the differences in ratings were not large enough to have much significance in personnel decisions (Centra and Gaubatz, 2000). By working on the study, Noreen learned about the use of MANOVA, which she applied in her dissertation study, and the importance of including effect size in interpreting results. Many faculty members believe they can improve their student ratings by giving students higher grades than they deserve. Many others believe that they can also receive higher ratings if they give less work to students. Research results may never be able to absolutely change these teachers’ minds, especially since there are some studies that support their beliefs. More of the findings, however, do not, including one I completed with over 50,000 courses in which the SIR II had been used (Centra, 2003). The large number of courses allowed me to take subject area into account and to control for such factors as class size, teaching method, and most importantly, student reports of their own learning in the course. A measure of student learning was important because of the definition of bias that has been widely accepted and was used in this study: Bias exists when a student, teacher, or course characteristic affects the evaluations made but is unrelated to any criteria of good teaching, such as increased student learning. After controlling for student-reported learning, the grades student expected to receive did not affect the evaluations they made. (Expected grade was the appropriate measure because students do not generally know their actual grade in a course when they complete an evaluation form, usually several days before the last class.) Moreover, courses rated just right in difficulty or workload received the highest ratings, while courses rated either too difficult or too elementary were rated lower. Courses taught at what students considered the right level of difficulty or workload received the highest ratings. These findings clearly indicated that teachers were not likely to improve their student evaluations by giving higher grades or less course work. While multiple regression was the main analysis used, the results became much clearer when I plotted the predicted evaluation values on bar graphs, with expected grade and difficulty/workload as predictors. It was one of three or four studies I have done where plotting the results was especially helpful in interpretations. In spite of what I consider convincing results, because I did not have an objective measure of student learning, such as final test results, some readers will probably question the results. But having such a measure for a large number of courses, along with the other variables that need to be considered, would be difficult if not 33
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impossible, to collect. I suppose this illustrates how most research has limitations, especially field studies in education, so all we can do is to design the best study possible under the circumstances.
CHANGING PACE In 1998 Syracuse University offered what it called a supported resignation program to its faculty members. Tenured faculty who had spent at least 10 years at the University could receive 2 years salary for resigning their position. At the time I had planned to teach and chair the program two or three more years. After much soul-searching I decided to accept the University’s offer; I was ready to start something new. I certainly was not ready to “do nothing,” as I said to my students and colleagues. My doctoral students were anxious that I might abandon them before they finished their dissertations, but I continued to advise those who had acceptable proposals; some seven or eight completed their programs over the next few years. I was given an office at the University that I still have as of this time. Vince Tinto left the Cultural Foundations of Education department at Syracuse University to take my place as chair of the Higher Education program, with Cathy Engstrom as coordinator of the student affairs sequence. The program began to focus on the study of students and student affairs administration. My title of Research Professor/ Professor Emeritus has allowed me to be eligible for funding with University sponsorship. Having more flexibility I decided to accept an offer to give a week of seminars at the Chinese University of Hong Kong. From Hong Kong I went on to Australia and New Zealand for 2 months where I continued to give seminars and talks on the evaluation and improvement of college teaching. My wife Nancy and I have always enjoyed traveling and seeing different cultures so we made sure we had plenty of time to explore all three areas. I have been fortunate to teach or attend international conferences in many countries over the years. This included a summer of teaching in The Netherlands, another in Indonesia, and conferences in Europe, Asia, and Algeria (where I was the lone American among representatives from most other countries in the world, a strange experience). While American higher education was initially built on models from England, Germany, and elsewhere, there is little question that our system has since become the envy of the world. The diversity of colleges and programs, the access we 34
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have provided to all types of students, and the excellence in teaching and research are, in my opinion, major reasons the United States has surpassed other countries in the world economically and socially. During the 1998–99 year I also taught for a semester at the State University of Buffalo, where Bruce Johnstone, formerly the Chancellor of SUNY, directed the higher education program. Like Syracuse, Buffalo’s program included many students with full-time administrative or teaching positions. I taught a course that included elements of both my evaluation and my research seminar, but my main objective was to help the dozen or so students identify or develop their dissertations. As it was with my own students, I found this to be a most challenging and satisfying experience. ASSESSING THE SCHOLARSHIP OF TEACHING Ernest Boyer (1990) introduced the phase “scholarship of teaching” in 1990 with his influential monograph, Scholarship Reconsidered (1990). In an effort to elevate the importance of teaching in academe, he identified it as one of four kinds of scholarship, the other three dealing with research functions. As an ex-U.S. Commissioner of Education and head of the Carnegie Commission, he had enough clout to underscore his message that good teaching was serious intellectual work that should be rewarded on a par with other kinds of scholarship. Boyer had only broadly described what he meant by the scholarship of teaching, so others, such as Gene Rice and Lee Shulman, expanded on what should be included. The timing could not have been better, with the 1990s being a time when research universities as well as other institutions began to re-examine their quality of teaching and the promotion criteria they used. Conversations and seminars on the scholarship of teaching took place throughout the decade at national conferences and numerous campuses. Quite likely these discussions led some institutions to alter their promotion policies. My own feeling, however, was that more could be done to build on the framework of the scholarship of teaching to improve college teaching. I thought that finding a way to define and assess it could bring about more change than simply discussing it. After reviewing the various articles and statements describing it, I concluded that the scholarship of teaching had three major emphases: making teaching public, focusing on teaching practices and learning outcomes, and having content and pedagogical knowledge. Moreover, while people had thought about the scholarship of teaching as something that was practiced by individual 35
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teachers, it seemed to me that it should also be supported by departments and other levels of an institution. The scholarship of teaching, therefore, should logically be a goal at both the individual and institutional levels. When I presented these ideas at one of the AAHE conferences there seemed to be a great deal of interest in the approach (Centra, 2001). Syracuse University, through the Office of Undergraduate Studies, decided that my proposal to develop a faculty inventory was worth supporting for use with the faculty at the University. The resulting instrument was based on not only the scholarship of teaching literature but also research on effective teaching and learning practices. It took about a year to pre-test and select 117 items. Titled the “Inventory on the Scholarship of Teaching and Learning,” the items reflected possible policies and practices of each department, each college, and the University as a whole. A final part asked faculty members about their own teaching practices. We met with each of the 10 college deans to enlist their cooperation, resulting in about half of the faculty members responding to the inventory during the fall 2002 semester. With college faculty, that level of participation is probably as good as could be expected. Analysis revealed some major differences among the colleges and departments in their support of teaching and learning practices, though all gave priority to several practices (e.g., emphasizing good teaching potential when hiring new faculty). While the faculty saw the University supporting faculty development programs and promoting good teaching in other ways, the annual awards for good teaching were little known or not valued. Most Syracuse University faculty viewed their own teaching as reflecting some of the concepts in the scholarship of teaching, such as relating concepts in their courses to real life, helping students make connections between prior learning and new knowledge, and using active learning. But on the whole, faculty members were less likely to endorse ways to make their teaching public, such as by inviting colleagues to their classes or sharing their syllabi with colleagues. This may well be a finding typical of most faculty members; they are much more willing to make their research public than their teaching. Each college and department was provided with an analysis and interpretation of the combined results. They also received their individual summaries, which were based only on their own faculty members. As of this writing it is too early to tell what kind of changes will take place in college or university policies and with faculty teaching practices. 36
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A follow-up “case study” will tell us more about how the inventory results can best be used. We also hope that more institutions will find the inventory appropriate for improving teaching and learning. In my opinion the scholarship of teaching concept in itself is limiting, but by adding to it what research has informed us about effective teaching and learning practices, the inventory is likely to be more useful in suggesting how institutions can be more supportive of teaching and what individual teachers can do to improve.
SOME FINAL THOUGHTS AND SUGGESTIONS I cannot think of a better life I might have had. I have thoroughly enjoyed every position I have held and my family has given me great satisfaction. Naturally there have been roadblocks and disappointments, as in most peoples’ lives, but I have always tried to move on in spite of them. I recall a student who was devastated when she lost a promising administrative position for no good reason. My advice to her was to see it as an opportunity to concentrate on doctoral study, which she did. She became an excellent researcher and teacher, something she had not planned on, and is today very happy and successful in her new career. For me ETS had been an ideal place, but when it changed I took the opportunity to return to a university where I found even greater personal satisfaction. And still do. Family has always been important to me. Nancy could not have been more supportive and because she is an educator herself, she has also been a colleague. My three daughters, two sons-in-law, and three grandchildren (currently) make holidays and vacations priceless times. My daughters still talk about the year we spent in California, our travels around the country, and our Christmas in Spain. One of them has become an assessment expert in her own right, though in public health, not higher education. I was fortunate to be starting my career at a time when higher education became a field of study. The topics I chose to investigate were in part both personal interest and circumstance. Critical questions at a particular time dictated funding possibilities and what I thought would be worth investigating. Future researchers will need to become aware of what the current issues may be and what their interests are. Following are a few final comments on research and teaching. 37
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ON RESEARCH Although I have been a quantitative researcher my entire career, I recognize the value of a qualitative approach. And while it’s certainly possible to do poorly with each, I think the frequent lack of validity data makes good qualitative research more rare. Perhaps this is my bias, but I have seen people “do” qualitative research without even studying the methodology. Of course there are also people who use statistics unknowingly. The purists in each camp say you cannot mix the two. I disagree. There are many times when one approach can inform the other, for example, in using respondent’s comments to help interpret and enliven survey results. More research is needed on student learning. The Bloom (1956) taxonomy of educational objectives was used in hundreds, maybe thousands, of studies on student learning. Testing companies and college instructors have also used it in designing achievement tests and curricula. In 2001 a revision of the Bloom taxonomy, titled A Taxonomy for Learning, Teaching, and Assessing (Anderson and Krathwohl, 2001), was published. The new classifications of knowledge and cognitive processing take into account changes in American society and education since 1956. This new structure should inspire a fresh look at student learning and assessment in college. As for faculty evaluation I am not sure how much more can be learned about student evaluations. Given the strong feelings faculty members often have about them, and given their wide use, researchers will likely continue to study them. What we need are studies about the teaching portfolio. While they have been highly promoted and various publications inform teachers about how to construct them, little is known about their validity. The quantity of information provided in them does not always equal the quality of teaching, as many people assume. I believe that colleagues can and should play more of a role in evaluating teaching, and judging portfolios is a logical step. How to best accomplish that is a subject for further research and development. I have mixed feelings about the use of theory in conducting research. Occasionally I have found it useful in understanding results, such as when I used equilibrium theory to predict why student ratings caused teachers to alter their teaching. But more often I and other researchers have used models to show how variables are expected to relate to each other. Employing a well thought-out model and then testing it through path or regression analysis is more useful than relying on a weak or ill-suited theory. Probably the most important skill for a researcher is being able to 38
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ask the right questions and knowing how to design a study to answer them. Instinct may be as important as knowledge in this regard. ON TEACHING I was recently on a National Research Council committee that produced a report titled Evaluating and Improving Undergraduate Teaching in Science, Technology, Engineering, and Mathematics (Fox and Hackerman, 2003). Not much new is included in the report but perhaps the NRC sponsorship will result in it having some impact. We know more about teaching and how to evaluate it than is put into practice. Faculty members have strong views about teaching even if those views sometimes contradict the evidence. Older teachers in particular are hard to change. Younger teachers, according to recent studies, are more open to using active learning, technology, and other less traditional approaches to teaching. Recent doctorates are also more likely to have had the opportunity to learn about teaching in their graduate programs. I have sprinkled many of my ideas about teaching and further directions for research throughout this essay. I can only hope that young scholars find my experiences as a researcher stimulating and recognize that it is possible to serve higher education by investigating the challenging questions that confront it. As for this essay, like research often does, it provided an expected result — many moments of self-discovery.
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REFERENCES Anderson, L.W., and Krathwohl, D.R. (eds.) (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. New York: Longman. American Association of Higher Education (1995). From Idea to Prototype: The Peer Review of Teaching, A Project Workbook, Washington, D.C. Astin, A.W. (1968). Undergraduate achievement and institutional excellence. Science 161: 661–668. Berquist, W.H., and Phillips, S.R. (1975). Components of an effective faculty development program. Journal of Higher Education 46: 177–211. Bloom, B.S. (ed.). (1956). Taxonomy of Educational Objectives: The Classification of Educational Goals Handbook I: Cognitive Domain. New York: Longmans Green. Bogdan, R., and Biklen, S. (1982). Qualitative Research for Education: An Introduction to Theory and Methods. Boston: Allyn and Bacon. Boldt, R.F., Centra, J.A., and Courtney, R.G. (1986). The validity of various methods of treating multiple SAT scores. In College Board Report, 86,4. New York: The College Board. Boyer, E.L. (1990). Scholarship Reconsidered: Priorities of the Professoriate. Princeton, N.J.: Carnegie Foundation for the Advancement of Teaching. Centra, J.A. (1970). Black students at predominantly white colleges: A research description. Sociology of Education Summer: 325–339. Centra, J.A. (1971a). Validation by the multigroup-multiscale matrix: An adaptation of Campbell and Fiske’s convergent and discriminant validational procedure. Educational and Psychological Measurement 31: 675–683. Centra, J.A. (1971b). How students perceive their college environment. The College Board Review 79: 11–13. Centra, J.A. (1972). A comparison of three methods of assessing college environments. Journal of Educational Psychology 62: 56–62. Centra, J.A. (1973a). The effectiveness of student feedback in modifying college instruction. Journal of Educational Psychology 65: 395–401. Centra, J.A. (1973b). Self-ratings of college teachers: A comparison with student ratings. Journal of Educational Psychology 10: 287–295. Centra, J.A. (1973c). The student as godfather? The impact of student ratings on academia, The Educational Researcher 2: 4–8. (Also published in A.L. Sockloff (ed.), Proceedings of the First Invitational Conference on Faculty Effectiveness as Measured by Students, Temple University, pp. 4–8.) Centra, J.A. (1974). Women, Men and the Doctorate. Princeton, NJ: Educational Testing Service. Centra, J.A. (1975). Colleagues as raters of classroom instruction. Journal of Higher Education 46: 327–337. Centra, J.A. (1977). Student ratings of instruction and their relationship to student learning. American Educational Research Journal 14: 17–24. Centra, J.A. (1978). Types of faculty development programs. Journal of Higher Education 49: 151–162. Centra, J.A. (1979). Determining Faculty Effectiveness: Assessing Teaching Research and Service for Personnel Decisions and Improvement. San Francisco: Jossey-Bass. Centra, J.A. (1980). College enrollments in the 1980’s: Projections and possibilities. Journal of Higher of Education Jan/Feb: 19–39.
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Centra: Service Through Research Centra, J.A. (1983). Research productivity and teaching effectiveness. Research in Higher Education 18: 379–389. Centra, J.A. (1986). Handicapped student performance on the Scholastic Aptitude Test. Journal of Learning Disabilities 19: 324–327. Centra, J.A. (1993). Reflective Faculty Evaluation: Enhancing Teaching and Determining Faculty Effectiveness. San Francisco: Jossey-Bass. Centra, J.A. (1994). The use of the teaching portfolio and student evaluations for summative evaluations. Journal of Higher Education 65: 555–570. Centra, J.A. (1998). Development of the Student Instructional Report II. Princeton, NJ: Educational Testing Service. Centra, J.A. (2001). A model for assessing the scholarship of teaching. Paper given at the 9th Annual AAHE Conference on Faculty Roles and Rewards, Tampa, FL. Centra, J.A. (2003). Will teachers receive higher student evaluations by giving higher grades and less coursework? Research in Higher Education October. Centra, J.A., Froh, P., Gray, L., Lambert, L., and Diamond, R. (1987). Evaluating Teaching for Promotion and Tenure. Littleton, MA: Copley Publishing Group. Centra, J.A., and Guliani, B. (1968). The woman veterinarian. Personnel and Guidance Journal June: 971–975. Centra, J.A., and Linn, R.L. (1970). On the interpretation of student perceptions of their college environment. Measurement and Evaluation in Guidance 3: 102–109. Centra, J.A., Linn, R., and Parry, M.E. (1970). Academic growth in predominantly negro and predominantly white colleges. American Educational Journal January: 109–121. Centra, J.A., and Rock, D.A. (1971). College environments and student academic achievement. American Educational Research Journal 8: 623–634. Cohen, P.A. (1981). Student ratings of instruction and student achievement: A meta-analysis of multisection validity studies. Review of Educational Research 51: 281–309. Cross, K.P. (1990). Classroom research: Helping professors learn more about teaching and learning. In P. Seldin and associates (eds.), How Administrators Can Improve Teaching: Moving From Talk to Action in Higher Education. San Francisco: Jossey-Bass. Donlon, T.R. (1984). The College Board Technical Handbook for the Scholastic Aptitude Test and the Achievement Tests. New York: The College Board. Feldman, K., and Newcomb, T., (1960). The Impact of College on Students. San Francisco: Jossey-Bass. Fox, M.A., and Hackerman (eds.). (2003). Evaluating and Improving Undergraduate Teaching in Science Technology Engineering and Mathematics. Washington, DC: National Research Council. Friedan, B. (1963). The Feminine Mystique. New York: W.W. Norton. Hartnett, R.T., and Centra, J.A. (1977). The effects of academic departments on student learning. Journal of Higher Education 48: 7–24. Honey, J.C. (1996). Beyond Utopia; Science Values and the Citizen. New York: Vantage Press. Pace, C.R. (1960). College and University Environment Scales (CUES). Technical Manual (2nd edn.). Princeton: Educational Testing Service. Pace, C.R. (1984). Measuring the Quality of College Student Experiences. Los Angeles: University of California, Higher Education Research Institute. Pascarella, E.T., and Terenzini (1991). How College Affects Students. San Francisco: Jossey-Bass.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Peterson, R.E, Centra, J.A., Hartnett, R.T., and Linn, R.L. (1970). The Institutional Functioning Inventory Technical Manual. Princeton: Educational Testing Service. Rock, D.A., Centra, J.A., and Linn, R.L. (1970). On the interpretation of student perceptions of their college environment. Measurement and Evaluation in Guidance 3: 102–109. Sanford, N. (ed.) (1962). The American College. New York: John Wiley and Sons.
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2. THE OPPORTUNITY AGENDA: A REEXAMINATION OF POSTSECONDARY REWARD AND OPPORTUNITY Scott L. Thomas University of Georgia Laura W. Perna University of Maryland
INTRODUCTION The American public generally believes that postsecondary educational credentials are necessary to be successful in today’s labor market and to attain a middle class standard of living (Immerwahr, 2002a). The baccalaureate degree, once seen as an advantage for the elite, is now understood to be required to gain access to quality jobs and economic opportunities. Underlying this realization is a radically transformed U.S. economy. Updating Mortenson (2001) reveals that ●
●
●
the proportion of nonagricultural employment in goods producing industries declined from a peak of 47.4 percent in 1943 to a low of 18.3 percent in 2002; the proportion of jobs in private service industries grew from a low of 38.3 percent in 1943 to a peak of 65.6 percent in 2002; the proportion of jobs in government/public service increased from 12.8 percent in 1941 to a peak of 19.1 percent in 1975, and then declined to 16.2 percent in 2002 (Bureau of Labor Statistics 2002).
Coinciding with shifts in the dominant sector of jobs in the United States is an increase in the minimum level of education that is required to perform the available jobs. The U.S. Bureau of Labor Statistics (BLS) J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XIX, 43–84. ©2004 Kluwer Academic Publishers. Printed in The Netherlands.
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projects that employment in occupations that generally require a college degree or other postsecondary award will grow faster than the average across all occupations. Jobs generally requiring a college degree constituted 29 percent of all jobs in 2000 and are expected to account for 42 percent of projected new job growth during the coming decade (BLS, 2002). A bachelor’s degree is required to access not only a growing percentage of jobs but also higher incomes. Between 1980 and 1997 the earnings differential between those with some college degree and those who graduated from high school more than doubled (Kane, 2003). Acknowledging the dramatically changed labor force requirements, Kane (2003) argues that “the rising payoff to a college education” has profound “implications for social mobility” (p. 3). While the occupational and economic rewards that are associated with higher education are increasing, equality of opportunity to gain access to these benefits is declining. Table 2.1 shows that while family income is unrelated to the rate of participation in 2-year colleges, it is strongly related to the rate of participation in 4-year institutions (Ellwood and Kane, 2000; Kane, 2001). High school graduates in 1992 from the
Table 2.1: Proportion of Students from Families in each Income Quartile (Parent Reported) who Enroll in Postsecondary Schools within 20 Months of Higher School Graduation
Parental Income Quartile
Type of Postsecondary Schooling Any Postsecondary
Vocational, Technical
2-year College
4-Year College
Class of 1980/82 (HSB) Bottom 3rd 2nd Top Total
0.57 0.63 0.71 0.80 0.68
0.12 0.11 0.10 0.06 0.10
0.16 0.19 0.22 0.19 0.19
0.29 0.33 0.39 0.55 0.39
Class of 1992 (NELS:88) Bottom 3rd 2nd Top Total
0.60 0.70 0.79 0.90 0.75
0.10 0.07 0.06 0.05 0.07
0.22 0.25 0.25 0.19 0.23
0.28 0.38 0.48 0.66 0.45
Table from Kane (2001) with permission.
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highest family income quartile were more than twice as likely as those from the lowest family income quartile to attend a 4-year college or university within 20 months of graduating from high school. Table 2.1 shows that 66 percent of 1992 high school graduates from families in the highest income quartile enrolled in a 4-year college or university within 20 months of graduating from high school, compared with 28 percent of high school graduates from families in the lowest income quartile. Although postsecondary participation rates have increased since the mid-1960s for high school graduates across all family income groups, Table 2.1 also shows that the gap in the 4-year college participation rate by family income increased over the past 20 years (Hearn, 2001; Kane, 2001). Postsecondary educational opportunity is stratified by family income in terms of both access to postsecondary education generally and the choice among postsecondary educational institutions to attend. Table 2.1 shows that students from lower income families are not only less likely than students from higher income families to enroll in college after graduating from high school, but, among those who enroll, are also less likely to attend 4-year institutions. Virtually all expansion of higher education opportunity has occurred in non-elite institutions. That is, the vast majority of growth in capacity has occurred through the establishment of new colleges, the expansion of existing colleges that are in the non-elite sector (e.g., non- and less-selective public colleges and for-profit institutions), and the growth in distance education and other forms of electronic delivery (Hearn, 2001). Thus, while there now exists greater capacity to accommodate the growing demand for higher education, the new opportunities that this expansion represents are the ones that are quite removed from those provided by the nation’s more prestigious (and least accessible) institutions (see Hansmann (1999) for a consideration of the importance of higher education as an associative good). The centerpiece of the federal government’s efforts to reduce the stratification of postsecondary educational opportunity is the set of student financial aid programs that is authorized under Title IV of the Higher Education Act of 1965. A primary goal of these programs is to ensure that students are not denied access to or choice among postsecondary educational institutions because of limited financial resources. The federal government invests substantial amounts of money in these programs ($54.3 billion in all federally supported, generally available aid programs in 2001–02, The College Board, 2002a,b). State governments have traditionally attempted to increase postsecondary educational opportunity by 45
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providing direct unrestricted aid to higher education institutions, thereby allowing institutions to reduce the sticker price charged to students (i.e., tuition), and by providing financial aid to students, thereby reducing the total share of this price that is ultimately paid by students. Persisting gaps in college access and choice by family income suggest that current public sector approaches to ensuring educational opportunity are insufficient and should be reconsidered. With the exception of the federal tax credits that were authorized in 1997, the last major structural change to the federal financial aid system took effect in 1973 with the implementation of what is now known as the Pell Grant program. While much has changed in the broader environment (e.g., shifting skill requirements, growing population, moving toward universal access, increasing costs of attendance, etc.), the federal government has done little to alter the financial aid policies that determine the ways in which families pay for college. The failure of government programs to respond to changes in the economy and socio-political structure begs for a reexamination of traditional approaches to increasing postsecondary educational opportunity for underrepresented groups of students. This chapter provides a systematic review of research examining the rewards that are associated with participation in college, and describes recent trends in public policy that are maintaining rather than reducing the stratification of postsecondary educational opportunity. In addition to this introduction, the chapter is divided into four sections. We begin by illustrating the significance of continued gaps in college access and choice through a review and synthesis of the literature on the returns to investments in higher education. The second section provides an overview of the changing political context in which policies about the public financing of higher education are developed and implemented. In a third section we describe recent trends in public policies that, in effect, de-emphasize the barriers that restrict college access and choice for low-income students. We conclude the chapter by summarizing current political challenges to reducing the stratification of American higher education and offering a set of recommendations for public policy.
ECONOMIC RETURNS TO HIGHER EDUCATION Systematic interest in the economic rewards that are associated with participation in higher education began in the early 1960s — coincident 46
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with an emergent political interest in dramatically expanding access. While work exists from earlier periods (e.g., Havemann and West, 1952) such research lacked the clear theoretical frame that emerged in the work of economists like Gary Becker, Theodore Shultz, and Jacob Mincer. Shultz’s (1961) and Becker’s (1962, 1964) works were of particular importance in this area as they formalized the concept of human capital, a theoretical position equating investments in people with investments in traditional physical capital. At its core, human capital theory assumes that an individual’s decision to invest in higher education is based on a rational choice between all competing uses of one’s time. Human capital theory also assumes that employment outcomes are determined by an individual’s productivity. Differences in productivity are expected to be attributable to differences in the investments that individuals have made in their personal development, including the quantity and quality of their education, as well as the amount of their on-the-job training, their geographic mobility, and their emotional and physical health (Schultz, 1961; Becker, 1962). Using census data from 1950, Becker estimated a private rate of return to the baccalaureate degree at 13 percent (Becker, 1975). This return was attributed directly to presumed human capital improvement realized as a result of college attendance. Becker’s estimated 12.5 percent public rate of return received less attention but nonetheless demonstrated a valuable generalization of the human capital concept and a quantification of the public benefits of higher education. While the human capital approach provides a useful framework for understanding private and public rates of return, it is not without its critics. Perhaps the most sustained critique comes from Michael Spence (1973, 1974) who observed that the strength of human capital theory rests on the assumption that education in the United States is fundamentally meritocratic — that is, individuals are limited only by their own ability and motivation. This early critique of human capital theory was enabled in part by work such as that by Sewell and Hauser (1975), which outlined the relationships between labor market experiences, college education, and the nonrandom allocation of students across different types of colleges (e.g., 2-, 4-year, selective or non-selective). Sewell and Hauser’s work, in particular, suggested that colleges do little to modify prior differences in students’ socioeconomic and class backgrounds — a finding that challenges a main premise of the human capital model. Spence (1974) in contrast to the structural functionalist perspective dominant in sociology up until the 1970s (e.g., Davis and Moore, 47
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1945) — a perspective quite compatible with the human capital perspective in economics — argued that the educational credential, or degree, serves as a signal to potential employers that an individual possesses certain characteristics that are more or less valued by a firm (see also Weiss, 1995; Wolpin, 1977). The signaling perspective asserts that colleges screen their graduates through a process of admissions and counseling that is much more comprehensive than most employers could offer. A key to this screening process is that it relies largely upon discrimination on attributes that individuals possess prior to entering college. Degrees, therefore, merely confirm the presence or absence of individual attributes that employers believe make for good workers (see Taubman and Wales, 1974, for a more complete consideration). In another early and distinctive attempt to assess the economic impacts of postsecondary education, Edward Denison (1962) concentrated on a broader conceptualization of the public rate of return to investments in higher education. Denison (1962) modeled GDP as a function of inputs such as labor, land, and capital and then attributed the residual to improvement in education of the labor force. Taken together, the work of Denison, Becker, and Spence highlight an emergent interest in quantifying the varied types of economic returns to investments in higher education. Moreover, the work of these scholars represents a systematic effort to identify the public and private benefits that are associated with personal and governmental investments in higher education. Much of the scholarship in the 1970s addressed the definition and measurement of public returns and non-pecuniary outcomes resulting from investments in higher education (see Alexander (1976) for a summary of such work). This emphasis was largely a reaction to what many economists argued was a period of over-investment in education (Brenman, 2001). Perhaps the most notable in the emergent concerns about such overinvestment was Richard Freeman’s (1976) popular book, The Over-Educated American. In this book, Freeman focused on the long prophesied bust in the post-WWII job market noting that the private rate of return was possibly as low as 7.5 percent in 1973, substantially lower than Becker’s (1975) earlier estimate of 13 percent. Freeman concluded that his lower estimate reflects a fundamental shift from the belief that investment in higher education is a guarantee of higher salaries and better jobs to one that would be better understood as a marginal investment. But what Freeman could not see in the mid-1970s was an impending contraction in the labor market for high school graduates. Leslie and 48
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Brinkman (1988) point out that this shift resulted in a sharp increase in the relative value of the baccalaureate degree — a reality that holds true today. The concerns of Freeman and others (e.g., Rumberger, 1981) notwithstanding, virtually all of the empirical research on the economic returns to college show sizable private economic benefits resulting from college participation. College graduates earn substantially more than high school graduates and these differences have increased over time (Murphy and Welch, 1989; Bound and Johnson 1992; Katz and Murphy, 1992; Levy and Murnane, 1992; Mishel, Bernstein, and Schmitt, 1997, Levy, 1998). A closer look at the corpus of work on the private benefits of higher education that has developed in this area over the last 40 years shows that at least two primary factors influence the magnitude of the wage premium that is associated with college attendance. First, research consistently shows that the academic major has a substantial impact on the earnings of college graduates (Rumberger, 1984; Berger, 1988; James, Alsalam, Conaty, and To, 1989; Rumberger and Thomas, 1993; Eide, 1994; Grogger and Eide, 1995; Thomas, 2000). This finding is important because the choice of academic major is made largely by the individual. There are a number of constraints on such choices (e.g., academic preparation or capacity within the major at any institution) but choice of major field of study is, by and large, in the student’s control. A second factor shown to impact on earnings is the perceived “quality” of the baccalaureate granting institution (Solmon, 1973; Sewell and Hauser, 1975; Trusheim and Crouse, 1981; Mueller, 1988; Smart, 1988; Fox, 1993; James and Alsalam, 1993; Rumberger and Thomas, 1993; Brewer and Ehrenberg, 1996; Thomas, 2000). While institutional “quality” and “prestige” are difficult concepts to operationalize, the findings are remarkably consistent across a large number of studies: graduates from more prestigious, more selective, and higher academic quality colleges enjoy small but significant wage premiums relative to peers graduating from less distinctive institutions. While characteristics such as academic performance are also known to affect positively the salaries of college graduates (Wise, 1975; James et al., 1989; Jones and Jackson, 1990; Rumberger and Thomas, 1993; Thomas, 2000) the two largest drivers of post-baccalaureate earnings are student choice of academic major and institutional type. While some have focused on the economic rewards that are associated with sub-baccalaureate credentials (e.g., Dougherty, 1988; Grubb, 1992; Monk-Turner, 1998; Sanchez and Laanan, 1998), most research focusing on 49
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qualitative differences in higher education has been limited to the “quality” of institutions conferring baccalaureate degrees. Such examinations have demonstrated slight differences in the earnings of graduates from institutions of differing quality, where quality is typically measured by the selectivity of the student body. These differences are generally small and favor graduates from more selective schools. Kingston and Lewis (1990) argue that the lack of substantial earnings differences across differing types of institutions is a partial result of researchers considering the entire range of institutions at the expense of distinct segments that are presumed to confer substantial labor market advantages to their graduates. Their work suggests that graduating from the most elite U.S. colleges confers substantial labor market rewards that are overlooked when institutions from all “prestige” segments are pooled in the analyses. This represents an important qualification to the general finding of the work on the effects of college “quality”, suggesting that a small but significant and positive earnings advantage results from attending more prestigious schools. The consideration of elite schools and stratification by Kingston and Lewis provides one of the more useful contributions to our thinking about how higher education informs what Anthony Giddens (1979) refers to as the “structuration of society” — in this case, the ways in which educational experiences build upon one another to create distinct tracks that correspond to broader patterns of socioeconomic status and class. This finding is also consistent with the earlier work of Sewell and Hauser (1975), work that informs the signaling or screening perspective. The interpretation of the cause of the relatively uniform positive effects of college quality on earnings continues to be debated. Specifically, to what degree are these effects attributable to value-added through the development of human capital rather than preexisting ability and motivation? This question revives the larger antagonisms between human capital theory and signaling — between structural-functionalism and critical theory. Becker (1975) and many others have attempted to resolve the debate by specifying models that correct for individuals’ self-selection into colleges — self-selection that is presumably based upon such background characteristics as socioeconomic status, race, gender, and prior schooling experiences (all of which are known to be interrelated). For example, based on their integrative review of prior research, Leslie and Brinkman (1988) concluded that 79 percent of the observed difference in earnings between individuals who have graduated from high school and individuals who earned a bachelor’s degree is attributable to receipt of a bachelor’s degree. In a reexamination 50
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of the earnings premium, Perna (2003) concluded that the alpha factor, or the correction for initial differences between individuals who graduate from college and individuals who graduate from high school, varies from 68 percent to 95 percent depending on the variables that are taken into account in the analyses. Despite these attempts, adequately taking into account the effects of self-selection on earnings continues to be one of the more persistent and vexing problems plaguing this body of literature. Other challenges characterize this literature as well. While some excellent work focuses on longer-range returns to college, much of the research uses data that are representative of high school graduates as opposed to college graduates (see Brewer and Ehrenberg (1996) for a good example of work using a sample that is non-representative of college graduates). When the interest is the relative advantage of a college degree over a high school diploma, data that are representative of high school graduates are appropriate. However, when the research is focused on identifying the unique impacts of certain types of college experiences on labor market outcomes it becomes much more important that the samples used represent graduates from the institutions that are presumed to confer some type of advantage or disadvantage. Most of the work using nationally representative samples of college graduates has addressed the impact of major field of study and the quality of the college attended on earnings that are realized shortly after receipt of the baccalaureate degree (usually one year after graduation, see Rumberger and Thomas (1993) or Thomas (2000) as examples). As a result, our knowledge about the longer-term labor market effects of the college experience is potentially biased by small, non-representative samples of graduates. Only within the last several years have longitudinal data become available that will permit a more complete assessment of the longer-term labor market impacts that are associated with the type of college attended (e.g., NCES’s Baccalaureate and Beyond). Work employing these data is beginning to emerge (Thomas and Zhang, 2001, 2002; Thomas, 2003; Price, forthcoming) and promises to illuminate the longer-terms effects of graduating from particular types of institutions. In summary, despite the volume of literature that has been developed over the past 40 years, questions remain about the mechanisms by which colleges advantage their graduates once they enter the labor market. We also know little about whether the variation in earnings by the selectivity of the college attended is due to the greater ability of more selective colleges to improve their students’ stock of human capital or due to these 51
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colleges admitting students with certain “cultural markers” (e.g., socioeconomic status or social class) that already provide advantage (or disadvantage) in society. Despite the corpus of work in this area, we also know comparatively little about the economic impact of different types of colleges on graduates from differing socioeconomic and class backgrounds. Does the typical state college equally advantage graduates from rich and poor backgrounds? Conversely, do students lacking the specific “cultural markers” that are presumably valued by elite institutions enjoy comparable labor market advantages upon graduation from these schools? Nonetheless, although we know little empirically about the ways in which attending and graduating from college rather than high school or attending a particular college influences labor market experiences, prior research demonstrates that success in today’s workforce and chances for upward socioeconomic mobility are powerfully impacted by college attendance and 4-year degree attainment. Attending and graduating from college has a positive impact on labor market outcomes and earnings. Research also suggests that unless an individual graduates from a relative handful of elite (and almost always private) institutions, the difference in the impact of college “quality” on labor market experiences is marginal — at least in the short term. Indeed, most research in this area suggests that, net of a host of confounding variables, graduates from higher quality schools fare better in terms of pay. Although relatively small (especially when compared to the general advantage conferred by having any 4-year college degree), the existence of such advantages is consistent across a large number of studies using a range of samples in a variety of time periods and economic conditions.
THE POLITICAL CONTEXT: AN IDEOLOGICAL BALANCE Federal government support of U.S. higher education predates the Constitution, originating with the provision for land grants in the Northwest Ordinances of the 1780s. The return on this support has been substantial with the country owing much of its unrivaled agricultural productivity, industrial power, and military might to the Morrill Act of 1862 and the supplemental acts that followed. While the goal of promoting economic and military stature may appear to be a primary driver of many federal and state funding mechanisms, the broader economic rationale for federal and state financing of 52
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higher education is the belief that colleges and universities provide benefits that are not completely captured by individual students but that are also realized by society at large. Because of these public benefits, the demand for higher education by individual students in the absence of government intervention would be less than the optimal social demand for higher education, thus resulting in a potential underinvestment in higher education (Paulsen, 2001). The government uses public subsidies to address this economic inefficiency by providing subsidies to institutions (e.g., state appropriations to higher education institutions) that enable these colleges to reduce the price of higher education charged to students (i.e., tuition), and by providing subsidies to students (i.e., student financial aid) that reduce the share of the price students pay for the education (Paulsen, 2001). In addition to contributions to economic productivity, the societal benefits of higher education include increased national income, reduced cost of publicly supported social support programs, lower crime rates, greater community service and civic involvement, and improvements in knowledge and technology (Leslie and Brinkman, 1988; Bowen, 1997; Paulsen, 2001). Direct attention to the public benefits of higher education has waned over time, partially due to the difficulty in accurately quantifying the myriad outcomes that are assumed to be impacted by investments in higher education. Nonetheless, notable efforts in the past decade include the Institute for Higher Education Policy’s (1998) Reaping the Benefits and Wolfe and Zuvekas (1995) paper, Nonmarket Outcomes of Schooling. A range of documents over the past 40 years captures the inherent tension between private returns and public investments (and vice-versa). Two of the more notable considerations are found in the Carnegie Commission’s 1973 document Higher Education: Who Pays, Who Benefits, Who Should Pay? and in Howard Bowen’s 1977 book, Investment in Learning. Economists (e.g., Kane, 1999; Paulsen, 2001) offer additional rationales that justify government intervention in the higher-education market. At least three of these rationales recognize the barriers that limit college enrollment for students from low-income families. First, economists argue that government intervention in the higher-education market is needed to correct for imperfections in private capital markets. Specifically, prospective students are unable to use their post-higher education level of human capital as collateral against which to borrow funds to pay the costs of the education (Kane, 1999; Paulsen, 2001). Prospective students from lowincome families are disproportionately impacted by this market failure since they are less likely than those from higher-income families to have 53
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access to alternative sources of funds. Second, economists also argue that government intervention is justified because of differences across income groups in individual willingness to forgo earnings in the present in order to realize higher earnings in the future (Paulsen, 2001). Finally, government intervention in the higher-education market is warranted when the public supports a reduction in inequities across income groups (Paulsen, 2001). Polices that increase higher-education enrollment, and thus build human capital, equalize incomes more efficiently than alternative interventions such as providing direct payments to low-income individuals (Paulsen, 2001). Not until the 1960s and 1970s did the federal government directly address the barriers that limit access to higher education for low-income students. Enabling this focus was a broad political consensus about the social and economic returns that are associated with the public finance of higher education. St. John and Parsons (in press) observe that liberals supported, and indeed promoted, the Civil Rights era expansion of funding because of their interest in expanding opportunity, while conservatives were content with the expansion of funding because it furthered their interest in promoting economic development. Liberals and conservatives disagreed not on whether to expand government support for higher education, but on the strategies by which to provide the support (St. John and Parsons, in press). Civil Rights era ideals of federal student aid programs (largely falling under Title IV of the Higher Education Act of 1965) focused on providing need-based grant aid to ensure that low-income youth would not face a greater economic burden than their peers from more affluent backgrounds. Such progressive ideals were soon eroded by the economic and political realities of the mid- to late-1970s, realities that radically altered the funding environment for higher education programs across the country. Brief but marked gains in low-income student access and persistence associated with the Title IV federal student aid programs were diminished as the need-based grant aid ideal was nudged toward the margins by more costeffective and politically palatable loan programs (Mumper, 1996). By the 1980s, conservative interests began to play a more dominant role in the development of higher-education finance policy. Faced with rapidly escalating prices in higher education, many conservatives argued that public support had gone too far and that colleges and universities had become relatively unproductive (Finn, 1988; Finn and Manno, 1996). During this period, student aid programs came under direct attack by conservatives arguing that the income transfer they created was partially responsible 54
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for the slowdown in economic growth during the 1980s (Hansen, 1983; Bennett, 1987). The trend away from the need-based ideals outlined in the early Title IV programs and the emergent dominance of the conservative political position was followed by a series of federal policy actions during the 1980s devolving federal responsibility for a wide variety of public programs down to the state level. This devolution effectively relieved an exploding federal budget from a large share of the funding burden that was associated with a number of traditionally federally sponsored programs, including numerous high cost health and welfare programs (see Breneman and Finney, 1997). Throughout the 1980s growth in the costs of higher education continued to outpace the general rate of inflation, while state subsidies to higher education were eroded by competing financial demands. The net result was a rise in the share of costs borne through tuition by students and their families (Breneman and Finney, 1997). The rise in the price of attendance, combined with shifts in financial aid toward programs emphasizing nonneed grants, various forms of loans, and tax credits has had an uneven impact on access, with poorer families all but priced out of higher education (see, e.g., Advisory Committee on Student Financial Assistance, 2001; Heller, 2002; Lumina Foundation for Education, 2002; National Center for Public Policy and Higher Education, 2002). The evolution and coincidence of these events is now observed at a time in which evidence suggests college is more necessary than ever for socioeconomic advancement. Thus, the political balance that existed until the late 1970s — a balance that allowed liberal goals of broader access to quality higher education to coexist with conservative goals of continued economic expansion — has been upset. The dominant view seems to be that the conservative goal of economic expansion can be more effectively achieved through policies that require students and their families to self-pay the costs of the education (e.g., by providing most financial aid in the form of loans rather than grants) and that reward students solely for their achievements (e.g., by awarding financial aid based on academic criteria rather than financial need) than through policies that reduce the barriers to college access and choice for historically underrepresented groups. A review of the changes that have occurred in public policies related to higher education finance since the early 1980s suggests that policymakers are now giving minimal consideration to the market imperfections that limit educational opportunity for low-income students. These policy shifts 55
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also reflect the belief that the private benefits of higher education, or the benefits that accrue to individual participants, far exceed the public or societal benefits. The political and economic forces that have shaped higher education policy over the last several decades provide a backdrop for the remainder of this chapter.
TRENDS IN PUBLIC POLICIES THAT MAINTAIN THE STRATIFICATION OF POSTSECONDARY EDUCATIONAL OPPORTUNITY A review of trends over the past two decades in public policies that are related to the financing of U.S. higher education suggests a decline in federal and state government commitment to ensuring postsecondary educational opportunity for all students. Among the most important trends are increased privatization of public higher education, escalating tuition, and shifts in student financial aid. In addition to an examination of these policy trends, this section also offers a reconsideration of the public sector’s involvement in the higher education market as it relates to the continued disconnect between K-12 and higher-education curricular requirements. The articulation between the nation’s secondary schools and colleges has been a focus of scholars who are interested in the role academic preparation plays in determining access (e.g., Tierney and Hagedorn, 2002; Perna, 2004). We are particularly interested in this piece of the access puzzle because of the well-documented inequities in K-12 finance — inequities that translate into under-preparation for and inadequate orientation to postsecondary opportunity. INCREASED PRIVATIZATION OF PUBLIC HIGHER EDUCATION State governments are the primary source of financial support for public higher education institutions in the United States. The 50 state governments were the source of more than $45.6 million of the $197.4 million current fund revenues at higher education institutions in 1995–96 (23 percent, NCES, 2002). State governments are a substantially more important source of financial support for public than for private higher education institutions. In 1995–96 they provided 36 percent of current fund revenues at public degree-granting institutions ($44.2 million of $123.5 million) and 2 percent 56
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of current fund revenues at private degree-granting institutions ($1.5 million of $74.5 million; NCES, 2002). While still the largest source of financial support for public highereducation institutions, state governments provide a considerably smaller share of public higher-education revenues now than in the early 1980s. Between 1980–81 and 1995–96, the share of higher-education current-fund revenues from federal, state, and local government sources declined from 62 to 51 percent at public degree-granting institutions and from 21 to 16 percent at private degree-granting institutions (NCES, 2002). Although the amount of state appropriations per student increased over this period, net of inflation (National Center for Public Policy and Higher Education, 2002), the largest decline in government support for public degreegranting institutions was in state appropriations, falling from 46 percent of current-fund revenues in 1980–81 to 36 percent in 1995–96. At private degree-granting institutions, the share of current fund revenues covered by state governments remained stable (about 2 percent between 1980–81 and 1995–96) but the share covered by the federal government declined from 19 percent in 1980–81 to 14 percent in 1995–96. In part because of the decline in government support, students and their families now provide a greater share of higher education revenues, as the share of currentfund revenues from tuition and fees rose from 13 percent in 1980–81 to 19 percent in 1995–96 at public degree-granting institutions and from 36 percent to 43 percent at private non-profit degree-granting institutions (NCES, 2002). One cause of changes over time in state appropriations to highereducation institutions is fluctuation in the strength of a state’s economy (Hovey, 2001; Heller, 2002; National Association of State Budget Officers, 2002). Heller (2002) identified five “boom and bust” cycles in state support for higher education between the mid-1960s and mid-1990s. His review shows that state support per student generally increased steadily between 1966 and 1978. Between 1978 and 1982, state support per student declined due to high rates of inflation as well as increases in enrollment. An economic recovery, slower rates of inflation, and stabilization in enrollments contributed to a rebound in per student state appropriations between 1982 and 1988. This “boom” was followed by a decline in state appropriations per student between 1988 and 1993 due to an economic downturn and an increase in enrollments. Between 1993 and 1995 per student appropriations again recovered as enrollments stabilized (Heller, 2002). Nonetheless, although state support increased (after controlling for 57
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inflation), state appropriations per student were lower in the mid-1990s than in the mid-1970s (Heller, 2002). While macroeconomic conditions play a role, some (e.g., Breneman and Finney, 1997; Hovey, 2001; Heller, 2002) argue that the lower level of state support for higher education beginning in the mid-1990s reflects a “new era” of reduced state support. Distinctive about this era is the growing competition for state financial support and increasing pressure on state officials to reduce spending on the small number of discretionary items in the state budget (such as higher education), growing distrust by the public and policymakers about higher education, and a rising belief that alternative (i.e., non-state) sources of revenues for higher education are available. Consider that in 2001 states allocated an average of 11.3 percent of their total state spending to higher education compared to 14.1 percent in 1982 (U.S. Bureau of the Census, 1983, 2003). While the values at these two points in time reflect an overall decline in state support relative to other publicly funded services, this comparison obscures the boom and bust funding cycles for higher education that occurred in this window. The squeeze resulting from heightened competition for public resources and the lack of a coherent state policy strategy for dealing with the ups and downs of state economies has created a destabilized environment for higher-education planning and threatens efforts that better ensure (let alone expand) access (Callan, 2002). One source of the decline in state support for higher education is increasing competition for scarce public resources. States face pressure to fund other priorities, including health care, welfare, corrections, and K-12 education (Hauptman, 1997; Hovey, 2001), and, some are required by law to provide a minimum level of funding for these priorities. In recent elections, state legislators have promised increased state support for local elementary and secondary schools (Hovey, 2001). For example, in 2002 Maryland passed the “Thorton bill” which requires, effective FY2004, a minimum level of per-student state funding to public elementary and secondary schools (Maryland State Department of Education, 2002). When the total amount of available revenues does not increase, or even decreases due to tax cuts, an increase in mandated expenditures, such as those authorized by the Thorton bill, reduces the amount of state appropriations that is available for such discretionary expenditures as higher education. Although the increased funding for K-12 education may improve elementary and secondary school students’ level of academic preparation and readiness for college, mandated funding for K-12 education also limits 58
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the amount of state support that is available to ensure that the state’s higher-education institutions have the capacity to serve these students. Higher education is being squeezed out of state budgets not only because of increased competition for spending on other priorities but also because of diminished public and state policymaker support for higher education. Although most Americans now believe that a college degree rather than a high school diploma is essential for success in the labor market, many are also distrustful of higher education (Immerwahr, 2002b). Despite the perceived importance of a college degree, most Americans agree that the cost of a college education exceeds the average family’s income (70 percent) and agree that higher education institutions can do more to reduce these costs (60 percent, Immerwahr, 2002b). State appropriations to higher education have also been subject to disproportionate cuts in tight economic times because of state legislators’ perceptions about higher education (Hovey, 2001). Hovey (2001) argues that state legislators perceive higher education as capable of compensating for declines in state revenues by drawing on reserves or increasing other sources of revenue, particularly tuition and fees, and easily reducing personnel and other expenditures. State appropriations for higher education are unlikely to increase in the near future because of the economic downturn of the early 2000s and growing structural state budget deficits (Hovey, 1999, 2001). Hovey (1999, 2001) argues that strong economic growth during the late 1990s masked a 0.5 percent annual gap between the level of state support that is needed to maintain current programs and tax revenues. While the magnitude of the problem varies across states, these structural deficits, especially when combined with the reluctance of elected officials to raise taxes, will continue to limit the availability of state funds for higher education (Hovey, 1999, 2001). In a recent update to Hovey’s 1999 analysis, Jones (2003) uses more current data to conclude that states (and higher education in particular) are likely to face tough budget conditions over the next decade. Moreover, to maintain the current level of services, state spending for higher education will have to increase faster than state spending in other areas ( Jones, 2003). Increased competition for public funding, decreasing public support for higher education, a lack of coherent state-level strategies for higher education budgeting, and structural deficits in states’ budgets encourage privatization of services and signal a decline in state commitment to ensuring postsecondary opportunity for all students. An artifact of this privatization is an increased reliance on tuition revenues to cover the costs of providing 59
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postsecondary education. When state general fund appropriations per student decline, institutions often respond to the need for additional revenues by increasing tuition charges — an action that has immediate consequences for accessibility.
ESCALATING TUITION Tuition at public higher education institutions has been increasing steadily since the 1960s (Heller, 2002). Because economic downturns are one cause of a decline in state appropriations to higher education and reductions in one source of revenue (i.e., state appropriations) often result in increases in another source (i.e., tuition), the largest increases in tuition generally occur at times when families are least able to afford such increases (National Center for Public Policy and Higher Education, 2002). While changes in state appropriations may be one source of recent increases in tuition, other possible sources of the growth in tuition since the 1960s include growing demand for higher education, increasing costs of providing the education (e.g., new services, new technology), and the absence of productivity increases (Heller, 2002). Because increases in tuition have exceeded increases in family income and inflation, affordability has declined (National Center for Public Policy and Higher Education, 2002; Heller, 2002). Heller (2002) observes that, during the 1980s, “affordability” became a problem as tuition increased steadily but family incomes stagnated. Tuition increases continued through the 1990s while family incomes changed minimally. As a result, tuition and other college-related expenses represent a larger share of family income (National Center for Public Policy and Higher Education, 2002). Data from the College Board (2002a) demonstrate that, although the rate of increase in tuition was greater during the 1980s than during the 1990s, the rate of increase in tuition continues to exceed the rate of increase in median family income. After controlling for inflation, average tuition increased between 1981–82 and 1991–92 by 62 percent at private four-year institutions and 58 percent at public four-year institutions, while the median income for families with parents between the ages of 45 and 54 increased by only 16 percent (The College Board, 2002a). Between 1991–92 and 2001–02, average tuition increased by 37 percent at private 4-year institutions and 38 percent at public four-year institutions while median family income increased by 8 percent (The College Board, 2002a). 60
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As the College Board (2002b) observes, attention to changes in the costs of attendance (defined as tuition and fees, room, and board) relative to changes in median family income, masks differences across groups. Disaggregating changes in family income shows that the enrollmentweighted cost of attending a public 4-year institution has represented less than 10 percent of family income for students in the highest family income quintile since the early 1970s (The College Board, 2002b). While the percentage of family income represented by the enrollment weighted cost-ofattendance at both public and private 4-year institutions has remained relatively small and virtually unchanged for students in the highest family income quintile, the pattern is dramatically different for students in the lowest family income quintiles. For students in the lowest family income quintile, the cost of attending a public 4-year institution increased from about 40 percent of family income in the 1970s to more than 60 percent in the late 1990s. The cost of attending a private four-year institution for a student in the lowest family income quintile increased from about 85 percent of family income in the 1970s to about 160 percent in the late 1990s (The College Board, 2002b). Attention to national patterns of increases in tuition relative to increases in family income also masks variations across the 50 states. The National Center for Public Policy and Higher Education (2002) notes that, between 1992 and 2001, the rate of increase in tuition at public 4-year colleges and universities was greater than the rate of increase in family income in 41 states, the increase in state appropriations to higher education was greater than the increase in both enrollment and inflation in 36 states, and the increase in tuition at public 2-year institutions was greater than the increase in family income in 34 states. The National Center for Public Policy and Higher Education’s most recent analysis of state budgets, tuition charges, and financial aid is reported as the “worst news for public higher education institutions and their students in at least a decade” and they predict that the future looks “even bleaker, with states continuing to cut higher education appropriations and campuses responding by raising tuition even higher, imposing new fees and reducing student financial assistance” (National Center for Public Policy and Higher Education, 2003, page 1A). Mortenson (2003) points out that there are three consistent findings in 50 years of academic and policy research on student demand for higher education. First, as in most markets, increased net price softens demand. Second, subsidies provided to students in the form of financial aid tend to 61
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mitigate the relationship between sticker price and demand. Third, the impact of financial aid on this price sensitivity is almost entirely isolated to the bottom half of the income distribution. Tuition has increased dramatically over the past 20 years and need-based financial aid has not kept pace. It follows therefore that the gap in college attendance across income groups will increase — just as the data in Table 2.1 show. Research that uses the state as the unit of analysis shows that an increase in tuition at public 4-year institutions is associated with an increase in enrollment at public 2-year institutions but a decrease in enrollment at public 4-year institutions (Kane, 1995). Using student-level data from the NELS:88/94, Kane (1999) found that, after controlling for relevant variables, a $1,000 increase in tuition at public two-year institutions in the state was associated with a 4.5 percent decline in college enrollment. Analyses also show that the likelihood of enrolling in college is negatively related to tuition at public 2-year colleges in the state and positively related to state need-based financial aid (Perna and Titus, 2002). Moreover, increases in tuition and decreases in state financial aid have a greater effect on enrollment at community colleges than on enrollment at public 4-year institutions (Heller, 1999; Kane, 1999). In short, low-income students are more sensitive than other students to changes in tuition (Kane, 1995, 1999). Public postsecondary institutions, reacting to reductions in state appropriations, continue to raise tuition at a rate that far outpaces the rate of general inflation and growth in personal income. This combined with reductions in student financial assistance signals a serious erosion of commitment to ensuring postsecondary opportunity for low-income students as well as middle-income students. Escalating tuition at state institutions threatens access for students from middle-class families, many of whom feel they are being priced out of an opportunity that had been heretofore all but guaranteed (Immerwahr, 2002a). The significant and sustained reaction of the middle-class has altered the landscape of financial aid programs that now focus increasingly on issues central to middle-class affordability and less on promoting access for students from lower-income families. SHIFTS IN STUDENT FINANCIAL AID POLICIES At the same time as the costs of higher education have been increasing, the amounts, types, and foci of federal and state financial aid policies have been shifting. Over the past two decades, the amount of financial aid 62
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that is available to students has increased at a slower rate than the costs of attending higher education, the types of financial aid available to students have shifted from grants to loans, and the emphasis of federal and state student financial aid programs has shifted from reducing financial barriers to college attendance for low-income students to increasing the affordability of college for middle-income students, as indicated by the increased consideration of characteristics other than financial need in awarding student aid, the establishment of federal non-refundable tax-credits, and the establishment of state-sponsored pre-paid tuition and college savings plans. As Hearn (2001) concludes, these shifts perpetuate low-income students’ “legacy of disadvantage relative to students whose families can afford to use savings and current income to pay for college attendance” (p. 445). Inadequate Increases in Student Financial Aid During the 1980s, increases in student financial aid failed to keep pace with increases in tuition and fees. Between 1980–81 and 1991–92, average tuition increased in real dollars by 62 percent at private 4-year institutions and 58 percent at public 4-year institutions, while average aid per full-time equivalent student increased by only 8 percent (The College Board, 2002a). During the 1990s, the pattern reversed, as the rate of increase in average aid per FTE (106 percent) exceeded the rate of increase in tuition at private 4-year (37 percent) and public 4-year (38 percent) institutions (The College Board, 2002a). Thus, the proportion of the average student’s financial need that was not met by student financial aid increased during the 1980s (Hossler, Lund, Ramin, Westfall, and Irish, 1997), but appears to have decreased during the 1990s. Nonetheless, the increase in aid per FTE during the 1990s came largely in the form of loans; between 1991–92 and 2001–02, loan aid per FTE increased by 122 percent while grant aid per FTE increased by only 53 percent (The College Board, 2002a). As part of the 1972 amendments to the Higher Education Act of 1965, Congress established the Educational Opportunity Grant, later renamed the Basic Educational Opportunity Grant and then the Pell Grant. Created to establish a “foundation” of financial support to financially needy students, the maximum Pell Grant award continues to be worth less than its peak value in 1975–76 (The College Board, 2002a). In constant 2001 dollars, the maximum Pell Grant award peaked at $4,655 in 1975–76 and declined through the late 1990s, to $2,796 in 1997–98. Although the maximum Pell 63
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Grant award has been increasing in real dollars since 1997–98, the maximum award in 2001–02 ($3,750) is still less than the maximum award in 1980–81 ($3,840 in 2001 dollars, The College Board, 2002a). The decline in the purchasing power of the Pell grant is further illustrated by the reduction in the share of the average costs of attendance (defined as tuition and fees, room and board) that the maximum Pell grant covers. In 2000–01, the maximum Pell grant covered 42 percent of the average costs of attending a public four-year institution, down from a high of 84 percent in the late 1970s, and 16 percent of the average costs of attending a private 4-year institution, down from a high of nearly 40 percent in the late 1970s (The College Board, 2002a). In addition to a reduced commitment to providing need-based grant aid, other reasons for the decline in the purchasing power of the Pell grant include the substantial rate of increase in tuition and other costs of attendance beginning in the 1980s and the increase in the number of individuals eligible for Pell grants which thereby reduced the growth in the award per recipient (Hauptman, 1997). Increased Reliance on Loans Rather than Grants The types of financial aid that are available to students are also shifting, as student financial aid programs are increasingly emphasizing loans rather than grants. Loans, a form of self-paying financial aid, represented 57 percent of financial aid awarded to postsecondary education students (excluding aid in the form of tuition tax credits) in 2001–02, up from 47 percent in 1991–92 and just 41 percent in 1980–81 (The College Board, 2002a). Over the same period, the proportion of student financial aid that took the form of grants declined from 55 percent in 1980–81, to 50 percent in 1991–92, to 42 percent in 2001–02 (The College Board, 2002a). Growth in student loans increased dramatically during the 1990s, largely as a result of the establishment of the unsubsidized federal loans under the 1992 amendments to the Higher Education Act of 1965. The total amount of aid to students through federally supported loan programs (Family Education Loans, Ford Direct Loans, and Perkins Loans) more than doubled during the 1990s, increasing from $19.1 billion in 1991–92 to $42.4 billion in 2001–02 (The College Board, 2002a). About one-half (51 percent) of the federal loan dollars in 2001–02 were unsubsidized (i.e., unsubsidized Stafford loans or PLUS). Unsubsidized Stafford loans differ from subsidized Stafford loans in terms of eligibility criteria and cost to the borrower. Unlike for subsidized 64
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Stafford loans, eligibility for unsubsidized Stafford Loans does not depend on financial need. The cost to students is higher for unsubsidized than for subsidized Stafford loans since interest charges begin accruing (and are added to the principal) at the time unsubsidized Stafford loan funds are disbursed, whereas the federal government pays the interest charges for subsidized Stafford loans while the borrower is enrolled. In addition to increased participation in the unsubsidized loan programs, many students and their families are turning to private-label loans (loans made entirely outside of the government student loan program) from financial institutions to pay for the costs of attending college (Institute for Higher Education Policy, 2003). Similar to unsubsidized Stafford loans, these private-label, or alternative, loans are not contingent upon financial need and interest accrues from the time funds are disbursed. Increased Use of Non-Need Based Criteria to Award Student Financial Aid In addition to providing direct appropriations to colleges and universities (which may be used to reduce the sticker price charged to students), state governments can also influence college enrollment patterns through state-funded student financial aid (which reduces the net price paid by students). State financial aid programs are a relatively small share of the total student financial aid pie, comprising only 6 percent of all aid awarded to postsecondary education students in 2001–02 (The College Board, 2002a). Nonetheless, the amount of financial aid available to students through state programs is increasing. In 2001–02, state grant programs provided $5.05 billion in financial aid to students attending postsecondary education institutions nationwide, a 100 percent increase in real dollars over the amount awarded in 1991–92 (The College Board, 2002a). Research suggests that state financial aid programs may be a particularly effective mechanism for promoting student choice among colleges and universities (Perna and Titus, 2004). Perna and Titus (2004) found that the likelihood of enrolling at different types of institutions in a state is related not only to the amount of state appropriations to higher education institutions and the gap in tuition between public and private institutions, but also to the availability of state need-based student aid. Possibly reflecting the early dependence of most state scholarship programs on support from the federal State Student Incentive Grant program (now Leveraging Educational Assistance Program) (Heller, 2002), the majority of state-funded financial aid is still awarded based on financial 65
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need (National Center for Public Policy and Higher Education, 2002). This balance is shifting however. Between 1981–82 and 1993–94 states awarded about 90 percent of their student financial aid dollars through programs that considered financial need (Heller, 2002), compared with only 78 percent in 1999 (National Center for Public Policy and Higher Education, 2002). States are increasingly devoting resources to merit-based financial aid programs (Heller, 2002). Whereas need-based programs award financial aid to the most economically disadvantaged students, merit-based programs award financial aid to students who meet a specified threshold of academic achievement, a criterion that is positively correlated with family income. Following the lead of Georgia’s HOPE Scholarship Program and Florida’s Bright Futures Scholarship Program, the two largest state-administered merit-based student aid programs, other states (e.g., Alabama, Kentucky, Louisiana, Maryland, Michigan, New Mexico, Texas, and Washington) have recently implemented such programs (Heller, 2002). Since the mid1990s, state funding for merit-based financial aid programs has increased at a faster rate than state funding for need-based programs (Heller, 2002). In constant dollars, nonneed-based state-grant aid increased by more than 300 percent during the 1990s, while need-based state-grant aid increased by only 60 percent over the same period (The College Board, 2002a).
Establishment of Education Tax-Credits The federal government has also signaled a reduced commitment to providing public resources to the most economically needy through the establishment of federal tuition tax credits in 1997. These tax credits include the Hope Scholarship Credit and the Lifetime Learning tax credit. The Hope Scholarship tax credit provides a tax credit of up to $1,500 per student for tuition expenses in the first two years of college. The Lifetime Learning tax credit provides a 20 percent credit, up to $10,000, on the first $5,000 of out-of-pocket expenses for students in the third and subsequent years of postsecondary education. Eligibility for both tax credits is restricted based on income; only families with incomes below $100,000 and single filers with incomes below $50,000 are eligible (Kane, 1999). The 1997 tax changes also eliminated the penalty that is associated with withdrawing funds from an existing IRA when the funds are used to pay the costs of tuition or room and board and provides tax benefits for college savings and prepaid tuition plans. Using data from the Internal Revenue 66
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Service, the College Board (2002a) estimated that the federal government provided $5 billion in aid through the Hope Scholarship and Lifetime Learning tax credits in the 2001 calendar year, a 37 percent increase in constant dollars over the amount provided in 1998. Although almost 6.5 million federal tax filers received the federal education tax credits in 1999, only a small share of the recipients were from low-income families (The College Board, 2002a). Only 14 percent of recipients in 1999 were from families with adjusted gross incomes below $20,000, while 33 percent were from families with adjusted gross incomes between $60,000 and $99,999 (The College Board, 2002a). For several reasons, the tax credits are of less benefit to students from low-income families than for other students. First, the tax credits are not refundable. This means that a family must earn an income high enough to incur federal tax. Second, the amount of the credit is based on tuition expenses only, thus excluding a substantial portion of the costs of attendance, and are less the amount of any federal, state, or institutional grant aid that a student receives. Because most grants continue to be awarded based on financial need, students from low-income families are disproportionately impacted by this requirement (Kane, 1999). Establishment of College Savings Plans As the federal government is developing alternative mechanisms for providing financial support to postsecondary education students via the federal tuition tax credits, state governments are also developing mechanisms outside of traditional student aid programs that assist students from middle-class families with paying the costs of attendance. By providing various federal and state tax advantages, state-sponsored college savings plans (which include prepaid tuition plans, college savings plan trusts, and college savings bonds) represent another way in which the public sector is directing resources away from promoting access to college for underrepresented groups of students while placing greater emphasis on increasing the affordability of college for middle- and upper-income families. After tax liability issues were resolved in the mid-1990s, growth in these programs, particularly college savings trusts, surged during the mid- to late-1990s (Roth, 2001). In 1999, 39 states had some type of college savings program in place and three states had programs pending (Roth, 2001). Roth concluded, based on his analysis, that states established these programs not to increase access and equity but to increase the affordability of higher education for students from middle-class families in the 67
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context of rising tuition and increasing competition for state resources. These programs reflect greater emphasis on the private than the public responsibility for paying the costs of higher education, requiring private resources (particularly parental resources) to be invested in order to gain access to public financial support. Reductions in state appropriations for higher education have created pressure on institutions to increase tuition in order to offset the loss of state revenue. This in turn has placed a greater financial burden on students and their families — a burden felt also by middle-class families who have lobbied successfully for middle-income assistance. The middleincome assistance has come in many forms and has often competed with assistance for students from families of more humble origins. As the focus of financial aid programs shifts increasingly from need- to merit-based, students from lower-income backgrounds increasingly find themselves priced out of higher education. Compounding this is a broader inequity in the funding of public primary and secondary schools. Inequity in finance at these levels has been linked to lower levels of performance and inadequate orientations to college. The first by-product of this inequity, lower academic performance, results in greater proportions of students from less well-funded secondary schools being less competitive for merit-based aid. The second by-product of this inequity in K-12 funding, inadequate orientations to college, often results in ill-informed academic choices and lower levels of completion for those students who do make it to college campuses. We explore this piece of the access puzzle in the following section. CONTINUED DISCONNECT BETWEEN K-12 AND HIGHER EDUCATION CURRICULAR REQUIREMENTS In addition to the trends in the public financing of higher education that are described above, postsecondary educational opportunity continues to be stratified by family income because of the continued disconnect between elementary and secondary education and higher education. Lowincome students are less likely to be adequately academically prepared to attend and graduate from college because of internal school practices (e.g., ability grouping, curricular tracking) and because of differences across schools in the availability of resources (Perna, 2004). A primary barrier to the adequate academic preparation of all students is the continued lack of alignment between the academic requirements for graduating from high school and entering college (Venezia, Kirst, 68
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and Antonio, 2001). In its 1983 report, A nation at risk: The imperative for educational reform, the National Commission on Excellence in Education called for states and high schools to require high school graduates to complete the New Basics curriculum, consisting of 4 years of English, 3 years of math, 3 years of science, 3 years of social studies, and one-half year of computer science. The Commission also encouraged students who expected to go to college to complete two years of a foreign language during high school. Two decades later, high school graduation requirements continue to vary across the 50 states (Education Commission of the States, 1998; Mortenson, 2003). By 2001 only 21 states had adopted the National Commission’s recommended New Basics requirements in English, social sciences, math, and science (Mortenson, 2003). Although the majority of states (44) mandate the minimum level of coursework that must be completed to graduate from high school, five states (Colorado, Iowa, Massachusetts, Michigan, and North Dakota) allow local school boards or districts to determine curricular requirements for graduation (Mortenson, 2003). Some states (California and Wyoming) require the completion of as few as 13 units for high school graduation, while others (Alabama, Florida, and Utah) mandate as many as 24 units (Education Commission of the States, 1998). In 24 states, students must pass an examination in certain subject areas before receiving a high school diploma (Education Commission of the States, 1998). In only two states are high school and college requirements aligned in math; only 10 states have aligned high school and college requirements in English (The Education Trust, 2001). The misalignment of the content of high school assessments and college admission and placement tests further illustrates the disjuncture between high school and college requirements (The Education Trust, 2001). One approach to ensuring that all students have the level of academic preparation that is required to enroll in college and complete a bachelor’s degree is to align high school graduation requirements with college admissions requirements. While seemingly simple, developing a “K-16” approach to education requires a change in the definition and operation of public education from two systems, K-12 and postsecondary, to one educational system with standards, curricula, and assessments that are aligned across successive educational levels (National Commission on the High School Senior Year, 2001). Developing the mechanisms for and removing the barriers to seamless transitions from K-12 education to postsecondary education takes time. 69
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Established in 1995, the Maryland Partnership for Teaching and Learning K-16 was one of the nation’s first explicit K-16 initiatives. The Maryland Partnership for Teaching and Learning K-16 has received external funding for a project that is designed to improve teacher quality, teacher retention, and student achievement through collaboration among 4-year colleges, community colleges, and a public school science and for a project that is designed to improve science teaching and learning through collaboration of high school and college science teachers (Shapiro, 2003). Other states have developed similar programs. Georgia’s P-16 Initiative and Ohio’s efforts with a wide variety of programs focusing on K-16 articulation provide additional examples. Nonetheless, most of the work to date has focused on establishing processes for addressing such tensions as simultaneous pressures to increase both the quantity and quality of teachers, the differential requirements on 4-year institutions versus public schools regarding professional development, public pressure to increase the role of community colleges in alleviating the shortage of qualified teachers, and the implications for remediation that are associated with new statewide assessments (Shapiro, 2003). With their attention to assessing the academic performance of various groups of students and reducing achievement gaps, the current standards movement and other K-12 school reform efforts may increase college preparation, access, and completion for students from underserved groups. But, achieving the academic goals of the federal No Child Left Behind Act of 2001 will require not only a substantial increase in educational funding and support but also a redistribution of funding to equalize disparities across schools ( Jennings, 2003). Many states and school districts lack both the fiscal capacity and technical expertise that are needed to achieve the goals of such initiatives and assist “failing” schools ( Jennings, 2003). The implementation of such reform initiatives must be carefully monitored to ensure that these efforts do not produce such unintended consequences as pushing underserved youth out of the nation’s educational system (Yohalem and Pittman, 2001).
COLLEGE DESTINATIONS —THE NONRANDOM DISTRIBUTION OF ABILITY AND MOTIVATION Many researchers (e.g., Hossler, Braxton, and Coopersmith, 1989; McDonough, 1997) have focused on the structures that determine how 70
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students are sorted into specific institutions and majors. One might assume that the diversity of institutions and freedom of major choice would create myriad opportunities that could be realized purely on the basis of merit — where the most talented and qualified could freely avail themselves to the most resourced colleges and universities. And, to be sure, the nation’s most prestigious institutions — as is true of most institutions — have a vested interest in attracting the best and the brightest students regardless of their social station or ability to pay. But this assumption belies the reality that children from less affluent families are still considerably less likely to attend college even after controlling for aptitude and preparation (Hearn, 2001; Kane, 2001). This issue also begs the question of how we define “merit” in our society. Drawing on several notable sources, Sacks (2003) argues that meritocracy in higher education opportunity is a myth that is perpetuated to preserve the existing class structure in the United States. This is not a new claim, merely updated with more contemporary empirical work. The roots of the powerful effects of social class in the postCivil Rights era education more generally go back to the so-called Coleman Study of 1966 (Coleman, 1966). Since that time many commentators have echoed the theme of classbased inequalities in education and society. Sociologist Jerome Karabel (1999), for example, states that “[m]eritocacy’s dirty little secret is that ‘merit’ in any society is defined by the powerful.” Karabel’s statement reminds us that meritocracy is, by design, a means through which the existing class structure, replete with its inequalities, is preserved while at the same time providing a rationale that everyone, regardless of where they may sit in that class structure, deserves their lot. Merit, at least as it relates to college opportunity in the United States, is an amalgam of standardized test scores, grades, and extracurricular activities that are highly correlated with particular schools which in turn are highly correlated with the socioeconomic status of the families of the children that populate them (McDonough, 1997). While the stratification of opportunity is evident in general collegegoing patterns it becomes much more pronounced when one examines the relative prestige of the postsecondary education institutions that students of different socioeconomic backgrounds attend. Indeed, Sacks’ (2003) essay points to this directly. This stratification stems, in large part, from students’ experiences at primary and secondary schools. As noted in an earlier section of this chapter, K-12 schools in the United States vary widely in their orientation to college and this variance is often problematically correlated with 71
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the socioeconomic and racial composition of their student bodies. Students bring to school certain values and predispositions to education in general and to college in particular, and these values and predispositions are importantly magnified by the primary and secondary school systems. The stratification of higher education reflects broader structural inequalities in American society and unfolds over the course of one’s childhood and early adult life (McDonough, 1997). Thus, interventions that occur at late high school or college admissions junctures are likely too late to remedy the consequences of a lifetime of unequal opportunity. By focusing only on the financial ability to pay the costs of college, traditional federal and state financial aid programs will yield only limited gains in the expansion of access to students from traditionally underserved socioeconomic groups (Gladieux and Swail, 1999). Policies to make college affordable enough to be seen as a realistic option are of vital importance. Such policies, however, do little to address the larger structural bias that discourages and even disqualifies students from families of lesser economic means from attending college, let alone providing access to the best resourced and most competitive institutions — the very institutions that are presumed to convey the largest economic advantages (Kingston and Lewis, 1990). Only by addressing the combination of issues that we tie together in this chapter can meaningful gains in access be achieved. Overall, a greater proportion of young people are attending college than ever before and a record number of degree-granting institutions are serving these students (NCES, 2003). While these facts might be cause for celebration, they mask two important realities. First, while a college degree can confer distinct economic advantages, it comes at a real price — even at the nation’s most affordable colleges. More often than not students seeking financial assistance to help pay for college costs find themselves mired in significant amounts of education-related debt upon graduation (Thomas, 2000; Price, forthcoming). Simply put, the cost borne by students — especially when financed via loans that are repaid over many years — can significantly undercut, and in extreme cases eliminate any economic advantage that students may realize. The extent to which the imbalance between costs and benefits is a concern is determined in part by one’s choice of major and in part by how closely one’s alma mater is aligned with good jobs. So, while existing federal and state financial aid policies are not sufficient to ensure college access and choice for all students (Gladieux and Swail, 1999), such interventions are both necessary and effective in improving access if they are thoughtfully developed and implemented. 72
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A second reality that might qualify our enthusiasm over increasing participation in postsecondary education is that many of these educational opportunities might be better understood as little more than what Brint and Karabel (1989) referred to as “diverted dreams.” Viewed in this way, these new educational opportunities, which include not only community colleges but also for-profit institutions and distance education ventures, have served to take pressure off of the nation’s most prestigious institutions — those that have traditionally served as credentialing bastions for the country’s, indeed much of the world’s, elite. Thus, recent expansion of opportunity, most of which can be accounted for by demand from students from nontraditional backgrounds, can be viewed as a bulwark protecting the institutions traditionally serving students from the nation’s most economically privileged families. These two realities, when taken together, help explain why many economists note that the increased value of the college degree is primarily a reflection of the declining value of the high school diploma (Kane, 2001). Expanding opportunities through loans to students enrolling in institutions with weak connections to the labor market does little to address the growing problems that are associated with economic inequality in the United States. A major point in all of this is that the real value being accorded to increased opportunity and participation in postsecondary education may be somewhat misplaced. While a college degree helped assure previous generations that they would move forward socioeconomically relative to the previous generation, the reality for the current generation is somewhat different. For most, the new economy has helped make the college degree a necessity for maintaining one’s rung on the socioeconomic ladder. Career options for those without college credentials are increasingly bleak. Those unable to attend or complete college are often limited to relatively menial jobs in the service sector that are marked by low pay, few if any benefits, and unstable employment terms. Those who do go on to college, however, will experience wide differences in both the costs and benefits of their attendance. Higher education in the United States has always been highly stratified (Allmendinger, 1975; Gordon, 1990). Despite this stratification, higher education has generally been viewed throughout the 20th century as the primary vehicle for socioeconomic advancement. This belief, especially in the face of the widening abyss between the rich and the poor in the United States, provides a symbol of hope that no matter how great the inequities 73
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of wealth and power, clear “ladders of ascent” remain for those who are ambitious and hardworking (see Brint and Karabel (1989) for a consideration of this). But the expansion of educational opportunity through a dramatically increased number of institutions has, for many new entrants to the higher education system, attenuated the linkage between educational attainment and socioeconomic mobility. To the extent that this attenuation exists, it becomes important to critically examine the question of access generally (and indeed there is no shortage of work in this area) as well as the question of “access to what?” more specifically (Hearn, 2001). This latter question is scarcely addressed in the access literature despite the number of key changes that have occurred over the past 30 years. We examine several of the key changes in the previous sections of this chapter but note here that stagnant or even declining private returns to education in particular segments will inevitably impact overall economic growth — a primary goal of conservatives. This recalls the historical liberal/conservative balance that has simultaneously supported expansion of opportunity and economic growth (St. John and Parsons, 2004). At what point will the ever-widening socioeconomic inequalities in the United States begin to encourage a level of class resentment that ultimately thwarts our goals of economic expansion? More centrally to those in higher education, to what degree will our education system, primary through postsecondary, encourage or impede these inequalities?
RECOMMENDATIONS Keeping these concerns in mind we conclude this chapter with four recommendations for policy. These recommendations are aimed at enhancing access to high-quality postsecondary educational opportunities for all individuals, regardless of their socioeconomic background. RECONSIDER EXISTING FRAMEWORKS FOR DEVELOPING AND IMPLEMENTING STATE HIGHER EDUCATION POLICY Our review suggests the need to reconceptualize the goals and organization of state higher education policies. As visible as major federal initiatives are (e.g., Land Grant Act of 1865, GI Bill of Rights, Higher Education Authorization Act of 1965, etc.) responsibility for implementation of these 74
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policies and control of higher education systems rests with the states. Each state has it own unique sociopolitical context that shapes the way it responds to external environments that influence higher education goals and spending. This results in policy processes and political environments that vary across the 50 states, in some cases dramatically. Thus, no single organizational or political model best deals with the issues we raise in this chapter. Nonetheless, all states to a greater or lesser degree will face expanding enrollments, fights over tuition levels, and policies that are illsuited to the emerging needs of the new fiscal realities outlined in this chapter (Callan, 2002). State policymakers will benefit from thinking more carefully about existing policies and their collective alignment with state needs and goals. If expert observers are correct, state budgets will no longer allow the boom and bust cycles of funding for higher education that have characterized state funding in the past. Changes in state economies are forcing decisions about priorities in state services, that have resulted in higher education being pushed down from its traditional position near the top of the funding list in state budgets. Through careful scrutiny of existing and future higher education policies, individual and collective, states can better ensure that these institutions achieve state education and economic development goals. UNDERSTAND THE CHALLENGES ASSOCIATED WITH SETTING TUITION LEVELS Callan (2002) notes that there is no other issue on which “expert” opinion so directly contradicts the public will. The expert opinion weighs heavily toward the “high tuition-high aid” model while the general public clearly favors low to moderate tuition with financial aid for academically qualified and needy students (Immerwhar, 1998). Although keeping tuition low has been shown to promote access, such a strategy has become politically infeasible given institutional dependence on tuition and fee revenue (Stampen and Layzell, 1997). The immediate alternative to the “lowtuition” model is the high tuition, high aid approach in which institutions set their tuition closer to the total cost of instruction and then provide student aid to ensure affordability for students from all socioeconomic backgrounds. Budgetary realities driving recent trends in state higher-education finance suggest that states will continue to move to a high tuition approach to funding the costs of higher education. The high tuition, high aid model 75
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has been shown to be more economically efficient than its low-tuition counterpart (under which all students are subsidized to the same degree regardless of socioeconomic background) but its effects on access are unclear (Stampen and Layzell, 1997). In order to make the high-aid model effective in terms of improving college access for students from low-income families, states must work to explicitly link need-based financial aid policies to state appropriations and tuition. Research shows that only a small number of states have policies that formally link tuition levels at public colleges and universities with state appropriations or state student aid (Hossler, Ramin, Westfall, and Irish, 1997), and that such policies are difficult to establish and sustain. Zumeta (1992) reports that higher education officers in 17 states believed that state tuition and state student aid policies are closely linked and found that tuition at public institutions is positively correlated with state funding for student aid. However, Hossler and colleagues (1997) conclude that appropriations for student aid are viewed as more discretionary than are appropriations for public institutions. Moreover, they conclude that student aid appropriations are unrelated to dominant political values, tuition at public institutions, and self-reported efforts to link financial aid appropriations to tuition levels at public institutions (Hossler et al., 1997). These and other studies point to the political challenges of linking financial aid appropriations to tuition levels, regardless of state economic conditions. The high-tuition model will only be as effective as the linkages to high aid are strong. KEEP A CLEAR FOCUS ON THE PUBLIC BENEFITS OF INVESTMENTS IN HIGHER EDUCATION As Kane (1999) observed, arguing for greater public support for higher education is difficult in the context of increasing competition for public resources and growing gaps in earnings by educational attainment. The monetary and non-monetary benefits to society of an investment in higher education are substantial. Although Hansen and Weisbrod (1969) concluded from their benefit–cost analysis of higher education in the late 1960s that the present value of the public subsidy for higher education exceeded the present value of the increased taxes resulting from higher levels of educational attainment, more recent analyses have generated different conclusions. For example, based on his benefit–cost analysis of Fijian higher education, Heaton (1999) concluded that public investment in higher education 76
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results in substantial economic benefits to both the public and individual participants and that the net financial returns are comparable for individuals and society. An analysis by Vernez, Krop, and Rydell (1999) suggests that the costs of raising the educational attainment levels of Blacks and Hispanics to the level of Whites would be repaid by the long-term reduction in the costs of public transfer and social-support programs, the increase in tax revenues, and the increase in individual earnings. Further evidence comes from Leslie and Brinkman’s (1988) integrative review of prior research from which they express little “doubt that very many public expenditures would yield greater returns from additional public spending than would increase spending for higher education” (p. 186). ENCOURAGE LINKAGES BETWEEN K-12 AND POSTSECONDARY POLICIES STATE AND FEDERAL LEVELS
AT BOTH THE
Inequitable and inadequate academic preparation for college is perhaps one of the greatest structural barriers to access (Perna, 2004). For those who do make it to the college campus with inadequate preparation, many will require remedial coursework and will be at a much higher rate of risk of dropping out before completing a degree program (McDonough, 1998; Venezia, Kirst, and Antonio, 2003). At a minimum, college officials need to be involved in discussions related to K-12 standards, while K-12 officials should similarly be involved in discussions about higher education admissions and placement requirements. Stanford University’s Bridge Project offers a number of useful policy recommendations that include: better dissemination of colleges’ academic standards; reviewing the alignment of K-12 exit-level standards and postsecondary placement exams; assessing the validity and reliability of college placement exams; sequencing undergraduate general education course with the appropriate senior-year high school course; expanding dual enrollment programs to include all students — not just the traditionally college-bound; and expanding federal grants to stimulate more state-level K-16 policymaking.
CONCLUSION Efforts to reduce the stratification of educational opportunity are likely to be met by actions that are designed to maintain class distinctions 77
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(Oakes, Rogers, Lipton, and Morrell, 2002). Specifically, middle- and upper-income families will likely respond to initiatives that refocus public resources toward individuals from lower-income families by working to secure additional resources that benefit their children and by identifying additional mechanisms that preserve class stratification (Lucas, 1999; Oakes et al., 2002). Moreover, effectively refocusing public policies in ways that reduce inequalities in postsecondary educational opportunity may require a shift in the current dominant political position, a conservative position that emphasizes self-payment of educational costs and awarding of financial aid based on academic criteria rather than financial need, instead of the structural barriers that limit opportunity for certain groups. Nonetheless, policymakers, educators, researchers, and others who are troubled by the persisting stratification of postsecondary educational opportunity must not be deterred by the political obstacles. Greater progress in equalizing postsecondary opportunity must be made if the United States is to maintain its economic, military, agricultural, and industrial dominance globally and fully realize the range of societal benefits that accrue from higher education. Although eliminating the stratification of postsecondary educational opportunity in the United States will also require attention to the structural barriers that limit persistence to degree attainment, considering the ways in which current public policies may be reconfigured to better ensure college access and choice for all students is essential.
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3. A CULTURAL ANALYSIS OF SHARED GOVERNANCE: THE CHALLENGES AHEAD* William G. Tierney University of Southern California
INTRODUCTION Throughout the 20th century the concept of shared governance has held a prominent place in the culture and mythology of academic organizations. Indeed, when one speaks of the structure of colleges and universities an inescapable discussion revolves around participative governance. For some, shared governance is a central totem of the academy; if academe did not have shared governance, then one’s conception of a college or university inevitably would change. For others, shared governance is the root cause of many of academe’s problems; if administrators were able to eliminate or overhaul academe’s governance structures, then postsecondary institutions might become more strategic and efficient. In doing so, administrators would be better able to deal with the myriad problems that currently exist for colleges and universities. At least three issues arise with regard to these differing perceptions of shared governance. First, the tenor of the literature on shared governance often reads like either a call to arms or a funeral oration. Whether one wants to reinvigorate shared governance or destroy it, the discourse is frequently overheated and bombastic. “The classic strategy,” wrote Joanna Vecchiarelli Scott (1996) in describing recent changes, “is what might be termed a stealth
* The author wishes to acknowledge the helpful comments of Neil Hamilton, George Keller, David Leslie, Yvonna Lincoln, and James Minor. J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XIX, 85–132. ©2004 Kluwer Academic Publishers. Printed in The Netherlands.
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attack on governance launched under cover of summer vacations” (p. 724). In another article Scott (1997) portrayed the takeover of governance as a crime scene (p. 28). Victor Baldridge (1982) wrote that “we hear much weeping about the loss of shared governance” (p. 13). Faculty senates are “dysfunctional” (Leatherman, 1998, p. A8) to others, and, adopting a medical metaphor, critics suggest that the patient (the institution) is dying, and in need of a transplant; the need for governance reform is “urgent” (Association of Governing Boards of Universities and Colleges, 1996). Second, although there is a great deal of hand-wringing about shared governance, the vast majority of the literature is anecdotal and atheoretical. When thoughtful studies of governance have been done they are usually at the state level and they have less to do with governance per se than with ways to enhance state-wide coordination (Ewell, 1985, 1990; McGuinness, 1994; Richardson et al., 1999). As Dill and Helm (1988) have noted, there is very limited contemporary research on governance structures (p. 327). Instead, scholars have tended to focus on leadership, defined as the college presidency (i.e., Birnbaum, 1988) or on decisionmaking (i.e., Schuster et al., 1994; Leslie and Fretwell, 1996). The lack of theoretical frameworks denies us the ability to diagnose governance from a particular vantage point, which in turn forces suggestions for improvement to be based on intuition rather than a logically nuanced framework. Third, shared governance is a term that is casually used with implicit meanings and little intellectual rigor. Indeed, more often than not, authors who use the concept neither build on previous definitions nor bring into question what has been incorporated into, and what has been excluded from, the term. Shared governance is a concept that has assumed an honorific stature in most academic writing. Even those critics who wish to dramatically change governance processes quite frequently cling to the desire to call those changes a permutation of shared governance. Thus, for some individuals shared governance is ahistorical and simply means what one desires it to mean. For others, shared governance is a static concept that was enshrined by the American Association of University Professors (AAUP) in 1967. On the one side, then, are fundamentalists who subscribe to a literal, unchanging interpretation of the term. On the other side are scholars who are the equivalent of postmodern deconstructionists, who believe the term changes based on current contexts. My purpose here is to shed light on these various meanings of shared governance, and to explicate the underlying premises, problems, and challenges. I take issue with many previous definitions of shared governance, 86
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not for what they say, but for what they leave out. As I will elaborate, governance in any organization is a process devised to achieve particular outcomes. If the problems that academe currently faces are to be resolved, one needs to question the processes used to resolve these problems. One also needs to be certain of the core values that circumscribe an organization. Values are not processes; they are beliefs and goals that lead to outcomes. Processes, however, are symbolic of the organization’s culture. They are emblematic of what the organization’s participants believe is important. As symbols, processes such as shared governance are embedded in socio-cultural contexts that undergo constant reinterpretation due to the entrance of new participants who bring new meanings to the organization’s culture. And yet, these symbols underscore the values of the organization. The literature is replete with examples about how colleges and universities differ from standard organizations. A goal of a large company, for example, will be based on profit, whereas the same cannot be said about a traditional college. A belief that customer satisfaction is a key value may be central in a company such as Wal-Mart, but in a university the usage of the term “customer” may be anathema. I will suggest that there are values that can be delineated for a college or university, and in doing so, one can then suggest the parameters of shared governance. I will argue that the core values of academe enable an institution’s participants to maintain an identity, and that these values are neither static nor illusory. In effect, I will challenge the thinking that a statement made a generation ago is not open to reinterpretation, but I also will question that such a reinterpretation is open to any definition an author wishes to provide. I will argue that shared governance as a symbolic process underscores fundamental values of the academy. Rather than conflate a process — shared governance — as a static structure we need to be cognizant of the values embedded in the idea of governance and ensure that such values remain constant as structures and processes adapt to the times. I will advance this argument in three parts. I first discuss previous definitions of shared governance and point out how the definitions do not so much contradict one another as these definitions take up entirely different issues. I then consider the frames of reference that have been employed to analyze and define shared governance. I conclude with a discussion of the problems and concerns that have been elaborated with regard to shared governance, offer possible ways to ameliorate those problems, sketch the lineaments of what I will define as a cultural definition of shared governance, and finally, offer suggestions about areas in need of research. One note of 87
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caution: I will use the organization as the unit of analysis, and I call upon the literature on shared governance that pertains to 4-year colleges and universities. As I discuss at the conclusion, I entirely concur that similar explications of shared governance need to occur with regard to community colleges, state systems, and the burgeoning number of for-profit institutions. At the same time, the vast majority of literature on shared governance deals with 4-year institutions; my first project is to consider the literature that exists in order to develop scaffolding for a cultural analysis of shared governance, and a sense of promising research areas.
DEFINING SHARED GOVERNANCE The point of departure for most discussions about shared governance is the statement written and endorsed by the AAUP in 1967 and “commended” by the American Council on Education (ACE) and the Association of Governing Boards (AGB). The authors of the document recognized that a variety and complexity of tasks performed by institutions of higher education produced an “inescapable interdependence” (2001, p. 218). The argument was put forth that although different decisions might be made by one or another constituency, some decisions necessitated “the initiating capacity and decision-making participation of all the institutional components” (2001, p. 218). The document relied extensively on a definition of governance that pertained to who shared in decision-making. In 1998 AGB came forward with its own endorsement of a definition of institutional governance. The authors of the AGB report studiously avoided using the term “shared governance.” AGB began by pointing out that much had changed since the 1967 AAUP statement. The authors opined that reduced fiscal resources, greater demands of accountability, competition from new providers, and a host of related issues necessitated a new statement on internal governance. The assumptions that drove the text was that “internal governance arrangements have become so cumbersome that timely decisions are difficult to make, and small factions often are able to impede the decision-making process” (Association of Governing Boards of Universities and Colleges, 1998, p. 5). The result, claimed AGB, was that even if decisions were reached on a particular issue, because of the search for consensus, the least-objectionable option was frequently chosen. Although the AAUP and AGB statements are not diametrically opposed to one another, there are significant differences. The AGB report 88
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portrayed a more hierarchical organization in which a board had ultimate authority to make decisions and the faculty were one of many stakeholders. The AAUP statement assumed a flatter organizational structure in which faculty, administrators, and the board discussed issues with one another in a more collegial process. The AGB statement also tended to rely more on a market-driven mission for academe in which the board decided its strategic plan in consultation with the president, and the AAUP authors opted for a jointly formulated strategic plan that focused on traditional conceptions of the university. In a carefully nuanced analysis Neil Hamilton (1996) compared the two statements and concluded that they “share much more common ground than the language of each suggests” (p. 26). He pointed out that the AAUP always had agreed that ultimate responsibility for the determination of the mission lay with the board, and that the AGB report still ceded to the faculty the greater say with regard to curricular decisions and faculty appointments. Hamilton (1999) also cautioned the various academic communities not to devolve into an “us versus them” mentality. He encouraged all groups to accept the responsibility of the public trust for colleges and universities and defined that trust as the inextricable connections of “mission, academic freedom, and shared governance” (p. 26). Hamilton touched on a helpful point that is often overlooked: what is the purpose of governance in general, and shared governance in particular? Oftentimes authors speak of shared governance as an end, rather than a process. For Hamilton, the mission of higher education is the creation and dissemination of knowledge. The role of shared governance is to help achieve those purposes. The search to cut costs and to be effective and efficient are important principles, Hamilton argued, but they are not the mission. And yet, even Hamilton conflated shared governance with “mission” and “academic freedom” as if shared governance were an end in itself, or the only possible structure that would enable an institution’s participants to achieve its mission. Presumably, without shared governance, academe would not be academe. One needs to make a careful distinction between the values of an organization and the symbols that express those values. If one assumes that the symbol, the artifact, is the actual value, then one has little ability to create change. Consider, for example, the manner in which the Catholic Church conducts Mass. A half century ago the altar was turned away from the congregants and the priest spoke in Latin. Those symbols expressed values of the Church; when the Church decided to turn the altar around 89
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and have the priests speak in the local dialect, the values of the Church did not change, but the symbolic processes did. To be sure, the changes caused consternation among more than a few individuals, but the Church’s purpose in doing so was to try to enrich its long-standing values with symbolic meaning for parishioners of the 20th century. Symbolic change frequently causes anger and resentment because many consider the symbol to have substantive meaning and value. Consider the current debate about whether women can be priests or if priests can marry. The argument revolves around the meaning of the symbolic change. Celibacy among men is merely an outmoded symbol to some congregants, and to others the symbol has actual meaning and purpose. The assumption is that when one changes the symbol a value of the organization changes as well; the challenge for those who drive change is to ensure to the various participants that the core values of the organization remain. Thus, the change of a symbolic process is most often not easy, but one also ought not to assume that symbols are unchangeable. Martin Trow (1998) disagreed somewhat with Hamilton on the purpose of governance. He offered two overarching principles: “These two principles are the maximization of the University’s autonomy — its capacity to direct its own affairs; and second, the pursuit of preeminence” (p. 202). Although one might assume that Trow was speaking about academic freedom when he mentioned autonomy, he actually had a different value in mind. Autonomy referred to the removal of politics from academic decisions so that the university might be a meritocracy. The pursuit of preeminence also had less to do with fiscal stability than with academic quality. Shared governance, then, inoculated the university from political interference and enabled the faculty to pursue excellence. The framework for excellence was defined as a meritocracy, and an effective system of shared governance ensured that evaluation occurred by judging the merit of one’s work. One should note that Trow’s work focused primarily on public institutions, whereas the AGB and AAUP statements were intended for all institutions. Henry Rosovsky (1990), former dean of the faculty at Harvard, offered a slightly different assessment. He noted that governance should improve the capacity for teaching and research (p. 276). Governance also pertained to power, argued Rosovsky: “who is in charge; who makes decisions; who has a voice, and how loud is that voice?” (p. 261). Governance, to Rosovsky (2001), was the formal and informal arrangements of power and authority that enabled decisions to get carried out (p. 95). Cynthia Hardy (1990) also 90
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relied less on the philosophical purpose of governance and more on its function: “governance is used to refer to the process of making academic decisions” (p. 393). Barbara Lee (1991) further defined the function of governance “as the way that issues affecting the entire institution, or one or more components thereof, are decided” (p. 41). In part, these various interpretations of academic governance appear a bit like the proverbial blind man describing an elephant: the position of the author determines what the individual will write about and how he or she will describe the shared elephant. One might expect a professional organization concerned with faculty such as the AAUP to call for a greater commitment to shared decision-making, and for an association composed of corporate business people such as the AGB to be concerned with fiscal security. A former dean of the faculty at a private institution may well think of governance as an internally defined political exercise, whereas a professor in an elite public institution may be concerned with helping the institution move up in the rankings, increase its prestige, and remain insulated from external interference. These disparate definitions frequently conflict and collide with one another. One way to highlight the differences among the various definitions is to consider how to evaluate whether or not an institution has an effective governance structure based on the interpretations that have been outlined. From an AAUP perspective, “the ideal governance model is one in which collaboration among the various governance components is the rule” (Ramo, 1998, p. 6). In this light the process of governance is what matters. Outcomes are irrelevant. One might, for example, see the institution slide into fiscal jeopardy, but claim that as long as the various constituencies collaborate, there is good governance. To be fair, the implicit assumption is that shared governance ensures “good” outcomes — but those outcomes are neither explicated nor have they been tested. The AGB will obviously disagree that outcomes are irrelevant. They might argue that processes are less important than ensuring that the institution is fiscally secure. A concern for academic freedom or the improvement of teaching would be incidental — except as they pertain to the enhancement of the fiscal stability and health of the institution. Rosovsky’s approach would investigate how governance has helped or hindered teaching and learning, whereas Trow would hinge the assessment on academic excellence, which at a research university frequently has little to do with teaching. Presumably if teaching and learning were not improving, or if the institution were not rising in the ranks, then one could 91
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justifiably question why the governance structures were failing. The assumption, of course, is that governance enables (or impedes) quality. Teaching, research, institutional quality, does not occur irrespective of the structures in which they are embedded. Simply stated: governance matters. Thus, from Hardy and Lee’s perspectives one will study the processes of governance to determine how one might improve what takes place. What is missing from their definitions, however, is how one assesses “good” governance. If one looks at the functions of the various processes of shared governance, what indicators might one use to ensure that it is functioning effectively? Is an absence of conflict, for example, an indicator of good governance or a moribund campus? Is an organization that is fiscally stable an indicator of a strong-willed administrator or a viable governance structure? Nevertheless, the assumption of all of these disparate definitions is that governance structures make a difference. Curiously, there is very little research to support such an assertion, but virtually everyone assumes that governance is the engine that drives reform. My concern is that unless individuals and constituencies work from common understandings of shared governance everyone will repeatedly be at odds with one another. Accordingly, in what follows I outline the frames of governance in order to develop more fully a sense of what an overarching definition of governance from a cultural perspective might be.
FRAMES OF REFERENCE One might analyze academic governance from any number of frameworks. In what follows I consider the most common frames that authors have utilized. AN HISTORICAL FRAMEWORK As with any topic, an understanding of the roots of an issue lends insight into how a topic has changed over time. As I commented above, such an observation is particularly germane in discussions about shared governance insofar as today’s participants frequently speak of governance as if what exists on their campus is the way governance exists everywhere and for all time. An historical lens points out significant discrepancies as well as continuities. As I will elaborate below, today’s critics often paint current boards of trustees as if they are a historical aberration because the 92
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membership represents the business world. However, business people have dominated boards of trustees for more than a century. Similarly, those who seek to imbue faculty senates with more power often suggest that such structures have been historical focal points for power and authority, whereas most senates have come into existence in the last half century. An historical analysis is helpful in enabling students of governance processes to gain a sense of how different constituencies and structures have changed over time. John Beach (1985) observed, for example, that in the 12th and 13th centuries the University of Bologna was thought to be composed of the students; the faculty were hired servants who either succeeded or were fired without recourse to appeal or renewal (p. 304). In Paris the opposite was the case. The faculty ran the institution and students attended the institution to learn. In the Middle Ages the Church thought of universities as purveyors of ecclesiastical doctrine; academic freedom would have been thought of as heresy. The Church originally granted permission for a university to open; only later was the emperor or king also endowed with the power to grant a charter. Such a charter permitted a form of self-governance in which the medieval professoriate functioned at a distance from the church structure as well as the state. If there is one vestige of historical import that has framed academic life in the 21st century it is the movement toward the establishment of a corporation with a lay board. The result has been twofold. On the one hand, the university has been relatively removed from the vagaries of public life. True, campuses have long been buffeted by the winds of change in their surroundings. Nevertheless, whether one speaks of the Reformation or the McCarthy era, however much intrusion existed, such interference was less for universities than for non-academic organizations that were wedded to the state. To be sure, during the reign of Henry VIII and his successors, as with today’s tension in Catholic institutions, there have been conflict and demands from external agents, but over time such problems have worked out relatively well with regard to self-governance. On the other hand, a lay board also removed the faculty from direct governance of the institution. Although over time some institutions have allowed a representative or two from the faculty to sit on the board, the faculty by and large have never been the legal overseers of the academic corporation. Even the AAUP has never called for a change in such an arrangement. The overall control of an American university lies in the “trust” of the board. 93
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One also might point out that American higher education reflects a uniquely Western European mode of organization. Although the first postsecondary institutions in the Americas were in Mexico and Latin America and were of Spanish origin, colleges and universities in the United States derive their identity from the United Kingdom and Germany. The establishment of colleges and universities in the colonies followed a European model and extended what the respected historian Walter Metzger (1987) referred to as “laicization” (p. 13). That is, American institutions extended ever further the assumption that non-academic/nonclerical individuals had formal authority over the governance of the institution. The other change that has continued throughout the history of the United States is that of privatization. Few countries have such an elaborated structure of private institutions that derive their support from nongovernmental sources. The implications for governance, of course, are significant. As the Dartmouth College case established, the state has no formal control over the organization of a private institution other than the ability to grant the institution legal authority as is done with any corporation. The board of a private college or university has no relationship to the state, and interference from the state is even further removed than at public institutions. Over time, of course, those individuals who have represented the interests of a particular constituency on a board have changed. Over a century ago the clergy dominated boards in ways that simply do not occur today; agricultural interests were better represented in the 19th century than the 21st. Representatives from society such as magistrates and judges have been well represented on boards. Currently, individuals are frequently chosen not because they are able to offer a religious aura or judicious advice, but because they have accumulated wealth. Insofar as wealth resides more with businesspeople than with, for example, teachers or truck drivers, a particular strata of society gets represented on boards, but as I discuss below, such participation has existed for a century. Although one may not need to return to a study of the Middle Ages whenever one wishes to change a particular aspect of current governance procedures, an understanding of the various phases of governance over the past century is helpful insofar as distinct phases have come and gone. The development of the concept of shared governance can be traced to about 1960. At that time John Corson defined governance in higher education as the authority to create rules and regulations concerning the governing of the academy and the relationships among various constituencies with the 94
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organization. Such an interpretation had its antecedents more firmly planted in the 20th century than throughout the ages. Dill and Helm (1988) have spoken of three periods of governance in the modern era: faculty control, democratic participation, and strategic policy-making (p. 321). Faculty control most closely resembles what the AAUP referred to in their statement on governance. The underlying assumption of the AAUP about postsecondary institutions in the United States from the early part of the 20th century until the 1960s was that the faculty controlled the institution. The college or university ran as a collegium and the faculty as a whole determined the direction of the organization. At times, scholars such as Thorstein Veblen (1918/1957) or Upton Sinclair (1923) railed against the intrusive nature of corporate America, but by and large the sentiment that existed about universities and colleges was that the faculty had a considerable voice in the institution. The administrative structure often was meager, and those individuals who were presidents were likely to be seen as leaders of the faculty rather than members of a separate entity. To be sure, part of the view of a college or university as a collegium in the early 20th century is a romanticized vision of the past. Robert Hutchins, Herman Wells, and John Hannah, to name but a few university presidents during this period, exerted control over their institutions in a manner unheard of today. At the same time, the faculty organized themselves as professions during the 20th century in ways that had not previously been done in the United States. If faculty had not become professionals in the first half of the 20th century, then the second period of governance most likely could not have taken place. Democratic participation had its genesis in the late 1950s and 1960s. The rise of faculty assemblies, faculty senates, and collective bargaining took hold. One is always able to debate the cause of an innovation, but certainly the rapid growth of higher education, a considerable influx of new students and faculty into academe, and the social and cultural events that were occurring in society led to a desire for discussions about how to make academe more representative. As Dill and Helm (1988) noted, “particularly at the most prestigious colleges and universities where faculty controlled the governance process, the dominant coalition of faculty members and administrators was confronted by demands to democratize the governance process and to include students and other disaffected constituencies in traditional faculty senates” (p. 322). The result was that structural changes took place that ostensibly allowed for greater participation in academic governance than had previously been possible. 95
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The rise of new institutions and collective bargaining also led to new twists in governance patterns. Community colleges, and teachers colleges that became state colleges or universities, did not have the history of governance that had been established at more traditional institutions. Of consequence, administrative, legislative, and bureaucratic forms of control were more easily established in these new organizations. Collective bargaining arrangements frequently redefined who was to participate and who might be considered “faculty.” Librarians, for example, increasingly were included in collective bargaining arrangements and thought of as faculty who had a right to participate in governance. Thus, throughout the 1960s and 1970s there was a rapid rise in the formalization of governance under new arrangements even though the basic premises remained the same. In the past 20 years, however, there has been a significant change in governance patterns. The experimentation in democratic forms of governance has most likely seen its heyday. The formalization of authority in a faculty senate or academic assembly also has branched out to other decision-making venues as strategic policy-making has risen in importance. Again, one might attribute these changes to any number of factors. With few exceptions, for at least a generation postsecondary institutions have faced fiscal shortfalls that have led to calls for more managerial involvement. Boards of trustees have become increasingly populated with more activist businesspeople who have expected colleges and universities to more closely resemble businesses. The country itself has become less interested in broad patterns of democratic participation such that the kind of governance structures one experienced on many campuses in the 1960s would seem like an anachronism today. The result is that when faculty participate in governance they do so in multiple venues such as ad-hoc committees or joint committees with administrators. As Dill and Helm (1988) summarized, “The tenets of faculty control and democratic participation were articulated during a period of growth and general prosperity for American higher education. The current environment of scarcity and competition is thus strange to both governance perspectives” (p. 324). Their debatable assumption, of course, is that faculty control and democratic forms of governance are anathema to dealing with an array of problems that arise during periods of fiscal shortfalls. More flamboyantly, and without any supporting data, Amacher and Meiners (2002) also concluded, “The notion that there is some sort of collective wisdom in the faculty that justifies democratic decision-making 96
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about most spheres of university operation is nonsense” (p. 34). Such an assertion, although certainly dyspeptic, is important because it represents a particular point of view about the need for a radical rethinking of what one means by shared governance. Thus, one frame of governance comes by way of competing historical perceptions. A second framework to which we now turn pertains to the contexts and structures of governance that have been investigated. Context concerns institutional type, and structure to the unit of analysis under study. CONTEXTS AND STRUCTURES AS A FRAMEWORK It is a truism of research in higher education that the overwhelming amount of investigations that have been done are about the kinds of institutions where the researchers reside (Tierney, 1999). That is, most scholars who do research on higher education work in research universities, and most research looks at various issues that pertain to research universities. The same point may be made about research on governance. As noted, there is very little empirical work on governance in community colleges. Although for-profit institutions are relatively new phenomena, they also are not being investigated in any systematic or comprehensive manner. State systems of higher education have a robust literature, but most of the literature looks at the organization of the system to the state and compares that organization to other states (Richardson et al., 1999). There is virtually no research, for example, on the role of faculty, students, or community members on state boards. Similarly and commonsensically, one also studies that which can be studied. Thus, there are very few works that have investigated in any rigorous manner members of boards of trustees. The most extensive body of research derives from the research arm of the AGB. Chait, Holland, and Taylor (1991, 1996) also wrote two works on the role of boards of trustees in institutional governance, and William Bowen (1994) offered armchair advice about board effectiveness, but other than their studies, most research on governance has looked elsewhere. A small body of research also has looked at nonprofit boards (Chait and Taylor, 1989; Taylor, Chait, and Holland, 1996), which has included a discussion of postsecondary boards. Gaining entrance to a board is frequently a hurdle that researchers cannot overcome, so even though boards are a critically important component of governance, they are also the least studied structural configuration 97
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in academe. When boards are studied the manner of investigation is most often neither through interview nor case study, but through document analysis. Hubert Beck, for example, studied the economic and social composition of governing boards in 1947. In many respects he followed up on a study that Scott Nearing conducted in 1917. Nearing concluded, as did Beck 30 years later, that “the college and university boards are almost completely dominated by [business people]. A new term must be coined to suggest the idea of an educational system owned and largely supported by the people but dominated by the business world — plutocratized education” (1947, p. 9). Earl J. McGrath (1936) undertook a similar study by using the same manner of analysis and arrived at the same conclusion: “The control of higher education in America, both public and private, has been placed in the hands of a small group of the population: namely financiers and business people” (p. 266). Around the time of the Civil War, observed McGrath, the clergy accounted for close to 40 percent of membership on boards, but 70 years later their numbers had dropped to less than 10 percent. Thomas, Pusser, and Slaughter (2002) continued this line of investigation in the late 20th century and came to similar conclusions. Edwin Duryea and Williams (2000) also presented a historical analysis of boards, and Holly Madsen published an AGB paper that discussed the composition of governing boards. Conversely, one is hard pressed to find an article on governance that does not mention an academic or faculty senate. Indeed, when one speaks of governance, the senate is often used as a synonym for governance, as if faculty senates are the only governance structure for higher education. Martin Trow (1990), for example, wrote of senates as key (p. 23). Gilmour (1991b) argued that governance — the senate — was more effective than one presumed (p. 16). Williams et al. (1987) noted that “the key to successful faculty participation in policy probably lies in a sophisticated refinement of the representative assembly already found on some campuses — the faculty senate” (p. 632). They went on to warn that if governance were to remain stable, “faculty members will have to devote time and energy to senate activities” (p. 632). Barbara Lee (1991) undertook an analysis of surveys of faculty attitudes toward campus governance and equated governance with senate involvement (p. 41). Thirty years ago an AAHE (1967) report rationalized that “faculty participation in campus decision-making requires formal arrangements through which faculty influence may be exercised” (p. 24), which assumed a formal structure governed by the 98
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faculty. Richard Chait (2002) also did a study of the role of tenure in governance and found that campuses with tenure had faculty who were more active in governance. David Hollinger (2001) also has written optimistically about governance by saying, “the Berkeley senate is one of the most powerful in American higher education” (p. 30). Thus, the senate at the research university has been almost exclusively the unit of analysis under investigation. Such an assumption, of course, is troubling for at least four reasons. First, senates are a relatively new organizational structure, so to equate governance with a senate is to forget the historical basis for academic governance. Second, academic senates often get discussed as they exist at private and public research universities when in reality more than half of academe does not resemble such an organizational type. Third, to speak only of senates and to overlook boards is akin to speaking about governance in the United States by analyzing the U.S. Senate and ignoring the House. And finally, as noted above, even faculty participation has broadened considerably from simply a legislative forum such as a faculty senate. As I will elaborate on, a cultural framework guides the analyst about ways to think of governance so that governance is more than simply one or another structure. Before we turn to a discussion of a cultural model, however, I consider another framework that has been utilized in studies of governance. CONSTITUENCIES AS A FRAMEWORK Given the foregoing discussion one ought not to be surprised that the group that is most discussed with regard to their participation in governance is the faculty. Perhaps most odd, however, is the paucity of research and discussion about the role of students and external constituencies in governance. Except for a brief burst of discussion in the 1960s, when students demanded a say in the running of the institution, students have been silent partners in academic life. The point is not merely that those who conduct research on higher education have fetishized their own role in governance, but that ignoring the student role in governance implicitly defines governance in a particular manner. Just as discussions of governance from one perspective or another assume that governance is important, when one studiously ignores a constituency, the assumption is more than that they “should” not have a role. By their absence, the point is made that they do not have a role. 99
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The literature that exists about student governance is generally confined to student affairs journals. Student participation in governance refers to the activities of student government; there is no sense of shared governance insofar as the sharing is seen as a tripartite arrangement across the board, the administration, and the faculty. Students are defined as undergraduates, and the graduate student role in governance is neglected. Even in the 1960s when individuals lobbied for a student voice in governance the point was to add a student or two to a committee, not to give the students a structural voice akin to a faculty senate. Two points are worth mentioning here. First, one ought not to overlook how Ameri-centric the research has been on academic governance. If one looks abroad either to Latin America or to Europe, there is a long tradition of the inclusion of students in the governance processes of the institution. My suggestion is not to argue that students should be included in governance in one way or another, but that within the United States researchers have constructed governance processes in a particular way that more closely resemble corporate models of governance rather than those founded on principles of communality. Even the most inclusive of organizations, the AAUP, has stated in their commentary: Ways should be found to permit significant student participation within the limits of attainable effectiveness. The obstacles to such participation are large and should not be minimized: inexperience, untested capacity, a transitory status which means that present action does not carry with it subsequent responsibility. . . (2001, p. 267).
One need not be a literary theorist to translate such a comment as one that reflects little role for students in the actual running of the institution. Student participation may impede “effectiveness.” The obstacles are “large.” Students do not have experience in governance, they are untested, and because they will exit the institution within a matter of years they are not responsible for carrying out the actions that are decided. One, of course, could raise related concerns with either the administration or the faculty. The average tenure of presidents is approximately 5 years, so the decisions they make are often not the ones that they must carry out. Faculty leaders often come to such roles with little, if any, experience. If a prerequisite for leadership is that an individual not be “transitory,” then presumably any number of professors or administrators would be unable to participate insofar as successful academics are frequently on the move. 100
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Again, the point is not to suggest that the path to student participation in the governance of an institution is easy or even warranted. However, one ought to acknowledge the socially constructed nature of this academic universe. For example, Deep Springs College has existed for close to a century in the California desert with a radical form of governance: students run the college. They choose the president, pick the faculty, and determine the curricula. Only the Board of Trustees faintly resembles what exists in most institutions (Tierney, 1993). Here, then, exists an institution that stands governance on its head. The assumptions of the AAUP document are flatly rejected, and if one were to study Deep Springs, of necessity one would need to discuss the role of students in the governance of the institution. Self-governance is a key precept, a raison d’etre, of Deep Springs. My second point, then, is that over the last generation there has been considerable discussion about the nature of inquiry. Broadly stated, history pertained to analyses of great men, not women; minorities seemed not to exist if one were to read about any number of components of 19-century America. My concern is similar when we look at the research on governance in higher education. If one is to look at such research one needs to consider what exists, but also what — and who — is absent. Such a suggestion points up the theoretical frameworks upon which the research rests, and to this we now turn. THE RESEARCH FRAMES OF GOVERNANCE What have been the methodologies and theoretical frameworks employed when studying governance? The methodological question is simply answered. There have been virtually no national surveys of governance, although the AAUP did a study in 1971 that has recently been replicated (Kaplan, 2002), and another national survey is underway (Tierney and Minor, 2002). Most quantitative studies have been surveys of fewer than 200 faculty or administrators at an institution or two (e.g., Williams et al., 1987; Miller, McCormack, and Newman, 1996) or a randomized sample of an academic population no greater than 750 (Gilmour, 1991a,b; Drummond and Reitsch, 1995; Blackwell and Cistone, 1999). Most quantitative studies have employed simple reporting techniques such as informing the reader that “x” percent of the faculty perceived governance one way, and “y” percent thought another way. Qualitative studies also have been relatively meager. There have been individual case studies that utilized interviews as the main technique 101
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(Dykes, 1968), as well as cross-site case studies (Millett, 1978; Eckel, 2000) that also employed interviews as the main data-gathering technique. Although their book has a much wider scope than simply governance, Leslie and Fretwell’s (1996) in-depth case studies of 13 institutions had governance as one area of investigation. Schuster et al. (1994) conducted quasicase studies for research pertaining to the role of cross-campus “strategic planning councils,” and Lionel Lewis (2000) wrote a case history of the contretemps with the academic governing board at Adelphi University. The overwhelming amount of writing, however, is based in neither qualitative nor quantitative methodologies. Instead, commissions and committees have written reports such as those of the AAUP and AGB. Former participants and combatants in governance have shared their experiences and reflections (e.g., Wolvin, 1991; Griffith, 1993; Duderstadt, 2000a; Hollinger, 2001). Numerous essayists with a great deal of perspective about higher education have offered their own opinions (Pfnister, 1970; Alfred, 1985; Keller, 1987; Longin, 2002). A pessimistic conclusion that one could draw about the research is that the literature on shared governance is methodologically weak. Indeed, one wonders why an area that has drawn so much discussion and commentary does not have a richer empirical base from which to draw conclusions. Whereas national studies of student attitudes, retention, and faculty work habits abound, there is a very thin data base to utilize about governance. An optimistic view is that a great deal of work awaits those who are searching for an area to investigate. One might make a similar comment about the theoretical frameworks that authors have employed in studying academic governance; however, such a point is slightly off-target. That is, one might argue that most of the articles, monographs, and books about governance in higher education are theoretically impoverished. Only a handful of studies have utilized explicit theoretical tools to diagnose a particular area of inquiry such as the role of the faculty senate. However, most of the texts have utilized one of two implicit theoretical frameworks: the collegial model or the bureaucratic model. Such a commentary is odd, given the wealth of frameworks that might be employed from business, public policy, sociology, and other disciplines. Additional analytic frameworks are the political model developed by Victor Baldridge in the 1970s and what Robert Birnbaum termed the cybernetic model. Nevertheless, most authors remain wedded to the bureaucratic and collegial approaches. A brief review of how each model diagnoses academic governance is useful. 102
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The bureaucratic model, first articulated by Weber, assumes that decisions and planning take place by way of a coordinated division of labor, a standardization of rules and regulations, and a hierarchical chain of command (Baldridge, 1971; Hardy, 1990). Unlike traditional bureaucracies, in which supervision and centralization were typical, investigators of academic bureaucracies argued that colleges and universities functioned in a different manner. Bureaucracy in colleges and universities got legitimized in decentralized units such as departments. Power existed in a decentralized fashion through the preset assumptions that a socialized cadre — the faculty — had internalized prior to joining the academy. Some argued that in a professional bureaucracy the standardization of skills did not occur by organizational rules, but by professional ideologies. The organization did not dictate that the academic needed to publish a specific set of articles or teach a particular number of classes — the profession did. A professional bureaucracy appeared as an oxymoron to some individuals, but actually, academic organizations developed ways to function that incorporated both perspectives. On the one hand, the loosely coupled nature of an academic institution suited professionals who at best shared their allegiance to their disciplines with the institution; on the other hand, these professionals also needed standardized, predetermined processes for organizational decisions such as recruitment, tenure, and curricular reform. The critics have pointed out that issues such as one’s commitment to the organization and the amount of teaching one does are exactly why a return to bureaucratic processes is warranted. Those who advocate for a more formalized process of governance point out that organizational outcomes and quality have suffered because of the decentralized decisionmaking nature of the academy. Numerous critics have pointed out that solutions exist that will improve the quality of the institution — the removal of tenure, an increase in teaching, and the elimination of unproductive units frequently get mentioned — but such solutions are impossible because of the governance processes of the institution (Healy, 1997). The answer is a more centralized approach to decision-making with greater power and authority at the presidential level (AGB, 1996). As Cary Nelson (1999) has noted, such approaches “consistently view the faculty largely as a resource to be ‘managed,’ as ‘human capital’ to be ‘defined, directed, and deployed’ with originality and attention to institutional mission” (p. B4). Richardson (1999), too, derided the movement toward bureaucratization and attributed such a desire to “obliviousness, indifference [and] hostility” (p. B9). 103
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The apocalyptic warnings of scholars such as Nelson and Richardson are frequently in reaction to the more flamboyant attacks on academe such as those made by an errant trustee or legislator. Obviously, no serious scholar would argue that every individual who calls for more bureaucratic controls is ill-willed or malevolent. However, two observations are pertinent. First, rhetoric often becomes heated when discussing possible changes in governance structures, whether one works from an explicit theoretical framework or not. Second, those who are most critical of a movement toward bureaucracy have as their implicit framework that of the collegium, to which we now turn. The collegial model is a view of academic life that assumes that a community of scholars operates around notions of respect and consensus. Neil Hamilton (1997) has pointed out that such an assumption works from a liberal, intellectual vantage point with regard to how knowledge creation works. Proponents of the collegial perspective argue that decisions get made through professional competence and authority rather than politics and rules. The loosely coupled and decentralized nature of the academy is well-suited to such a framework. John Millett (1962), one of the earliest advocates of the collegium, nicely summarized the position by stating: “I do not believe that a structure of hierarchy is a desirable prescription for the organization of a college. . . . The concept of community presupposes an organization in which functions are differentiated . . . through a dynamic of consensus” ( p. 5). Although such a view of the academy has numerous proponents, there is very little empirical literature that supports the notion that the academy is now, or has ever been, a collegium. As Baldridge (1971) noted, “Frequently it is obvious that the discussions of a collegium are more a lament for paradise lost than a description of present reality” (p. 7). Nevertheless, the collegial model remains remarkably popular with authors. Changes in the structure and work of academic life are seen as attacks on the collegial model, and responses are often based on the desire for a return to the status quo — even if that status quo never really existed. In a lament for the changes that are currently taking place in the academy, for example, Mary Burgan (1998), General Secretary of the AAUP, wrote, “I cannot believe that the solution to our present problems is to turn our backs on such an ideal of community” (p. 20). Similarly, Keetjie Ramo (1997) critiqued the proposals for reform of governance and found that “the arguments used to question the faculty’s role in governance do not hold up well” (p. 43). In other words, one ought to return to the notion of collegiality, community, and hence, shared governance. 104
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The political model took hold in the late 1960s and early 1970s. Baldridge rejected the forced choice one had to make between a college or university as a bureaucracy or as a consensus-driven association of scholars. Conflict, give-and-take, and bargaining, rather than routinized processes and consensus, were what existed in academe. In some respects, such a model provided a very useful tool to analyze academic processes. Especially during times of duress such as the student movement in the 1960s, an analysis of how issues got resolved inevitably took on a political tint. Collective bargaining, demands from external constituencies, and systemwide bargains are additional examples where the political lens may be a useful analytic tool. However, as Hardy (1990) has noted, the problem of the political model is that it seems to incorporate all organizational action and all theoretical models under its rubric (p. 399). The entire organizational world becomes political. The bureaucratic, collegial, and related models get incorporated into the political model. And yet, the political model did not seem especially useful for studying the more ordinary, mundane processes that tended to dominate academic life, rather than the more crisis-laden actions that had made the political model possible. After an initial burst of usage by scholars, the model appears to be under-utilized, rather than discarded. On the one hand, those who subscribe to the bureaucratic model are more concerned with practical concerns, so a model that diagnoses, rather than prescribes, is insufficient. On the other hand, the proponents of the collegial model are concerned with describing how the academic world should be, rather than how it is, so a political model also is of little use. The cybernetic model, championed by Robert Birnbaum, is the most recent proposal to dominate the theoretical landscape. Birnbaum argued: The cybernetic paradigm integrates existing models by suggesting how bureaucratic, collegial, political, and anarchical subsystems function simultaneously in colleges and universities of all kinds to create selfcorrecting institutions. The cybernetic paradigm posits that organization control systems can be described in terms of sensing mechanisms and negative feedback loops that collectively monitor changes from acceptable levels of functioning and that activate forces that return institutions to their previous stable state. These self correcting (cybernetic) processes function as institutional “thermostats” (1989, p. 239).
Because the model is relatively new, it has not attracted a great deal of analysis or critique. One observation is that the research that Birnbaum conducted to produce this model derived from studies of college presidents 105
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and decision-making, rather than academic governance. The model has relatively little to say about the role, for example, of faculty or boards in decision-making. Instead, the model helps college presidents and administrators think through how they might manage the organization in a more organic and flexible manner. Although one might be able to conceivably derive some idea about what to expect in a cybernetic organization from faculty, trustees, or other groups, very little empirical work has been done that delineates such a finding. A second observation is that the cybernetic model might be more fruitfully applied in organizations that are doing relatively well, or are on stable ground. As Birnbaum (1989) noted, the adage “If it’s working, keep doing it. If it’s not working, stop doing it. If you don’t know what to do, don’t do anything” is appropriate for the cybernetic leader (p. 251). Such advice, of course, flies in the face of organizations that face disruptive technologies. We have learned, for example, from the work of Christensen (1997), and Frank and Cook (1996) that technologies such as the worldwide web and the internet have remarkable power to change a marketplace. Equilibrium in a dynamic environment cannot be achieved, and those who seek it are those who will be at risk. If one accepts the assertion that academic organizations are in dynamic environments that necessitate changes, then the maxim to keep doing what one has been doing is ill-advised. An additional framework that is not so much a theoretical model but a way of thinking about decision-making and governance was first proposed by Mortimer and McConnell (1978). In a thoughtful piece about how the processes of governance might function more effectively, the authors posited that various stages of consultation were necessary. Subsequent authors (Hardy et al., 1983; Powers and Powers, 1983; Alpert, 1986; Tierney, 2001) elaborated on the work of Mortimer and McConnell by pointing out the importance of early consultation, the role of temporality in decisionmaking, how one utilizes feedback and communicates to multiple constituencies, and the import of comparative and evaluative criteria. The assumption of these authors was that shared governance is necessary for sustained, successful reform, but in general their critiques do not subscribe to any particular theoretical framework. Thus, I have outlined four frameworks that have been utilized to study governance. Analysts who use an historical framework primarily look at the varying stages of governance over time. Those who utilize a contexts and structures framework emphasize the setting in which governance takes place and investigate different decision-making bodies such as an 106
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academic senate. Students of the constituency framework look at who participates. Finally, proponents of a research framework in general employ bureaucratic, collegial, or political models. Each framework has particular strengths such as the ability to look over time at how governance has changed in the historical framework, or to focus in-depth analysis at a particular constituency such as the faculty. The frames may serve as filters through which to think about shared governance. The challenge for students of higher education research is threefold. First, the theoretical models that have been utilized appear to be of limited utility. In particular, even though the bureaucratic and collegial models remain the popular lenses through which to view academic governance, the models do not accurately provide a holistic portrait of the environments in which colleges and universities currently exist. Second, the empirical base on which most current work on governance has been written is thin, to say the least. At a time when quantitative and qualitative measures have become increasingly sophisticated, one expects to find more thoughtful uses of different techniques. Third, the kind of academic organization one needs in the 21st century is a new kind of institution. I am not suggesting that academic traditions be dropped in a simpleminded fashion, or that colleges and universities as we have known them be abandoned in favor of for-profit or corporate organizations. However, academic organizations have been superb at functioning in a stable, closed environment. The current contexts, however, are the opposite — the environment is unstable and open to market forces. For the first time in its history, the American college faces competitors in an unregulated, competitive market. What might these changes augur for academic governance? I address this question in the following section before turning to a cultural model of shared governance.
RETHINKING SHARED GOVERNANCE IN THE INNOVATING ORGANIZATION Colleges and universities with active faculties frequently will have developed detailed handbooks and by-laws pertaining to governance. Comments such as the following are not uncommon: “ . . . most institutional decisions should be arrived at through varying degrees of consultation with and involvement of faculty” (Bylaws, n.d). Anyone familiar with academe will readily comprehend the sentiments of such a statement as a call 107
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for shared governance. The problem, of course, arises not with a generic call for shared governance, but with the shared understanding of the words of the sentence. Should faculty really be involved in “most” institutional decisions? Who decides how “varying” the consultation is with each decision? How “involved” should the “faculty” be in these decisions; who determines how to define the “faculty”? The questions are not indicative of loose wording by an errant author, insofar as many individuals will have wildly different interpretations of the ideas, rather than the words. Some will say that the purpose of academic senates, school councils, and departmental meetings is precisely to deal with “most” institutional decisions; others will point out it is absurd to think that any representative forum could deal with the array of decisions that need to get made on a daily basis. Some administrators and faculty will point out that “institutional” decisions are not simply administrative actions such as whether to repave a parking lot, but decisions that affect the organization. Still other individuals will argue that the paving of a parking lot actually should have faculty input. A strong leader may consult with a kitchen cabinet that include faculty on the direction he or she intends to take, and the president will then say that faculty were involved in the decision; others will argue that only if the senate votes on an issue is there adequate faculty consultation. A satisfactory determination of how an institution’s participants might deal with both everyday and long-term issues goes to the heart of what is meant by “shared governance.” I have suggested that in order to define shared governance so that such questions might be answered one needs to come to terms with the multiple constituencies, contexts, and socio-cultural environments in which an organization exists. At present, the field has neither adequate data nor theoretical models to explain how to approach answering these questions. Insofar as I am more concerned with coming to terms with an understanding of shared governance for the 21st century than with simply an historical exegesis about shared governance, the challenge is to understand the cartography within which academe exists in the early 21st century. In 1970 Allan Pfnister wrote, “With the increase in size and complexity of the academy, it has been necessary to add a management function. Yet faculties hold to the tradition of the collegium and tend to become antiorganization and anti-administration when they feel that they have less opportunity to influence directly the qualities of the institution” (p. 432). More recently, Ramo (1997) rejected the assumption of a need for greater 108
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administrative authority by deriding the notion that “if old-fashioned bureaucracy is good for the Acme Widget Manufacturing Company, then it is undoubtedly good for Midwest State University” (p. 40). Both points are important because they underscore the importance of context. Those who want less formal faculty involvement in governance often speak of the complexity of the 21st century university (Duderstadt, 2000b). Those who reject such an assertion frequently point out that such arguments have always been used to lessen faculty participation in governance — evidence the comment by Pfnister made 30 years ago. Similarly, Ramo painted a stark picture by comparison: who wants a university to become a widget company? Rather than reject out of hand that the organization is too complex for shared authority, or accept that because of the complexity of organizational life, shared governance is no longer viable, I turn to a consideration of the current contexts of academic life. I move away from the creation of a “straw man” by assuming universities are about to become a widget factory insofar as only the most pedestrian of observers call for returns to “old-fashioned bureaucracy.” Increasingly what one finds in organizational life is a more nuanced sense of decision-making that may well suit the needs of academic governance in the 21st century. DISRUPTIVE TECHNOLOGIES IN TRADITIONAL ORGANIZATIONS In The Innovator’s Dilemma, Clayton Christensen (1997) argued that new technologies sustained or disrupted an industry. Audiovisual equipment or the microphone might be seen as a sustaining technology for teaching and learning at colleges and universities. Both technologies helped improve the organization, yet did not disrupt the normal flow of activities. Teachers still taught in the same classrooms in the same manner, albeit with more advanced tools than a blackboard and a piece of chalk. The concept of “teacher” did not change, and the “student” still needed to function in the same way as before the invention of AV equipment or the microphone. A disruptive technology is more significant. The new technology provides different benefits, creates new markets, and threatens existing ones. One might consider the internet, distance learning, and the worldwide web as disruptive technologies for academic organizations. True, the internet and the web might be seen as sustaining technologies. The teacher who once provided class notes as handouts now simply puts them on the web. The class now may post one another’s comments to a listserv rather than 109
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reading to one another in a face-to-face study group. However, the potential for disruption is vast. The traditional idea of the “teacher” might be dispensed with if the curriculum is entirely on-line. The assumption that students need to take a class at a specific location and at a particular time may be discarded. Teachers always assumed that their class notes were their intellectual property. The consumers of those notes were the few hundred students who received instruction from the professor. If the professor wrote a textbook to teach the class, then the individual benefited from the royalties of the text. Electronic technologies disrupt such basic assumptions. In a world where the curricula in a professor’s class may not reach hundreds of students in a classroom building, but thousands of students in multiple venues around the world, who owns the intellectual property becomes a question. Of consequence, who receives the royalties becomes subject to debate. The result is that a technology has the potential not merely to change, but to revolutionize an industry — in this case, higher education. An interesting aspect of disruptive technologies is that they begin with sub-par performance or quality and they are frequently expensive. Established companies usually do not develop disruptive technologies precisely because the technologies at the outset are not equivalent to what the companies currently offer their customers. The established companies have a customer-base that expects a particular level of quality at a predetermined cost. Start-up companies that have a new idea and little to lose are the locales where disruptive technologies are usually born. The new technology will create new markets rather than improve current ones, so the start-ups are not competing against well-established companies. Start-up companies have room to experiment, innovate, and improve; if they are successful they have a head start on utilizing a revolutionary technology that will appeal to an enormous customer-base. The computer is the most obvious example. Those consumers who used manual typewriters readily adapted to the sustaining technology that created electric typewriters. The companies that manufactured typewriters saw the rationale for their customers with a new improved technology. However, the names of computer-software companies are not Olivetti or Smith-Corona because the computer was a disruptive technology. Some young fellows worked in their garage and involved customers who were intrigued by the possibilities of a computer; they improved their product, lowered their prices, and the rest, as they say, is history. New companies utilize the disruptive technology in large part because they have less to lose. New markets emerge, costs go down, and quality 110
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goes up. “At this point,” observed Lloyd Armstrong (2000), “mainstream customers perceive the disruptive technology as providing a superior product, because it brings additional benefits compared to the established technology. Given its lower cost structure, the disruptive technology then rapidly displaces the established products, and leads to a revolutionary change in the industry” (p. 22). Such changes do not occur over a century because if they did it would enable traditional companies gradually to adapt. Disruptive technologies are more like a tidal wave that washes over rigid organizational structures that are ill-prepared to adapt and innovate. THE BUFFETED ORGANIZATION If disruptive technologies were the only impact on higher education, the implications for governance would be significant. However, colleges and universities are being buffeted by multiple forces, not one. Changing demographics are more significant today than at any time in a century. Students enter and exit postsecondary institutions with greater frequency than ever before; “retention” takes on a different meaning when students do not “drop out” but instead decide to leave for a time and return — perhaps to a different institution — at a later date. The nature of employment is being reconfigured so that “work” is no longer considered as lifetime employment at one company; employees increasingly approach organizations as “free agents.” Academics, already more wedded to their disciplines than their institution, have even weaker loyalties to the organization. A byproduct of the internet is the explosion in knowledge, the reconfiguration of disciplines, and the need for specialization. Globalization impacts markets, which in turn impact educational providers. The fastestgrowing sectors in postsecondary education are those organizations that are not traditional colleges and universities. Postsecondary institutions are now in a competitive market where they need to compete with an array of providers. Each of these points underscores how differently one might define “complexity” today than in 1970, much less 1950. Previous analysts thought of complexity as the array of units and departments that a “complex” organization needed to provide to the consumer. Although that internal definition of complexity has remained, the definition of the consumer has multiplied, and the external environment has made the organization itself a more complex interpretive undertaking. That is, a generation ago if someone said “college” or “university” a particular image came to mind. Such an image is no longer clear. 111
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A change in one area presages changes in others. A new definition of what one thinks of as faculty work suggests that employment contracts and tenure will be redefined. Changes in the labor market are much more complicated in a mature industry such as higher education that has multiple sectors, multiple demands, and multiple interpretations. The implications of a disruptive technology, for example, have different implications for an elite research university and a public state college. How a low-status professional school such as education reacts to changes will also differ whether the school is at a struggling small liberal arts college or a comprehensive university. As David Collis (2000) has observed, “Part of the problem . . . is that many items are interrelated. It is hard to distinguish what are the truly independent and underlying drivers of change and establish a clear logic of cause and effect. As a result, it is difficult to cleanly determine how each of these forces will change higher education” (p. 50). The assumption, of course, is not if change will occur, but how higher education will change. If one accepts even part of the thumbnail sketch that I have provided, then to claim that the postsecondary organization is going through significant contextual changes and is being buffeted by external demands, constraints, and forces, ought not to be thought of as the cries of academic Chicken Littles. There will be winners and losers, and as Robert Frank (2000) has succinctly claimed, there will be a “winner-take-all trend in higher education where success breeds success and failure breeds failure” (p. 3). One also ought to see that those who subscribe to bureaucratic calls for governance at such a time run the risk of irrelevance. Simply recreating organizational life a half century ago is not helpful in an environment framed by disruptive technologies, changing demographics, never-before-seen competition, and other forces. If anything, the opposite sentiment seems warranted. Rather than a lethargic call for the reinstallation of bureaucracy, those who study the changes that are taking place tend to advocate a new governance structure. David Collis (2000) has written that a strategic necessity “that I believe has become even more important [is] speed” (p. 123). He goes on to argue: This implies that universities should attach a great urgency to debates about their future. Rather than sitting back and observing how the market develops, university presidents and administrators should be proactively determining the future of their institutions. Otherwise they will be condemned to be the bystanders that get swept away in the tides of change (2000, p. 123).
Lloyd Armstrong (2000) has arrived at essentially the same conclusion, and pointed out the implications for shared governance. He writes, 112
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“Because the private sector can move rapidly and with very significant financial resources, the resulting pressures on universities and colleges could push them to act much more quickly than is usually possible within the tradition of shared governance” (p. 24). The point, of course, is not simply the speed with which an organization’s participants make a decision. A quickly made poor decision is as futile as a lethargic one. The assumption, however, is that the complexity of the current environment demands thoughtful analyses leading to deliberate decisions that position the organization to compete in ways that have been unnecessary until the dawn of the 21st century. Accordingly, calls for the reinstallation of bureaucracy or the reduction of the argument to simply that one’s opponents want to create a production model for the academy belies the complexity of the current climate. At the same time, the leisurely pace demanded of a consensual approach appears impossible if one wants to create an innovating organization. Perhaps an apt analogy might be the distinction between a large oceangoing vessel and a sailboat. Colleges and universities are traditional vessels, and they have weathered one or another storm without too much concern about the external environment. Ships such as the Titanic were not able to be either agile or adaptive. Their success came through their strength. Sailboats are able to shift with the wind; they are buffeted by the seas, but they are able to respond, and a skilled team is able to reach its destination. A call for a commander who has the skills of a ship’s captain is as mistaken as assuming that the only metaphor for an organization is that of a ship’s. Obviously, the movement from a mentality that assumes organizational action is determined by a rigid plan to one that is more interpretive is not a simple transformation that occurs according to a predetermined set of instructions. What, then, might be the lineaments of a solution? THE INNOVATING ORGANIZATION Letts, Ryan, and Grossman (1999) have observed that “ ‘innovative’ often means little more than ‘well implemented’ ” (p. 18). Programs that stand out are ones that are well implemented, but there is little sense if they work. Outcomes certainly matter; however, in academic organizations the focus has generally been on a static concept of innovation. Someone creates an innovation in an organization and then it gets replicated. Or a new concept gets implemented after a multiyear review. Consider, for example, 113
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changes to general education, intellectual property rights, or the role of part-time faculty. Each change is looked on as a unique idea that is successful if it gets implemented. If one believes the comments made in the previous section, however, rather than a static notion of “innovation” what the governance process needs to be attuned to is the ability for innovativeness — the capacity to innovate repeatedly (Light, 1998) and at the same time maintain what Burton Clark (1998) has labeled a “steering core” (p. 5). In a previous work (Tierney, 1999) I have talked about the twin challenges of maintaining an organizational identity on the one hand and, on the other, building an experimental environment. If an organization’s governance structure is geared toward maintaining the status quo, then in the kind of environment I have just outlined, the campus will face great difficulties. At the same time, if the organization’s governance structures are set up to enable the college or university to merely adapt to the environment then the campus will ultimately run into trouble. The challenge is to create processes and structures of governance that enable academic organizations to create and sustain an experimental environment while at the same time holding onto core values. Obviously, such a question touches a variety of issues that have become the buzz words of recent years — total quality improvement, high performance, and restructuring, to name but a few. My point here is not to provide an analysis on any of these thorny concepts but to focus on how the governing structures of traditional colleges and universities might reorient their processes to ensure that innovativeness is fostered. In doing so, I accept neither that “shared” governance is dead nor that the academic world is so complex that the only route to agile decision-making is through a reenergized form of martial law in which the president makes all the decisions. Instead, in what follows, I work from a cultural perspective that has five provisional tenets pertaining to governance. More than a decade ago, in an article about university governance, Cynthia Hardy (1990) noted that “the new direction of research is toward culture” (p. 405). However, other than an article or two (e.g., Lee, 1991) a discussion that employed culture as a theoretical model for diagnosing governance has been absent; as might be expected, there also has been a paucity of empirical studies that worked from a cultural perspective when studying governance. My purpose, then, is to sketch the outlines of an approach as a trial of some ideas that might then be examined and revised or refuted. To encourage analysis I discuss these points as assertions so that they can be proved or disproved. 114
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ORGANIZATIONAL CULTURE AND SHARED GOVERNANCE The underlying tenet of a cultural perspective is that one needs to constantly interpret the environment and the organization to internal and external constituencies. Organizations and the environments in which they exist neither come predefined nor are capable of instantaneous redefinition as if the contexts in which they exist are irrelevant. Although some organizational cultures may have had bureaucratic, collegial, or cybernetic governing mechanisms, what I am suggesting here is that those who think of their environment and the organization from a cultural perspective will look at governance from a different vantage point. If a key determinant of governance is that of interpretation, then how one thinks of governance changes. In particular, five precepts arise based on previous definitions of organizational culture (Tierney, 1988, 1991). As I will discuss, the precepts are tightly connected to one another; one cannot employ one and ignore another insofar as a cultural perspective assumes that an organization’s culture is pervasive. All acts are interpretive and dynamic. To assume that one act — such as a speech — is a symbolic event and another — the budget — is not is to mistake the meaning of culture. Hence, one needs to think of governance and its components as symbolic and interpretive. DEFINE DECISIONAL OUTCOMES AND PURPOSE What is the purpose of governance? All too frequently governance has been discussed without a sense of the reason why one has constructed a governance structure in a particular format. The process of governance has been treated as an end in itself. Instead, an organization’s participants need to think of governance as a symbolic and interpretive process devised to achieve particular outcomes. Outcomes are not always quantifiable. The advancement and protection of academic freedom, for example, may not be readily quantified. A rise in academic quality, however, may lend itself to measurable criteria. Both outcomes lend themselves to particular ways to approach governance. A concern for academic freedom suggests that faculty ought to be involved in the processes taken to ensure its protection. In traditional colleges and universities faculty also will be involved in defining the criteria for academic quality. As Martin Trow’s quote suggested earlier, an additional role of shared governance might be to insulate the organization from political interference. Again, such an outcome is less easily quantified, and 115
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most likely pertains more to public institutions than to private. Thus, outcomes are context dependent and may be evaluated in a number of ways. This symbolic aspect of governance pertains to those who are involved and those who get left out, as well as the outcomes one uses to determine the effectiveness of the governance process. In a buffeted organization one needs to be able to make agile decisions of importance to the organization’s participants. Such ability depends upon how the organization’s participants interpret their environment. Simply because structures exist is not a sufficient reason for claiming governance works. What are the indicators one might employ to think about in judging the strengths and weaknesses of the governance processes of a particular institution? The answer to such a question is one step beyond simply bemoaning or celebrating that an organization has an academic senate, faculty involvement, or a strong Board of Trustees. Instead, the point pertains to how one might gauge the effectiveness of shared governance. If a cultural framework for governance is in a constant state of creation/recreation, then of necessity, ongoing reflective dialogues and debates ought to occur over who is involved in what particular format with how much authority in an institution. The collegial assumption of consensus is dropped in favor of a cultural model that accepts the notion of creative conflict. Cultures are not consensual; different individuals and groups will have different perspectives. Insofar as cultures are not monolithic, it stands to reason that governance structures also will not be uniform. The challenge for researchers is to investigate the multiple venues employed in reaching a decision and to determine whether these venues are effective in enabling the organization to achieve its goals. DEFINE VENUES OF DECISION-MAKING AND UNITS OF ANALYSIS A similar effort ought to be made with regard to the venues of decision-making and the units of analysis. As has been outlined, most discussions of faculty governance inevitably equate faculty deliberations with the academic senate. And yet, faculty deliberate in multiple venues with multiple levels of input and authority. A structural focus is only one way to analyze governance. Additional ways are to investigate the multiple arenas where people become involved and to look at specific issues to see who is involved or not on a particular topic. The challenge here is to move away from a linear and hierarchical chain of decision-making and toward a more protean analysis that accepts that not all decisions are equal, not all decisions require multiple levels of review, not all decisions necessitate 116
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a hierarchical chain of command, and not all decisions will be reached by a faculty or a board having veto power. Some observers of higher education organizations will comment that I am merely stating the obvious: of course, the Board of Regents is not involved in every decision; of course, all decisions are not equal. However, if one returns to an earlier section of this text we find precisely such assumptions about faculty power and authority. Recall the comment about the need for faculty to be involved in “most” decisions. What one needs to do is determine the level of input and then ensure that varying levels of participation occur in a systematic and thoughtful manner. Clearly, a return to a centralized hierarchical structure is not conducive to the kinds of changes I am suggesting for a buffeted organization. A risk is that how one perceives a particular group’s input will vary from constituent to constituent. Without centralization, different groups will make decisions independent of one another because they feel it is in their domain of influence. A crucial issue is to define the domain and nature of influence by different constituents. The domain of influence refers to the levels of power and control a group has on a particular issue such as standards for evaluating teaching or policies pertaining to intellectual property. The nature of a group’s influence considers the varying ways by which influence is exerted. Do the faculty have veto power over defining teaching standards or merely input? There is not a certain, singular response. In a dynamic environment the culture of the organization is constantly interpreted and reinterpreted so that how one institution equitably decides such questions may differ from how another organization does so. All too often, however, the assumption has been that governance is a one-size-fits-all framework that may be replicated from one institution to the next. Governance, however, is the product of an interaction between cosmopolitan academic norms and localized cultural norms. The lineaments of a cultural strategy need to be outlined, and then the organization’s participants allowed to fill in the answers. Without a sense of organizational identity, a decentralized style of decision-making such as ought to occur in a buffeted organization will deteriorate into a loosely affiliated federation in which the parts are tangential to one another and the culture erodes. DEFINE THE CORE IDENTITY As one defines the purposes of the processes of shared governance, and one implements a radically decentralized process, of necessity one 117
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must have a clear sense of organizational identity. I have argued elsewhere (Tierney, 1998, 1999) about the overall importance of institutional identity, but in particular, if governance is to improve and move away from a bureaucratic or a collegial model, then an organization’s participants ought to have a sense about the core values of the institution. As Burton Clark (1998) noted, “Strong cultures are rooted in strong practices. As ideas and practices interact, the cultural or symbolic side of the university becomes particularly important in cultivating institutional identity and distinctive reputation” (p. 7). Curiously, some have assumed that a strong culture is one that is wedded to the past and resistant to change. However, as Clark commented, the reverse is also possible — if not mandatory. To create an innovating environment one neither needs to revert to calls for strong presidential leadership nor try to create an entrepreneurial climate in which tradition is disparaged. Instead, the challenge is to understand what cultural elements are vital to the core identity of the organization and use those elements as ways to enhance dynamic participation in shared governance. An innovating organization has a culture that enables its governance structure to foment change. That is, in a dynamic environment where an organization’s participants aim to encourage innovation, one needs to view the governance processes as emergent and fluid rather than as developed and static. Structures will continually adapt. Any a priori notions that shared governance is equated with an academic senate, or that governance is confined to the trinity of faculty, trustees, and administration is eschewed in favor of a more protean analysis of what constitutes governance. A strong organizational identity that is widely shared and believed is necessary. David Leslie nicely summarized this point: Successful organizations seem to be good at continuous adaptation, seem to have strong cultures, and seem to enjoy well-developed communication skills (both internally and externally). They form strong internal value systems that serve as compasses and filter information from a wide variety of sources through that value system. They do not make ‘strategic’ decisions in the old linear/rational way but sense and flow in a continuous process of growth, change and reimagining (1996, p. 109).
An organization without an identity is oftentimes one whose mission is ill-defined, programs continue to be added because the core is unclear, and resources are sprinkled across the multiple units within the organization. Frequently, there is a great deal of discussion about the processes of 118
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governance, again, as if these processes are outcomes. When governance becomes a main focal point then the organization is unsure about its direction, where it wants to go, and how it should get there. The mistake is to obsess about governance, void of a discussion about institutional and governance-related outcomes. Relatedly, a common flaw for those who want to create change is to assume that change occurs through a linear process. First one assesses the environment, then one consults with particular individuals, then one draws up a plan, and finally the plan gets implemented. Organizational identity does not enter a cultural undertaking as the first or third or final element. Each of these points, instead, is interlocked in cycles with one another. They feed, support, or distract from one another, and as the entire entity is in a state of constant change and permutation, so are each of the points. What is often overlooked is that insofar as humans are interpretive beings they interpret not only the large aspects of an organization such as its mission, but also the microscopic components of the organization. Such a reinterpretation — how the campus decides about a particular issue, for example, or who is involved in the decision — relates to the broader understandings of the organization itself.
FOCUS ON THE COMMUNICATIVE PROCESSES OF GOVERNANCE As David Leslie (1996) cogently argued when he wrote against linearrational approaches to strategic planning, “change in colleges and universities comes when it happens in the trenches; what faculty and students do is what the institution becomes. It does not happen because a committee or a president asserts a new idea” (p. 110). Unfortunately, most research on governance reverts to old-fashioned notions of power so “where the buck stops” is the one who has the authority. If the buck does not pass by the faculty or end on the desk in the boardroom, then the assumption is that governance is not shared. But governance in a decentralized 21st century organization needs to be more than a simple check of who gets to vote and who is denied the opportunity. Shared governance does not result from formal allocations of spheres of responsibility and authority (Trow, 1990, p. 24). Instead, informal arrangements and processes need to be interpreted by the academic collective about the relative weights to different academic bodies in different decisions. Strategic governance is more an ongoing communicative 119
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process that works in organizations where participants trust one another and understand the identity that is trying to be cultivated. Formalized governance occurs in systems where there is a lack of trust and the collective has little sense of institutional purpose and ideology. In a system where shared governance functions effectively communication is key. At a time when organizations are buffeted by the winds of change, and where decentralization is encouraged, ongoing communication about the institution’s identity and direction is essential. Who communicates to whom is again symbolic of the nature of governance. If the president is the only individual who sends out messages, one symbol is sent; in an organization where the faculty have ongoing discussions with academic staff and students about the nature of the organization another message is sent. Without systematic efforts at communication the system freezes.
DETERMINE THE EFFECTIVENESS OF GOVERNANCE PROCESSES IN ENABLING DECISIONS TO OCCUR Although a strong core is essential, and the ability to communicate that core is equally important, one also has to focus on how symbolic structures and processes get defined, carried out, and evaluated in the “real” world. That is, although where a parking lot gets placed may be a core issue over identity on one campus at one point in time, it is foolhardy to claim that such issues rise to the level of major cultural issues of organizational identity for all campuses all the time. The point here is important because generally assumptions about the organization’s culture work from a macro perspective when the opposite is more likely to happen. Authors assume that one or another symbolic act takes place because it reinforces the general tenets of the culture. From this perspective, ideology is all-encompassing and inscribes meaning in all organizational action. The opposite takes place: organizational actions provide meaning about the general tenets of the culture. To be sure, at times a particular theme or ideology pervades most aspects of the academic organization. A conservative Christian university, for example, may decide that what people wear is inappropriate, or they may define particular kinds of behavior such as coed dorms as inappropriate, even immoral. And yet, even at such an institution not every action is a major signifier of the culture. 120
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However, the manner in which individuals work with one another, how they decide issues, the formal structure of governance, and the like provide clues about the culture. Indeed, more often than not, individuals find meaning not from broad sweeping statements or events, but from the routine, microscopic aspects of everyday life. As I noted in the first section, if there is one issue that individuals in all types of colleges and universities have bemoaned about campus governance, it is the efficiency, speed, and organization with which academic governance functions (Kezar and Eckel, 2002). Administrators feel stymied. Faculty feel their time is often wasted. The culture of an organization need not be one of governance by conversation (Tierney, 1983) in which decisions are endlessly delayed and the assumption is that the summer months are idle. Instead, one needs to diagnose how to improve the cultural processes that are in place to enable smoother, more efficient decisions. The assertion of administrative prerogative on peripheral issues is not a problem in an academic community that is based on trust, ongoing communication, and a clear identity. The challenge is threefold. First, if the other cultural precepts are not clearly delineated, it is impossible to articulate whether or not the governance processes are functioning efficiently. In unstable environments individuals are likely to demand structure if they are unsure of where the organization is heading or if an atmosphere of distrust exists. Second, if the organization remains wedded to a collegial model of consensus that was articulated a half century ago, any individual will be able to filibuster or delay a decision simply because he or she disagrees. The processes of governance need to be fluid enough to move issues to a conclusion while at the same time advancing, rather than stifling, communication. Third, in a dynamic system the assignment of issues to different groups and venues becomes critical. Rather than assume that there is one best system for decision-making, the community needs to draw upon the multiple venues that are possible to garner responsible input. Ultimately, an academic community needs to foment active involvement so that individuals are talking and thinking about the issues that confront the organization rather than the processes one might use to discuss those issues. A successful governance process is one in which multiple constituencies have been involved in the main problems that confront the college or university. An unsuccessful campus is one where structures exist, but because of angst or alienation no one participates or the dialogue focuses on the structures rather than the issues and problems. 121
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CONCLUSION: THE NEXT GENERATION OF RESEARCH I began by outlining the paucity of research that exists on a critically important topic. I noted that the manner in which governance has been studied is primarily in four frames. The frameworks that have been utilized are those that are historical, structural, constituency-focused, and research-based. I then critiqued the research based on the current conditions that exist in academe and suggested that a cultural model might be a more appropriate way to analyze governance. From this perspective governance is a process and outcome. Governance provides the foundation upon which organizations may prosper or fail. Governance is also little more than what a foundation is to a house — it is the individuals who make of that house a home. Governance is a mixture of academic cultural norms that have been built up over time and the localized cultural norms of a specific institution. Governance is more than merely an organizational chart that maps decision-making. Governance occurs in multiple venues. Accordingly, five avenues for research appear ripe for investigation. DATA MATTER If there is one particular need with regard to governance it is the collection and analysis of data. Surveys will be able to provide broad-based understandings of how governance functions in colleges and universities as well as gauge the perceptions of different constituencies. Longitudinal data will be most useful in order to track the changes that occur over time. Case studies, interviews, and ethnographies are likely to provide in-depth understanding to individuals’ perceptions of governance. Qualitative methodologists also will be able to sketch contextual issues so that readers might be able to understand the rationales for why particular changes have taken place. If there is a caution it is twofold. On the one hand, what the field needs less of are exhortations and lamentations about the state of governance from either those who want more administrative authority or those who perceive the demise of shared governance. Although such articles have served a purpose, they fall more accurately into op-ed pieces for newspapers than as research. On the other hand, researchers need to move beyond their own campuses in their efforts. A case study of a senate, for example, where the researcher has been involved presents all sorts of methodological 122
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shortcomings just as a survey of one’s colleagues will have a circumscribed utility. CONTEXT MATTERS This text has focused on institutions where most of the writing has been done about academic governance: 4-year colleges and universities. Although a great deal remains to be done in this arena, there are broad swaths of territory that remain virtually ignored. Community colleges account for almost half of the population of postsecondary institutions, and they are the least studied. Although most community colleges are public and frequently part of a system, there is little reason why the internal governance mechanisms for 2-year institutions are not investigated. More importantly, as constituencies from the external environment have raised expectations and make increased demands on community colleges, a fruitful line of research is to see how a community college’s governance procedures respond. The fastest growing sector of academe is the arena of for-profit and non-traditional institutions. These institutions, such as DeVry, the University of Phoenix, the Keck Graduate Institute, and Cardean University, have vastly different arrangements for governance. Academe is currently facing the greatest increase in innovative organizations since the 1960s. The experiments of the 1960s were closely watched and written about in great detail (Grant and Riesman, 1978). The opposite is currently true with the innovations that are taking place. Researchers need to begin to broaden their horizons, stop looking at only institutions where they work, and begin looking at alternative organizational types. The purpose of such research is not to support or condemn such growth, but to analyze it in an objective manner. Although non-traditional institutions are the fastest growing sector in academe, the largest number of students remain in state-wide systems of higher education. The literature on state systems of higher education, however, is virtually void on research about the interstices of governance. The state governance literature in general analyzes how states shift from one system to another, or how coordinating boards differ from state to state. Longitudinal studies are virtually absent, and a discussion of the role of different constituencies in state systems of higher education is nonexistent. There is, for example, no research on the role of the faculty on a state board, much less that of students or other constituencies. 123
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There is also very little research on the impact of collective bargaining on academic governance. Just as governance is successful in some public institutions and not others, presumably collective bargaining has successful and unsuccessful examples of working with traditional governance structures. The dynamics of how collective bargaining functions at an institution have vast implications for the future of academic governance insofar as the movement seems to be toward greater unity of participation of multiple constituencies on campuses. PEOPLE MATTER Research on governance has been reduced to a triangle of constituencies — trustees, administrators, and faculty. Of those three the least discussed group is that of the trustees, and the greatest number of articles refer to faculty. When research has been done about faculty the definition has been focused on full-time, tenure-track faculty. However, the fastest growing groups on some campuses are either non-tenure-track or part-time faculty. What is their role in the governance process? How does participation function for part-time and adjunct faculty who are not at the top of the academic ladder and are often perceived as second-class citizens? There is no small amount of irony that at a time when faculty in various academic disciplines have focused their energies on studying groups who have been excluded or ignored in fields such as history, literature, and political science, within the academy those same groups who have been marginalized remain ignored. Although a great deal of research remains to be done with regard to understanding the faculty’s role in governance, the fastest growing group in academe is the academic staff. Professional staff who are non-faculty fall into the interstices of categories. They are not faculty; they are not administrators; they are not classified staff; they are not students. And their growth has been enormous over the last decade. Their role in governing the institution needs to be investigated both for what is occurring and how they have changed the culture of governance. Finally, students have been participants in governance for more than a generation and they, too, are overlooked; indeed, when one discusses students the focus is on undergraduates. Graduate students, however, have become increasingly vocal participants in governance, particularly at the departmental and school levels. As graduate student unions continue to increase on private and public campuses a fruitful line of research will 124
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be to see how unionization changes the role of students in their representation, power, and authority in governance. COMMUNICATION MATTERS Although one might conduct research through any number of disciplinary lenses, if one works from a cultural perspective in a manner akin to what I have sketched here, a particularly germane line of work pertains to the discursive codes through which governance gets enacted. Most research has used the case study method and discussed how organizational structures pertaining to governance function. An alternative manner of investigation is to look not at structures, but at communication. How do constituencies communicate with one another? Who communicates with whom? In an age when texts and discussion are increasingly mediated by electronic technologies, how does the internet influence governance? If communication is important for the effectiveness of governance, then is campus governance enhanced by listservs and virtual meetings? Up until now far too much of the research on governance has derived from a structural standpoint. The field also will benefit by standing the typical line of research on its head: rather than trace the history and changes of structures, study how different groups have communicated about specific issues.
EFFECTIVENESS MATTERS Whether one bemoans or celebrates calls for shared governance, the assumption is that governance matters. Indeed, in yet another armchair declaration about governance, a celebrated group of academic leaders concluded that “The governance of universities is becoming increasingly crucial” (Hirsch and Weber, 2001, p. vii) not just within the United States but throughout the world. In an earlier section I argued that one needs to have indicators of effectiveness for governance. At the outset of the text I touched on various interpretations a few analysts had provided about the purpose of governance. Henry Rosovsky, for example, had said that the purpose of governance is to enhance teaching and research, and Martin Trow suggested that one purpose is to remove public institutions from political interference. Regardless of the purposes, no one knows whether, once a purpose has been defined at a college or university, the venues of governance 125
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enhance, impede, or are irrelevant to the institution achieving its goal. One could, for example, develop a baseline of indicators for judging quality, select a group of similar institutions, and determine over a 5-year time horizon which institutions have gotten better and which have not. A retrospective case study of each institution might lend insight about the role governance plays in institutional improvement. To be sure, there are any number of methodological stumbling blocks with such a scenario. However, at present the field is virtually void of any form of comparative or longitudinal analysis. Indeed, when comparative studies are considered, they focus within the United States. At a time when globalization has increased the need for greater understanding about how different systems function, there is a particular urgency for comparative research. In sum, my purpose has been neither to restrict nor encapsulate worthwhile avenues for research. Higher education is currently experiencing as great a time of change as any in the last century. During periods of change one might not be surprised that studies of leadership occur, or that armchair observers proffer one or another opinion. What is critically needed, however, is to move beyond retrospective observations of the organization or studies of the individual leader, and to consider instead the manner in which postsecondary organizations undertake governance to meet the multiple needs of the 21st century.
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REFERENCES Alfred, R.L. (1985). Organizing for renewal through participative governance. New Directions for Higher Education, no. 49 13(1): 57–63. Amacher, R., and Meiners, R. (2002). Free the Universities: Reforming Higher Education to Keep Pace with the Information Age. San Francisco: Pacific Research Institute for Public Policy. American Association for Higher Education. (1967). Faculty Participation in Academic Governance. Washington, DC: AAHE-NEA Task Force on Faculty Representation and Academic Negotiations. American Association of University Professors. (1971, April). At the brink; preliminary report on the economic status of the profession, 1970–71. Paper presented at the annual meeting of the American Association of University Professors, Philadelphia, PA. American Association of University Professors (2001). Statement on government of colleges and universities. In AAUP Policy Documents and Reports (9th edn.). Washington, DC. Armstrong, L. (2000). An academic leader’s perspective on a disruptive product. Change 32(6): 20–27. Association of Governing Boards of Universities and Colleges. (1996). Renewing the academic presidency: Stronger leadership for tougher times. Report of the Commission on the Academic Presidency, Washington, D.C. Association of Governing Boards of Universities and Colleges. (1997). Composition of governing boards of independent colleges and universities. AGB Occasional Paper No. 36, Holly Madsen, Washington, DC. Association of Governing Boards of Universities and Colleges. (1998, November 8). AGB statement on institutional governance. Retrieved October 13, 1999, from http://www. agb.org/governance.cfm Baldridge, J.V. (ed.) (1971). Introduction: Models of university governance — bureaucratic, collegial, and political. In Academic Governance: Research on Institutional Politics and Decision Making. Berkeley, CA: McCutchan Publishing. Baldridge, J.V. (1982). Shared governance: A fable about the lost magic kingdom. Academe 68:12–15. Beach, J.A. (1985). The management and governance of academic institutions. The Journal of College and University Law 12: 301–341. Beck, H.P. (1947). Men Who Control Our Universities. Morningside Heights, NY: New York. Birnbaum, R. (1988). How Colleges Work: The Cybernetics of Academic Organization and Leadership. San Francisco: Jossey-Bass. Birnbaum, R. (1989). The cybernetic institution: Toward an integration of governance theories. Higher Education 18: 239–153. Birnbaum, R. (1991). The latent organizational functions of the academic senate: Why senates do not work but will not go away. New Directions for Higher Education, no. 75 19(3): 7–25. Blackwell, E.A., and Cistone, P.J. (1999). Power and influence in higher education: The case of Florida. Higher Education Policy 12: 111–122. Bowen, W.G. (1994). Inside the Boardroom: Governance by Directors and Trustees. New York, NY: John Wiley & Sons, Inc. Burgan, M. (1998). Academic citizenship: A fading vision. Liberal Education 84(4): 16–21. Bylaws: James E. Beasley School of Law, Temple University (n.d.). (Available from the James E. Beasley School of Law, Temple University, 1719 N. Broad Street Philadelphia, PA 19122.)
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Chait, R.P. (2002). The Questions of Tenure. Cambridge, MA: Harvard University Press. Chait, R.P., and Taylor, B. (1989). Charting the Territory of Nonprofit Boards. Harvard Business Review Jan.–Feb., 44–54. Chait, R.P., Holland, T.P., and Taylor, B.E. (1991). The Effective Board of Trustees. New York: Maxwell Macmillan International. Chait, R.P., Holland, T.P., and Taylor, B.E. (1996). Improving the Performance of Governing Boards. Phoenix, AZ: ACE/Oryx Press. Christensen, C.M. (1997). The Innovators Dilemma: When New Technologies Cause Great Firms to Fail. Boston, MA: Harvard Business School Press. Clark, B.R. (1998). Creating Entrepreneurial Universities: Organizational Pathways of Transformation. Oxford: Pergamon. Collis, D. (2000). “When industries change” revisited: New scenarios for higher education. In M. Devlin, and J. Meyerson (eds.), Forum Futures: Exploring the Future of Higher Education. San Francisco: Jossey-Bass. Corson, J. (1960). Governance of Colleges and Universities. New York, McGraw-Hill. Dill, D.D., and Helm, K.P. (1988). Faculty participation in strategic policy making. In J. Smart (ed.), Higher Education: Handbook of Theory and Research (Vol. 4). New York, NY: Agathon. Drummond, M.E., and Reitsch, A. (Summer/Fall 1995). The relationship between shared governance models and faculty and administrator attitudes. Journal for Higher Education Management 11(1): 49–58. Duderstadt, J.J. (2000a). Fire, ready, aim!: University decision making during an era of rapid change. Paper presented at the Glion Colloquium II, La Jolla, California. Duderstadt, J.J. (2000b). A University for the 21st Century. Ann Arbor, MI: The University of Michigan Press. Duryea, E.D., and Williams, D. (eds.) (2000). The Academic Corporation: A History of College and University Governing Boards. New York: Falmer Press. Dykes, A.R. (1968). Faculty participation in academic decision making (American Council on Education Monograph). Washington, DC: American Council on Education. Eckel, P.D. (2000). The role of shared governance in institutional hard decisions: Enabler or antagonist? The Review of Higher Education 24(1): 15–39. Ewell, P.T. (ed.) (1985). Assessing Educational Outcomes. San Francisco: Jossey-Bass. Ewell, P.T. (1990). State Policy on Assessment: The Linkage to Learning. Denver, CO: Education Commission of the States. Frank, R.H. (2000). Higher education: The ultimate winner take-all market. In M. Devlin, and J. Meyerson (eds.), Forum Futures: Exploring the Future of Higher Education. San Francisco: Jossey-Bass. Frank, R.H., and Cook, P.J. (1996). The Winner-take-all Society: Why the Few at the Top Get so Much More than the Rest of Us. New York: Penguin Books. Gilmour, J.E. (1991a). Participative governance bodies in higher education: Report of a national study. New Directions for Higher Education, no. 75 19(3): 27–39. Gilmour, J.E. (1991b). Your faculty senate: More effective than you think? Academe 77(5): 16–18. Grant, G., and Riesman, D. (1978). The Perpetual Dream: Reform and Experiment in the American College. Chicago: University of Chicago. Griffith, R. (1993). Budget cuts and shared governance. Academe 79(6): 15–17. Hamilton, N. (1997). Peer Review: The Linchpin of Academic Freedom and Tenure. Academe 83(3): 5–19.
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Tierney: A Cultural Analysis of Shared Governance Hamilton, N. (1999). Are we speaking the same language? Comparing AAUP & AGB. Liberal Education 85(4): 24–31. Hardy, C. (1990). Putting power into university academic governance. In J. Smart (ed.), Higher Education: Handbook of Theory and Research (Vol. 4). New York: Agathon. Hardy, C. et al. (1983). Strategy Formation in the University Setting. Review of Higher Education, 6: 407–433. Hirsch, W.Z., and Weber, L.E. (2001). Governance in Higher Education: The University in a State of Flux. London: Economica. Hollinger, D.A. (2001). Faculty governance, The University of California, and the future of academe. Academe 87(3): 30–33. Kaplan, G. (2002). 2001 survey on higher education governance (available from The Hauser Center of Nonprofit Organizations, Harvard University, 79 JFK St., BT-220B, Cambridge, MA 01238). Keller, G. (1987). Shotgun marriage: The growing connection between academic management and faculty governance. In J. Schuster, and L. Miller (eds.), Governing Tomorrow’s Campuses. New York, NY: ACE/MacMillan. Kezar, A., and Eckel, P. (2002, March). Meeting today’s governance challenges: A synthesis of the literature and examination of a future research agenda. Paper presented at the meeting of the American Education Research Association conference in New Orleans, LA. Leatherman, C. (1998). “Shared governance” under siege: Is it time to revive it or get rid of it? The Chronicle of Higher Education January 30: A8. Lee, B. (1991). Campus leaders and campus senates. New Directions for Higher Education, no. 75 19(3): 41–61. Leslie, D.W., and Fretwell, E.K. (1996). Wise Moves in Hard Times: Creating and Managing Resilient Colleges and Universities (1st edn.). San Francisco: Jossey-Bass. Letts, C.W., Ryan, W.P., and Grossman, A. (1999). High Performance Nonprofit Organizations: Managing Upstream for Greater Impact. New York: John Wiley & Sons. Lewis, L.S. (2000). When Power Corrupts: Academic Governing Boards in the Shadow of the Adelphi Case. New Brunswick, NJ: Transaction Publishers. Light, P. (1998). Sustaining Innovation: Creating Nonprofit and Government Organizations That Innovate Naturally. San Francisco, CA: Jossey-Bass Publishers. Longin, T.C. (2002). Institutional governance: A call for collaborative decision-making in American higher education. In W.G. Berberet, and L.A. McMillin (eds.), A New Academic Compact. Bolton, MA: Anker Publishing Co. McGrath, E.J. (1936). The control of education in America. The Educational Record 17: 259–272. McGuinness, A.C. (1994). State Postsecondary Education Structures Handbook. Denver, CO: Education Commission of the States. Metzger, W.P. (1987). Academic governance: An evolutionary perspective. In J. Schuster, and L. Miller (eds.), Governing Tomorrow’s Campuses. New York, NY: ACE/MacMillan. Miller, M., McCormack, T., and Newman, R. (1996). Faculty involvement in governance: A comparison of two faculties. The Journal of Staff, Program, and Organization Development 27:180–190. Millett, J.D. (1978). New Structure of Campus Power: Successes and Failures of Emerging Forms of Institutional Governance. San Francisco: Jossey-Bass. Mortimer, K.P., and McConnell, T.R. (1978). Sharing Authority Effectively. San Francisco: Jossey-Bass. Nelson, C. (1999). The war against the faculty. The Chronicle of Higher Education April 16: B4–B9. Pfnister, A.O. (1970). The role of faculty in university governance. Journal of Higher Education 41: 430–449.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Ramo, K.J. (1997). Reforming shared governance: Do the arguments hold up? Academe 83(5): 38–43. Ramo, K.J. (1998). Assessing the Faculty’s Role in Shared Governance: Implications of AAUP Standards. Washington, DC: AAUP (American Association of University Professors). Richardson, J.T. (1999). Centralizing governance isn’t simply wrong: It’s bad business, too. The Chronicle of Higher Education February 12: B9. Richardson, Jr., R.C., Bracco, K.R., Callan, P.M., and Finney, J.E. (1999). Designing State Higher Education Systems for a New Century. Phoenix, AZ: American Council on Education and The Oryx Press. Rosovsky, H. (1990). The University: An Owner’s Manual. New York, NY: W.W. Norton & Company, Inc. Rosovsky, H. (2001). Some thoughts about university governance. In W. Hirscht, and L. Weber (eds.), Governance in Higher Education: The University in Flux. London: Economica. Schuster, J.H., Smith, D.G., Corak, K.A., and Yamada, M.M. (1994). Strategic Governance: How to Make Big Decisions Better. Phoenix, AZ: American Council on Education/Oryx Press. Sinclair, U. (1923). The Goose-step: A Study of American Education. Pasadena, CA: Upton Sinclair. Scott, J.V. (1996). The strange death of faculty governance. PS: Political Science and Politics 29: 724–726. Scott, J.V. (1997). Death by inattention: The strange fate of faculty governance. Academe 83: 28–33. Taylor, B., Chait, R.P., and Holland, T. (1996). The new work of the nonprofit board. Harvard Business Review Sept.–Oct.: 36–46. Thomas, S.L., Pusser, B., and Slaughter, S. (2002). Playing the Board Game: An empirical analysis of university trustee & corporate board interlocks. Unpublished Manuscript, University of Arizona Center for the Study of Higher Education, Tucson, AZ. Tierney, W.G. (1983). Governance by conversation: An essay on the structure, function, and communicative codes of a faculty senate. Human Organization, 42: 172–177. Tierney, W.G. (1988). Organizational culture in higher education: Defining the essentials. Journal of Higher Education 59(1): 2–21. Tierney, W.G. (1991). Academic work and institutional culture: Constructing knowledge. Review of Higher Education 14(2): 201–219. Tierney, W.G. (1993). Building Communities of Difference: Higher Education in the 21st Century. Westport, MA: Bergin & Garvey. Tierney, W.G. (ed.) (1998). The Responsive University: Restructuring for High Performance. Baltimore, MD: The Johns Hopkins University Press. Tierney, W.G. (1999). Building the Responsive Campus: Creating High Performance Colleges and Universities. Thousand Oaks, CA: Sage Publication, Inc. Tierney, W.G., and Minor, J. (2002). Challenges for Governance (available from The Center for Higher Education Policy Analysis, Rossier School of Education, The University of Southern California, WPH 701, Los Angeles, CA 90089-0031). Trow, M. (1990). The academic senate as a school for university leadership. Liberal Education 76(1): 23–27. Trow, M. (1998). Governance in the University of California: The transformation of politics into administration. Higher Education Policy 11: 201–215.
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4. STATEWIDE COMMUNITY COLLEGE GOVERNANCE STRUCTURES: FACTORS THAT INFLUENCE AND ISSUES THAT TEST EFFECTIVENESS Cheryl D. Lovell and Catherine Trouth University of Denver
The community college system has evolved in the last century from one institution in Illinois in 1901 to over a thousand institutions (Tollefson, 2000). This remarkable past has been documented and chronicled from those within and outside of the community college movement (Brint and Karabel, 1989; Cohen and Brawer, 1996; Cohen, Brawer, and Associates, 1994; Goodchild and Wechsler, 1997; Ratcliff, Schwarz, and Ebbers, 1994). Even with this well-documented history, little is known about how statewide governance systems shape or influence community colleges and the extent to which they are effective. To date, few discussions, outside of Lovell and Trouth (2002) and Richardson, Bracco, Callan, and Finney (1999), have examined statewide patterns and far fewer have examined the factors that influence effective community college governance systems. The statewide system design of higher education and its relationship to the structure of the state government is critical because a flawed or inadequate structure nets limited successes even when strong and effective leaders are present (Richardson Bracco, Callan, and Finney, 1999). In this chapter we describe several different types of governance systems used in today’s state environment for community colleges. Our examination begins with the context of statewide governance patterns for all higher education institutions and then focuses specifically on community colleges. Second, factors that influence statewide governance practices
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for community colleges are presented with a brief synopsis of the potential influence these factors have on the effectiveness of community colleges governance systems. We then provide an examination of certain key issues that continually test the effectiveness of community college governance systems. This chapter concludes with our own simplified taxonomy for describing these systems as well as a recommendation to assess on a continuing basis the system’s effectiveness.
DEFINITIONS AND TAXONOMIES OF GOVERNANCE SYSTEMS Community college governance is characterized by a complex web of relationships and arrangements that have evolved over the years. No brief discussion will do justice to the long history of how governance developed within each state, let alone across all 50 states; therefore, this overview will focus on how governance patterns typically differ among states. Before examining statewide governance structures, it is useful to define the terms used in describing them. Governance is the decision-making authority for an organization that is typically exercised by boards. Governing Boards typically appoint the chief executive of the institution or system, establish policies and approve transactions related to faculty and personnel, ensure fiscal integrity, and perform other management functions (Education Commission of the States, 1997). Although governing boards have control over their institutions, in practice they attempt to balance their authority with some level of institutional autonomy (Berdahl and McConnell, 1999). Historically, boards have been categorized as consolidated governance systems, segmental systems, and campus-level boards (Education Commission of the States, 1997; Kerr and Gade, 1989). In a system with consolidated governing boards, one board governs all public institutions within a state, or one board governs all baccalaureate campuses with different arrangements for community college institutions. A segmental system is characterized as having separate boards for different types of institutions. Under a segmental system, all types of institutions, including research universities, comprehensive colleges, and community colleges may have separate boards. An institution-level board is an autonomous board with authority over a single institution, even if the institution itself has multiple campuses. Another key term is statewide coordination. Statewide coordination is necessary to ensure that postsecondary systems work collectively toward 134
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the state interest (Education Commission of the States, 1997). Statewide coordination comprises the formal mechanisms that states use to organize higher education in a united manner. Coordinating boards tend to have the functional responsibility for statewide planning and policy leadership; policy analysis and problem resolution; defining the mission for each postsecondary institution in the state; academic program review and approval; budget development, development of funding formulae, and resource allocation; providing financial aid to students; information, assessment, and accountability systems; licensing and oversight; implementing statewide projects and initiatives; and quality assurance (McGuinness, 1997). With these key terms in mind, we can now examine common classification systems of statewide governance already described in the literature. The five taxonomies, we have identified, include two that describe statewide governance for all public higher education institutions, and three that describe governance taxonomies specifically for community colleges. In the first taxonomy, developed by McGuinness and the Education Commission of the States, states are formally divided into three types of decision-making structures: governing board states, coordinating board states, and planning/service agency states (Education Commission of the States, 1997; McGuinness, 2002). Consolidated governing board states assign coordinating responsibilities to a board that also has primary responsibilities to govern the institutions under its jurisdiction. As displayed in Table 4.1, there are 21 states classified in this taxonomy as governing board states. Coordinating board states have boards that function as coordinating agencies between the state government and the governing boards of the institutions as governance is decentralized in these states. There are 25 coordinating board states. Finally, planning/service agency states have no statutory entity with coordinating authority, but may have an entity to ensure good communication among the institutions or sectors in postsecondary education. There are four planning/service agency states. The second statewide governance taxonomy is based on a recent study that classifies states in terms of federal systems, unified systems, and segmented systems (Richardson, Bracco, Callan, and Finney, 1999). A federal system, according to Richardson, Bracco, Callan, and Finney (1999), organizes institutions under a range of governing boards that are required to work directly with a statewide coordinating board. In this system, the coordinating board has authority from the legislature to represent the public 135
HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Table 4.1: A Statewide Governance Taxonomy for Postsecondary Institutions from the Education Commission of the States Governing Board States
Coordinating Board States
Planning/Service Agency States
Alaska Arizona Georgia Hawaii Idaho Iowa Kansas Maine Mississippi Montana Nevada New Hampshire North Carolina North Dakota Oregon Rhode Island South Dakota Utah Vermont Wisconsin Wyoming
Alabama Arkansas California Colorado Connecticut Florida Illinois Indiana Kentucky Louisiana Maryland Massachusetts Missouri Nebraska New Jersey New Mexico New York Ohio Oklahoma South Carolina Tennessee Texas Virginia Washington West Virginia
Delaware Michigan Minnesota Pennsylvania
Source: McGuiness, A. (2002). Models of Postsecondary Education Coordination and Governance in the States. Denver, CO: Education Commission of the States.
interest in areas such as budgeting, program planning and approval, articulation, and information collection and reporting. This system is termed a federal system because it reflects the influences of federalism (a federation of entities) such as the one described in the U.S. Constitution. A unified system places all institutions under a single governing board that works directly with the governor and legislature in executing the above functions. A segmented system has two or more governing boards that supervise single institutions or groupings of institutions. In a segmented system there is no single statewide agency with statutory authority for governance and coordination. 136
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Part of the problem with these two statewide taxonomies is that they do not take into consideration the context of the complex structures found in many states, such as multicampus systems, single board institutions, vocational and technical institutions, and most importantly, community college governance systems. To reflect the specifics of community college coordination and governance, three additional taxonomies are examined. In the third taxonomy, developed by The Education Commission of States (ECS) in 1997, the states are classified according to the type of board that has primary responsibilities for community colleges. In this taxonomy, many states fall into more than one category, as displayed in Table 4.2. This effort is an important contribution to the literature as it was the first attempt to provide a descriptive view of current statewide structures of community college governance and coordination. When analyzing this taxonomy together with the first ECS taxonomy of statewide governance, certain observations come to mind. For example, if the state is a governing board state (as noted in Table 4.1), community colleges governance tends to be placed under a consolidated governing board with both 2- and 4-year institutions (as noted in Table 4.2). For community colleges in states that use a coordinating board system, community college governance tends to be in the hands of local boards. Tollefson (1999) presents a variation of the ECS taxonomy and it is sufficiently different to warrant presentation here as the fourth taxonomy. Tollefson sorts states into five types of state-level coordination and governance with each state classified according to which type of state board has responsibility for community colleges. In the first classification, the State Board of Education is responsible for community colleges along with the K-12 system. These boards usually have minimal control over the community colleges and often the community college local boards remain autonomous to control their own institution(s). In the second classification, responsibility for community colleges resides in a State Higher Education Board or Commission. These boards generally have authority to approve programs and recommend appropriations priorities. The states in this classification typically also have local governing boards for community colleges. In Tollefson’s third classification, Statewide Community College Coordinating Boards exercise responsibility for community colleges. These boards have moderate control, particularly in financial and academic operations. In the fourth classification, there is a State Community College Governing Board with direct control over the community college operations. In Tollefson’s final classification, a State Board of Regents is responsible for community 137
Consolidated Governing Board for Both 2- and 4-Year Institutions Governs Community Colleges
Alaska Georgia Hawaii Idaho Maine Minnesota Montana Nevada
State Board of Education Coordinates and Regulates Community Colleges
Alabama Florida Idaho Iowa Michigan Oregon
138 Arkansas Indiana Kansas Maryland Massachusetts Missouri Nebraska New Jersey
Coordinating Board for All Higher Education Coordinates Locally Governed Community Colleges Arizona California Colorado Florida Illinois Mississippi Washington Wyoming
Independent State Board Coordinates Community Colleges and/or Technical Institutions
Colorado Connecticut Delaware Georgia Indiana Kentucky Maine New Hampshire
Independent State Board Governs Community Colleges and/or Technical Institutions
Alaska Arkansas Hawaii Louisiana New Mexico Ohio Oklahoma Pennsylvania
Four-year Institutions have 2-year Branches
Table 4.2: A Taxonomy of State Coordination and Governance Based on Coordination of Community Colleges and Other 2-year Institutions
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New Mexico Ohio Oklahoma Pennsylvania Texas
North Carolina South Carolina Virginia Wisconsin
South Carolina Texas Wisconsin
Note: South Dakota has 2-year technical institutions, but no community colleges. Source: Education Commission of the States (1997). State Postsecondary Education Structures Sourcebook: State Coordinating and Governing Boards. Denver, CO: Education Commission of the States.
New York North Dakota Rhode Island Tennessee Utah Vermont West Virginia Puerto Rico
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Table 4.3: Tollefson’s Taxonomy of State-Level Coordination/Governance for Community Colleges State Board with Responsibility for Community Colleges State Board of Education
State Higher Education Board or Commission
Statewide Community College Coordinating Board
State Community College Governing Board
State Board of Regents
Alabama Idaho Iowa Kansas Michigan Oregon Pennsylvania
Arkansas Maryland Massachusetts Missouri Montana Nebraska New Jersey New Mexico New York (SUNY) Ohio Pennsylvania Texas
California Colorado (local district colleges) Florida Michigan Mississippi New Hampshire North Carolina Oregon South Carolina Washington Wisconsin Wyoming
Colorado (statesystem colleges) Delaware Kentucky Maine Minnesota
Alaska Georgia Hawaii Louisiana Montana North Dakota Rhode Island Tennessee Vermont West Virginia
Source: Tollefson, T.A. (1999). Mission, Governance, Funding, and Accountability Trends in State Systems of Community Colleges. In T.A. Tollefson, R.L. Garrett, W.G. Ingram and Associates (eds.), Fifty State Systems of Community Colleges: Mission, Governance, Funding and Accountability. Johnson City, TN: Overmountain Press.
colleges. These boards typically govern both community colleges and state universities. Table 4.3 shows states that fall into one of these classifications. Though similar to the first taxonomy by ECS it is useful in highlighting the level of state control involved in delegating responsibility for community colleges to one type of board as opposed to another type. As noted within Tollefson’s (2001) taxonomy, the states are more evenly distributed across the five classifications. Most community college governance systems were classified as having State Higher Education Board or Commissions (n ⫽ 12), the second highest number of states were classified as having Statewide Community College Coordinating Boards (n ⫽ 11), and the third highest number of states classified as having a State Board of Regents (n ⫽ 10). 140
Lovell and Trouth: Statewide Community College Governance Structures Table 4.4: Richardson and de los Santos: A Taxonomy of State Structures for Community Colleges State Governance and Coordination Arrangements FOR COMMUNITY COLLEGES
State Governance and Coordination for all Postsecondary Institutions FEDERAL
UNIFIED
SEGMENTED
FEDERAL
(1) 2 States
N/A
(5) 10 States
UNIFIED
(2) 7 States
(4) 9 States
(6) 7 States
SEGMENTED
(3) 11 States
N/A
(7) 5 States
Source: Richardson, R., and de los Santos, G. (2001). Statewide governance structures and 2year colleges. In B.K. Townsend and S. B. Twombly, (eds.), Community Colleges: Policy in the Future Context (pp. 39–56). Westport, CT: Ablex Publishing.
A fifth taxonomy of community college systems structures was suggested by Richardson and de los Santos (2001). Their State Community College Governance Structures Typology is displayed in Table 4.4. This taxonomy posits seven categories for describing the array of statewide governance systems in place today for community colleges. The authors build on the three categories noted above about statewide governance structures (Richardson et al., 1999). The seven categories in this fifth taxonomy include Federal/Federal States, Federal/Unified, Federal/Segmented States, Unified States, Segmented /Federal States, Segmented/Unified States, and Segmented/Segmented States (Richardson and de los Santos, 2001). Richardson and de los Santos provide a conceptual overview of statewide structures for all higher education and specifically for community colleges. Their typology reveals that almost half of the states (n ⫽ 23) have community colleges and technical institutes governed by a single statewide board to which all higher education institutions report. Fifteen of these states have the community colleges as part of a consolidated system that includes some of the baccalaureate institutions. Eleven states have coordinating boards that focus solely on community colleges. The first category is the Federal/Federal State category. Two states, Illinois and Washington, are included in this category. According to Richardson and de los Santos (2001), these states “have a coordinating board for all higher education, a separated statewide coordinating structure 141
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for community colleges, and local governing boards” (p. 45). The second is Federal/Unified States with seven states under this category including Alabama, Colorado, Connecticut, Kentucky, Massachusetts, Tennessee, and Virginia. These states have “a statewide coordinating board for all higher education and a single statewide governing board for community colleges and technical institutes” (p. 46). The Federal/Segmented States is the largest category with 11 states including Arkansas, Indiana, Louisiana, Maryland, Missouri, Nebraska, New Jersey, Ohio, Oklahoma, South Carolina, and Texas. These states have “a statewide board that coordinates all higher education and more than one community college or technical institute with its own governance arrangements” (p. 47). The Unified States category includes nine states: Alaska, Hawaii, Idaho, Montana, Nevada, North Dakota, Rhode Island, South Dakota, and Utah. These states have “a single board that governs all degree-granting institutions of higher education” (p. 47). Note, however, that South Dakota does not have any community colleges, but the state does have 2-year technical colleges. The Segmented/Federal States category represents the second largest group of 10 states. These states are Arizona, California, Florida, Georgia, Kansas, Mississippi, New York (SUNY), North Carolina, Wisconsin, and Wyoming. These ten states “have two or more governing boards for higher education along with a coordinating or governing board for community or technical colleges” (p. 48). The Segmented/Unified States category includes seven states: Delaware, Maine, Minnesota, New Hampshire, New York (CUNY), Vermont, and West Virginia. These states “have two or more statewide governing boards for higher education, one of which has responsibility for community colleges or technical institutions” (p. 50). Finally, the Segmented/Segmented States category has five states, including Iowa, Michigan, New Mexico, Oregon, and Pennsylvania. These states “have two or more governing boards for higher education, local governing boards for community colleges, and no statewide agency with effective coordinating or governing responsibilities for community colleges and technical institutions” (p. 50). While this typology is meant to explain state structures in a simple model, there are also some problems with this typology. As with any model meant to simplify a complex subject, not all categories are distinct or clearly defined. For example, not all states fit neatly into one category. Richardson and de los Santos (2001) admit to making a number of “judgement calls” in placing states that exhibited characteristics of more than one category. Also, the designated names for the categories do not give 142
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a good sense of the governance arrangement implied by the category without explanation. For instance, in this taxonomy, a federal system is a state structure, which is confusing to readers who may associate the term with national-level governance rather than with the concept of “federalism.” Thus, it could be difficult for some readers to grasp the concept of a federal/federal system that only applies at the state level. In addition, since the terms federal, segmented, and unified were developed to identify separate types of systems (Richardson et al., 1999), combining them into categories in this matrix (i.e., federal/segmented, segmented/unified) further confuses whatever distinction is being made between the systems. On the other hand, one of the strengths of the Richardson and de los Santos (2001) taxonomy is that it ties together community college systems that have similar issues in governance. For instance, federal/ federal systems of community college governance may not be cost-effective structures. On the other hand, federal/segmented systems show a tendency towards lack of coordination as too little oversight is provided and the system becomes more segmented. The Richardson and de los Santos taxonomy is an important step in understanding why it is necessary to gain better knowledge of how different statewide community college governance systems work. By understanding governance and coordination systems, leaders can predict the strengths and weaknesses of the systems in meeting future challenges. States with underdeveloped, inefficient systems will have difficulty in responding to challenges in a relevant and efficient manner (Richardson and de los Santos, 2001, p. 53). The last three taxonomies examined, those that speak directly about community colleges, shed light on the complex relationships states have developed with community colleges. Part of the explanation for these complex patterns is found in the history of the development of community colleges. Community colleges have been seen, at various times in their development, as an extension of high school and therefore part of secondary education; as the first 2 years of a college system; and as a unique educational enterprise separate from both secondary and higher education (Diener, 1994). As the interpretation of the purposes of the community college changed, governance and coordination patterns also changed, reflecting the move towards placing community colleges firmly in the postsecondary community (Tollefson and Fountain, 1994). Although these taxonomies provide a foundational understanding of how to describe statewide community college governance patterns, the taxonomies alone do not suggest what constitutes effective governance. 143
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Several factors and issues also need to be examined to paint a complete picture of effective community college governance. These concepts are clustered around two important themes: factors that shape effective community college governance and issues that continually test the effectiveness of community college governance.
FACTORS THAT INFLUENCE EFFECTIVE STATEWIDE GOVERNANCE After examining the taxonomies that have emerged for describing the myriad arrangements for statewide community college governance, one might legitimately ask: What difference does it make? What makes one set of arrangements better than another? In other words, what factors influence effectiveness? Four key factors are described: the placement of community colleges within state higher education configurations, the composition of boards, the degree of centralization of governance within a state system, and the arrangements for funding. PLACEMENT OF COMMUNITY COLLEGES WITHIN STATEWIDE SYSTEMS The position of the community colleges within a particular state structure influences the effectiveness of that governance system. Where boards supervise both 2- and 4-year colleges, 2-year colleges can often be overlooked by the board members for more pressing issues at the 4-year institutions. On a more positive note, these systems may be well positioned to respond to initiatives designed to improve demands for articulation and collaboration in a K-16 postsecondary model (Richardson and de los Santos, 2001, p. 52). From 1963 to 1989 there were major changes in the types of state-level boards for community colleges. Two major changes included an increase from 38 to 49 states that had statewide community college systems and an increase from 6 to 22 states with separate state boards specifically for community colleges (Tollefson, 1996). This suggests a trend toward positioning arrangements that provide more focus and visibility for community colleges. States that have designed federal systems also enjoy certain advantages. States with a federal system avoid major restructuring inherent in the segmented and unified systems. They also separate the public interest from institutional advocacy, giving those responsibilities to separate 144
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boards, thereby avoiding conflicts of interest. An empowered statewide board can provide leadership for initiatives that require collaboration, such as the use of technology in creating access and mobility for diverse populations (Richardson and de los Santos, 2001, pp. 52–53). Depending on its place within a state system, a community college may face certain problems and tensions set up by differing levels of governance and coordination. Conflicts between state and local boards, or between boards and the state legislature, can arise when there is dispute over which entity has governing responsibilities. As states “take on primary funding and/or governing responsibilities, the line that separates state-level responsibilities from local board responsibilities sometimes blurs” (Davis, 2001, p. 5). A clear understanding of the institution’s place in the governance system is necessary to identify legitimate authority in such disputes. The existence of so many levels of governance may also contribute to these misunderstandings about responsibilities. A study in California found that 22 different agencies and offices shared community college governance responsibilities (Davis, 2001). Sometimes the complexities of the system need to be streamlined. Occasionally, there is no clear entity at all with coordination or governance responsibilities for community colleges. In a recent report released by the Pennsylvania Commission for Community Colleges, it was suggested that steps be taken to strengthen local governance and statewide coordination in Pennsylvania for community colleges (Center for Public Higher Education Trusteeship and Governance, 2002). This would include creating a new statewide community college services entity to coordinate community colleges while strengthening the local governances of community colleges. Several states have recently enacted laws that would change the placement of their community colleges within the state system. Florida and Arizona recently made the most drastic governance changes. Florida HB 2263, the Florida Education Governance Reorganization Act, reorganized Florida’s higher education governance (Center for Public Higher Education Trusteeship and Governance, 2002). A new state board of education, appointed by the governor, replaced the current K-12 and higher education state boards. Responsibility for many governance issues is being shifted to local governing boards. Yet state coordination will also be maintained as the governor now appoints new board members. Arizona directed governance change specifically at the community college sector. Arizona effectively dissolved the state board of directors for the community colleges of Arizona on July 1, 2002 (Morgan, 2002). 145
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The board was reduced to five members; the board’s budget was cut from $700,000 to $237,000 annually; and tuition, fee, and transfer of credit approval was removed from the board’s responsibilities. In a less dramatic yet still significant move, West Virginia also directed governance changes at the community colleges. SB 703 is taking community colleges out from under the aegis of the 4-year universities and creating independently accredited community college and technical institutions throughout the state (Center for Public Higher Education Trusteeship and Governance, 2002). Other states have also reconsidered their governance structures. In 2001, Alabama SB 66D created the Commission on Public Education Assessment, Organization, and Allocation. This board will provide recommendations on state governance and structure by December 2, 2003 (Center for Public Higher Education Trusteeship and Governance, 2002, p. 9). Recently, Iowa legislators introduced a bill to establish a task force to study the restructuring of governance in order to make community colleges run more cooperatively, effectively, and efficiently as a state system (Center for Community College Policy, 2002). In Colorado, a report from the Northwest Education Research Center (NORED) recommended that Colorado consider certain structural realignments in its governance system to increase the potential for responsiveness to community and regional higher education needs (Northwest Education Research Center, 2000). In Oregon, HB 2015 created a commission to revise governance structures, but the commission was not funded (Center for Public Higher Education Trusteeship and Governance, 2002). It will be important to watch what happens in Alabama, Iowa, Colorado, and Oregon over the next few years to see if governance changes happen as a result of their studies, commissions, and recommendations. Although problems may arise from having different levels of governance and coordination, this distribution of responsibilities can have the salutary effect of balancing the diverse interests of all the stakeholders involved in a community college system (Davis, 2001). The challenge may not be to decrease either state or local governance. Instead, “lines of accountability must be clarified so that everyone knows who is responsible for what” (Davis, 2001, p. 2). Clarifying responsibilities and restructuring boards where necessary should be aimed at better serving the public interest. Responsibilities for governance should reside in boards that can best determine the public interest. While statewide governing boards could be effective in some states, for other states governing boards should be local 146
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and the state board should play a coordinating role (Davis, 2001). State policy makers and institutional leaders need to work together to ensure that each state system best reflects the needs of the public served by community colleges within the state. Let the main point not be lost, however, that the position of the community colleges within the governance system makes a difference. COMPOSITION OF BOARDS The composition of boards also has far reaching consequences for community colleges. Studies conducted on boards of trustees for all types of institutions show that governing board members are still usually white, over 50, and male, although women and minorities are slightly more represented on governing boards of public institutions (Hines, 1997). Some states have attempted to address this problem. Kentucky HB 135 would revise the nominating process for governing board members and broaden the membership of the boards of the Kentucky Community College and Technical System (Center for Public Higher Education Trusteeship and Governance, 2002). Although changes are slowly being made, boards often do not reflect the diverse constituencies they serve. The question remains open as to whether such non-representative boards make policy decisions that hinder or discriminate against certain groups or whether the symbolism of a non-representative board influences decisions such as students’ choosing to enroll or taxpayers’ willingness to support the institution. Members of both governing and coordinating boards can be appointed or elected. Popular election is practiced for local community college boards in at least 20 states (Hines, 1997, p. 384). One might assume that board members elected by popular vote might legitimately represent the interests of diverse stakeholders. Yet, in one recent election, only 10 percent of eligible voters turned out to vote for community college trustees (Davis, 2001). With such a small turnout, it is easier for special interest groups to influence the outcome of the election. In North Carolina, SB 166 created a commission to study board selection, term of office, and board size (Center for Public Higher Education Trusteeship and Governance, 2002). As might be expected, more states are beginning to pay attention to public involvement in these elected boards. In public institutions where board members are appointed, it is often the governor who appoints board members, while in private institutions current members of the board nominate and elect new members, although 147
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in some cases alumni balloting is used to appoint some trustees (Hines, 1997). At public institutions where board members are appointed, board agendas may change whenever a new political party wins the governor’s office (Davis, 2001). Often “the election or appointment of a single new trustee can mean an abrupt change in the institution’s direction” (Davis, 2001, p. 3). Davis (2001) suggests that irresponsible board members should be subject to recall, whether they are appointed or elected (p. 14). A welldesigned provision for recall that protects good members from attacks for unpopular decisions could support board members as they struggle to hold themselves to high standards of governance. Most boards are lay boards consisting of citizens from the larger community served by a college. Consequently, board members are not necessarily appointed or elected because of their expertize in community colleges. The governor of Virginia is trying to rectify this by signing an executive order establishing an Advisory Commission on Higher Education Board Appointments to review potential governing board appointees. This board is to identify candidates with “merit, experience, sound judgment, and proven leadership” (Center for Public Higher Education Trusteeship and Governance, 2002, p. 15). Once appointed, new board members are often not well prepared for their responsibilities (Davis, 2001). If board members do not understand their role, governance or coordination may suffer. At the local level, that means that they may either overstep their authority, taking on responsibilities that rightfully belong to the president or faculty of an institution, or underestimating their responsibility and delegating away their proper authority. In Mississippi legislation was enacted in 2002 to solve this dilemma. SB 2621 delineates the duties of the president and the boards of trustees of community and junior colleges (Center for Community College Policy, 2002). Better orientation for new board members should result in better governance for community colleges. Recently Kentucky has addressed this issue by creating the Institute for Effective Governance. This institution will fulfill a number of roles, including providing orientation and training for governing boards of the Community and Technical College System, providing seminars on topics of statewide importance, and providing boards with guidelines for establishing effective board behavior (Center for Public Higher Education Trusteeship and Governance, 2002, p. 13). Wellman (2002) suggests that board members should be more proactive in their responsibilities. She suggests several responsibilities that board members 148
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should consider primary to their role. For example, board members should identify their institution’s short- and long-term challenges; refocus their institutional mission, planning, and programming; assess and integrate their institution’s tuition, aid, and outreach strategies; redouble their institution’s commitment to cost management and cooperation; and pay attention to enrollment planning and management (Wellman, 2002). There are many resources available to board members and states that wish to be active in preparing board members for service. The Association of Community College Trustees (ACCT) provides trustee education and assists boards in developing and affecting public policy. As they become more active in public policy, board members influence policy to reflect the concerns and purposes of the institutions they serve. The American Association of Community Colleges (AACC) also provides information on legislation affecting community colleges and actively promotes the goals of community colleges in Washington. The ECS recently established the Center for Community College Policy to conduct research on policy issues affecting community colleges and to organize workshops on the issues facing community colleges. No matter what governance structure is established, its effectiveness depends to some extent on the composition and quality of its board members. DEGREES OF CENTRALIZATION The extent to which governance in the state community college system is centralized or decentralized is another key factor that shapes the effectiveness of governance. A study by Garrett (1999) demonstrated that centralized state systems tended to be administered by governing-type boards while decentralized state systems tended to have coordinating boards. In an attempt to classify states on a continuum of degree of centralization, Garrett identified four states that operate in a highly centralized manner, and only two states that operated in a highly decentralized manner. Table 4.5 shows where each state falls on the continuum between these two extremes. Several variables are associated with the degree of centralization within a state structure including: the percentage of state versus local funding is correlated with centralization or decentralization; the type of governing board established in initial legislation enacting a state system may determine the degree of centralization; the size of a community college system may influence the degree of centralization; and the time period in which the 149
HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Table 4.5: The Degree of Centralization of State Governance and Coordination of Community College Systems Highly Centralized
Colorado Connecticut Hawaii Kentucky Tennessee
Centralized
Alabama Alaska Delaware Georgia Indiana Louisiana Maine
Moderately Centralized
North Carolina Oklahoma South Carolina Utah Washington
Moderately Decentralized
Arizona Arkansas California Florida Illinois Massachusetts
New York North Dakota Ohio Oregon Wisconsin Wyoming
Decentralized
Idaho Iowa Kansas Maryland Michigan Mississippi
Missouri Nebraska New Jersey New Mexico Texas
Highly Decentralized
Montana Pennsylvania
Minnesota Nevada New Hampshire Rhode Island Vermont Virginia West Virginia
Source: Garrett, R.L. (1999). Degrees of Centralization of Governance Structures in State Community College Systems. In T.A. Tollefson, R.L. Garrett, W.G. Ingram, and Associates (eds.), Fifty State Systems of Community Colleges: Mission, Governance, Funding, and Accountability. Johnson City, Tennessee: The Overmountain Press.
state system was established may affect the degree of system centralization (Garrett, 1999). Degrees of centralization are critical to keep in mind as governance patterns are described along the continuum of centralized to decentralized. The degree of centralization can shape actions of the governing decision-making system in terms of which policy issues are addressed, 150
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how activities will be funded, or what strategic planning might take place. The degree of centralization, therefore, can also influence effectiveness. STATE FUNDING ARRANGEMENTS State funding is an important factor to consider when exploring community college governance patterns in terms of how states allocate funding to community colleges and how community colleges use those resources. Funding decisions often shape power sources or drive decision-making. Although funding decisions should not drive policy agendas unfortunately they often do. Priorities and strategic planning should be primary rather than allowing funding to serve as the driver. Regardless, state funding should be examined in the context of governance and understood as a major factor influencing the effectiveness of governance and decision-making patterns. While community colleges in many states still collect support through local taxes, usually property taxes, the trend for the last three decades has been for states to fund an increasing percentage of community college operating costs (Education Commission of the States, 2000). This raises the question as to whether there will then be a shift away from local governance control towards greater state governance or coordination for community colleges. One study found “a high correlation between states’ proportional funding of community colleges and the decision-making authority that state boards and agencies have for community colleges” (Garrett, 1999). While authority resides with the state boards, Garrett (1999) also found that much of that authority is delegated to local community colleges. Community colleges have so far retained much of their local governance control, but there is no guarantee that states will continue to delegate their authority to the local boards. Some states are examining current funding for community colleges. In Mississippi, HB 1612 requires the State Board of Community and Junior Colleges to conduct a study of the state funding structure (Center for Community College Policy, 2002). In Idaho, amendments to an existing law provide that tuition at a community college may be increased by increments of not more than 10 percent per annum (Center for Community College Policy, 2002). At the heart of this issue is whether community colleges will remain largely local institutions or become state entities similar to many 4-year colleges. If the community colleges remain local institutions, governance is likely to remain more with the local boards. Inequities in local funding sources are also complicating factors to understand in state funding 151
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arrangements. Some community colleges and community college districts enjoy a strong local tax base that enhances any amount of additional state allocations, at the same time, community colleges in less wealthy regions must rely on the state appropriations much more heavily than the other institutions. However, if the trend towards greater statewide coordination continues, governance may gradually shift to a statewide level. To the extent that centralization depends on funding patterns, this shift could be a slow movement, because current constraints on state finances will probably continue in the near future. Current state funding conditions do not look positive for increased funding for community colleges. A recent report by the National Council of State Legislatures (NCSL) indicates most state “revenues are anemic” (National Council of State Legislatures, 2002, p. 1). The January Update relates that 28 states report spending is above budgeted levels; 30 states have implemented budget cuts or hold backs; and 15 states have tapped reserve funds to balance the FY02 budgets (National Council of State Legislatures, 2002). Most disconcerting is the fact that 37 states say they face potential budget gaps in the next fiscal year as well. The problem is further compounded because when state appropriations drop, tuition jumps, as demonstrated in Figure 4.1 (Wellman, 2002, p. 29).
Figure 4.1: When State Appropriations Drop Tuition Jumps Source: Wellman, J.V. (2002). Weathering the Double Whammy: How Governing Boards Can Negotiate a Volatile Economy and Shifting Enrollments. A Working Paper for the Association of Governing Boards of Universities and Colleges National Conference on Trusteeship.
152
Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland
State
5,347,000 5,750,000 6,330,000 3,350,000 79,865,000 6,705,000 11,686,000 2,844,000 19,736,000 17,300,000 3,834,000 2,002,000 25,476,000 9,594,000 4,603,000 4,702,000 7,429,000 6,476,000 2,507,000 11,132,000
FY ’02 General Fund State Resources1 (in thousands) 1,116,129 204,837 949,926 653,386 9,468,062 783,421 761,942 189,228 2,882,083 1,699,438 349,159 330,776 2,922,599 1,321,191 830,226 715,585 1,084,605 997,813 239,892 1,297,406
FY ’02 Total Appropriations to Higher Education2 (in thousands) 21 4 15 19 12 12 6 7 14 10 9 17 11 14 18 15 15 15 10 12
FY ’02 Percentage of State Appropriations to Higher Education (%) 234,189 1,767 136,593 88,854 2,849,302 144,447 126,052 51,183 820,424 169,632 87,117 20,581 409,066 135,253 142,723 85,174 183,535 134,207 40,336 208,370
FY ’02 Appropriations to 2-Year Colleges2 (in thousands)
Table 4.6: Community College Funding as a Percentage of Total Appropriations to Higher Education
21 1 14 14 30 18 17 27 29 10 25 6 14 10 17 12 17 13 17 16
FY ’02 Percentage of Higher Education Appropriations to 2-year Colleges1 (in thousands) (%)
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153
Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma
State
Table 4.6: Continued
24,621,000 9,290,000 14,142,000 3,422,000 7,830,000 1,503,000 2,821,000 1,946,000 1,138,00 21,730,000 4,400,000 43,532,000 14,713,000 887,000 21,830,000 5,181,000
FY ’02 General Fund State Resources1 (in thousands) 1,009,921 2,273,532 1,382,576 805,964 1,049,504 149,738 525,220 346,845 107,608 1,794,946 611,173 3,574,159 2,442,690 201,497 2,205,481 824,891
FY ’02 Total Appropriations to Higher Education2 (in thousands) 4 24 10 24 13 10 19 18 9 8 14 8 17 23 10 16
FY ’02 Percentage of State Appropriations to Higher Education (%) 234,142 319,596 52,352 170,731 152,161 5,843 65,530 94,918 15,529 177,104 50,324 453,277 650,090 40,841 268,059 122,272
FY ’02 Appropriations to 2-Year Colleges2 (in thousands)
23 14 4 21 14 4 12 27 14 10 8 13 27 20 12 15
FY ’02 Percentage of Higher Education Appropriations to 2-year Colleges1 (in thousands) (%)
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154
5,140,000 20,736,000 2,642,000 5,409,000 864,000 7,610,000 32,510,000 3,805,000 894,000 12,241,000 11,228,000 2,994,000 11,259,000 659,000
714,837 2,035,092 174,939 896,773 141,973 1,073,136 5,074,633 608,644 73,195 1,681,646 1,373,895 392,051 1,192,913 169,929
14 10 7 17 16 14 16 16 8 14 12 13 11 26
33 8 23 20 11 18 19 17 19 38 9 12 35
232,519 163,675 40,558 175,636 15,137 189,877 967,962 102,981 314,107 516,649 36,172 148,584 60,071
1 National Governors Association and National Association of State Budget Officers (May, 2002). The Fiscal Survey of the States. Available from http://www.nga.org/cda/files/MAY2002FISCALSURVEY.pdf. 2 Center for Higher Education Finance. Grapevine: A National Database of Tax Support for Higher Education, available from http://coe.ilstu.edu/grapevine/.
Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming
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Funding for higher education reflects the declining state budgets from which this funding is appropriated. Table 4.6 displays total general funding resources, total dollars appropriated to higher education, the percentage of the state budget that is appropriated to higher education, appropriations to community colleges, and finally the percentage of higher education appropriations received by community colleges. Simple percentages were calculated by dividing the amount allocated to higher education by state resources and that calculation derived the percentages noted in the fourth column. Additionally, the allocations to community colleges were determined by taking the allocations to higher education dividing the amount appropriated to community colleges. Thus the percentage allocated to community colleges is displayed in the last column. Community colleges receive a respectable share of the total state appropriations to Higher Education, though for some states community colleges enrollment growth is greater than that for 4-year institutions. Table 4.6 does not display funding from local sources though many community colleges may also be funded by local taxes. The relative proportion of state to local funding has been shown to have an impact on the autonomy of local community college governing boards, as state control increases with the size of state funding relative to local funding (Garrett, 1999). Another aspect of local funding is that some community colleges may have inequitable resources despite state funding patterns. For instance, community colleges in rural districts may not have as large a tax base as urban community colleges. Funding arrangements are crucial, of course, and adequate and equitable funding naturally influences effective governance.
ISSUES THAT TEST STATEWIDE GOVERNANCE EFFECTIVENESS Certain key issues continually test the effectiveness of statewide governance and coordination systems that are in place in a particular state. Regardless of the type of governance structure, these key, perennial issues must be addressed by all community colleges. The issues, which continue to test the effectiveness of a particular type of governance system, include: financial aid policies, accountability and performance funding, articulation, PK-16 systems, collective bargaining, workforce development, and technology. 156
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FINANCIAL AID Probably one of the most important aspects of America’s higher education system is the financial aid program. Wellman (2002) argues that institutional boards need to understand enrollment management and focus on tuition and financial aid policies. Boards should assess and integrate tuition, aid, and outreach strategies by asking the following questions: ●
●
●
●
●
How dependent is the institution on charges for tuition as a revenue source, net of the financial aid provided to students? How has this figure changed over time? How strong is the institution financially, and what does this tell the board about tuition and aid policies? Should the size of the institution increase, decrease, or stay the same? What would be the implications of each alternative on the budget and on access? Has the board taken a serious look at long- and short-term outreach strategies to diverse economic and racial/ethnic communities? If so, what has the board done to strengthen service and market development efforts? Is it possible to increase tuition, improve diversity, and prevent the exodus of middle-class students, yet still have adequate funds after meeting student-aid requirements to pay for program and facility improvements and increases in faculty and staff compensation? (p. 27).
Financial aid is sometimes also provided to students at the state level. Often this aid helps to promote the policy interests of the state. In 2001, by passing AB 1241, the California legislature established financial aid for students to complete teacher education programs (Center for Community College Policy, 2002). In Texas SB 1596, passed in 2001, established the Towards Excellence, Access, and Success (TEXAS) grant program. These grants enable eligible students to attend community college, opening access to higher education to a more diverse set of people in the state (Center for Community College Policy, 2002). In addition to financial aid provided by the state and the institutions, the federal government provides financial aid to students in order to increase access to higher education. Federal financial aid regulations raise issues for community colleges that other institutions do not face (Lovell, 2001). For example, in many states, community colleges provide the bulk 157
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of remediation for students. Since federal regulations limit the amount of financial aid that may be used for remedial coursework, “community college administrators must monitor course-taking patterns of its students in a manner that baccalaureate institutions do not” (Lovell, 2001, p. 34). There are also ability-to-benefit (ATB) requirements in place that pertain to institutions with open access. Open access is one of the primary missions of community colleges, so these requirements particularly affect such institutions. These requirements are in place to ensure that a student receiving federal financial aid has the potential to successfully complete a program, which places additional monitoring and reporting constraints on participating institutions. Another area of concern for community colleges is federal regulations that require students receiving financial aid to make sufficient progress towards completing their program of study (Lovell, 2001). Community college governing systems need to be effective in accessing and distributing financial aid while complying with regulations and requirements. They need to be able to support their institutions’ ability to maintain eligibility for federal student financial aid. Governing boards will need “to know how to get the needed federal support without sacrificing local direction and control” (Lovell, 2001, p. 34). Financial aid policies regarding part-time students are also an issue for community colleges. Students who attend on a less than half-time basis are not eligible for federal financial need-based aid. Currently, 66 percent of public community college students are enrolled on a part-time basis (Vorhees, 2001). This leaves a large part of the student body ineligible for federal financial aid. This is another key issue for governing and decisionmaking boards since it affects a large part of the community college student body nationally. Institutional resources may be redirected to support these less than half-time students since they make up such a large percentage of the community college enrollment. How well the community college governance systems cope with financial aid issues and policies is an important test of its effectiveness. ACCOUNTABILITY AND PERFORMANCE FUNDING Community college leaders are faced today with accountability concerns such as quality indicators and performance funding. Community colleges, along with the rest of higher education, face diminishing fiscal resources, increasing student diversity, and both federal and state mandates for accountability (Laanan, 2001). Community colleges have particularly 158
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come under state scrutiny because they are major users of state revenues (Richardson and de los Santos, 2001). Currently, 27 states require community colleges to report on specific performance indicators, and these indicators are linked to budget allocations in ten of these states (Education Commission of the States, 2000). For instance, North Carolina passed HB 438 that clarifies performance measures on which Community Colleges are evaluated for the purpose of performance budgeting (Center for Community College Policy, 2002). Community college leaders “are in a critical position to affect the policy discussions in state capitols and in Washington” (Laanan, 2001, p. 73). The governing and coordinating boards of community colleges must work to ensure that accountability measures are designed and implemented to measure the true success of community colleges. A challenge for these governance systems and boards is to disseminate information about the effectiveness of their institutions to the public and the policy makers in a clear manner that is easily understood by their external constituencies (Laanan, 2001). More recently, statewide accountability and performance funding efforts are being used as national comparisons due in part to a recent report entitled Measuring Up 2000 (2000) (National Center for Public Policy and Higher Education, 2000). State boards, regardless of type, are paying more attention to how they are “performing” compared to each other. Performance on certain measures of performance is a key test of the effectiveness of community college governance systems. ARTICULATION ISSUES One of the oldest missions of community colleges is to provide the first 2 years of education for students seeking a bachelor’s degree (Rikfin, 1998). However, articulation can be a problem for community college students hoping to transfer to a 4-year college. According to Boswell (2000, p. 3), “many universities are reluctant to allow articulation of community college associate degrees with applied technical baccalaureate programs, limiting the opportunity for a student who completes an applied associate degree to pursue a 4-year degree.” Governance control in the area of articulation is affected by the methods states have followed to formulate articulation agreements. Most states have promoted voluntary articulation agreements where institutions are encouraged to negotiate agreements among the institutions in the state. As of 2001, 40 states have used such cooperative agreements (Education 159
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Commission of the States, 2001). Other states have legislated policies that enhance articulation, such as a common course numbering system or a core general education curriculum (Rifkin, 2001). In 2001, 23 states had a common core and 8 states had common course numbering (Education Commission of the States, 2001). Voluntary articulation agreements put this governance issue in the hands of local boards, while legislative policies place this issue in the hands of state-level boards. Recently, Illinois created a new means of articulation through the Illinois Articulation initiative (Rifkin, 2001). This initiative created a statewide general education core. A student taking this core satisfies general education at all state public institutions. This solution also defines articulation as the concern of state-level boards. In Connecticut, SB 1366 requires the Advisory Council on Student Transfer and Articulation (ACSTA) to develop a plan for coordinating articulation plans between the state system of higher education and independent colleges in the state. This bill also requires public and private boards of trustees to implement articulation agreements in the area of nursing (Center for Community College Policy, 2002). The difference in effectiveness of statewide articulation initiatives and voluntary institutional articulation has not been documented (Rifkin, 2001). Articulation may prove to be a governance issue that both local and state-level boards must face together “because state policies ultimately are implemented at the system and institutional levels” (Rifkin, 2001, p. 8). Yet if local institutions fail to adequately promote articulation, states may be tempted to assign the responsibility for articulation to state boards. This trend may already be evident. A recent study identified 34 states with statewide articulation agreements (Ignash and Townsend, 2001, p. 180). While many of these agreements were not legislated and were only moderate in strength, this trend demonstrates growing state interest in articulation initiatives. How well the system deals with articulation issues is yet another test of effective governance. SEAMLESS K-16 SYSTEM Many states are calling for a seamless K-16 educational system to better prepare and serve their citizens and the states’ needs. Creating such systems could have far reaching consequences for the governance of community colleges. According to Orr and Bragg (2001), “community colleges and public school systems are well positioned for system integration” 160
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(p. 102). The authors contend that there are several reasons for this: they are the largest and broadest serving of public education systems; both respond primarily to local and state needs; community colleges have a similar mission to K-12 education; they both emphasize access and affordability; and both are pressured by similar social forces for social equity and workforce development (p. 102). The integration of K-12 and postsecondary systems may require states to reconsider the traditional separation of K-12 and higher education governance (Boswell, 2000). States may consider establishing commissions with authority to coordinate both K-12 education and postsecondary education. Already, community colleges provide remediation to fill the gap between high school and college studies and increasingly provide dual credit to high school students enrolled in college-level classes, and this interdependence is furthering their convergence (Orr and Bragg, 2001). In three states, Ohio, Maryland, and Georgia, higher education board members at both the local and state levels are working on K-16 councils aimed at establishing reform (Boswell, 2000). In Ohio, the K-16 council has significant authority to coordinate and manage these reform efforts. The duties of the Ohio Learning Extension Network include defining what entering freshmen should be able to do; providing early assessment and intervention services for students; targeting or reallocating existing fiscal resources; and building a common education agenda through a council of state education and higher education board members (Boswell, 2000). Georgia’s P-16 initiative began in 1995 and involves four state agencies complemented by voluntary regional and local councils (Tafel and Eberhart, 1999). The state agencies set state-level goals and objectives that are adapted by the local councils to specific regional circumstances. The P-16 strategy has five goals: to improve student achievement at all levels; help students move from one education system to another; help all students in higher education to succeed; increase access to postsecondary education; and reform both teacher education and public schools (Tafel and Eberhart, 1999). Maryland also began its K-16 partnership in 1995. It is a voluntary collaboration between the Maryland State Department of Higher Education, the Maryland Higher Education Commission, and the University System of Maryland. The goals of this partnership include setting standards for students; increasing college participation and graduation rates; reducing the need for remediation; and redesigning teacher education to include strong content preparation for teachers (Tafel and Eberhart, 1999). K-16 coordination ability is another marker of community college governance effectiveness. 161
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COLLECTIVE BARGAINING AGREEMENTS Many states have university employees who are part of a collective bargaining contract. Since control over personnel issues is a common characteristic of governing boards, the presence or absence of unions can affect the level of effectiveness of that governance system. The collective bargaining contracts often dictate specific work arrangements including the length of the workday, types of work assignments employees can be given, and other items related to personnel policies. For academic employees, collective bargaining contracts can cover such items as class size and textbook selection. These agreements can limit the span of management control that can influence the direction of a community college. The number of faculty involved in collective bargaining agreements in community colleges has grown substantially. Over the last 30-year period, activity with unions drastically increased as half of the states passed authorizing legislation (Cohen and Brawer, 1996). The growth of unions spread by the beginning of the 1990s as “over two-thirds of full-time administrators in public community colleges were working under contracts negotiated collectively” (Cohen and Brawer, 1996, p. 128). Unions now represent 51 percent of full-time faculty at public 2-year institutions and 27 percent of part-time faculty (National Center for Education Statistics, 2001). Since 1993, there has been an overall gain of 8 percent in the total number of community colleges participating in collective bargaining. Specifically, there has been a 22 percent increase in the number of part-time faculty at community colleges participating in collective bargaining (National Center for Education Statistics, 2001). Since most unionized faculty work at the community college level, the nature of collective bargaining is an influencing factor to statewide and local campus-based governance as many decisions are already decided in the collective bargaining agreements. Statewide and campus-based governance often takes place in a collective bargaining environment. Collective bargaining can make it difficult to focus attention, of a local governing board, on policy issues since often times the board member’s attention is geared more towards operational management. The role of the local governing board is to provide strategic leadership by establishing goals and objectives and evaluating how effectively the college is meeting these goals (Smith, 2000). Management of daily operations is normally delegated to the institution’s president and faculty, and boards lose 162
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their opportunity to define institutional purpose when they become too focused on managerial duties (Davis, 2001). Governing boards should represent the voice of their institution to state-level boards and legislators. The advent of collective bargaining, however, may result in greater antagonism between governing boards and faculty and staff of community colleges, diminishing the board’s ability to speak for all members of the institution. Collective bargaining contracts may be institution-based or cover all community colleges within a system. For example, Minnesota, Massachusetts, and Florida each have one contract for faculty that covers all public community colleges in that state. Local administrative issues on a given campus are frequently overlooked when considering a statewide agenda. Campus administrators then have to balance their own management needs with those of all campuses within the system. The complexity of statewide agreements definitely influences administrative decisions. On the other hand, the benefits of not having to negotiate the contracts directly campus by campus are very noteworthy. It is also important to note the various unions with which community college employees affiliate. There are several different unions that might represent community college faculty including the National Education Association (NEA), the American Federation of Teachers (AFT), or local unaffiliated groups. Other non-instructional groups might represent employees other than faculty, such as the American Federation of State, County, and Municipal Employees (AFSCME), the International Brotherhood of Electrical Workers (IBEW), the Service Employees International Union (SEIU), the International Association of Fire Fighters (IAFF), and the Teamsters. Another test of the effectiveness of the community college governance system is how well it navigates the collective bargaining environment. WORKFORCE PREPARATION Recent federal legislation has created a number of federal and state school-to-work and vocational preparation programs. The Workforce Preparation Act and the reauthorized Perkins Vocational Act were passed in 1998. These legislative acts tied federal funding to workforce training offered on campuses and were intended “to keep a competitive workforce and to keep citizens employable” (Lovell, 2001, p. 31). In a 1998 survey, governors also identified providing job training and employment skills as an 163
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important function of higher education (Education Commission of the States, 2000). Workforce preparation is already one of the primary goals of community colleges. Federal and state mandates for workforce preparation serve to strengthen this mission of community colleges. Several state laws recently enacted enhanced workforce preparation efforts. In Virginia, for example, SB 572 requires community colleges to offer non-credit courses at a time and place to meet the needs of employers and to deal with employers directly in designing programs to meet current and projected workforce training requirements (Center for Community College Policy, 2002). Further, North Carolina SB 531 encourages private enterprises located in community colleges to support economic and business development (Center for Community College Policy, 2002). Finally, federal funding regulations and state interpretations of federal legislation, as they pertain to federal funds that flow through states to individual institutions, shape and influence how local institutions develop and deliver their programs. Although little is yet known about the actual impact of many federal workforce preparation initiatives (Bragg, 2002), they are an important aspect of community college programming. How well the governance system facilitates participation in these programs, is another test of its effectiveness. TECHNOLOGY As access to technology grows, “students will be more likely to select educational institutions based on offerings, convenience and price than on geography” (Mingle and Ruppert, 1998, p. 4). This could profoundly affect community colleges, which are based on providing access to students in a local geographical area. In this environment, the role of the community college could be altered to become a site that receives imported curricula, providing access to external providers (Mingle and Ruppert, 1998). This technology may alter the structure of existing community colleges. If the role of community colleges changes as a result of distance education, governance structures will need to be flexible enough to cope with this change. In 1997, Colorado created the Colorado Community College Online, a collaborative effort to offer delivery of degrees from 13 community colleges on the Internet (Mingle and Ruppert, 1998). The interconnection of a state’s community colleges online may increase the trend away from local governance and towards greater state governance and coordination. As the 164
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geographical boundaries of community colleges erode, the question arises: Who is the constituency served and how does one create a governing body that reflects the constituency? As distance-education grows, the “confusion about who’s in charge will only get worse” (Davis, 2001, p. 5). Funding from a local tax base imparts authority to local governing boards. Funding for technological infrastructure usually must come from a broader support base. Mingle and Ruppert (1998) state that “while the traditions of campus autonomy have often constrained joint program development, the competitive factors brought about by global learning networks may be enough to push institutions to collaborate out of economic necessity” (p. 11). This shift from local to state funding initiatives for technology will pose a key test to the effectiveness of statewide governance and coordination systems for community colleges.
CONCLUSIONS Community college governance has undergone tremendous changes in the past 100 years. These governance changes have defined community colleges as local community postsecondary institutions as well as statewide institutions. As community colleges enter their second century, they face many issues that may continue to redefine their place in the American educational system. In this chapter we examined two statewide governance taxonomies and three taxonomies specifically targeted to explain community college governance. Several factors that influence and test these governance structures were explored. How these factors are handled will vary by the type of state community college governance system and the kind of governance structure in place for a particular community college. The taxonomies used to describe community college governance patterns may be somewhat cumbersome and abstract, and the factors that test the effectiveness of those patterns are often complex and difficult to grasp. Therefore, as a synthesis of the community college governance taxonomies discussed in this chapter, we would like to propose one additional taxonomy that classifies community colleges according to two key characteristics: type of community college state system or board and degree of centralization. The taxonomy is displayed in Table 4.7. In our taxonomy, we build on Tollefson’s classification of the states according to the type of state agency responsible for community colleges to 165
166
Moderately Centralized
Centralized
Highly Centralized
Alabama
State Board of Education
Indiana
State Higher Education Board or Commission
North Carolina South Carolina Washington
Delaware Maine Minnesota
Colorado (state system colleges) Kentucky Connecticut
Colorado (local district colleges)
New Hampshire
State Community College Governing Board
State Community College Coordinating Board
Table 4.7: State Community College Structures and Degree of Centralization
Utah Oklahoma
Alaska Georgia Louisiana Nevada Rhode Island Tennessee Vermont Virginia West Virginia
Hawaii
State Board of Regents
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Pennsylvania
Highly Decentralized
Maryland Missouri Nebraska New Jersey New Mexico Texas
Arkansas Massachusetts New York (SUNY) Ohio Michigan Mississippi
California Florida Illinois Oregon Wisconsin Wyoming
Arizona New York (CUNY)1
New York CUNY actually has a city-level governing board that operates in a similar fashion to a state-level board.
Idaho Iowa Kansas Michigan
Decentralized
1
Oregon
Moderately Decentralized
Montana
North Dakota
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show the placement of the community colleges within the state system. We chose his classification of the type of state agency responsible for community college governance, as it is simple and easy to grasp. Concomitantly, Garrett’s measure of the degree to which each state community college system is operated in a centralized or decentralized manner is also utilized in our taxonomy. With our taxonomy, we believe it is easy to see both which state agency is responsible for community colleges and whether there is more state or local control over community colleges (or more centralized or decentralized control of the community colleges). An important feature of our taxonomy is that we included seven states and NY-CUNY that were not included in Tollefson’s original taxonomy. We also made additional decisions to place Montana and Pennsylvania in only one type of state board that, we believe, more accurately reflects their statutory authority. These additions allow a more complete view of all 50 states and the placement of their community college governance according to type of board and degree of centralization. Some observations about our taxonomy are important to make. First, states that place community colleges under boards that have responsibility for more than the state community college system usually delegate authority to the local level. For instance, State Boards of Education also usually oversee K-12 education, while State Higher Education Commissions or Boards normally have responsibility for all higher education in a state. Second, states that place community colleges under these types of boards normally have a decentralized system where more authority rests with the local community college boards. These states tend to provide a more decentralized governance structure. Perhaps implied is that the boards with broader responsibilities for multiple educational entities, are not well suited to be as involved in community college activities and thus more local control occurs. On the other hand, states with a Board of Regents, which is normally a governing board, or with a Governing Board responsible primarily for community colleges tend to exercise more state level control. These states tend to provide more centralized governance. Further, states with Coordinating Boards tend to have the most variability in whether control is at the state or the local level. Thus these states have varying degrees of centralization that are not as obvious or predictable as other states with different types of governance structures or systems. As states continue to examine their governance and coordination patterns in their states, the placement of the community colleges and locus of 168
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control may change. Governance and coordination patterns may continue to change in response to new and emerging issues facing community colleges that could redefine the purposes or mission of the community college. Traditionally these purposes include open access, affordability, workplace training, and articulation. States may want to examine their governance systems not just for current effectiveness, but also to ensure that these systems promote the purposes of the community college rather than hinder them. Those working within the community colleges should be involved in the evaluation of the governance system, and should work to define and communicate their mission to the state legislature and other policy makers. At the same time, community college leaders will need to understand the legitimate needs of the state in helping to coordinate their institutions. This means understanding the whole system of statewide coordination and understanding where their particular institution belongs in this system. State policy makers and institutions need to work together to establish state systems that meet the needs of all the constituents of the community colleges. Local board members, faculty, and staff at community colleges should be proactive in becoming involved with reviews of state systems. They need to ensure that states carefully consider the purpose of community colleges before deciding on changing their place within a state system. An effective state system is an important goal, but it should not change the mission of the community college. Rather, a restructured state system should better reflect the community college mission. There is a growing debate about whether the mission of the community college needs to change. Some leaders have discussed possible transformations of the role of community colleges, such as transforming community colleges into 4-year colleges or changing them into 2-year university branch campuses (Dougherty, 1994). Others have called for recasting the community college as a non-collegiate institution concerned primarily with vocational education. If the purpose of community colleges changes, then it will necessitate a change in statewide systems for coordination and governance. In the meantime, more attention needs to be given to assessing the effect of alternative governance structures on local institutions. Different structures produce differing results and not all governance systems are equally effective. We recommend that leaders of state systems and local community colleges work together to assess on a continuing basis, the effectiveness of their governance systems. Our simplified taxonomy can be used as the 169
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starting point to identify and describe the key features of the existing system. Once that has been done, searching questions should be asked about the effectiveness of the system, how well it helps in addressing key issues, and whether it enhances or hinders the fulfillment of the mission of the colleges it serves.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Fifty State Systems of Community Colleges: Mission, Governance, Funding and Accountability. Johnson City, Tennessee: The Overmountain Press. Goodchild, L., and Wechsler, H. (1997). The History of Higher Education. Needham Heights, MA: Simon and Schuster. Hines, E.R. (1997). State leadership in higher education. In L.F. Goodchild, C.D. Lovell, E.R. Hines, and J.I. Gill (eds.), Public Policy and Higher Education (pp. 376–409). Needham Heights, MA: Simon and Schuster. Ignash, J.M., and Townsend, B.K. (2001). Statewide transfer and articulation policies: Current practices and emerging issues. In B.K. Townsend and S.B. Twombly (eds.), Community Colleges: Policy in the Future Context (pp. 57–76). Westport, CT: Ablex Publishing. Kerr, C., and Gade, M. (1989). The Guardians: Boards of Trustees of American Colleges and Universities: What They do and How Well They do it. Washington, DC: Association of Governing Boards of Universities and Colleges. Laanan, F.S. (2001). Accountability in community colleges: Looking toward the 21st century. In B.K. Townsend and S.B. Twombly (eds.), Community Colleges: Policy in the Future Context. Westport, CT: Ablex Publishing. Lovell, C.D., and Trouth, C. (2002). State governance patterns for community colleges. In T. H. Bers and H. D. Calhoun (eds.), New Directions for Community Colleges: Next Steps for the Community College, 117: 91–100. San Francisco: Jossey-Bass. Lovell, C.D. (2001). Federal policies and community colleges: A mix of federal and local influences. In B. K. Townsend and S. B. Twombly, (eds.), Community Colleges: Policy in the Future Context. Westport, CT: Ablex Publishing. McGuinness, A. (2002). Models of Postsecondary Education Coordination and Governance in the States. Denver, CO: Education Commission of the States. McGuinness, A. (1997). The function and evolution of state coordination and governance in postsecondary education. In Education Commission of the States (ed.), State Postsecondary Structures Sourcebook: State Coordinating and Governing Boards. Denver, CO: Education Commission of the States. Measuring Up 2000. (2000). National Center for Public Policy and Higher Education. Mingle, J.R., and Ruppert, S.S. (1998). Technology planning: State and system issues. In Center for Community College Policy (ed.), Community College Policy Handbook. Denver, CO: Education Commission of the States available at http://communitycollegepolicy.com Morgan, R. ( June 20, 2002). Arizona strips state college board of money and authority. Chronicle of Higher Education. Accessed on June 20, 2002 from http://chronicle.com/daily/2002/06/ 2002062002n.htm National Center for Education Statistics. (2001). National Study of Postsecondary Faculty, 1993 and 1999. Accessed July, 2001 from http://nces.ed.gov/surveys/nsopf National Governors Association and National Association of Budget Officers (May, 2002). The Fiscal Survey of States. Accessed June, 2002 from http://www.nga.org/cda/files/ MAY2002FISCALSURVEY.pdf National Council of State Legislatures. (2002). State Fiscal Outlook for FY 2002. Denver, CO: National Council of State Legislatures. Northwest Education Research Center. (2000). Steady progress: Higher education governance in Colorado at the dawn of the 21st century. A Report to the Colorado Department of Higher Education in Response to HB 99–1289. Accessed September, 2001 from http://www.nored.net/noredprojects.htm
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Lovell and Trouth: Statewide Community College Governance Structures Orr, M.T., and Bragg, D.D. (2001). Policy directions for K-14 education — Looking to the future. In B.K. Townsend and S.B. Twombly (eds.), Community Colleges: Policy in the Future Context. Westport, CT: Ablex Publishing. Ratcliff, J., Schwarz, S., and Ebbers, L. (1994). Community colleges. Needham Heights, MA: Simon and Schuster. Richardson, R., and de los Santos, G. (2001). Statewide governance structures and two-year colleges. In B.K. Townsend, and S.B. Twombly (eds.), Community Colleges: Policy in the Future Context. Westport, CT: Ablex Publishing. Richardson, R.C., Bracco, K.R., Callan, P.M., and Finney, J.E. (1999). Designing State Higher Education Systems for a New Century. Phoenix, AZ: Oryx Press. Rifkin, T. (1998). Improving articulation policy to increase transfer. In Center for Community College Policy (ed.), Community College Policy Handbook. Denver, CO: Education Commission of the States. Smith, C.J. (2000). Trusteeship in Community Colleges: A Guide for Effective Governance. Washington, DC: Association of Community College Trustees. Tafel, J., and Eberhart, N. (1999). Statewide School–College (K-16) Partnerships to Improve Student Performance. Denver, CO: State Higher Education Executive Officers. Tollefson, T.A. (April, 2000). Martorana’s legacy: Research on state systems of community colleges. Paper presented at the annual meeting of the Council for the Study of Community Colleges, Washington, D.C. (ERIC Document Reproduction Service No. ED 443 461). Tollefson, T.A. (April, 1996). Emerging patterns in state level community college governance: A status report. (ERIC Document Reproduction Service No. ED 437 076). Tollefson, T.A. (1999). Mission, Governance, Funding, and Accountability Trends in State Systems of Community Colleges. In T.A. Tollefson, R.L. Garrett, W.G. Ingram and Associates (eds.), Fifty State Systems of Community Colleges: Mission, Governance, Funding and Accountability. Johnson City, TN: Overmountain Press. Tollefson, T.A., and Fountain, B.E. (1994). In J.L. Ratcliff (ed.), Community Colleges (2nd edn.). Needham Heights, MA: Simon and Schuster. Vorhees, R. (2001). The finance of community and technical colleges. In M.B. Paulson, and J.C. Smart (eds.), The Finance of Higher Education: Theory, Research, Policy, and Practice. New York: Agathon Press. Wellman, J.V. (2002). Weathering the double whammy: How governing boards can negotiate a volatile economy and shifting enrollments. Working Paper for the Association of Governing Boards of Universities and Colleges Conference on Trusteeship.
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5. COMPUTING AND INTERPRETING EFFECT SIZES Crystal Reneé Hill Texas A&M University Bruce Thompson Texas A&M University and LSU Health Science Center
Since its conception (Huberty, 1999), statistical significance testing has had both supporters and critics (cf. Boring, 1919). Journal editor Loftus (1994), like others, has lamented that repeated publications of these concerns [about statistical significance testing practices] never seem to attract much attention (much less impel action). They are carefully crafted and put forth for consideration, only to just kind of dissolve away in the vast acid bath of our existing methodological orthodoxy. (p. 1)
On the one hand, “There is a long and honorable tradition of blistering attacks on the role of significance testing in the behavioral sciences, a tradition reminiscent of knights in shining armor bravely marching off, one by one, to slay a rather large and stubborn dragon” (Harris, 1991, p. 375). On the other hand, supporters of statistical significance testing (i.e., Cortina and Dunlap, 1997; Robinson and Wainer, 2002) have praised it for what it can do, and have argued that if null hypothesis significance testing (NHST) did not exist, it would have to be invented (Abelson, 1997). It has been empirically demonstrated that many social scientists do not understand the logic of the method and use NHST incorrectly (Mittag and Thompson, 2000; Nelson, Rosenthal, and Rosnow, 1986; Oakes, 1986; Rosenthal and Gaito, 1963; Zuckerman, Hodgins, Zuckerman, and Rosenthal, 1993). As Thompson (1999b) noted, “I do not feel that we can J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XIX, 175–196. ©2004 Kluwer Academic Publishers. Printed in The Netherlands.
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safely presume that psychologists and educators really understand what statistical significance does and does not do (i.e., parroting mumbled words about “due to chance,” even when accompanied by enthusiastic hand flapping, doesn’t count as real understanding)” (p. 164). Of course, many social science researchers recognize that the older quantitative sciences, such as physics, chemistry, and electronics, do not currently use, nor have they ever used, the significance test as it is currently used in the behavioral sciences. Therefore, one might assume that there must be other alternatives to the significance tests, and indeed there are (Hunter, 1997). The purpose of the present chapter is to review some of the alternatives and/or compliments to statistical significance testing. Specifically, the chapter has four major sections. First, some criticisms or limitations of NHST are briefly summarized. Second, some popular effect sizes and considerations for making selections are reviewed. Third, recommendation effect size interpretation strategies are presented. Fourth, related developments involving “clinical” significance and confidence intervals (CIs) for effect sizes are briefly summarized.
CRITICISMS AND LIMITATIONS OF NHST Numerous problems with NHST have been noted. Here we summarize only four of the criticisms, limitations, or errors associated with statistical significance testing. “STATISTICAL” SIGNIFICANCE ⫽ RESULT REPLICABILITY Many researchers erroneously believe that a statistically significant result implies the replicability of results. Instead, statistical significance testing evaluates the probability or the mathematical likelihood or the sample results, given certain assumptions. Result likelihood and result replicability are very different issues, indeed! What does the p value in statistical testing tell us? Thompson (1996) explained that “p calculated is the probability (0–1.0) of the sample statistics, given the sample size, and assuming the sample was derived from a population in which the null hypothesis (H0) is exactly true” (p. 27). Or, as Baugh and Thompson (2001) explained, “Statistical significance is solely concerned with probability that a sample result is due to sampling error or 176
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chance, given the sample size and a presumption that the null (usually “nil” null of zero effect) hypothesis is exactly true in the population” (p. 122). The calculated probability value ( pCALCULATED) evaluates the probability of the sample results, but does not evaluate the probability of the same results occurring in either the population or in future samples (Cohen, 1994; Thompson, 1996). If p values did evaluate the probability that sample results matched those in the population, then NHST would indeed deal with result replicability. Future researchers drawing samples from the same population could reasonably expect similar results under these conditions. This would be very important to many researchers, because most of us want to detect only replicable results, as most of us do not wish to be embarrassed by discovering cold fusion or other events that no one else can replicate. But p does not evaluate the probability of the population. And therefore p values do not bear upon questions of replicability. Of course, as Cohen (1994) noted, the statistical significance test “does not tell us what we want to know, and we so much want to know what we want to know that, out of desperation, we nevertheless believe that it does!” (p. 997). THE “p ⫽ 0.00” ERROR It is not uncommon to see researchers report that “p ⫽ 0.00” (or even that “p ⬍ 0.00”!; see Gregg and Leinhardt, 2002). Saying that “p ⫽ 0.00” means that the researcher is declaring that impossible results were obtained. It is impossible to obtain impossible results. This error occurs because some commonly used statistical packages print “p ⫽ 0.00” when p is in fact small, but non-zero. Of course, some researchers believe that God programmed SPSS and other packages, and may not realize that these packages, actually programmed by people, may in some instances print erroneous results. This error also itself reflects endemic misunderstanding of what NHST is really doing. As Tryon (1998) recently lamented, [T]he fact that statistical experts and investigators publishing in the best journals cannot consistently interpret the results of these analyses is extremely disturbing. Seventy-two years of education have resulted in minuscule, if any, progress toward correcting this situation. It is difficult to estimate the handicap that widespread, incorrect, and intractable use of a primary data analytic method has on a scientific discipline, but the deleterious effects are doubtless substantial . . . (p. 796)
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NHST EVALUATES SAMPLE SIZE Given the defaults in commonly used statistical packages, virtually all published uses of NHST evaluate what Cohen (1994) called “nil” null hypotheses (i.e., hypotheses that presume zero difference or zero relationship). But the “nil” null can never be true in a sample. As Thompson and Keiffer (2000) explained, “Because probability equals the given occurrence divided by the total number of occurrences, given that the denominator is infinite, the probability [of having a sample with zero difference or zero relationship] is infinitely small” (p. 4). The first implication of this realization is that for given non-zero sample effects the null hypothesis will always be rejected at some sample size. Therefore, according to Kupersmid (1988), “The question is never whether the result is statistically significant, but rather, at what N the data would reach statistical significance” (p. 636). Thompson (1998a) teased, “If we fail to reject [the null hypothesis], it is only because we’ve been too lazy to drag in enough participants” (p. 799). The implication is that: Statistical significance testing can involve a tautological logic in which tired researchers, having collected data from hundreds of subjects, then conduct a statistical test to evaluate whether there were a lot of subjects, which the researchers already know, because they collected the data and know they’re tired. This tautology has created considerable damage as regards the cumulation of knowledge . . . (Thompson, 1992, p. 436)
“STATISTICAL” SIGNIFICANCE ⫽ “PRACTICAL” OR “CLINICAL” SIGNIFICANCE Thompson (2002a, pp. 7–8, 2002b) delineated three kinds of significance: “statistical,” “practical,” and “clinical.” Statistical significance evaluates the probability of the sample results, as explained previously. Practical significance evaluates the noteworthiness or import of results. Clinical significance evaluates the extent to which an intervention means that cases in a diagnostic group (e.g., depressives, learning disabled) no longer meet diagnostic criteria, and thus presumably no longer require intervention. But an unlikely event is not necessarily a practically or clinically important event! Shaver (1985) illustrated the divergence of these foci in his classic dialogue between two hypothetical doctoral students. Chris: I set the level of significance at 0.05, as my advisor suggested. So a difference that large would occur by chance less than five times
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Hill and Thompson: Effect Sizes in a hundred if the groups weren’t really different. An unlikely occurrence like that surely must be important. Jean: Wait a minute, Chris. Remember the other day when you went into the office to call home? Just as you completed dialing the number, your little boy picked up the phone to call someone. So you were connected and talking to one another without the phone ever ringing . . . . Well, that must have been a truly important occurrence then? (p. 58)
In short, “Statistical significance simply means statistical rareness” (Carver, 1978, p. 384). But very unlikely events can be completely trivial (as in the Shaver (1985) example of the phone being answered before it rang). Or, conversely, very likely events may nevertheless be highly noteworthy (e.g., it is very likely you will not die during the next few minutes you spend reading this chapter, but this may nevertheless be very important to you!). The p values in studies are not themselves good indices of result importance. This is because p values are confounded by the joint influences of sample sizes and sample results. As Thompson (1999a) explained, Because p values are confounded indices, in theory 100 studies with varying sample sizes and 100 different effect sizes could each have the same single pCALCULATED, and 100 studies with the same single effect size could each have 100 different values for pCALCULATED. (pp. 169–170)
EFFECT SIZES Cohen (1969) has been credited with popularizing the term, “effect size,” although calculations of effect sizes appeared in the literature much earlier (Huberty, 2002; Kirk, 1996). An effect size is the “Degree to which a certain phenomenon exists in a population” (Cohen, 1969, p. 9). Alternatively, effect size can be described in terms of the degree of departure of the actual sample results from those specified in the null hypothesis. As Cohen (1969) noted, “It is convenient to use the phrase ‘effect size’ to mean the degree to which the null hypothesis [of no difference] is false . . .When the null hypothesis is false, it is false to some specific degree, i.e., the effect size (ES) is some specific nonzero value in the population” (pp. 9–10). Snyder and Lawson (1993) presented another definition of effect sizes. They stated “A magnitude-of-effect [i.e., effect size] statistic tells us how much of the dependent variable can be controlled, predicted, or explained by the independent variable(s)” (p. 335). Various synonymous 179
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terms that have been used to refer to these estimates, including: (a) estimates of magnitude of the effect, (b) estimates of the magnitude of the experimental effect, (c) estimates of explained variance, (d) effect size estimates, (e) estimates of the strength of relation, (f ) estimates of the strength of association, (g) variance-accounted-for effect size, and (h) effect magnitude (Murray and Dosser, 1987; O’Grady, 1982). REQUIRED EFFECT SIZE REPORTING Given the previously discussed limitations of NHST, researchers have increasingly emphasized ES reporting. In 1994, the fourth edition of the American Psychological Association’s (APA) publication manual noted, “Neither of the two types of probability values reflects the magnitude of effect because both depend on sample size . . .You are encouraged to provide effect-size information” (APA, 1994, p. 18, emphasis added). Subsequently, in 1999, the APA Task Force on Statistical Inference declared, “Always provide some effect-size estimate when reporting a p value” (Wilkinson and APA Task Force, 1999, p. 599). The APA Task Force further emphasized, “reporting and interpreting effect sizes in the context of previously reported effects is essential [emphasis added] to good research” (p. 599). Thompson (1998b) stated that Merely encouraging effect-size reporting is akin to invoking Santa Claus or the Tooth Fairy as the sole incentive for reasonable behavior: Some kids are more susceptible than others to these influences, the incentive’s vagueness may itself help render some temptations too strong for even the nicest kids to resist, and the incentive system may not be operational on a daily basis throughout the year. More important, to only encourage what is minimally reasonable behavioral creates an inherent contradiction and thereby inevitably weakens the moral authority of the admonition. (p. 337)
These (and other) admonishments must have worked, because now the fifth edition of the APA’s publication manual (2001) stated, For the reader to fully understand the importance of your findings, it is almost always necessary to include some index of effect size or strength of relationship in your results section . . . The general principle to be followed . . . is to provide the reader not only with information about statistical significance, but also with enough information to assess the magnitude of the observed effect or relationship. (pp. 25–26, emphasis added)
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The new Manual labels “failure to report effect sizes” as a “defect in the design and reporting of research” (APA, 2001, p. 5). Today, because “encouragements” to report effects have had demonstrably limited impact (Vacha-Haase, Nilsson, Reetz, Lance, and Thompson, 2000), the following 23 journals (cf. Snyder, 2000; Trusty, Thompson and Petrocelli, 2004) now require the reporting of effect sizes: Career Development Quarterly Contemporary Educational Psychology Early Childhood Research Quarterly Educational and Psychological Measurement Educational Technology Research and Development Exceptional Children Journal of Agricultural Education Journal of Applied Psychology Journal of Community Psychology Journal of Consulting and Clinical Psychology Journal of Counseling and Development Journal of Early Intervention Journal of Educational Psychology Journal of Educational and Psychological Consultation Journal of Experimental Education Journal of Experimental Psychology: Applied Journal of Learning Disabilities Journal of Personality Assessment Language Learning Measurement and Evaluation in Counseling and Development The Professional Educator Reading and Writing Research in the Schools. More are on the way.
EFFECT SIZE CATEGORIES Some researchers erroneously believe that there is only one effect size statistic (e.g., Cohen’s d ). However, there are literally dozens of effect size choices (Elmore and Rotou, 2001). For example, Kirk (1996) catalogued 41 choices, and his list was not completely comprehensive. 181
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Various frameworks for organizing the choices have been presented. For example, Kirk (1996) used three categories in his summary, one of which was a miscellaneous category that he labeled “other measures.” Here, however, a four-category matrix (cf. Thompson, 2002b) defined by two rows (i.e., uncorrected vs corrected) and two columns (i.e., differences vs variance-accounted-for) will be used to summarize a few of the most popular effect size choices. The goal here is not to summarize every effect size statistic. Instead, the goal is to familiarize the reader with some of the available choices and to highlight some of the factors that should be considered when making effect size choices. Uncorrected Differences In medicine one might wish to characterize the efficacy of a new drug targeting weight loss. The classic double-blind experiment might be performed in which people are randomly assigned to either the new drug or a placebo group, such that neither the participants nor the drug dispensary knows which people are receiving which treatment. At the end of the 12-month intervention a straightforward effect size might be computed using the group means of post-intervention weights: ES ⫽ ME ⫺ MC. If the outcome data were measured in pounds, this effect size would also be in the metric of pounds. For example, the effect size might be ⫺20.5 pounds. Assuming the new drug had no noteworthy side effects and was reasonably affordable, most of us would deem this effect dramatic. We are familiar with the metric of pounds, and we have some idea of what are the typical impacts on weight of diets or medications. The effect is readily interpretable. The problem is that in education and psychology our measures have no intrinsic meaningful metric (see Fidler, 2002, pp. 766–767). For example, self-concept can be measured with a tool yielding a standard deviation (SD) of 7, of 15, of 27.5, or of 90. In the social sciences we often obtain scores that are more variable simply by using measures with more items. And no one measure is intrinsically better or more meaningful simply because its scores tend to be more spread out. We also confront the difficulty that some self-concept researchers may use different tools to measure effects of intervention on this outcome. Yet we 182
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want to be able to compare effects across studies using different measures with different scales. Medical researchers do not confront this dilemma because they typically have an accepted meaningful scale in which to measure effects (e.g., pounds or kilograms lost in weight interventions). Social scientists often resolve this dilemma by “standardizing” their difference effect size statistics. This is accomplished by dividing the mean difference by some estimate of the population SD. Glass (1976) proposed the standardized difference, ⌬. The Glass conducts the standardization by dividing the mean differences by the SD of only the control group. The logic behind this choice is that an intervention might affect both the mean and the SD of the intervention group’s outcome scores. Under this view the SDC gives the best estimate of the population SD. However, Cohen (1969) reasoned that some interventions may be expected to not impact the SD of outcome scores. Furthermore, a more precise estimate of the population SD might be derived by using the outcome score SDs of both groups, because sample size will be larger for this approach (i.e., N ⫽ nE ⫹ nC ⬎ nC). Thus, Cohen presented d as an effect size in which the mean difference is standardized by an average of the SD of both groups. Reflection on these two choices make clear that no one effect size can be expected to fit every situation. If group sizes were both large and the intervention was expected to impact outcome score SD, Glass’ ⌬ might be the most reasonable choice. If group sizes were small and the intervention was not expected to impact outcome score SD, Cohen’s d might be the most reasonable choice. But under other conditions the correct choice is less clear and requires even greater thoughtfulness. As elsewhere throughout statistics and measurement, judgment must be exercised. Uncorrected Variance-accounted-for Statistics Because all parametric analyses are part of a single underlying General Linear Model (GLM) (Bagozzi, Fornell, and Larcker, 1981; Cohen, 1968; Knapp, 1978), and are correlational (Thompson, 2000a,b), r 2 analogs can be computed for all these methods. Unlike difference effect sizes, varianceaccounted-for statistics are in a squared metric. These statistics have the advantage of being familiar to researchers, who regularly consult the Pearson r 2, but have the disadvantage that directions of effects are lost. Unstandardized differences retain the scale of the original outcome measures; standardized differences are in an unsquared metric but have 183
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been made “scale-free.” But all variance-accounted-for effect sizes are “metric free” (or scale-free) indices. Examples of these variance-accounted-for effect sizes are r 2, R2, RC2 (the squared canonical correlation), and the ANOVA or t-test effect size called eta squared (2). The omnipresence of the GLM can be seen, for example, in the related equations for computing the multiple regression R2 and the ANOVA or t-test 2. One formula for either r 2 or R2 is the sumof-squaresEXPLAINED divided by the sum-of-squaresTOTAL. The exact same formula is used to compute the ANOVA or t-test 2.
Corrected Variance-accounted-for Statistics No sample from the population perfectly represents the information contained in the population data. The variability in sample data that exists only in a given sample, and not in the population, is termed “sampling error variance.” Sampling error variance leads to inaccuracies in results for the sample, including inaccuracies in estimating effect sizes, because all GLM methods capitalize on all sample variance, including sampling error variance. Put simply, the GLM analysis (e.g., ANOVA, t-test, regression, MANOVA) cannot distinguish between variance that is unique or idiosyncratic to the sample, and that variance in the sample which represents variability also present in the population. However, we do know the three factors that create greater sampling error variance within sample data. There is greater sampling error (and thus greater effect size overestimation) when: 1. sample size (n) is smaller; 2. the number of measured variables is larger; and 3. the population effect size is smaller. Thus, these are the three factors invoked in the statistical correction for the positive bias in uncorrected effect sizes, which attempt to remove this bias and produce more accurate effect estimates (see Kromrey and Hines, 1996). Examples of such estimates are the regression “adjusted R2” and the ANOVA omega2 (2) and epsilon2 (⑀2). For example, the “adjusted R2 ” (R2⬘) due to Ezekiel (1930), which is always presented in SPSS as part of any multiple regression analysis, can be computed as: R2⬘ ⫽ 1 ((n ⫺ 1)/(n ⫺ v ⫺ 1)) * (1 ⫺ R2), 184
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v
n/v
n
R2⬘
Dif.
0.8 0.8 0.8 0.8 0.8 0.8 0.4 0.4 0.4 0.4 0.4 0.4 0.001 0.001 0.001 0.001 0.001 0.001
12 8 6 12 8 6 12 8 6 12 8 6 12 8 6 12 8 6
10 10 10 3 3 3 10 10 10 3 3 3 10 10 10 3 3 3
120 80 60 36 24 18 120 80 60 36 24 18 120 80 60 36 24 18
0.7776 0.7775 0.7774 0.6957 0.6933 0.6909 0.3327 0.3324 0.3321 0.0870 0.0800 0.0727 ⫺0.1110 ⫺0.1116 ⫺0.1121 ⫺0.5202 ⫺0.5318 ⫺0.5439
0.0224 0.0225 0.0226 0.1043 0.1067 0.1091 0.0673 0.0676 0.0679 0.3130 0.3200 0.3273 0.1120 0.1126 0.1131 0.5212 0.5328 0.5449
% Dif. 2.80 2.82 2.83 13.04 13.33 13.64 16.82 16.90 16.98 78.26 80.00 81.82 11203.74 11256.34 11309.43 52121.74 53280.00 54490.91
Note: “Dif.” ⫽ difference. “% Dif.” ⫽ percent difference.
where v is the number of predictor variables. Alternatively, the corrected value can be computed as: R2⬘ ⫽ R2 ⫺ ((1 ⫺ R2) * (v/(n ⫺ v ⫺ 1))). The dynamics within these corrections can be easily explored using a spreadsheet. Consider the illustrative comparisons within Table 5.1. The tabled results make clear that the amount of correction is small as the presumed population effect size is very large, even if sample size is small and the number of predictor variables is large. The table also illustrates that it is possible to obtain a negative corrected variance-accounted-for ES even though this is an estimate of a squared value. Of course, negative estimates for other variance-accountedfor statistics, such as Cronbach’s alpha (Thompson, 2002a), are also possible. Such estimates indicate severe problems in the design. Finally, the tabled results indicate that interpreting uncorrected effect sizes when sample size is small and the number of measured variables is large would be very problematic. The uncorrected estimate would represent, in effect, less than nothing! This comparison also suggests that 185
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corrected effect size estimates are particularly important when sample size is small or the number of measured variables is large. It should also be noted that the most common of these corrections (e.g., “adjusted R2”, 2, ⑀2) adjust for positive bias in sample results in an effort to estimate the effect size in the population (Snyder and Lawson, 1993). There are corrections that attempt to estimate expected effects in future samples (cf. Herzberg, 1969; Lord, 1950). Thompson (1993) argued that “From one perspective it might be argued (and has been by some — see Stevens, 1992) that estimates in the last class [future sample estimates] are the most relevant, because in practice scientists extrapolate expectations from previous studies with samples and hope their results will be replicated in future studies with samples” (p. 366) and we never have access to the full population. And there are effect size corrections that adjust for the attenuation due to the measurement error present in all scores (Thompson, 2002a). Baugh (2002) presented an overview of these corrections. As Thompson and Vacha-Haase (2000) pointed out, score reliability can fluctuate across test administrations. Thus, because “interpreting the size of observed effects requires an assessment of the reliability of the scores” (Wilkinson and APA Task Force on Statistical Inference, 1999, p. 596, emphasis added), the APA Task Force on Statistical Inference recommended that authors “provide reliability coefficients of the scores for the data being analyzed even when the focus of their research is not psychometric” (p. 596). Corrected Standardized Differences There has been some work suggesting that a corrected Cohen’s d might be computed (cf. Thompson, 2002b). However, some Monte Carlo research (cf. Roberts and Henson, 2002) suggests that such corrections are unnecessary. WHICH EFFECT SIZE IS BEST? Huberty and Morris (1988, p. 573) argued, “As in all statistical inference, subjective judgment cannot be avoided. Neither can reasonableness!” Therefore, let it be said that there is not a “one-size-fits all choice” for effect sizes. Both standardized difference and variance-accounted-for effect sizes have appealing features. Standardized differences are a natural fit with 186
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experimental designs focusing on means and involving only two groups. However, variance-accounted-for estimates can be easily computed in all parametric studies regardless of what analysis is employed. And as Thompson (1999a) noted, “On the one hand, variance-accounted-for indices do not have the benefit of reinforcing the realization that all classical analyses are correlational” (p. 171). Of course, effect sizes can be converted into each other’s metrics. For example, Cohen (1988, p. 24) provided the following formula for deriving r from d when the groups of interest are of approximately the same size: r ⫽ d/[(d 2 ⫹ 4)0.5 ]. Friedman (1968, p. 346) proposed the following formula to derive d from r: d ⫽ [2 (r)]/[ 1 ⫺ r 2 )0.5 ]. Aaron, Kromrey and Ferron (1998) provide more detail on these conversions.
INTERPRETING EFFECT SIZES CAUTIONS Various cautions must be considered when interpreting effect sizes. First, all statistic methods have assumptions. So, too, do the effect size calculations associated with a given analysis. If we violate the assumptions of an analytic method, all the results, including the related effect sizes, will be somewhat inaccurate (Thompson, 2002c). However, some new effect indices have been proposed that may be more robust to the violation of classical statistical assumptions. The work of Huberty and his colleagues (Hess, Olejnik, and Huberty, 2001; Huberty and Holmes, 1983; Huberty and Lowman, 2000) on his I statistics is particularly noteworthy. As the field continues to place greater emphasis on effect sizes, more work will be done on revising and improving the available statistics. It is also extremely important to recognize that effect sizes from different studies may not be directly comparable. This is because the context of a given study impacts the resulting effects. For example, as Olejnik and Algina (2000) pointed out in their important article, an intervention comparing the effects on comprehension skills of 10, 20, 30, and 40 min of free 187
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reading time is likely to produce smaller effects than a study comparing 30, 60, 90, and 120 min of free reading time. Intervention intensities impact detected effects. Differential intensities may need to be considered in interpreting effects across studies. The problem is that some intensities (e.g., minutes of free reading time) can be reasonably quantified, but this is not always so easy to do. Nevertheless, as Rosnow and Rosenthal (1989) noted, “It is important to recognize how the [study] characteristics might influence the size as well as one’s interpretation of the magnitude-of-effect estimate” (p. 1280). DO NOT USE FIXED BENCHMARKS In his various books Cohen (1969, 1988), almost against his better judgment, provided benchmarks for what he judged to be “small,” “medium,” and “large” effects, only as regards the typicality of the effects as compared with those reported in the social science literature as a whole. Cohen (1988) himself stressed, The terms “small,” “medium,” and “large,” are relative, not only to each other, but to the content area of behavioral science or even more particularly to the specific content and research method being employed in any given investigation . . . In the fact of this relativity, there is a certain risk inherent in offering conventional operational definitions . . . in as diverse a field of inquiry as behavioral science . . . (p. 26)
In the literature today by far the most common effect size interpretation strategy is to compare the effects in a given study against Cohen’s benchmarks. This is also an inappropriate interpretation strategy. The appropriate interpretation strategy explicitly and directly compares the effects in a given study with the effect sizes obtained in prior studies in the related literature. The recommended interpretation strategy is the correct interpretation approach for at least two reasons. First, the suggested strategy recognizes that effect magnitudes are context-specific. As Baugh and Thompson (2001) emphasized, “even some seemingly ‘small’ effect estimates (e.g., 2%) may be remarkably important when critical outcomes such as human life-or-death issues are involved” (p. 125). The use of fixed benchmarks across diverse literatures ignores the inherent context-dependency of effect sizes and their meanings, and is therefore inappropriate. Second, the interpretation of effect sizes in direct and explicit comparison with prior reported effects forces the researcher to evaluate the replicability of effects across studies (Fidler, 2002). This is essential. It is this 188
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emphasis, and not statistical significance testing, that optimally protects against serendipitous results and yields informed estimates of true effects. As Thompson (2001) recently noted, “if people interpreted effect sizes [using fixed benchmarks] with the same rigidity that ␣ ⫽ 0.05 has been used in statistical testing, we would merely be being stupid in another metric” (pp. 82–83). Similarly, Thompson (2002b) emphasized, “The potential benefits of reporting and interpreting an effect size (e.g., Cohen’s d, Glass’ delta, 2, or adjusted R2) arise not from interpreting effects against benchmarks, but rather by comparing effect sizes directly with the effects reported in related prior studies” (p. 30). The APA Task Force on Statistical Inference report sounded exactly these themes: We must stress again that reporting and interpreting effect sizes in the context of previously reported effects is essential to good research. It enables readers to evaluate the stability of results across samples, designs, and analyses. (Wilkinson and TFSI, 1999, p. 599, emphasis added)
Of course, these comparisons of effects in a given study with the effect sizes in prior studies will be vastly facilitated once all researchers routinely always report effect sizes, so that researchers reviewing prior studies do not themselves have to compute missing effect size estimates.
TWO RELATED DEVELOPMENTS Two related developments warrant some brief mention here. Our purpose is not to fully summarize these developments, but instead is intended only to alert the reader to some important ongoing related work. “CLINICAL” SIGNIFICANCE Some researchers conduct inquiry in areas in which clinical diagnostic criteria (e.g., depression, high cholesterol) are relevant. Effect sizes are indices of “practical” significance (Kirk, 1996). But two studies might yield identical effect sizes and nevertheless differ in their clinical impact. Consider two different depression interventions involving comparable samples of clinically depressed participants in both the intervention and the control conditions. Presume that outcome measure has a normative mean of 50, an SD of 10, and that the diagnostic cut off for being considered 189
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depressed is a score of 70 or more. That is, people with scores of 70 or more on this measure are deemed by psychologists to require clinical treatment (i.e., either therapy or medication, or both). Both depression intervention studies might yield Cohen’s d effect sizes of ⫺0.5, meaning that on the average both interventions reduced depression. However, in study 1 after the intervention 100% of the participants in both conditions still require treatment (i.e., still meet diagnostic criteria), while in study 2 after intervention 100% on the control participants, only 50% of the intervention participants, require treatment. Clearly study 2 has greater “clinical” significance. Jacobson, Roberts, Berns, and McGlinchey (1999) defined clinical significance as returning to normal functioning. They further specified that two conditions are necessary for a change to be considered clinically significant: “(a) the magnitude has to be statistically reliable and (b) by the end of therapy clients have to end up in a range that renders them indistinguishable from well-functioning people” (p. 300). Both considerations raise technical methodological issues. These have been explored in recent scholarship (Kazdin, 1999; Kendall, 1999), including the half-dozen articles in a 1988 special issue of Behavioral Assessment (e.g., Saunders, Howard, and Newman, 1988). CONFIDENCE INTERVALS FOR EFFECT SIZES Empirical studies confirm that CIs are almost never reported in the published literature (Finch, Cumming, and Thomason, 2001; Kieffer, Reese, and Thompson, 2001). Regarding CIs the APA Task Force noted that: Comparing confidence intervals from a current study to intervals from previous, related studies helps focus attention on stability [or the lack thereof] across studies . . . Collecting intervals across studies also helps in constructing plausible regions for population parameters. (Wilkinson and APA Task Force on Statistical Inference, 1999, p. 599)
And the new APA (2001) Publication Manual suggests that CIs represent “in general, the best reporting strategy. The use of confidence intervals is therefore strongly recommended” (p. 22, emphasis added). Computing CIs for effect sizes raises some very thorny technical issues (Cumming and Finch, 2001; Fleishman, 1980), but most of these can be resolved with specialized software (cf. Smithson, 2001; Steiger and Fouladi, 1992). The use of CIs for effect sizes has the special appeal of helping
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researchers to “think meta-analytically” (Cumming and Finch, 2001; Thompson, 2002c). Thinking meta-analytically is important, because “Metaanalysis . . . has revealed how little information there typically is in any single study. It has shown that contrary to widespread belief, a single primary study can rarely resolve an issue or answer a question” (Schmidt, 1996, p. 127). It is the effect size in a given study in the explicit comparison with effect sizes in related studies that helps us understand the literature as a whole.
SUMMARY Effect sizes will be routinely reported only once editors promulgate policies that make these practices normatively expected. As Sedlmeier and Gigerenzer (1989) argued, “there is only one force that can effect a change, and that is the same force that helped institutionalize null hypothesis testing as the sine qua non for publication, namely, the editors of the major journals” (p. 315). Glantz (1980) agreed, noting that “The journals are the major force for quality control in scientific work” (p. 3). The fact that 23 journals, including two major journals of large professional associations, now require effect size reporting bodes well for improved practices. As Fidler (2002) recently observed in her penetrating essay, “Of the major American associations, only all the journals of the American Educational Research Association have remained silent on all these issues” (p. 754). As Thompson (1999a) noted, “It is doubtful that the field will ever settle on a single index to be used in all studies, given that so many choices exist and because the statistics can be translated into approximations across the two major classes” (p. 171). But three practices should be expected: 1. report effect sizes for all primary outcomes, even if they are not statistically significant (see Thompson, 2002c); 2. interpret effect sizes by explicit and direct comparison with the effects in related prior studies (Thompson, 2002c; Wilkinson and APA Task Force on Statistical Inference, 1999); and 3. compute CIs for results, including effect sizes (cf. Cumming and Finch, 2001), and when a reasonably large number of effects for current and prior studies are available, consider using graphics to facilitate comparisons (Wilkinson and APA Task Force on Statistical Inference, 1999).
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REFERENCES Aaron, B., Kromrey, J.D., and Ferron, J.M. (November, 1998). Equating r-based and d-based effect size indices: problems with a commonly recommended formula. Paper presented at the annual meeting of the Florida Educational Research Association, Orlando, FL (ERIC Document Reproduction Service No. ED 433 353). Abelson, R.P. (1997). A retrospective on the significance test ban of 1999 (If there were no significance tests, they would be invented). In L.L. Harlow, S.A. Mulaik, and J.H. Steiger (eds.), What if There Were no Significance Tests? (pp. 117–141). Mahwah, NJ: Erlbaum. American Psychological Association. (1994). Publication Manual of the American Psychological Association (4th edn.). Washington, DC: Author. American Psychological Association. (2001). Publication Manual of the American Psychological Association (5th edn.). Washington, DC: Author. Bagozzi, R.P., Fornell, C., and Larcker, D.F. (1981). Canonical correlation analysis as a special case of a structural relations model. Multivariate Behavioral Research 16: 437–454. Baugh, F. (2002). Correcting effect sizes for score reliability: A reminder that measurement and substantive issues are linked inextricably. Educational and Psychological Measurement 62: 254–263. Baugh, F., and Thompson, B. (2001). Using effect sizes in social science research: New APA and journal mandates for improved methodology practices. Journal of Research in Education 11(1): 120–129. Boring, E.G. (1919). Mathematical vs. scientific importance. Psychological Bulletin 16: 335–338. Carver, R. (1978). The case against statistical significance testing. Harvard Educational Review 48: 378–399. Cohen, J. (1968). Multiple regression as a general data-analytic system. Psychological Bulletin 70: 426–443. Cohen, J. (1969). Statistical Power Analysis for the Behavioral Sciences. New York: Academic Press. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd edn.), Hillside, NJ: Erlbaum. Cohen, J. (1994). The earth is round (p ⬍ .05). American Psychologist 49: 997–1003. Cortina, J.M., and Dunlap, W.P. (1997). Logic and purpose of significance testing. Psychological Methods 2: 161–172. Cumming, G., and Finch, S. (2001). A primer on the understanding, use and calculation of confidence intervals that are based on central and noncentral distributions. Educational and Psychological Measurement 61: 532–574. Elmore, P., and Rotou, O. (2001, April). A primer on basic effect size concepts. Paper presented at the annual meeting of the American Educational Research Association, Seattle (ERIC Document Reproduction Service No. ED 453 260). Ezekiel, M. (1930). Methods of Correlational Analysis. New York: Wiley. Fidler, F. (2002). The fifth edition of the APA Publication Manual: Why its statistics recommendations are so controversial. Educational and Psychological Measurement 62: 749–770. Finch, S., Cumming, G., and Thomason, N. (2001). Reporting of statistical inference in the Journal of Applied Psychology : Little evidence of reform. Educational and Psychological Measurement 61: 181–210. Fleishman, A.I. (1980). Confidence intervals for correlation ratios. Educational and Psychological Measurement 40: 659–670.
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Hill and Thompson: Effect Sizes Friedman, H. (1968). Magnitude of experimental effect and a table for its rapid estimation. Psychological Bulletin 70: 245–251. Glantz, S.A. (1980). Biostatistics: How to detect, correct and prevent errors in the medical literature. Circulation 61: 1–7. Glass, G. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher 5(10): 3–8. Gregg, M., and Leinhardt, G. (2002). Learning from the Birmingham Civil Rights Institute: Documenting teacher development. American Educational Research Journal 39: 553–587. Harris, M.J. (1991). Significance tests are not enough: The role of effect-size estimation in theory corroboration. Theory & Psychology 1: 375–382. Herzberg, P.A. (1969). The parameters of cross-validation. Psychometrika Monograph Supplement 16: 1–67. Hess, B., Olejnik, S., and Huberty, C.J (2001). The efficacy of two Improvement-over-chance effect sizes for two-group univariate comparisons under variance heterogeneity and nonnormality. Educational and Psychological Measurement 61: 909–936. Huberty, C.J. (1999). On some history regarding statistical testing. In B. Thompson (ed.), Advances in Social Science Methodology (Vol. 5, pp. 1–23). Stamford, CT: JAI Press. Huberty, C.J. (2002). A history of effect size indices. Educational and Psychological Measurement 62: 227–240. Huberty, C.J., and Holmes, S.E. (1983). Two-group comparisons and univariate classification. Educational and Psychological Measurement 43: 15–26. Huberty, C.J., and Lowman, L.L. (2000). Group overlap as a basis for effect size. Educational and Psychological Measurement 60: 543–563. Huberty, C.J., and Morris, J.D. (1988). A single contrast test procedure. Educational and Psychological Measurement 48: 567–578. Hunter, J.E. (1997). Needed: A ban on the significance test. Psychological Science 8(1): 3–7. Jacobson, N.S., Roberts, L.J., Berns, S.B., and McGlinchey, J.B (1999). Methods for defining and determining the clinical significance of treatment effects: Description, application, and alternatives. Journal of Consulting and Clinical Psychology 67: 300–307. Kazdin, A.E. (1999). The meanings and measurement of clinical significance. Journal of Consulting and Clinical Psychology 67: 332–339. Kendall, P.C. (1999). Clinical significance. Journal of Consulting and Clinical Psychology 67: 283–284. Kieffer, K.M., Reese, R.J., and Thompson, B. (2001). Statistical techniques employed in AERJ and JCP articles from 1988 to 1997: A methodological review. Journal of Experimental Education 69: 280–309. Kirk, R.E. (1996). Practical significance: A concept whose time has come. Educational and Psychological Measurement 56: 746–759. Knapp, T.R. (1978). Canonical correlation analysis: A general parametric significance testing system. Psychological Bulletin 85: 410–416. Kromrey, J.D., and Hines, C.V. (1996). Estimating the coefficient of cross-validity in multiple regression: A comparison of analytical and empirical methods. Journal of Experimental Education 64: 240–266. Kupersmid, J. (1988). Improving what is published: A model in search of an editor. American Psychologist 43: 635–642. Loftus, G.R. (1994, August). Why psychology will never be a real science until we change the way we analyze data. Paper presented at the annual meeting of the American Psychological Association, Los Angeles.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Lord, F.M. (1950). Efficiency of Prediction when a Regression Equation from One Sample is Used in a New Sample (Research Bulletin 50–110). Princeton, NJ: Educational Testing Service. Mittag, K.C., and Thompson, B. (2000). A national survey of AERA members’ perceptions of statistical significance tests and other statistical issues. Educational Researcher 29(4): 14–20. Murray, L.W., and Dosser, D.A. (1987). How significant is a significant difference? Problems with the measurement of magnitude of effect. Journal of Counseling Psychology 34: 68–72. Nelson, N., Rosenthal, R., and Rosnow, R.L. (1986). Interpretation of significance levels and effect sizes by psychological researchers. American Psychologist 41: 1299–1301. Oakes, M. (1986). Statistical Inference: A Commentary for the Social and Behavioral Sciences. New York: Wiley. O’Grady, K.E. (1982). Measures of explained variance: Cautions and limitations. Psychological Bulletin 92: 766–777. Olejnik, S., and Algina, J. (2000). Measures of effect size for comparative studies: Applications, interpretations, and limitations. Contemporary Educational Psychology 25: 241–286. Roberts, J.K., and Henson, R.K. (2002). Correction for bias in estimating effect sizes. Educational and Psychological Measurement 62: 241–253. Robinson, D.H., and Wainer, H. (2002). On the past and future of null hypothesis significance testing. Journal of Wildlife Management 66: 263–271. Rosenthal, R., and Gaito, J. (1963). The interpretation of level of significance by psychological researchers. Journal of Psychology 55: 33–38. Rosnow, R.L., and Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist 44: 1276–1284. Saunders, S.M., Howard, K.I., and Newman, F.L. (1988). Evaluating the clinical-significance of treatment effects — norms and normality. Behavioral Assessment 10: 207–218. Schmidt, F. (1996). Statistical significance testing and cumulative knowledge in psychology: Implications for the training of researchers. Psychological Methods 1: 115–129. Sedlmeier, P., and Gigerenzer, G. (1989). Do studies of statistical power have an effect on the power of studies? Psychological Bulletin 105: 309–316. Shaver, J. (1985). Chance and nonsense. Phi Delta Kappan 67(1): 57–60. Smithson, M. (2001). Correct confidence intervals for various regression effect sizes and parameters: The importance of noncentral distributions in computing intervals. Educational and Psychological Measurement 61: 605–632. Snyder, P. (2000). Guidelines for reporting results of group quantitative investigations. Journal of Early Intervention 23: 145–150. Snyder, P., and Lawson, S. (1993). Evaluating results using corrected and uncorrected effect size estimates. Journal of Experimental Education 61: 334–349. Steiger, J.H., and Fouladi, R.T. (1992). R2: A computer program for interval estimation, power calculation, and hypothesis testing for the squared multiple correlation. Behavior Research Methods, Instruments, and Computers 4: 581–582. Stevens, J. (1992). Applied Multivariate Statistics for the Social Sciences (2nd edn.). Hillsdale, NJ: Erlbaum. Thompson, B. (1992). Two and one-half decades of leadership in measurement and evaluation. Journal of Counseling and Development 70: 434–438. Thompson, B. (1993). The use of statistical significance tests in research: Bootstrap and other alternatives. Journal of Experimental Education 61: 361–377.
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Hill and Thompson: Effect Sizes Thompson, B. (1996). AERA editorial policies regarding statistical significance testing: Three suggested reforms. Educational Researcher 25(2): 26–30. Thompson, B. (1998a). In praise of brilliance: Where that praise really belongs. American Psychologist 53: 799–800. Thompson, B. (1998b). Review of What if there were no significance tests? Educational and Psychological Measurement 58: 332–344. Thompson, B. (1999a). If statistical significance tests are broken/misused, what practices should supplement or replace them? Theory & Psychology 9: 167–183. Thompson, B. (1999b). Journal editorial policies regarding statistical significance tests: Heat is to fire as p is to importance. Educational Psychology Review 11: 157–169. Thompson, B. (2000a). Canonical correlation analysis. In L. Grimm, and P. Yarnold (eds.), Reading and Understanding More Multivariate Statistics (pp. 285–316). Washington, DC: American Psychological Association. Thompson, B. (2000b). Ten commandments of structural equation modeling. In L. Grimm, and P. Yarnold (eds.), Reading and Understanding More Multivariate Statistics (pp. 261–284). Washington, DC: American Psychological Association. Thompson, B. (2001). Significance, effect sizes, stepwise methods, and other issues: Strong arguments move the field. Journal of Experimental Education 70: 80–93. Thompson, B. (ed.) (2002a). Score Reliability: Contemporary Thinking on Reliability Issues. Newbury Park, CA: Sage. Thompson, B. (2002b). “Statistical,” “practical,” and “clinical”: How many kinds of significance do counselors need to consider? Journal of Counseling and Development 80: 64–71. Thompson, B. (2002c). What future quantitative social science research could look like: Confidence intervals for effect sizes. Educational Researcher 31(3), 24–31. Thompson, B., and Kieffer, K.M. (2000). Interpreting statistical significance test results: A proposed new “What if” method. Research in the Schools 7(2): 3–10. Thompson, B., and Vacha-Haase, T. (2000). Psychometrics is datametrics: The test is not reliable. Educational and Psychological Measurement 60: 174–195. Trusty, J., Thompson, B., and Petrocelli, J.V. (2004). Practical guide to implementing the requirement of reporting effect size in quantitative research in the Journal of Counseling & Development. Journal of Counseling and Development. Tryon, W.W. (1998). The inscrutable null hypothesis. American Psychologist 53: 796. Vacha-Haase, T., Nilsson, J.E., Reetz, D.R., Lance, T.S., and Thompson, B. (2000). Reporting practices and APA editorial policies regarding statistical significance and effect size. Theory & Psychology 10: 413–425. Wilkinson, L., and APA Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist 54: 594–604 (reprint available through the APA Home Page: http://www.apa.org/journals/amp/ amp548594. html). Zuckerman, M., Hodgins, H.S., Zuckerman, A., and Rosenthal, R. (1993). Contemporary issues in the analysis of data: A survey of 551 psychologists. Psychological Science 4: 49–53.
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6. FOLLOW THE MONEY: THE CHANGING WORLD OF BUDGETING IN HIGHER EDUCATION William F. Lasher and Charlotte A. Sullivan The University of Texas at Austin
INTRODUCTION AND OVERVIEW This chapter continues and updates the discussion of what we know about budgeting in higher education that was begun in 1993 by Lasher and Greene in their chapter on “College and University Budgeting: What Do We Know? What Do We Need to Know?” in Volume IX of Higher Education: Handbook of Theory and Research. That chapter was recognized as a “sophisticated primer” on higher education budgeting, when it was re-published in 2001 as part of the ASHE Reader on Finance in Higher Education, Second edition. It was also re-published with an Epilogue in Michael Paulsen and John Smart’s recent book, The Finance of Higher Education: Theory, Research, Policy and Practice (2001). The intent of the Epilogue was to begin the process of updating the traditional topics about higher education budgeting in light of changes in student applicants, delivery systems, accreditation and accountability trends, performance funding, and responsibility center budgeting (RCB). We encourage readers to review the original discussion and the epilogue update. However, because the environment of budgeting in higher education has changed so much since the 1993 chapter was written, and even faster since the 2001 epilogue was written, a complete reexamination of traditional topics, and a thorough examination of new and emerging topics, are needed in order to better inform administrators, J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XIX, 197–240. ©2004 Kluwer Academic Publishers. Printed in The Netherlands.
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policy-makers, policy analysts, and researchers regarding what we have learned about budgeting in a rapidly changing environment. The purpose of this chapter is twofold: first, to reexamine the traditional topics associated with budgeting in light of the substantial and varied changes in the demographic, economic, political, and institutional characteristics of the contemporary environment in which higher education budgeting takes place; and second, to thoroughly examine changes in the environment and how both traditional and newer approaches to budgeting in higher education have developed or evolved in response to such changes. We look first at the nature of budgeting and the budget process in the current environment. Next, we present an extensive discussion of the environmental factors (economic, financial, political, demographic, and institutional) that influence budgeting and the budgeting process. Then, we describe and explain the nature, strengths and weaknesses of the traditional approaches used in budgeting in higher education and discuss how the use of various budgeting approaches has developed or evolved in recent years in response to changes in environmental conditions. Finally, we conclude with some modest speculation on the near-term future.
CHANGES IN BUDGET PROCESS Merriam Webster’s Collegiate Dictionary (1993) defines a budget as a “statement of the financial position of an administration for a definite period of time based on estimates of expenditures during the period and proposals for financing them; a plan for the coordination of resources and expenditures; the amount of money that is available for, required for, or assigned to a particular purpose.” Wildavsky (1988) defined a budget as the “link between financial resources and human behavior in order to accomplish policy objectives” (p. 2). Basically, a budget is an organization’s current year plan for how it’s going to accomplish its priorities, expressed in dollars. This definition has not changed. Nor has the importance of developing a budget changed at various levels of government. Several years ago, a former Lieutenant Governor of Texas was quoted as saying, “The appropriations bill is the most important piece of legislation the legislature considers. The rest is poetry.” What has changed in the current environment is the need for flexibility. The budget process continues to consist of multiple overlapping processes. While the budget for the current year is being administered, the 198
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budget for next year is being developed, and last year’s budget is being evaluated (although this phase probably exists more in theory than in practice) and audited. At the same time, in public institutions, the request for the next appropriations cycle is being developed. Later, we provide a thorough discussion of the current economic situation facing higher education. Suffice it here to say that, many institutions are faced with the prospect of mid-year recisions, that is, the realization that budgeted revenues will not be as high as originally estimated. While this has happened before (in the early 1990s at many public institutions), the impact on the administration of the current year budget at the affected institutions can be devastating. The timing of the occurrence of these events is especially important. A very simple example will illustrate this point. Let us say that a public institution receives word from the state that its appropriations allotment for the current fiscal year will be reduced by 4 percent. Let us also say that the institution receives this word 6 months into the fiscal year. Assuming that the cuts have not been rumored and that the institution has been spending its appropriation allotment at the originally adopted rate, the effective impact on the second half of the fiscal year is an 8 percent reduction in revenue. In this scenario, the resulting need to reduce expenditures is substantial. When an unexpected mid-year reduction in appropriations is announced, budget officers must remain flexible, be prepared to make adjustments in the current year’s budget and assess the probable impact of such reduced appropriations on the development of next year’s budget. THE RELATIONSHIP BETWEEN BUDGETING AND PLANNING Such an environment also affects the important relationship between budgeting and planning. The notion of the budget-as-plan was prominent in the definitions of budgeting given earlier. Nevertheless, this crucial relationship is often confounded by the very nature of these processes (Meisinger, 1994; Schmidtlein, 1989). ●
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Planning is oriented to the long-term future — 5, 10, 20 years. Budgeting also focuses on the future, but on the near-term the next 1–2 years. Planning deals with general concepts — the institution’s outputs and outcomes; its mission, goals, and objectives. Budgeting deals with specifics — the inputs to produce the outputs and outcomes, organizational units and departments, specific programs, and resources such as faculty and staff, space, and dollars. 199
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Planning deals with dreams and “What ifs.” Budgeting is concerned with current realities — political and economic conditions, availability of funds. Planning deals with concepts. Budgeting deals with details. Planning is concerned with vision and leadership. Budgeting is concerned with administration and management.
Unfortunately, when financial conditions become tight, the time horizon that institutional stakeholders are willing to consider shrinks. They become focused on the next few months (how will this affect the institution?), rather than the longer term (what can this institution become?). And if the troubling financial conditions persist, the only planning that may be accomplished is that which is associated with the budget.
THE EFFECTS OF GASB-35 Budgeting is related to accounting and an institution’s budget is greatly affected by its chart of accounts and its accounting practices. The budget and the process through which it is prepared are, of course, much larger than the accounting system, but changes in accounting structures, rules, and standards can impact the budget. Of particular importance in this regard are the recent changes in accounting practices required by GASB-35. The Governmental Accounting Standards Board (GASB) is responsible for creating accounting standards and rules followed by state and local governments, including public colleges and universities ( June, 2002). These standards affect how institutions prepare their financial statements and other information that convey to financial institutions and other interested parties their financial condition, that is, their financial health. GASB-35 is a set of accounting rules, approved in November 1999, that substantially changes the way public colleges and universities report their information. Private colleges and universities were required to change their financial statements in 1993, and the changes required by GASB-35 will make the information from public institutions look more like that from private institutions. Two of the major changes are that public institutions will now have to calculate depreciation on their buildings, land, and equipment, and they will have to report their financial information in a consolidated format rather than according to the tenets of fund accounting. Fund accounting is a method that classifies all resources into separate fund groups according 200
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to specific limitations placed on their use by the providers of the resources (Wainwright, 1992, p. 222). Each fund group has its own set of accounts; its own assets, liabilities, and fund balances — all of which are reported separately. GASB-35 requires that these several balance sheets be consolidated into one. Public colleges and universities are moving to these new accounting rules in phases. Institutions with more that $100 million in annual revenues were required to follow GASB-35 standards by the end of fiscal year 2002. Those with revenues between $10 million and $100 million were required to make the move by the end of fiscal 2003, and the remaining institutions must comply by the end of fiscal 2004 ( June, 2002). In many ways, this is a matter of reporting the same information in a new format. The expectation is that, apart from developing new consolidated financial statements, public institutions will continue to rely on fund accounting for many years. The experience at many private institutions so far is that the decision-making involved in the budgeting process is largely unaffected by the required changes in accounting practices. The requirement to depreciate buildings and equipment may have a greater impact on budgeting. Conceptually, the cost of buildings and major equipment is prepaid in advance of the utilization of the asset. As the asset is utilized over its life in operations, the cost is allocated in the form of depreciation. But depreciation is not a cash expenditure, and institutional budgets typically focus on sources and uses of cash. Discussions concerning ways to appropriately and effectively budget depreciation are already under way at many public institutions. Regardless of the outcome of such discussions, it is likely that developing appropriate budgets and reserves for the upkeep and renewal of facilities will receive even more attention during discussions of deferred maintenance. Capital renewal is, conceptually, the reinvestment of dollars to maintain or restore facilities to extend their useful lives. These costs can vary from year to year depending on the age of the building and its subsystems, that is, roof, air handling, etc. Institutions may budget some capital renewal funds, but very few are able to budget sufficient funds to provide for consistent facilities renewal, especially during difficult financial periods. (Unlike personnel resources, buildings don’t complain about budget cuts.) The reporting and budgeting problems associated with depreciation and renewal funds are separable, but related. Over time, planning for depreciation write-offs may bring these problems to the forefront of institutional planning and budgeting discussions in new ways and with greater intensity. 201
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ENVIRONMENTAL FACTORS THAT INFLUENCE BUDGETING ECONOMIC AND FINANCIAL ENVIRONMENT The National Situation David Breneman (2002) observed that each decade since 1970 has opened with a recession in the United States. The early 1970s were marked by rising inflation and slow economic growth, accompanied by a national energy crisis. Institutions of higher education were surprised by that recession, having experienced sustained growth in enrollment and financial support since the baby boom following World War II. With the recession of the early 1980s, many blamed public schools for the nation’s economic difficulties. This was fueled by the publication of A Nation at Risk, a report from the U.S. Department of Education, which indicated that America’s public schools had failed to educate students to be competitive in the global market (U.S. Department of Education, 1983). Double-digit inflation caused institutions of higher education to begin to raise their tuition significantly. In the early 1990s, the end of the Cold War and decelerated spending on national defense caused a slowing of economic activity. Additionally, states were faced with increasing demands for other public services such as prisons and Medicaid. As a result, total state appropriations for higher education across the nation — measured in current dollars — actually decreased in 1992–93, the first time that had happened since this type of information had been collected. Following that recession, the nation experienced tremendous economic growth, and total state appropriations grew each year through 2001–02 (Breneman, 2002). The economic downturn of the early 2000s reflects the impact of such factors as the collapse of the dot-com industry, the attacks of September 11, 2001, and the accounting scandals in several major corporations, which has led to subsequent filings for Chapter 11 bankruptcy. The current downturn is predicted to be short-lived, but its effects may linger for a time. In the States The ebb and flow of the nation’s economic cycle affects individual states to varying degrees. The recession of the early 1990s, impacted states 202
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dramatically. In 1991, state budget shortfalls amounted to 6.2 percent of total state general revenues, requiring 28 states to impose budget cuts. Even though the recession ended in 1991, state revenue growth lagged behind the nation’s recession. In 1992, state revenue shortfalls amounted to 6.5 percent of revenues, forcing 35 states to enact budget cuts (National Association of State Budget Officers [NASBO], 2002b). In contrast, the late 1990s represented a financial boom for the nation’s economy. The state budgets developed at the turn of the century reflected the confidence based on the financial boom of the late 1990s, but as the national recession began state revenues could not match their optimistic budget estimates. In July 2002, the National Conference of State Legislatures (NCSL) reported that state fiscal conditions continued to deteriorate. Many states were forced to reduce spending to close mid-year budget gaps caused by lower revenues and declining general funds. Forty-two states reported budget shortfalls for fiscal year 2002 totaling $37.2 billion or an estimated 7.5 percent (NASBO, 2002b). Based on the experiences of the recession of the early 1990s, it is predicted that state revenue growth will again lag behind the end of the national recession by 12–18 months (NASBO, 2002b). Accordingly, the aggregate state budget gap for fiscal year 2003 was estimated to be $57.4 billion (NCSL, 2002). California accounted for more than 40 percent of this estimate with an estimated budget gap of $23.7 billion. In order to manage these deficits, state officials began to implement acrossthe-board cuts, tap into rainy day and other state funds, enact hiring freezes, reorganize programs, and draw on tobacco settlement funds. Nineteen states reduced funding for higher education, and tuition be increased to cover the deficit. Similarly, states employed additional measures to close the budget gaps for fiscal year 2003: cutting spending, increasing taxes, and raising fees. Institutional Measures In order to manage fluctuations in the economic and financial environment, institutions must take measures to increase revenue, reduce spending, or both. During economic recessions, when state funding decreases, state officials and institutions of higher education have typically transferred a greater portion of the cost of education to students and their parents in the form of increased tuition and fees (Paulsen, 1991, 2000). A recent report by the National Center for Public Policy and Higher Education (NCPPHE), “Losing Ground: A National Status Report on the 203
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Affordability of American Higher Education,” found that over the last 20 years, tuition has risen most sharply during times of economic difficulty (NCPPHE, 2002b). Thus, education costs rise sharply at times when students and their families are least able to pay due to rising unemployment and losses in state public services. A similar finding was reported by the Nation Center for Education Statistics (NCES). In 1998, Congress directed NCES to conduct a study to determine the amount of higher education costs paid by institutions as well as students and their families. The report examined college costs and prices between 1988–89 and 1997–98 and found that tuition increased at a faster rate than inflation (Cunningham, Wellman, Clinedinst, Merisotis, and Carroll, 2001). For public 4-year institutions, the report found that changes in tuition were most closely associated with changes in revenue from state appropriations. Decreases in state appropriations required an increase in tuition. For private 4-year institutions, two factors most strongly affected charges in tuition: institutional aid and the average amount of faculty compensation. Larger institutional aid and faculty compensation levels required higher tuition. Other factors — endowment income, private gifts, grants, and contracts — had a somewhat smaller influence on tuition charges at private 4-year institutions. As these revenue sources decrease, tuition tends to increase. Further complicating the situation is the availability of financial aid for low-income families. Over the last 20 years, tuition has increased faster than financial aid grants (NCPPHE, 2002). Since 1980, tuition has increased by 107 percent. The average federal Pell grant covered 98 percent of tuition in 1986; in 1999, it only covered 57 percent. State grants (both need-based and non-need-based) covered 75 percent of tuition in 1986, but only 64 percent in 1999 (NCPPHE, 2002). The Advisory Committee on Student Financial Assistance (ACSFA) provides advice and recommendations to the Congress and the Secretary of Education concerning ways to maintain and enhance access to postsecondary education. This group and others have reported that policy-makers at both the federal and state levels have shifted priorities from low- to middle-income students (ACSFA, 2001, 2002; Callan, 2002). Examples of this shift include: the state programs, patterned mostly after Georgia’s HOPE Scholarship program, that provide funds based on merit rather than financial need; and the tuition tax credits developed at the federal level during the mid-1990s, which apply to families with taxable incomes between $40,000 and $90,000. Therefore, now that states are experiencing decreases in revenue, many will likely be unable to afford increases in their financial aid programs. 204
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To the extent that these programs have shifted emphasis to merit-based aid programs, states may face another set of budgeting challenges, especially if they are confronted with increased numbers of students from low-income families who desire access to public institutions, as expected. Thus, the affordability problem that already exists for many low-income families at public institutions may be exacerbated further. Private institutions use tuition discounting to strategically accomplish their admissions and retention goals (Breneman, Doti, and Lapovsky, 2001). According to Loren Loomis Hubbell and Lucie Lapovsky, tuition discounting has continued to increase over the last 12 years they have been studying the matter. In 2001, tuition for entering full-time freshman was discounted 38.2 percent on average at the private 4-year colleges and universities participating in their study. The largest tuition discounts were found at small colleges with relatively low tuitions; in 2001, students at these institutions received discounts that averaged 43 percent, up from 28.5 percent in 1990. The number of students receiving aid at these institutions also increased; in 2001, 89.7 percent received aid, up from 73 percent in 1990 (Hubbell and Lapovsky, 2002). From the standpoint of an institution’s annual operating budget, the most important impact of tuition discounting is on net tuition revenue, that is, gross tuition revenue, less revenue shifted to financial aid. At present, private institutions retain an average of 62¢ of each $1.00 generated from increased tuition. If an institution had to put all of the money generated from increased tuition into its financial aid program in order to attract students, there obviously would be nothing left to spend on improvements in education programs and other institutional activities. If financial aid has to grow faster than gross tuition, net tuition revenue increases more slowly, and may even decline. Hubbell and Lapovsky have found that small colleges with high tuition levels (defined in their latest study as greater than $19,880) and large colleges and universities (defined as having full-time freshmen enrollments of greater than 850) tend to generate additional revenue from tuition increases. Small colleges with low tuition levels (less than 850 freshmen and below $19,880) tend to generate less. Hubbell and Lapovsky’s information was as of Fall 2001. The national economic situation has not improved appreciably since then. If small, less competitive institutions have trouble generating sufficient funds, they may have to reduce their budgets to such an extent that it may be difficult for them to offer the level of educational quality they need to remain viable. Fund-raising provides an additional revenue stream for both public and private institutions. As of October 2002, 20 public and private 205
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institutions had instituted billion dollar campaigns (Reese, 2002). The difficulty in using income from gifts and bequests has to do with its restricted nature. Few donations are provided as a direct subsidy for current operations without some limitations on how they can be used. Ongoing conventional expenditures by institutions for things such as overall staff salaries, maintenance of existing facilities, or equipment purchases are not always appealing to donors. Instead, donors like to provide support for more interesting objectives such as named professorships, student scholarships, or new facilities — especially if their name can be tied directly to the program as a lasting tribute. Further complicating the problem is the impact of the recession on the financial markets and donor portfolios, which are dependent on the return on investments to provide the wherewithal for philanthropic intentions. If a donor’s assets lose value, the contribution may be lower than expected or postponed. In some situations, donors have had to delay or reduce the payment of pledges in order to meet their own fiscal realities. A national recession can also impact college and university endowments. Typically, institutions determine how much of their endowment to use in support of their annual operating budgets through a spending policy based on a pre-specified percentage of a moving average of the market values of their endowments over a specified number of recent years. Those endowments losing value leave a smaller sum of money to be spent in the future unless policies are altered. According to a survey conducted by the National Association of College and University Business Officers (NACUBO), in fiscal year 2001, eight of the ten largest endowments experienced negative returns and the average college endowment lost 3.6 percent of its value (Klinger, 2002). Losses occurred in the 2002 fiscal year as well. The most vulnerable institutions are the small private, relatively poor institutions. The National Association of Independent Colleges and Universities indicates that almost 800 colleges have endowments of $12 million or less. These institutions are heavily dependent on tuition and have little endowment revenue with which to moderate the effects of lost revenue (Van Der Werf, 2002). As indicated above, they also tend to be the institutions that have relied heavily on tuition discounting (Breneman, 1994). During “good” economic times, college and university leaders often argue that their budgets need to increase by at least the rate of inflation in order to maintain their current level of activity. Because higher education is a labor-intensive industry, and because library acquisitions and specialized
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equipment are expensive (among other factors), inflation in institutions of higher education is often said to be higher than in the larger economy. In fact, the Higher Education Price Index was developed by Kent Halstead to track these differences. However, Howard Bowen and others have taught us that colleges and universities are so driven by the pursuit of excellence and prestige that “ . . . there is virtually no limit to the amount of money an institution could spend for seeming fruitful educational ends” (Bowen, 1980, p. 20). Under Bowen’s revenue theory of cost, colleges and universities generate all the income they can, and they spend it all. Obviously, these are over-statements, but they do indicate some of the reasons why, if colleges and universities are to be required to spend fewer dollars or use their resources more efficiently, the onus will have to come from the external environment. That certainly seems to be happening as we move further into the first decade of the new century. Institutions are being asked by forces in their environment to do “more with less.” State governments are giving that message to public institutions. The financial markets are giving that message to private institutions. Students and families are wondering aloud why tuition and fees have to increase at twice the rate of inflation. Since colleges and universities rely so heavily on funding sources from their environment, they are reacting. Techniques for retrenchment and reallocation in higher education have been used in the past. They are being used again. We shall discuss them more specifically later in this chapter. POLITICAL ENVIRONMENT More Transparent Financial Information In 1997, the public’s anxiety over college costs and increased demands for accountability led congressional leaders to establish the National Commission on the Cost of Higher Education (NCCHE) as an independent advisory body to examine college costs. These leaders were particularly interested in the rising cost of tuition and had been considering measures to curb the rising cost of college before reauthorizing the Higher Education Act, which controls most federal student aid programs (Burd, 1997a,b). In 1998, the Commission published a report, “Straight Talk About College Costs and Prices,” which presented an action agenda for various entities. For institutions of higher education, the Commission advocated measures to keep college affordable and advised colleges and universities to increase
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their accountability to the public by providing detailed information about college costs in order to regain the public’s trust (NCCHE, 1998). In response to the Commission’s charge, NACUBO established an Ad Hoc Committee on College Costs to develop a uniform methodology that all institutions might use to explain the cost of 1 year of undergraduate education using existing financial statements that present the information in a clear and concise manner. A template was developed and field-tested by 150 colleges and universities. From this project, the Ad Hoc Committee made several observations (NACUBO, 2002, p. 10): ●
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Cost exceeds price. In essentially every instance, the cost of providing an undergraduate education exceeds the full “sticker” price charged to students and their families in the form of tuition and related fees, by anywhere from a few hundred dollars to as much as $20,000 or more . . . The majority of costs are for instruction and student services. At community colleges and public 4-year institutions, instruction and student services costs comprise about 85 percent of the total. At independent colleges and universities, the comparable share is around 70 percent, largely because those institutions spend significantly more of their own resources per student on financial aid . . . American higher education is very diverse. Costs vary greatly, consistent with the tremendous diversity of American higher education... Some institutions spend as little as $5,000 per student each year and provide an excellent education for the particular population they serve; other institutions serving different populations and with different missions (and different resources) spend as much as $40,000–$50,000 per student . . .
None of these observations are particularly startling or new, but they do reflect basic economic characteristics of colleges and universities. It is important that they have been placed prominently in the political arena, so that students, parents, the media, policy-makers, and the general public can develop a better understanding of the financial aspects of colleges and universities and their impact on institutional revenues and expenditures.
Higher Education as a Discretionary Budget Item At the state level, higher education has increasingly been viewed as a discretionary item. In contrast to the reduction of higher education 208
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allocations as a percentage of state expenditures, states significantly increased spending on Medicaid in the early 1990s. In 1990, 1991, and 1992, states increased Medicaid allocations by 20.6 percent, 28.0 percent, and 29.5 percent, respectively (Roherty, 1997). In 2001, state Medicaid expenditures rose almost 11 percent; in 2002, expenditures rose 13.4 percent (NASBO, 2002b). They were projected to grow by another 8.2 percent in 2003 (NCSL, 2002). But Medicaid is just one example of where states have provided greater levels of support than they have for higher education. Public elementary and secondary education, prisons, and mental health services are other areas that are often supported at the expense of higher education. There have even been cases (e.g., Texas in the mid-1990s) where tax cuts were determined to be of greater importance to a state than increasing appropriations to public higher education. Harold Hovey has further argued that higher education is viewed as a “balance wheel in state finance” (Hovey, 1999, p. vii). This means that when state revenues are strong, appropriations for higher education rise disproportionately to the appropriations of other state functions. However, when state budgets are weak, higher education experiences disproportionate cuts. Hovey also posited several reasons why governors, legislators, and key staff members in the executive and legislative branches of state government perceive higher education as being a discretionary budget item. First, colleges and universities have separate, non-state revenue sources that lead to the perception that they have the ability to absorb financial adversity more easily than other state functions. Second, institutions of public higher education are seen as having greater ability to translate appropriation cuts into payroll cuts than other state agencies because they are less often bound by collective bargaining agreements. Third, higher education is seen as having greater ability to generate savings by increasing class sizes, reducing courses, increasing faculty loads, or reducing enrollment as compared with other state programs which may have relatively fixed spending levels as set by state statute, court mandate, or federal requirement. Fourth, public colleges and universities are seen as having the ability to solve many of their financial problems by passing costs onto students and their families through increased tuition and fees (Callan, 2002; Hovey, 1999). So public colleges and universities should not be surprised when their appropriations are reduced by larger proportions than those of other state functions when their state’s economy is stressed. Policy-makers perceive — rightly or wrongly — that these institutions can balance their budgets by using local techniques not available to other state 209
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agencies. However, policy-makers should not be surprised if one result of treating higher education as the “balance wheel” to solve their state’s financial problems leads, over time, to what Callan and Finney have called, “The Cycle of Erosion” (NCPPHE, 2002, p.10). This cycle refers to the erosion of affordability of public higher education caused by the generous appropriations described by Hovey — sometimes accompanied by tuition rollbacks or freezes — during prosperous economic times, followed by the disproportionate appropriation cuts — accompanied by large tuition increases — during difficult economic periods. This cycle of erosion most affects students from lower income families.
Tuition Politics Tuition trends were discussed earlier in the preceding section. As stated, as long as tuition continues to increase at rates significantly greater than the rate of inflation and faster than most other items, American families purchase, as well as personal income, tuition will continue to be a political issue in this country. Add to this the likelihood that public institutions will increase tuition in response to reductions in state appropriations and private institutions will do so in response to decreases in endowment income, among other things, and there is little reason to expect that tuition will be withdrawn from the political agenda (Paulsen, 2000; Paulsen and Smart, 2001). In addition, tuition decisions are not all made at the same level. In private institutions, the governing boards have the final say. As a result, tuition setting is an important part of the budget process, serving as a way to make up the difference between expected revenues and desired expenditure levels. In public institutions, however, the authority to set tuition varies by state. In some, the institutional governing board has the authority as in the case of private institutions. In others, a system governing board has the authority. In a few, the legislature maintains the control. Tuition decisions are almost always political, but this is especially true as the distance between the institution and the entity setting the tuition increases. Discussions of “tuition as fee for service” turn into arguments concerning “tuition as tax,” and the number of groups trying to influence the process increases (Institute For Higher Education Policy, 1999). When the general perception is that tuition and fees are too high, the political discourse can become even more strident. 210
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Accountability Report Cards As mentioned previously, the public’s interest in accountability has increased along with the cost of higher education, especially in the area of affordability. The examples of this interest that have perhaps the largest scope are the report cards published by the NCPPHE in 2000 and 2002. These report cards assessed the performance of all 50 states on preparation — that is, how well students in each state are prepared to take advantage of college; participation — that is, whether state residents have sufficient opportunities to enroll in college-level programs; affordability — that is, how affordable is higher education for students and families in each state; completion — that is, do those who enroll make progress toward and complete their certificates and degrees in a timely manner; benefits — that is, what economic and civic benefits does each state receive from the education of its residents; and learning — that is, what do we know about student learning as a result of education and training beyond high school (NCPPHE, 2000, 2002). The affordability measure has received notable criticism. In 2000, all states generally perform worst in affordability as compared with the other measures — except for learning, where the states received a grade of incomplete (NCPPHE, 2000; Selingo, 2000). In 2002, the affordability grade dropped from 2000 levels in a majority of the states (Margulies, 2002; NCPPHE, 2002). This drop was due in part to the methodology employed, which did not credit financial aid programs based on merit, such as the Georgia HOPE scholarship program (Margulies, 2002). Even so, the report cards are being seen as tools to assess the performance of higher education in individual states, which can then assist policy-makers in determining objectives that will enhance future performance. Potentially, they could affect the appropriations received by public institutions. We shall return to such performance-related issues and reporting later. DEMOGRAPHIC CHARACTERISTICS A number of demographic characteristics impact budgeting. Information published in the report, “Knocking at the College Door: Projections of High School Graduates by State and Race/Ethnicity 1996–2012,” indicates that enrollments in public schools are growing in all regions with the largest percentage of growth in the West (9 percent) followed by the Northeast and South (6 percent), and the North central (3 percent). This same report reveals that the number of high school 211
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graduates is projected to peak in 2007–08 at 3.2 million, which will surpass the largest graduating class of 1979 by 60,000 graduates (Western Interstate Commission for Higher Education and The College Board, 1999). Moreover, a report from NCES estimates that college enrollment will expand from 14.8 million in 1999 to 17.7 million in 2011, a 20 percent increase (Gerald and Husser, 2001). By 2008, the Bureau of Labor Statistics projects a 22 percent increase in jobs requiring some college education. Furthermore, the retirement of baby boomers by 2020 will require an estimated 49 million new workers with some college education (Conklin, 2002). This information suggests that a large number of young college applicants will be enrolling in higher education in the near future, a fact which differentiates the current national recession from previous recessions, where student enrollment was not at an all-time high. Increasing enrollments place a greater demand on educational resources. Other indicators signal a change in the ethnic composition of the U.S. labor force. Fry (2002) states that “between 2000 and 2005, the white working age population will decline by five million” while “Working age Latinos are projected to increase by 18 million” (p. 1). Thus, the nation’s workforce will depend heavily on the education of new workers from more diverse backgrounds. Undeniably, a growing number of students in higher education will be from historically underrepresented groups. For instance, by 2008 Texas will become a minority-majority state: 40 percent Hispanic, 11 percent African American, 45 percent white, and 4 percent Asian Americans and other groups (Texas Higher Education Coordinating Board, 2000). Since Hispanic and African Americans have traditionally enrolled in colleges and universities at a lower rate than that of whites, the Texas Higher Education Coordinating Board is concentrating its efforts to close the gap in participation and graduation rates between ethnic groups. Without these measures, Texas will have a proportionately lower college educated population, and thus, will not be able to meet the needs of the future labor force. Of course, the lower participation rates in higher education on the part of African Americans and Hispanics is not just a problem in Texas. Institutions of higher education across the country will need to continue to work to offer greater access to people from all ethnic groups. INSTITUTIONAL FACTORS A number of institutional factors shape an institution’s budget: mission, student body characteristics, governance structure, overall financial 212
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condition, pattern of instruction, age, size and location, and investment in athletics. An institution’s mission — established by constitution, statute, or governing board mandate — dictates the scope and breadth of programs and curriculum. Different missions influence the resources needed to initiate and maintain institutional goals. Therefore, they require varying levels of faculty training, equipment and facilities as well as different program mixes (i.e., level of instruction, method of instruction, and class size). Student body characteristics are stipulated by an institution’s admission policies, which also reflect its mission. Those institutions with open admissions may enroll less-prepared students, who require remediation. Institutions enrolling older students may require child-care facilities and other measures to meet their needs as working parents. An institution’s governance structure impacts its budget. Many public institutions operate in multi-campus systems that function under a single governing board. The board members are either appointed by the governor or elected by state voters. These board members formulate policy for multiple institutions, which can impact the amount of time needed to prepare and approve an institution’s budget as well as the broad policies affecting budget priorities. On the other hand, private institutions operate under a single self-perpetuating governing board. These board members are commonly nominated and chosen by the current board, and they may be alumni of the institution. In either case, they are typically expected to accept significant fund-raising responsibilities. Budgeting is also influenced by an institution’s overall financial condition. Institutions with limited revenues as well as comparatively few sources of funds may have a difficult time supporting their budgets. As state appropriations have decreased as a percentage of the operating budgets of public institutions, these institutions have raised tuition and fees, engaged in sizeable fund-raising efforts, and in some cases increased indirect cost revenues from sponsored grants and contracts. In the same fashion, private institutions have sought state support for resident students and research initiatives. Among public institutions, research initiatives have increasingly become a more important budgeting concern as state legislatures have pushed them to commercialize research and collaborate with the business community to boost their state’s economy through the creation of new businesses and jobs (Schmidt, 2002b). Patterns of instruction have been increasingly influenced by the introduction of emerging technologies. Unfortunately, the costs of information technology have been difficult to calculate because of its ubiquitous 213
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nature in not only academic support services but administrative and student support as well. Nevertheless, the costs have been high. As states and institutions have invested large amounts in information technology, questions have been raised concerning the benefits of these expenditures. In order to assist institutions in determining costs, the Technology Costing Methodology (TCM) was developed and implemented at pilot institutions; it is not a precise accounting protocol, but rather, a tool for making decisions and assisting institutions in solving the difficulties of estimating technology costs ( Johnstone and Poulin, 2002). New technologies have also allowed institutions of higher education to tap into new student markets through distance education, which in turn provide new revenue streams. Institutions are pursuing other new revenue streams through additional forays into continuing education and packaging courses in innovative ways for certificate programs. These programs may or may not rely on technology. The emphasis here is on the search for new revenue streams that make sense from a cost/benefit standpoint and help keep the institution in a favorable competitive position. An institution’s age as well as its size and location also impact its budget. Older institutions generally have older buildings, which require proportionately larger expenditures for maintenance and upkeep, particularly when adding new technologies. Many research universities and institutions in metropolitan areas necessitate greater security measures by the nature of their sensitive programs and activities or because of their locations. As mentioned previously, capital renewal in general continues to be a budget concern. During difficult financial times, institutions have balanced their budgets by reducing physical plant expenditures, that is, by deferring maintenance. For an institution to function efficiently, its buildings require renewal in order to avoid structural and building system erosion over time. Buildings must also be adapted to changes in mission, program delivery, and safety standards, as examples. The question then revolves around the amount of funds institutions should set aside to preserve the value of their physical plants. Several years ago, the Society for College and University Planning, the Association for Physical Plant Administrators of Colleges and Universities, the National Association for College and University Business Officers, and Coopers and Lybrand studied the problem. They recommended that institutions budget 1.5–2.5 percent of current replacement value annually to keep their physical plants in good condition, another 0.5–1.5 percent to adapt to institutional and environmental changes — a total, therefore, in the range of 2.0–4.0 percent of 214
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replacement value each year (Dunn, 1989, p. 19). This range has served as a useful “ballpark” standard since it was developed, even when refined to include the useful life of building subsystems (e.g., roof, plumbing, electrical, air-handling, etc.). Unfortunately, few institutions have been able to budget this level of funding commitment. In order to avoid the increasing difficulties of maintaining an institution’s physical plant, capital renewal and replacement costs will need to be seriously considered as a part of every institution’s budgeting process in the years ahead. Finally, there is a special characteristic that deserves mention. Those institutions that have a major commitment to intercollegiate athletics (especially, Division I-A by NCAA standards) are experiencing what has been called an “arms race of spending and building to reach impractical financial goals” (Knight Foundation, 2001, p. 16). A panel of university presidents, professors, and business representatives studied the phenomena of growing intercollegiate athletics budgets and summarized their findings in a report sponsored by the Knight Foundation (2001), “A Call to Action: Reconnecting College Sports and Higher Education.” They concluded that certain college sports programs — particularly “big-time” football and basketball programs — are working to accommodate extravagance. In the last seven years, capital expenditures at Division I-A institutions (e.g., construction or remodeling of athletics facilities, capital equipment, etc.) increased 250 percent. From east to west, north to south, the test becomes who can build the biggest stadiums, the most luxurious skyboxes . . . The building boom in college sports facilities now under way across the nation will cost well over $4 billion, with the resulting debt stretching far into the future (Knight Foundation, 2001, p. 17).
Commercialization through television deals, merchandise contracts, and advertising space in stadiums has also become a concern in college sports. For example, between 2002 and 2013, the CBS network is expected to pay the NCAA $6.2 billion for broadcast rights for the Division I men’s basketball tournament (Knight Foundation, 2001). These expenditures call into question the underlining values of “big-time” collegiate athletics and those of the institutions that house them. The report concluded that collegiate athletics more closely mirrors professional athletic programs. If institutions can accommodate this level of spending and meet the other obligations associated with their missions, their budgets may not be unduly affected by this race. However, there are many reports of the difficulties associated with doing so. There is no question that such programs: (1) are popular among many in society, (2) provide entertainment and 215
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relationships to institutions for some people who otherwise would have no other contact with higher education, and (3) have a positive economic impact on the communities in which the athletic contests take place. There is also no question that reducing the emphasis at some institutions would be very difficult to accomplish. However, such programs must be kept financially separate from the real mission of the institution. If institutional leaders make budgetary decisions that negatively impact their instruction and research programs in order to compete athletically, they will have done a disservice to their students, faculty, staff, alumni, and the society they serve.
CHANGES IN BUDGETING APPROACHES In Lasher and Greene’s (1993) original chapter on budgeting in volume IX of this Handbook, various budget approaches or tools were discussed. The strengths and weaknesses of incremental budgeting, formula budgeting, program budgeting, zero-base budgeting, performance budgeting, incentive budgeting, and cost center budgeting were outlined in substantial detail. This section reexamines the nature, strengths, and weaknesses of each of these same approaches to budgeting, but does so in light of the changing environment in which these approaches are now utilized, thereby providing a review of the fundamental characteristics of, as well as an updated and contemporary perspective on, these well-known approaches to budgeting. Then the focus of the discussion shifts to an analysis of recent developments in policies and practices related to performance budgeting and responsibility center budgeting (another name for cost center budgeting), because most of the developments in budgeting approaches in recent years have occurred in those two areas. While it is possible to find conceptual elements and terminology from virtually all of these well-known approaches mentioned in state or institutional budgeting practices, changes in recent years have not been substantive. TRADITIONAL APPROACHES TO BUDGETING Incremental Budgeting Incremental budgeting is the oldest and most common approach used in higher education and, indeed, in every other kind of organization. 216
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Vandement (1989) referred to it as the “budgeting method that uses essentially the same budget from one year to the next, allowing only minor changes in revenue levels and resource distribution” (p. 128). The basic assumption here is that the main objectives of the institution, organizational unit, or program will not change from the current. Therefore, next year’s budget will be higher or lower than this year’s by some percentage or specific dollar amount(s). If new programs or initiatives are started, they are reflected in the budget, but most departments see only minor changes in salary and operating expense levels. Charles Lindblom (1959) characterized this approach as “the science of muddling through.” Incremental budgeting’s strengths are also its weaknesses. It is simpler, easier to understand and apply, and more flexible than other approaches (Meisinger, 1994; Vandement, 1989; Welzenbach, 1982). Other strengths include: ● ●
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It conserves time and energy. It increases the ability to predict the consequences of budget alternatives. It is more pragmatic than other, more theoretical, approaches. Since budget items tend to be treated the same, the amount of conflict generated is generally lower. During times of fiscal stability, it compliments long-term organizational commitments. It is generally better understood and accepted by governing board members and legislators.
Other weaknesses include (Hossler, Kuh, and Bateman, 1989; Vandement, 1989; Welzenbach, 1982): ●
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The current budget becomes thought of as “the base,” the absolute minimum necessary to sustain the institution without greatly reducing its effectiveness. It is a non-aggressive approach. There is little incentive to question the justification of continuing programs, or their quality, or their productivity. It may be affected by institutional politics (“the squeaky wheel gets the grease”) or administrative preference (budgeting by “king’s decree”). It is based more on inputs than on outputs or outcomes. 217
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Formula Budgeting Formula budgeting is a procedure for estimating future budgetary requirements by using relationships between program demands and costs. The basis for formula elements can be historical data, estimated trends, and/or negotiated parameters to generate requested funding levels (Meisinger, 1994). Put another way, formula budgeting is a method that calculates the amount of funding a program requires by applying selected measures of unit costs to selected output measures (Vandement, 1989). Because formulas are highly quantitative, they give the impression of being objective. While this is true to a degree, it must be remembered that formula budgeting is basically “a combination of technical judgments and political agreements” (Meisinger, 1994, p. 183). Over the years, it has been used primarily at the state level as a method for public institutions to prepare their appropriations requests. The advantages and disadvantages of formula budgeting have been debated since its introduction in the 1950s. Specific strengths of formula budgeting include (Brinkman, 1984; Caruthers and Orwig, 1979; Meisinger, 1994; Morgan, 1984; Welzenbach, 1982): ● ● ●
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It provides an equitable distribution of funds among institutions. Budget requests are more uniform and easier to prepare. It provides a framework through which institutions can communicate with the state legislature. The objectivity of formula budgeting depoliticizes the appropriations process by relying on quantitatively-oriented decisions rather than the power and influence of traditional politics. Because of the agreed-upon algorithms for distributing funds, conflict is reduced.
The weaknesses of formula budgeting include (Brinkman, 1984; Caruthers and Orwig, 1979; Hossler, Kuh, and Bateman, 1989; Welzenbach, 1982): ●
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Although formula budgeting appears more objective and less political, it just shifts the level of politics to the more technical level associated with the mathematical relationships in the formulas. Formulas are typically enrollment-driven, which may cause problems when enrollments drop. Formulas do not deal with issues of quality very well. 218
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Since formulas are primarily based on historical relationships, they tend to perpetuate existing programs. New programs and other innovations are discouraged. There are typically built-in incentives which encourage institutions to develop high-cost programs (e.g., engineering programs, or doctoral programs in general) because the formula generates more funds for them. Formula approaches often do not adequately recognize differences in mission across institutions. Because formulas treat institutions the same, they tend to have a leveling effect over time. Formulas tend to focus on those things that can be measured and modeled, rather than on those things that should be considered. Formula approaches can serve as devices for controlling institutional budgets.
Program Budgeting Program Budgeting was one of the first attempts to develop a more output-oriented approach to budgeting. Vandement (1989) defined this approach as a method, “in which budgets are created for specific programs or activities, rather than departments, and each program’s budget is apportioned among the several departments that contribute to the program’s activities” (p. 129). For example, rather than focusing on objects of expense (e.g., faculty salaries, staff salaries, or supplies) in an English department, as is the case in incremental budgeting, program budgeting would focus on the Bachelor of Arts degree program in English. As such, undergraduate students majoring in English would take many of their courses in the English Department, but they would take courses in many others as well — such as, History, Biology, and Mathematics. Presumably administrative departments could be thought of as contributing to the English degree program as well. In any event, program budgeting would allocate funds to all the activities associated with the English degree program across the campus. The basic process involves developing program goals and objectives, considering alternative ways to meet those objectives, costing each alternative, identifying the benefits associated with each alternative, so the best alternative(s) can be selected at the next higher organizational level. Program budgeting evolved in the early 1960s in the form of Planning, Programming, and Budgeting Systems (PPBS) in the U.S. Department of 219
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Defense. It was later tried in other federal agencies; however, the approach was never fully integrated into the federal bureaucracy, and it fell from favor. Several states and institutions of higher education attempted to implement it, but none were particularly successful. Nevertheless, because of its theoretical elegance, program budgeting still has proponents. Its strengths include (Caruthers and Orwig, 1979; Meisinger, 1994; Morgan, 1984): ● ● ● ●
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It focuses on ends rather than means. It relates means to desired ends. It includes qualitative dimensions. It groups activities by function to obtain output-oriented cost information. It allows for estimating future expenditures in cases where multiyear commitments are important. It provides for quantitative evaluations of various alternatives.
On the other hand, the weaknesses of program budgeting include (Hossler, Kuh, and Bateman, 1989; Meisinger, 1994; Morgan, 1984; Vandement, 1989; Welzenbach, 1982): ●
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It requires strong central management to reach agreement on program goals and objectives — something that does not readily fit the decentralized, loosely coupled organizations of most colleges and universities. It is often difficult in higher education to reach agreement on what constitutes a program. It is often difficult to identify and measure specific program outcomes — especially activities and programs that have joint outcomes. While it makes sense conceptually to aggregate activities into programs, most colleges and universities are not organized that way. It focuses more on objectives that must be accomplished and less on policies, programs, and activities that need to be implemented to accomplish those objectives. It falsely assumes that program cost and other management information already exists and is readily available. It is usually easier to hold organizational units accountable for allocated resources than programs which span many departments. It is easier to budget resources to organizational units based on functional needs than across units based on program characteristics. 220
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Zero-base Budgeting Whereas incremental budgeting assumes that this year’s budget provides the base from which next year’s budget is developed, zero-base budgeting assumes there is no prior year base. Therefore, each activity and program must be re-justified each year. Unlike program budgeting which, in its traditional form, tended to have a top-down orientation, zero-based budgeting is a bottom-up approach. Each budget unit evaluates its goals and objectives, justifies the need for various activities, and assesses alternatives (Meisinger, 1994). This process produces decision packages for each activity which contain a description, performance measures, costs, and benefits. Decision packages are ranked at each level of the organizational hierarchy. Zero-base budgeting was developed and used by Texas Instruments in the late 1960s. It was used in the state of Georgia when former U.S. President Jimmy Carter was Governor in the early 1970s. Like many management fads, it was considered in higher education, but never widely implemented. The strengths of zero-base budgeting include: ● ● ●
its focus on outcomes and results; it is a highly rational, objective approach; Preparing decision packages provides an excellent understanding of units, programs, and activities.
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assuming no budget history runs counter to continuing commitments, such as faculty tenure, that characterize higher education; preparing decision packages for every activity is highly timeconsuming and generates a great deal of paperwork; the validity and reliability of the criteria used to rank decision packages may be suspect.
Performance Budgeting Performance budgeting is based on funding desired outcomes or accomplishments. It developed during the late 1940s and represented the first attempt to focus on programs and activities as ends, rather than broader organizational objectives. It relies on activity classifications, performance measures, and performance evaluations. Performance budgeting 221
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is clearly an approach where institutional funding depends on the institution performing in certain ways and meeting certain expectations. The approach was little used until the 1980s, when it experienced renewed attention at the state level as an approach for relating resources to activities and outcomes (Meisinger, 1994) as the accountability movement became more prominent. The strengths of performance budgeting include (Meisinger, 1994; Morgan, 1984): ●
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It focuses on accomplishments and results rather than on inputs and processes. Once defined, the approach is relatively simple. It promotes an equitable allocation of resources to those colleges and universities that meet performance objectives.
Its weaknesses include (Hossler, Kuh, and Bateman, 1989; Meisinger, 1994): ●
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It is often difficult to define performance criteria and appropriate measures. There is a tendency to measure only that which is most easily measured. The time gap between achieving a goal, measuring that accomplishment, and receipt of the associated funding is often too long for normal institutional planning cycles. Diversity among institutional missions is often not taken into account in setting performance criteria. The development of performance measures often flows downward from the state level to the institutional level. It is sometimes less politically attractive for legislators because it tends to limit “pork barrel appeal.”
Since performance budgeting has undergone a great deal of change in recent years, we shall have more to say about this approach later. Incentive Budgeting This approach continued higher education’s pursuit of output-oriented budgeting, similar to performance budgeting. During the 1980s some states set aside pools of funds earmarked for allocation when state institutions of higher education achieved certain specified goals. Other states established initiative programs that provided funds to support institutional proposals for programs to achieve certain state goals. Although terminology varied 222
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across states, the major types of incentive funding included those programs that rewarded results after performance had occurred, and those programs that provided prospective funding for new programs and activities for promised results (Berdahl and Holland, 1989). In one case, programs that funded results were referred to as “incentive funding” and those that funded prospective results were referred to as “initiative funding” (Texas Higher Education Coordinating Board, 1990). In either case, incentive programs motivated institutions to move toward state goals through the prospect of additional funding, rather than coercing them through threatened budget cuts or increased regulation. The strengths of incentive budgeting include (Berdahl and Holland, 1989; Folger, 1984; Holland and Berdahl, 1990): ●
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It is a method whereby states encourage public colleges and universities to meet important state goals. It focuses on results and outputs. Qualitative issues can be addressed rather than just quantitative issues. Incentive programs are most effective when faculty members are involved, since they are closest to where results do or do not occur. Incentive programs that use matching funds to leverage private giving are especially effective.
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In higher education, measurement of outputs and outcomes is difficult. As in performance budgeting, there is a tendency to measure what is measurable. Incentive programs tend not to be useful for accountability purposes. Incentives are less effective when supported by funds taken from the base appropriations for higher education and more effective when supported by funding that is additional to that base.
Cost Center Budgeting/Responsibility Center Budgeting Cost Center budgeting originated with Harvard’s President James Conant who stated that “Every tub stands on its own bottom, each dean 223
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balances his own budget” (Caruthers and Orwig, 1979). In this approach each unit is treated as being self-supporting. That is, sufficient revenues must be raised by each unit to support projected expenditures. In an academic college, this means that faculty and staff salaries, operating expenses, as well as a share of physical plant costs, utilities, library costs, computing, and general administration must be covered by the college’s income from tuition, fees, indirect costs from research, endowments, gifts, and research grants. The approach generally allows support units to charge for their services, and some academic units are allowed to tax others for the service instruction they provide. The use of cost center budgeting was generally confined to private institutions until 1989, when Thomas Ehrlich moved from the position of provost at the University of Pennsylvania to the presidency of Indiana University. Ehrlich brought responsibility center budgeting (RCB), as cost center budgeting has become known, to the public university sector. Since then, it has been used in various forms in several institutions. In RCB, income from tuition and fees is attributed to the academic unit that generates it, while support units receive income through charges to the academic units (Whalen, 1991). Generally at public universities, state appropriations are controlled by central administration. They are allocated to units to offset remaining expenditures and to support certain programs. The strengths of cost center/responsibility center budgeting include (Leslie, 1984; Meisinger, 1994; Morgan, 1984; Strauss, Curry, and Whalen, 2001; Whalen, 1991): ● ●
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It is a rational approach to budgeting. Operating units have greater responsibility for budget development and budget control. Decisions concerning academic priorities are made closer to the instructional level. Tuition resources are moved in relation to the institution’s enrollment patterns. There is an incentive to enhance revenues and manage costs more effectively. The development of specific charges for space-related costs results in a better understanding of the value of space. It encourages entrepreneurship.
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It makes clear that academic decisions have financial consequences.
The weaknesses of cost center/responsibility center budgeting include (Hossler, Kuh, and Bateman, 1989; Leslie, 1984; Meisinger, 1994; Strauss, Curry, and Whalen, 2001; Whalen, 1991): ●
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Academic programs may become budget-driven at the risk of sacrificing academic performance and priorities. Local services (including certain types of instruction) that duplicate those offered elsewhere may be expanded to generate revenue. Effective central controls may be difficult to establish. Developing equitable cost algorithms for taxing units can be problematic. Institutional politics may influence decisions regarding which unit receives credit for certain curricular offerings or services, or the mechanisms for allocating indirect costs. Professional units may thrive while core academic units are pressured to generate sufficient revenue.
THE CURRENT SITUATION Incremental Budgeting It remains true that the place most institutions start when they begin to develop next year’s budget is the current year budget. The current year’s financial plan is assumed to be the base level for consideration of the nearterm future. For all of its disadvantages, incremental budgeting remains the most widely used budget approach. Lasher and Greene paraphrased Winston Churchill (1993), “Incremental budgeting is the worst budgeting approach, except for all the others.” Especially at the institutional level, that statement remains true today. The underlying assumption is that the institution’s fundamental goals and objectives will not change markedly from this year to next. New programs may be started to be sure, but most of the time, institutional departments see budget changes that amount to minor dollar or percentage changes from current (base) levels. In the current economic environment, many institutions have learned that incremental budgeting can also mean “decremental” budgeting as revenue losses from state appropriations or endowment income streams have led to cuts in budgeted expenditures.
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Formula Budgeting Formulas continue to play a role in budgeting at the state level and at many institutions. Although the number of states using funding formulas changes from year to year, it is fairly safe to say that at any one time, 50–60 percent of the states are using them in some fashion to help determine appropriations for public higher education institutions (McKeown, 1996). Formulas continue to be popular because it can be argued that they provide for an equitable distribution of funding among institutions. States use them in different ways. In some cases, the higher education governing or coordinating board uses formulas to recommend to the governor and legislature the resources needed for each campus. In others, legislative or executive fiscal staffs use formulas to make their recommendations for institutional support (McKeown and Layzell, 1994). In some states, formulas are used to determine institutional allocations once the total appropriation to public higher education is determined (McKeown, 1996). Although originally touted as reducing the politics of the higher education appropriations process, those that have worked to modify formula systems know that the level of politics is simply shifted from the traditional arena to the level of technical judgments concerning the nature of the mathematical relationships included in the formulas. Typically, the reaction of institutional representatives to a proposed formula change is based more on the increase or decrease in funding that would result for their particular institution rather than any overall benefit that might accrue to the state’s higher education system as a whole. In several states there has also developed a relationship between formula budgeting and performance budgeting. Performance measures may be included as incentives in the basic components of the formula or performance funding may be a separate category of the formula system. In any case, institutions would rather that the state funding formula system be considered a revenue generation mechanism, and not a set of regulations for micro-managing internal budget allocations. Although, institutions often use formulas to allocate certain smaller pots of money while the budget is being administered during a fiscal year, they mostly prefer that internal budget decisions be based on institutional and program need and administrative discretion rather than state formula relationships. This is also true at institutions that use RCB. In these instances, the algorithms that are developed for various intra-campus transfers and “taxes” necessary to carry out such systems are basically formulas. However, they reflect the 226
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governance and financial characteristics of the particular campus. We will have more to say later about both performance budgeting and RCB. Program Budgeting, Zero-base Budgeting, and Incentive Budgeting Elements of program budgeting, zero-base budgeting, and incentive budgeting can certainly be found, but as full-blown budgeting approaches, they are not currently being emphasized. Aspects of program budgeting are often used when new programs are proposed. Such budgets are based on implementing the goals and objectives of the specific program. However, overall institutional budget processes still focus on funding organizational units rather than on funding broad campus programs. Likewise, zero-base budgeting is often used in developing new programs and other start-up activities that truly are starting from a zero-base; the technique can be used as a management tool to review the complete justification for a unit beset by problems. However, institutions typically do not find re-justifying every unit or program or prioritizing resulting decision packages something they can undertake during each budget cycle. Finally, incentive budgeting has basically evolved into a form of performance budgeting. During the 1980s especially, some states used incentive budgeting to encourage institutions to achieve state goals for educational quality. However, as the accountability movement gathered momentum and the questions of state policymakers shifted from what the state should do for their public colleges and universities to what those institutions have done for the state, incentive budgeting techniques were largely replaced by performance approaches, although its terminology still shows up in other approaches. RECENT DEVELOPMENTS Performance Budgeting Performance budgeting approaches have been called one of the most important developments in the way states view the financing of their public institutions of higher learning in recent years. The utilization of these approaches continues to be monitored closely by Joseph Burke and his colleagues in the Higher Education Program at the Nelson A. Rockefeller Institute of Government. In a recent report, they state that such performance-based programs “ . . . have become increasingly popular in 227
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state capitals, although not on public campuses. The trend toward linking — in some way — state budgeting to performance of public campuses is unmistakable” (Burke and Minassians, 2001, p. 2). They found that 36 of the 50 states (72 percent) relied on one of the two performance budgeting techniques they identified. This was an increase from less than half of the states 5 years earlier. The two techniques include performance funding and performance budgeting. Although the distinction may be more in the eye of the researcher than the policy-maker or administrator, it is important nevertheless. Performance funding ties specified state funding directly and tightly to the performance of public campuses on individual indicators . . . In performance funding, the relationship between funding and performance is tight, automatic, and formulaic. If a campus achieves a prescribed target or an improvement level on defined indicators, it receives a designated amount or percent of state funding (Burke and Minassians, 2001, p. 4).
The primary distinction between performance budgeting and performance funding is that performance budgeting is more flexible. [It] allows governors, legislators, and coordinating or systems boards to consider campus achievement on performance indicators as one factor in determining campus allocations . . . In performance budgeting, the possibility of additional funding due to good or improved performance depends solely on the discretion of state, coordinating or system officials (Burke and Minassians, 2001, p. 4).
Obviously, performance budgeting has some political advantages for legislators. They can tout the importance of improving institutional performance in general, but protect the appropriations of the institution(s) in their home districts. On the other hand, Burke and Minassians suggest a possible relationship between the preference for either of these two techniques and a state’s economy. Because of some changes in behavior in state capitals, there is some evidence that performance funding may be the preferred approach during times of tight state revenues, while the more flexible performance budgeting may be preferred during better times. “At such times, governors and legislators push programs that press colleges and universities for better performance as cover for diminished state support. These initiatives leave the impression with taxpayers that public higher education does not deserve budget increases until it improves performance” (Burke and Minassians, 2001, p. 3). This suggestion resonates well with the notion of higher education as a discretionary state expense as discussed earlier. 228
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However, only a small percentage (5 percent or less) of higher education state appropriations are provided through performance budgeting approaches. Even the South Carolina experiment to rely more heavily on performance techniques has been revised. In 1996, the South Carolina General Assembly passed legislation with the intent that 100 percent of the state support for the state’s public colleges and universities would be based on their performance on 37 quality indicators. However, institutions need to be able to plan for basic operations from year to year. Because there is often a lag in the allocation of performance funding as results from measurements of the performance indicators are reported and the resulting allocations developed, institutional budgeters find it difficult to deal with performance funding as a primary appropriations technique. The actual experience in South Carolina has been changed from what was originally intended. The number of performance indicators actually used for funding purposes was reduced to 14, and only about 3 percent of the state’s appropriations to higher education institutions were allocated based on performance (Schmidt, 2002a). South Carolina’s reduction in emphasis is in line with another Burke and Minassians finding. “Recent projects have retreated from the radical goal of reforming public higher education for the less ambitious objective of improving institutional performance in specific areas, such as increasing access and raising graduation and retention rates” (Burke and Minassians, 2001, p. 10). Another development that may affect the use of performance budgeting approaches is the use of what Burke and Minassians refer to as performance reporting. As of 2001, 39 states had produced such reports, which describe the performance of public colleges and universities on selected indicators in much the same way as in performance funding or performance budgeting approaches (Burke and Minassians, 2001). The difference is that the results are not used in a budget or appropriations process. Rather, the results are simply reported through the news media. Interest in this technique may have been spurred by the state-by-state report cards produced by the National Center for Public Policy and Higher Education. Regardless, the results of performance have been profound at the campus leadership level. The threat of bad publicity or public embarrassment may actually be a greater motivator for campus presidents and chancellors than a lower appropriation or a reduced performance funding allocation. Suffice it to say, performance funding/budgeting/reporting is a very active area in higher education finance and budgeting — one that needs to be watched by those interested in how institutions of higher education, 229
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especially those in the public sector, are funded. A product of the accountability movement, this approach is the primary way that results-oriented budgeting is manifested in today’s environment. However, the evidence to date suggests that performance approaches have had little impact below the campus level to academic departments. There, more traditional budget approaches continue to be the norm.
Responsibility Center Budgeting In recent years, various forms of responsibility center budgeting have been adopted at several major public universities in the U.S. and Canada in addition to Indiana University (e.g., the University of Michigan, UCLA, Ohio State University, the University of Illinois, and the University of Toronto). It has been referred to variously as cost center budgeting, responsibility center budgeting, responsibility center management, value center management, incentive-based budgeting, mission-focused budgeting and planning, and revenue center management. Responsibility center budgeting, or RCB, has become, more or less, the generic term. In more recent years, there has been an increase in activity-based costing and activitybased budgeting. The principles of this approach are very similar to those of RCB. The approach’s basic notion continues to be conveyed by the rather inelegant phrase, “each tub on its own bottom.” Basically, each primary academic unit within the institution is considered a cost center, and is expected to be self-supporting. Daniel Lang (1999) of the University of Toronto has summarized the basic operating principles of RCB as follows (p. 2): ●
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All costs and income generated by each college, faculty, or department are attributed to that unit, appear in its budget, and are under its control. Incentives are created and barriers are removed to allow each academic unit to increase income and reduce costs according to its own academic plans and priorities. All costs of administrative and service units are allocated to academic units. Decisions about optimal balances between costs and revenue are made by the academic units. They set priorities and link plans to budgets. Restrictions on line-by-line budgets are relaxed or eliminated. Each academic unit allocates the global revenue base available to it. 230
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The strengths and weaknesses listed previously have been found to be largely replicated in these public institutions. Entrepreneurial behavior is encouraged for increased revenue generation, and decisions concerning resource allocation are located at a lower level where there is more knowledge and expertise to make them. However, a few additional disadvantages have been discovered: more sophisticated financial information systems are required than may be available; higher unit level management skills are required than may exist; and any disconnects between governmental funding formulas and institutional cost structures will be highlighted. It is safe to say that each institution that has adopted this approach has modified it to reflect its own institutional character and situation. For example, the University of Michigan has modified its version of RCB to the point where they simply refer to it as the University Budget (UB) model (Courant and Knepp, 2002). After implementing their version of RCB for the 1997 fiscal year (then called value centered management), there were concerns raised by some faculty members that focusing on schools, colleges, and separately budgeted research units as responsibility centers would damage interdisciplinary research and teaching, other collaborative activities, and academic activities that are vital, but not particularly popular. There were also concerns that the university library was considered by the model to be a service unit. By fiscal 1999, the budget approach had been modified further to the UB model mentioned previously. This system was still activity based. That is, units that engaged in revenue-generating activity were still allocated the bulk of those revenues. They were also allocated their share of costs. But the system has been modified, as compared with similar approaches at other institutions, such that considerably more authority is retained by central administration (specifically the Provost) and more support is provided for campus-wide functions whose activities do not lend themselves to revenue generation. Those units that are considered activity based “receive a significant portion of their revenue as a function of what they do — whether it be enrolling students, obtaining NIH grants, or selling football tickets” (Courant and Knepp, 2002, p. 16). Those units that are not considered activity based (e.g., libraries, museums, campus police department, admissions, office of general counsel) have their budgets determined centrally. Units are also treated differently based on whether they contribute directly to the University’s core missions. Academic units (e.g., schools and colleges, research units, libraries, and museums) are treated differently than other non-academic support units. Non-academic units that are activity based (e.g., auxiliary enterprise units) are assessed for charges for the business and administrative services they use. 231
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Non-academic units that are not activity based (e.g., campus police department, admissions, office of general counsel, president’s office) have their budgets determined centrally, but there are incentives in the system to keep them as small as possible. The primary focus of the UB model is on academic and service units supported from Educational and General funds sources. In their budgets, activity-based units are attributed revenues (i.e., tuition, indirect cost recovery, interest) and costs (financial aid, space). These units are also assessed for a variety of expenditure taxes through various formulas which provide funds to be used by the Provost to provide support for those units whose budgets are centrally determined and for reallocation. The Michigan University Budget approach is designed so that no Educational and General fund unit really functions as “a tub on its own bottom.” Some supplementation is needed. “It is this element that gives the Provost leverage in determining the budget and, therefore, the set of activities undertaken by units” (Courant and Knepp, 2002, p. 27). This Michigan example is a good one in that it shows how one institution has modified a more generalized budgeting approach to fit its needs at a particular time. The UB model is dynamic and flexible in order to meet the institution’s needs. Entrepreneurial behavior is encouraged, but not in units where that would be inappropriate. Greater central control is maintained in order that the importance of University goals and objectives continues to be more visible than the activities of any particular segment of campus. However, certain more general characteristics associated with RCB are also apparent. First, sophisticated financial systems are required to provide the necessary information about institutional costs and to provide the basis for the various formulas and attribution algorithms that are required under such an approach. Second, the approach demands greater financial management skills at lower administrative levels than have historically been present at many institutions. Many larger, financially complex institutions have or are developing this level of skill in their managers. Others still have a way to go. RCB is not for every institution. Nevertheless, the fact that it is now being used, in various forms, in public institutions is an important development.
IMPLICATIONS FOR THE FUTURE The budgeting approaches that colleges and universities, and their states, utilize reflect the larger financial environment, perhaps the 232
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management fad of the day, and the intellectual abilities and propensities of budgeters to make sense out of the constant change that confronts them and their institutions. In a time of limited financial resources, institutions can basically increase revenues, decrease expenditures, or pursue a combination of the two in order to avoid budget deficits. In developing more specific strategies, there are several questions that might help assess a financial “crisis.” First, will there really be cuts? Is the situation bad enough that actual reductions in base budgets will be required, or are we talking about “cuts” as decreases in requested revenue increases with no threat to base budgets? (Politicians often refer to cuts in this latter sense.) Second, how big is the crisis, or how large will the cuts likely be? Some feel that 1–4 percent cuts are tolerable, while 5 percent cuts mark a much more substantial threat (Lovett, 2002). The reality is that depending on the institutional factors discussed earlier, the threat of 2 percent cuts in base funding levels might appear catastrophic to one institution, while being considered a minor setback by another. Third, how long will the crisis last? If the answer is just this year, the institutional strategy will be much different than if the crisis is expected to last for the “foreseeable future.” The answers to these questions will determine whether the strategies developed are resistive — that is, current programs and activities are maintained, although perhaps at a reduced level — or adaptive — that is, the institution will need to consider altering its mission or role and scope in some substantial way. Strategies that are typically employed when the outlook is short term or the financial impact is expected to be relatively small include: cutting slack resources (e.g., contingency funds), cutting vacant positions, implementing a hiring freeze, declaring salaries frozen, relying on attrition, reducing building maintenance, cutting travel, and cutting equipment. Protecting core academic programs is typically the primary overall strategy. If the situation is seen as being more severe, that is larger and longer term, the strategies move to: cutting course offerings (although this really doesn’t generate savings unless instructional salaries are reduced), faculty and staff layoffs or furloughs (staff first, then part-time faculty; tenured faculty are almost always last), reviews to cut programs (academic and other) that are no longer considered central to the institution’s missions. In the “short term/small” environment, the decisions are often made by the campus administration. In the “long term/large” environment, however, the level of participation is typically much broader, perhaps with representation from, and participation by, all of the major campus stakeholders. In this situation, 233
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process is as important as product. If the campus leadership ensures that an appropriate level of participation is evident, implementing the ultimate plan and making the necessary budget adjustments will be easier and more generally accepted. It seems that in the current environment, institutions and states, have been forced to more severe measures faster than in the 1970s, 1980s, and 1990s. There have been reports of emergency appropriations recisions, canceled classes, reduced course offerings, community colleges turning away students, other institutions imposing enrollment caps, technology allotments being chopped, threatened funding reductions in state and institutional financial aid programs, large tuition and fee increases, limitations set on service-learning, community outreach, and dual-enrollment admissions programs, cuts in student support programs, salary freezes, salary bonuses rather than salary increases, early retirement programs for senior faculty members, hiring more adjunct or part-time faculty, increased faculty workloads, greater reliance on teaching assistants, and increased class sizes, to name several strategies that have been prominently mentioned. As indicated previously, a few of these are relatively typical first-order responses. However, the cancellation of classes, the reduction of course offerings, the turning away of students are severe measures usually reserved for major financial downturns. As mentioned previously, institutions typically use incremental budgeting as they try to craft their financial plans to meet the challenges of a tumultuous economic environment. The primary objective of campus leadership is to maintain current missions and, if possible, improve institutional quality during difficult periods. (In fact, there is ample evidence that those involved with institutional budget processes are more innovative during such periods than when times are better.) Of course, difficult periods bring home only too graphically the notion that incremental budgeting can also mean decremental budgeting at certain times. Generally, however, the environment’s current message to higher education is “do more with less.” With state support shrinking further because of the current recession in many states, decreasing returns from weaker performing endowments, affordability issues, and enrollment surges, that is certainly the message at present (Breneman, 2002). States further emphasize this message through the performance budgeting and reporting approaches that most of them employ. Some institutions have tried to improve their budgeting systems by adopting at least some of the techniques of responsibility center budgeting. Others are considering similar approaches such as 234
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activity-based costing and activity-based budgeting. In the last analysis, however, the response to this pervasive message will rest on strong institutional leadership as well as plans and initiatives based on good information and rational decision processes. Reflecting the economic, political, and demographic aspects of their environments, institutions of higher education face challenging financial futures. New budgeting approaches will in all likelihood be developed to help meet them. Whether they will be fundamentally different from incremental budgeting remains to be seen. One thing is certain, however, it will be an interesting ride.
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REFERENCES Advisory Committee on Student Financial Assistance. (2001, February). Access denied: Restoring the nation’s commitment to equal educational opportunity, http://www.ed. gov/offices/AC/ACSFA/ access_denied.pdf Advisory Committee on Student Financial Assistance. (2002, June). Empty promises: The myth of college access in America. Washington, D.C., http://www.ed.gov/offices/AC/ ACSFA/empty_promises.pdf Berdahl, R., and Holland, B. (eds.) (1989). Developing State Fiscal Incentives to Improve Higher Education. Proceedings from a National Invitational Conference. National Center for Postsecondary Governance and Finance, University of Maryland, College Park, MD. Bowen, H. (1980). The Costs of Higher Education. San Francisco: Jossey-Bass. Burke, J.C., and Minassians, H. (2001). Linking State Resources to Campus Results: From Fad to Trend — The Fifth Annual Survey. Albany, NY: Rockefeller Institute of Government. Breneman, D.W. (1994). Liberal Arts Colleges: Thriving, Surviving, or Endangered? Washington, D.C.: The Brookings Institution. Breneman, D.W. (2002). For colleges, this is not just another recession. Chronicle of Higher Education June 14: B7. Breneman, D.W., Doti, J.L., and Lapovsky. (2001). Financing private colleges and universities: The role of tuition discounting. In M.B. Paulsen, and J.C. Smart (eds.), The Finance of Higher Education: Theory, Research, Policy and Practice. New York: Agathon Press. Brinkman, P. (1984). Formula Budgeting: the fourth decade. In L. Leslie (ed.), Responding to New Realities in Funding. New Directions in Institutional Research, No. 43, San Francisco: Jossey-Bass. Burd, S. (1997a). Federal commission on the cost of college says it isn’t so expensive after all. Chronicle of Higher Education November 28: A33. Burd, S. (1997b). The finger-pointing begins over the work of a federal panel on college costs. Chronicle of Higher Education December 17: A28. Callan, P.M. (2002). Coping with recession: Public policy, economic downturns and higher education. A National Center for Public Policy and Higher Education Report #02–2, http://www.highereducation.org/reports/cwrecession/MIS11738.pdf Caruthers, J.K., and Orwig, M. (1979). Budgeting in higher education. AAHE/ERIC Higher Education Research Report No. 3 ED167857. Washington, D.C.: American Association for Higher Education. Conklin, K.D. (2002, March/April). After the tipping point: A new first principle for state postsecondary education finance. Change 34(2): 24–29. Courant, P.N., and Knepp, M. (2002). Activity-based budgeting at the University of Michigan: A case study. In D.M. Priest, W. Becker, D. Hossler, and St. E. John (eds.), Incentivebased Budgeting Systems in Public Universities. Camberley Surrey, U.K.: Edward Elgar Publishing Ltd. Cunningham, A.F., Wellman, J.V., Clinedinst, M.E., Merisotis, J.P., and Carroll, C.D. (2001, December). Study of college costs and prices, 1988–89 to 1997–98. National Center for Education Statistics, http://nces.ed.gov/pubsearch/pubsinfor.asp?pubid⫽2002157 Dunn, J. (1989). Financial Planning Guidelines for Facility Renewal and Adaption. (A joint project of The Society for College and University Planning, The National Association for College
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Lasher and Sullivan: The Changing World of Budgeting in Higher Education and University Business Officers, The Association of Physical Plant Administrators of Colleges and Universities, and Coopers and Lybrand.) Ann Harbor, MI: Society for College and University Planning. Evelyn, J. (2002). Budget cuts force community colleges to consider turning away students. Chronicle of Higher Education July 26: A25. Folger, J. (ed.) (1984). Financial Incentives for Academic Quality. New Directions for Higher Education, No. 48. San Francisco: Jossey-Bass. Fry, R. (2002). Latinos in higher education: Many enroll, too few graduate. Pew Hispanic Center, http://www.pewhispanic.org/site/docs/pdf/latinosinhighereducation–sept5–02.pdf Gerald, D.E., and Husser, W.J. (2001, August). Projections of Education Statistics to 2011. Washington, D.C.: U.S. Department of Education, National Center for Education Statistics, http://nces.ed.gov/pubs2001/proj01/ Holland, B., and Berdahl, R. (1990). Green carrots: A survey of state use of fiscal incentives for academic quality. A paper presented at the annual meeting of the Association for the Study of Higher Education, November 1–4, Portland, OR. Hovey, H.A. (1999). State spending for higher education in the next decade: The battle to sustain current support. A National Center for Public Policy and Higher Education Report #99–3, http://www.highereducation.org/reports/hovey/hovey.pdf Hubbell, L.L., and Lapovsky, L. (2002, February). Tuition discounting in challenging times. Business Officer 35(8): 24–33. Hossler, D., Kuh, G., and Bateman, J.M. (1989). An investigation of the anticipated effects of responsibility center budgeting at a public research university: The first year. Paper presented at the Annual Meeting of the American Educational Research Association, March 27–31, San Francisco. Institute for Higher Education Policy (1999, February). The Tuition Puzzle: Putting the Pieces Together. Washington, D.C. Johnstone, S.M., and Poulin, R. (2002, March/April). So, how much do educational technologies really cost? Change 34(2): 21–23. June, A.W. (2002). Public colleges see red but don’t panic. Chronicle of Higher Education September 6: A39. Klinger, D. (2002, April). Good company. Business Officer 35(10): 38–40, 43–48. Knight Foundation. (2001, June). A call to action: Reconnecting college sports and higher education, http://www.knightfdn.org/default.asp?story⫽news_at_knight/special_reports/ coi_athletics.html Lang, D.W. (1999). A Primer on Responsibility Centre Budgeting and Responsibility Centre Management. Professional File €17, Canadian Society for the Study of Higher Education. Winter 1999. Toronto, ON. Lasher, W.F., and Greene, D.L. (1993). College and university budgeting: What do we know? What do we need to know? In J. Smart (ed.), Higher Education Handbook of Theory and Research (Vol. 9). New York: Agathon Press. Lasher, W.F., and Greene, D.L. (2001). College and university budgeting: What do we know? What do we need to know? In J.L. Yeager, G.M. Nelson, E.A. Potter, J.C. Weidman, and T.Z. Zullo (eds.), ASHE Reader on Finance in Higher Education (2nd edn.). Needham Heights, MA: Pearson Custom Publishing. Leslie, L. (ed.) (1984). Responding to New Realities in Funding. New Directions in Institutional Research, No. 43. San Francisco: Jossey-Bass.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Lindblom, C. (1959). The science of “muddling through.” Public Administration Review 19: 79–88. Lovett, C.M. (2002). Tough times for colleges demand structural changes. Chronicle of Higher Education October 14: B12. Margulies, J. (2002). Grading the states: Group’s second “report card” finds some improvement since 2000, but still awards many C’s. Chronicle of Higher Education October 11: A24. McKeown, M.P. (1996). State Funding Formulas for Public Four-Year Institutions. Denver: State Higher Education Executive Officers. McKeown, M.P., and Layzell, D.T. (1994). State funding formulas for higher education: Trends and issues. Journal of Education Finance 19: 319–346. Meisinger, Jr., R.J. (1994). College and University Budgeting: An Introduction for Faculty and Academic Administrators (2nd edn.). Washington, D.C.: National Association of College and University Business Officers. Merriam Webster’s Collegiate Dictionary. (1993). Tenth Edition, Springfield, MA: MerriamWebster Inc. Morgan, A. (1984). The new strategies: Roots, context, and overview. In L. Leslie (ed.), Responding to New Realities in Funding. New Directions in Institutional Research, No. 43. San Francisco: Jossey-Bass. National Association of College and University Business Officers. (2002). Explaining college costs: NACUBO’s methodology for identifying the costs of delivering undergraduate education, http://www.nacubo.org/public_policy/cost_of_college/ National Association of State Budget Officers. (2002a, March 12). Fact sheet: Quick rebound? State fiscal recovery could be gradual, lag national economy 12–18 months. http://www.nasbo.org/Publications/PDFs/reboundlag.pdf National Association of State Budget Officers. (2002b, May). The fiscal survey of the states. http://www.nasbo.org/Publications/fiscsurv/may2002fiscalsurvey.pdf National Center for Public Policy and Higher Education. (2000). Measuring Up 2000: The State-by-State report card. Washington, D.C. National Center for Public Policy and Higher Education. (2002a). Measuring Up 2002: The State-by-State report card. Washington, D.C. National Center for Public Policy and Higher Education. (2002b). Losing ground: A national status report on the affordability of American higher education. http://www.highereducation. org/reports/losing_ground/affordability_report_final.pdf National Commission on the Cost of Higher Education. (1998). Straight Talk About College Costs and Prices. American Council on Education, Phoenix, AZ: The Oryx Press. National Conference of State Legislatures. (2002, July 24). State budget and tax actions 2002: Preliminary report. http://www.ncsl.org/programs/fiscal/presbta02.htm Paulsen, M.B. (1991). College tuition: Demand and supply determinants from 1960 to 1986. The Review of Higher Education 14(3): 339–358. Paulsen, M. (2000). Economic perspectives on rising college tuition: A theoretical and empirical exploration. In J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XV. New York: Agathon Press. Paulsen, M.B., and Smart, J.C. (2001). The Finance of Higher Education: Theory, Research, Policy and Practice. New York: Agathon Press.
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Lasher and Sullivan: The Changing World of Budgeting in Higher Education Research Associates of Washington (1998). Inflation Measures for Schools, Colleges, and Libraries: 1998 Update. Arlington, VA: Research Associates of Washington. Reese, S.J. (2002, October 23). Updates on billion-dollar campaigns at 20 universities. Chronicle of Higher Education (Today’s News) October 23, http://chronicle.com/daily/ 2002/10/2002102309n.htm Roherty, B.M. (1997). The price of passive resistance in financing higher education. In P.M. Callan, and J.E. Finney (eds.), Public and Private Financing of Higher Education. American Council on Education, Phoenix, AZ: The Oryx Press. Rosenbaum, D.E. (2002). States’ vast budget gaps bring higher fees and emergency cuts. New York Times May 15: A1. Schmidt, P. (2002a). Most states tie aid to performance, despite little proof that it works. Chronicle of Higher Education February 22: A20. Schmidt, P. (2002b). States push public universities to commercialize research. Chronicle of Higher Education March 29: A26. Schmidtlein, F. (1989). Why linking budgets to plans has proven difficult in higher education. Planning for Higher Education 18(2): 9–23. Selingo, J. (2000). Grading the states on higher education: College officials squirm as the first- ever “report card” awards lots of C’s. Chronicle of Higher Education December 8: A24. Shoichet, C.E. (2002). With dollars tight, states struggle to find money for merit scholarships. Chronicle of Higher Education August 2: A23. Strauss, J., Curry, J., and Whalen, E. (2001). Revenue Responsibility Budgeting. In J.L Yeager, G.M. Nelson, E.A. Potter, J.C. Weidman, and T.Z. Zullo (eds.), ASHE Reader on Finance in Higher Education (2nd edn.). Needham Heights, MA: Pearson Custom Publishing. Texas Higher Education Coordinating Board. (1990). Report of the Initiative and Incentive Subcommittee, March, Austin, TX. Texas Higher Education Coordinating Board. (2000). Closing the gaps: The Texas higher education plan, http://www.thecb.state.tx.us/AdvisoryCommittees/HEP/HEplan Final.PDF U.S. Department of Education, National Commission on Excellence in Education. (1983). A Nation at Risk: The Imperative for Educational Reform, http://www.ed.gov/pubs/ NatAtRisk/ risk.html Van Der Werf, M. (2002). Recession and reality set in at private colleges. Chronicle of Higher Education March 1: A26. Van Der Werf, M., Blumenstyk, G., and June, A.W. (2002). Fallout from Wall Street hits colleges hard. Chronicle of Higher Education August 9: A27. Vandement, W. (1989). Managing Money in Higher Education: A Guide to the Financial Process and Effective Participation Within It. San Francisco: Jossey-Bass. Wainwright, A. (1992). Overview of financial accounting and reporting. In D. McDonaldGreene (ed.), College and University Business Administration (5th edn.). Washington, D.C.: National Association of College and University Business Officers. Western Interstate Commission for Higher Education and The College Board. (1999). Knocking at the college door: Projections of high school graduates by state and race/ethnicity 1996–2012. Publication €2A302 (Boulder: WICHE).
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7. TUITION FEES IN EUROPE AND AUSTRALASIA: THEORY, TRENDS AND POLICIES Ben Jongbloed University of Twente
INTRODUCTION Americans coming over to Europe often are stunned to learn that European students enrolling in higher education1 either pay only a modest tuition fee or no fee at all. Comparing this situation to their own country, where the price of obtaining a 4-year degree from one of America’s Ivy League universities will easily surpass the figure of $100,000, the immediate questions that arise are why European universities and colleges do not charge fees, and why they are not overburdened with students and at the same time under-funded? During the course of this chapter, we will look at the role and impact of tuition fees, the reasons for charging tuition fees and why some (European) governments do not allow universities and colleges to charge fees. Tuition policies in Europe, Australia, and New Zealand form the core of this chapter and we will present tables that show the levels of fees for a number of European and Australasian countries.
The contents of this chapter owe a great deal to past research by CHEPS; especially the work carried out with colleagues from the CPB Netherlands Bureau for Economic Policy Analysis (CPB/CHEPS, 2001). 1 We will use the term higher education for all formal education programs that are founded on (or built upon) some form of completed secondary education program and lead to an officially recognized diploma. So the term may be used interchangeably with the terms ‘post-secondary education’ or ‘tertiary education’.
J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XIX, 241–310. ©2004 Kluwer Academic Publishers. Printed in The Netherlands.
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The topic of charging student fees, however, is placed in a broader theoretical framework that addresses the role that fees may play as a quasiprice on the higher education market. Because the debates on fees and the tuition fee policies implemented by governments are often based on the added benefits of higher education for individuals and society, we will also present estimates of the private and social rates of return to investing in higher education. The effects of charging fees will also be discussed here, and we will especially be interested in the question whether fees affect the size and the composition of the student body. We will look at the students’ price responsiveness in general and discuss in particular the effects of fees on students from families of disadvantaged socio-economic backgrounds. This is where we touch upon the issue of student support and other policies to promote access and equal opportunity in higher education. Although European governments still show a reluctance to introduce (or increase) tuition fees, they have in recent years adjusted student support systems in such a way that students are asked to make larger private contributions to their costs while studying. Grants and scholarships have been cut and interest subsidies have been decreased. Finally, we will discuss fee deregulation. The institutions that have the freedom to set their own fees will often be private institutions. However, allowing institutions to set their own fees can also be extended to public institutions. While introducing market-driven fees may still look improbable to many of today’s European higher education administrators, the U.S. system can teach us some lessons here. Fee deregulation touches upon the relationship between fee levels and quality, as well as the institutions’ policies and strategies with regard to student admission and selectivity.
FEES AS QUASI PRICES Tuition fees are charges levied upon students, or upon students and their parents, that cover some portion of the underlying cost of higher education ( Johnstone, 1998). Tuition fees are related to the institutional costs of instruction and are thus distinct from charges related to the costs of student living, or maintenance — for example, room, board, laundry, transportation — even though such maintenance charges may also be levied upon students or parents by the institution if it operates dormitories and dining halls. 242
Jongbloed: Tuition Fees in Europe and Australasia Tuition fees are not a price like any other price that is paid for a commodity or service. The fees are more like a quasi price. The reason is that higher education is a non-profit sector, whose primary feature is that government subsidizes education in order that colleges and universities can provide their services for a price that is far less than the average cost of production (Williams, 1997). Nearly all costs related to higher education, including the underlying costs of instruction as well as the costs of student living, are borne by some combination of students, parents, and taxpayers. Economists, when speaking of tuition fees, prefer using the term “user charges” or levies, instead of prices. In the for-profit sector, prices are always greater than production costs (the difference being profits) while in higher education tuition fees are always less than production costs. Thus, the principle issues surrounding tuition fees relate to the division of the burden of covering instructional costs between the government, or the taxpayer, on the one hand, and the students and/or the parents on the other. The fact that the institution’s cost of instruction are only partly borne by students (and their parents) implies that the market we are talking about is different from the market for any other commodity and that charges paid by consumers (i.e., students) do not play the same role as in any other market. For instance, in a ‘standard’ market, the price plays the following four roles: ● ● ● ●
unit of resourcing, rationing available supply, signaling device, income (re-)distribution.
We will discuss the four functions and see how they relate to tuition fees. The first role focuses on the role of a price in generating resources for the supplier. Through fees, universities and colleges receive income to cover their costs. The income generation role of fees is especially important in Anglo-Saxon countries like the United States, Canada, the United Kingdom, Australia, and New Zealand, where tuition fees represent a substantial source of revenues for higher education institutions. In the United States, households cover about 40 percent of the instructional cost. In Australia the figure is about one-third. In Europe, the figures are much lower. It is important to make a distinction between public and private providers. Public providers of higher education will depend largely on the state for their income. Private providers often will have to rely on the income generated from fees. Within this subset, private for-profit providers will try and create a surplus in order to make a profit. Normally, if suppliers are free to set their prices they will try 243
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and maximize their revenues, taking into account that a higher price will decrease demand for the goods and services on offer. In higher education, this would mean that some students would decide not to go to college or go to another higher education provider. The second role of a price lies in rationing the available supply across those expressing a demand for it. If prices are flexible, they will adjust up to the point where demand equals supply and the services are sold to those people who are prepared to offer the most. In higher education, this often is not the case. In many cases (i.e., for the higher education programs offered by public institutions), the prices — the tuition fees — are fixed. The state regulates the fees. The tuition fee is not an equilibrating price that rations the available supply among all consumers that place a value on the education that is at least as high as the rate of the tuition fee. For example, in programs in disciplines like medicine or dentistry, the state often will set the number of available study places, each of them offered for the same price. This creates excess demand and requires rationing schemes, entrance tests, or (as in the Netherlands) weighted lotteries to decide which students are offered a place. If demand exceeds supply in a “normal” market, this would signal producers to supply a higher quantity of the commodity in question. Resources, thus, would flow towards the areas of excess demand. However, in higher education, an excess demand cannot lead to an increase in the price level, partly because this might create problems with access for students from low-income families (as will be argued later on in this chapter). Excess demand will not be eliminated by means of increased (“market clearing”) prices and, therefore, there is no guarantee that students that place the biggest value on the program in question will occupy the available places. The third function of a price is that it acts as a signal on a market. Ideally, prices reflect the (marginal) cost of producing a particular product. This confronts consumers with the cost they are incurring and encourages an economic (i.e., efficient) use of resources. For higher education, students making their decisions about what and where to study are not led by signals (i.e., prices) that reflect costs and scarcities on the market. Especially, if tuition fees are the same across all programs that each have different costs. From a societal point of view this might lead to an inefficient use of resources and phenomena like an excessively long time to degree. Although some states have increased tuition fees in an effort to create incentives for students to choose more wisely or to make them study more quickly, they have chosen to implement across-the-board rises 244
Jongbloed: Tuition Fees in Europe and Australasia instead of differentiated fees. Moreover, if the state chooses to maintain a system of uniform fees across all providers, it implicitly sends out the signal that all programs have the same quality. Turning to the fourth function of a price, we observe that consumers who decide to pay the price will, along with the product they are buying get the attached government subsidies — if any — invested in the product. This role is more of an indirect one and is relevant especially in the case where the difference between the real cost and the tuition fee is relatively high. The bigger the difference, the bigger is the implicit subsidy from the government. For higher education this means that a student paying a fee that is only modest compared to the total program cost receives a larger subsidy. In the case of uniform tuition fees, it means that students in expensive programs, such as engineering, medicine, and natural sciences, receive a larger subsidy than students in social sciences or humanities. From an equity — that is societal — point of view this could be problematic if the highly subsidized students once graduated turn out to be the ones that profit the most from their education in terms of higher earnings. From a societal point of view it might have been better if subsidies were used to educate students in low-cost programs that have important societal returns. The obvious examples are programs in teacher training and nursing. In short, tuition fee policies have important implications in terms of the direction of government subsidies. Ideally, decisions on government subsidies would need to be guided by equity arguments and the external effects of particular education programs. From this overview of the role of prices it will be clear that tuition fees are different than prices charged for commodities produced by private firms. Often, tuition fees only play a minor role in generating revenues, enhancing student choice, improving efficient resource use, and optimizing the allocation of government subsidies. Now let us look at the level of the fees charged to students in a number of OECD member states.
LEVELS OF TUITION FEES We will now present some facts about the levels of tuition fees in Europe and Australasia. Recent levels of fees (expressed in the Euro currency) are shown in Table 7.1. Fee levels for the United States are also included for the sake of reference. 245
246
England and Wales
Ireland Netherlands
Germany
France
Austria Denmark Finland Flanders (Belgium)
Country
University (Ba/Ma) Université (Ba) Université (Ma) Grandes Écoles Universität (Ba/Ma)/ Fachhochschule (Ba) University, college “Hogeschool” (higher vocational education; Ba) University (Ba/Ma) Part-time and “slow lane” students (unis/hogeschool) MBA programs Bachelor (UK/EU students) Bachelor (non-EU students) Master: taught MA (UK/EU students) Master: research (UK/EU students) Master (non-EU students) MBA programs
Fachhochschule (Ba), Universität (Ba/Ma) Ba/Ma Ba/Ma Higher vocational education (Bachelor)
Type/Sector of Higher Education
406 660
50 80 104
2,605
1,302
1,500 1,500 4,860 12,810 3,000 4,500 3,910 4,640 7,880 12,920 average: 14,290
1,302 1,302
1,302 1,302
“Studentenbeitrag” ⫾50 670 670
800
726 0 86
Maximum
726 0 51
Minimum
Public Institutions
Table 7.1: Tuition Fees in Selected OECD Countries: Rates in Year 2000/2001 (in Euro)
4,500
1,585
1,400
Minimum
24,000
2,950 5,210
5,600
Maximum
Private Institutions HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX
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Source: CHEPS.
New Zealand United States
Scotland Spain Sweden Australia
Bachelor Graduate endowment: 2,840 University 500 770 Ba/Ma Union fee: 30 Bachelor (Australian students) HECS rates: Humanities, social sciences, education, nursing, arts 2,076 Economics, natural sciences, engineering, math., IT 2,957 Medicine, law 3,461 Bachelor (fee-paying Australian students) 4,500–12,500 Bachelor (overseas students) 7,200–14,400 Master (coursework Ma; Australian students) 3,500–6,800 Master (research Ma; Australian students) HECS rates University (Ba) Average: 1,720 (depending on institution) Average: min–max University (Bachelor, 4-year) 2,890 1,260–6,930 University (Ma) 3,500 University (first professional degree in Law) 6,670 18,160 University (first prof. degree in Medicine) 9,980 23,740
Average: 2,400 (depending on program) Average min–max 16,650 13,620–21,870 12,030
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From Table 7.1 it is immediately clear that in many European countries tuition fees are either non-existent or comparatively low. It is important to realize that in Europe the private higher education sector is very small compared to the United States. Although Belgium and the Netherlands do have a substantial private sector, the private institutions are in fact subsidized by the government on exactly the same terms as the public institutions. The private character of the institutions relates to their religious basis at the time of their foundation. Over the years these private institutions have become subjected to government regulation and, as a result, have qualified for public subsidies. Nowadays, the private institutions are completely equivalent to their public counterparts as far as their teaching and research is concerned. A similar situation exists in the United Kingdom, where most universities are set up as private charitable bodies that receive government funding and are subjected to government regulation, although formally they are self-governing institutions. In other words, a “really” private and independent sector has not yet come into existence in Europe. In cases where private higher education providers exist these are as heavily subsidized as the public institutions. Private (and public) institutions in Europe, except for a few old and prestigious ones, have almost no endowment income, making it very difficult for them — even if they were allowed — to decide themselves on the fees charged to (particular groups of) students. For a discussion of the facts presented in Table 7.1, let us first turn to the two European countries that — compared to the other countries — charge relatively high tuition fees: the United Kingdom and the Netherlands. In the United Kingdom, from 1977 to 1998, tuition fees for undergraduate students were paid automatically by the government — through the Local Education Authorities. Three fee categories (or fee bands) existed: for classroom-based subjects (a fee of £750 in 1997/98), for laboratory-based courses (£1,600), and medical courses (£2,800). Before, that is until 1977, fees were payable where income (usually that of the student’s parents) was above a certain level. In addition, fees had always been charged for parttime students, postgraduate students, and many students in sub-degree higher education (Barr, 2001, p. 203). Between 1977 and 1998, full-time university bachelor students were exempt from fees. From the academic year 1998/1999, the government implemented a flat-rate tuition charge of £1,000 (on average 25 percent of average teaching costs) per student per year, irrespective of university or subject studied. This was accompanied 248
Jongbloed: Tuition Fees in Europe and Australasia by an income test, which meant that students from poor backgrounds paid no fees and students from well-off backgrounds paid the entire fee. In between a lower and an upper income threshold, a tuition fee was charged on the basis of a sliding scale. Today, the fee is £1,100 (€1,500) representing the highest level in Europe. Later on in this chapter we will return to the case of Britain, when we discuss the future plans announced by the government in the beginning of 2003. In the Netherlands, tuition fees for regular full-time students are centrally determined by Parliament (based on policy proposals by the Minister of Education) and are uniform for all subjects in the two main sectors in higher education, the universities and the hogescholen (universities of professional education). The rate for full-time students as of 2003 amounts to €1,515. Expressed as a percentage of the total direct instructional costs, the private contributions have been relatively stable at around 19 percent of average direct costs in the university or hogescholen sector. From September 1996 on tuition fees for part-time students and for fulltime students who have not completed their studies within the nominal program length plus 2 years have been set by the institutions themselves at levels above a government-imposed minimum. The institutional rates, however, do not show wide variations across universities. For hogescholen, the situation is even more homogeneous. Turning to the countries that charge low or modest fees, we first point out the cases of Belgium (the Flanders community) and France. These are cases where uniform national fees do exist, but students receiving student support are exempted. This means that in France, bursary holders, representing around 15 percent of all students in the first (2-year) and second (1- to 3-year) cycle of higher education, are not paying fees. Regular students in the French public institutions are paying fees, set by the ministry of Education, ranging from €100 for general programs to €800 for specialized programs. In private institutions the fees are determined by the institutions themselves and are much higher. In Belgium, bursary holders only pay some 15 percent of the tuition fee paid by non-holders. In the Scandinavian countries and Germany, the only contributions paid by students are (compulsory) student union membership fees or health services payments. In Greece (not shown in the table) there are no fees. In Italy, since 1992 universities are free to impose fees, which may vary from 400 to (in some cases) €2,500 and are levied on top of registration fees. The public universities in Spain have to charge uniform fees, according to field and level of study. The fees vary between €500 and €750. 249
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Austria introduced tuition fees in 2001. The level of the fee is the same across all institutions: €726. Therefore, apart from the Netherlands and the United Kingdom, European governments have tried to stick to a tradition of free (or relatively inexpensive) education for all. Parliaments have been very reluctant to introduce tuition fees. For instance, in the case of Ireland Parliament even decided to abolish fees in 1996, which means that as of 2003 Irish students pay an annual registration fee of €670. Before, Irish students paid substantial tuition fees (on top of the registration fee), ranging from €2,400 to €4,500, depending on the level and field of study. Often, the absence of tuition fees is defended by referring to one or more of the following reasons ( Johnstone, 1998). First, proponents of a “no fees” system emphasize the predominance of the public benefits of higher education. Higher education is important to all citizens, rather than just those who attended as students. Because all benefit, all should pay. Any tuition could begin to limit participation and thus detract from this public good. Second, any tuition fee, even if it is accommodated by means-tested grants for students from low-income families, may still discourage enrolment and persistence from low-income or rural and ethnic-minority youth. In order to achieve the social goal of equality as well as increasing the overall educational level of the population, it is argued that higher education should be free of charge. Third, apart from the tuition fees, students are already faced with the high costs of accommodation, travel, and general living expenses. And on top of that, there are the costs of foregone earnings during the student years (a topic we will address below). Therefore, even without tuition fees, substantial expenses are already being borne by most students and their parents. Introducing fees or raising fees then would imply raising the cost of going to college with some students either having to rely more on their parents, taking out loans or doing part-time work. In short, the absence of fees is defended by referring to equity and equal access arguments. We will not discuss the validity of the arguments here, but merely add that, so far, Parliaments in European states have been very sensitive to them. On top of that, the principal immediate beneficiaries of free public higher education — students and friends and families of students — are enormously powerful politically, by virtue of their predominantly middle- and upper-class backgrounds, their status as intellectual and social elites. 250
Jongbloed: Tuition Fees in Europe and Australasia Reviewing the fee rates in Table 7.1, one is struck by the differences between the European countries, included in the top half of the table, and countries like the United States, Australia and New Zealand, contained in the bottom half. We will discuss the Australasian tuition systems later on in this chapter. The difference between the top and bottom half of the table is even bigger if one takes into account the fact that in many European countries, in addition to being free from tuition fees or being subject to comparatively low fees, higher education students are assisted by varying combinations of grants, low-interest loans, tax breaks, subsidized services, and family allowances. The Scandinavian countries (Denmark, Norway, Sweden, Finland) and Germany all have grants and family benefits to help students pay for their living costs. In the Netherlands, all full-time students receive a basic grant, irrespective of their parents’ income. In the United Kingdom, where, at first sight, students pay a comparatively high tuition fee, the actual fee paid is dependent on the parents’ income.
PRIVATE RETURNS FROM HIGHER EDUCATION Now let us look at tuition fees from the perspective of the student; placing fees in the bigger picture of the costs and benefits associated with higher education. Higher education provides benefits to the student. This is an undisputed fact that has to be taken into account when forming an opinion on tuition fees. And the saying goes “who benefits pays.” This principle, at first sight, might be used as an argument in favor of charging fees to students. However, before subscribing to this principle one should look more closely at a student’s benefits and costs of attending higher education. This, first of all, leads to the question of why people attend higher education. Students participate in higher education for two basic reasons: consumption and investment. Under the consumption motive, higher education generates immediate benefits related to a student’s curiosity and the pleasure to learn. Many courses, however, are worth more to the student than instant gratification; they equip students with knowledge and skills which will enhance her productivity at work for years to come ( Johnes, 1993). This is the investment motive, which means that students incur the costs of education (both time and money) in the short run in order to derive benefits eventually in the form of a future income that is higher compared to the earnings of 251
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workers without a college degree. This argument revolves around the idea that a student’s productivity increases due to education and training. Private benefits accrue to graduates in the form of human capital. This is the assumption underlying the theory of human capital (Schultz, 1961; Becker, 1964): education enhances the knowledge and skills embodied in people, thus raising their human capital. More human capital, in turn, implies higher salaries and a smaller chance of ending up unemployed. The benefits accruing to individuals take the form of personal, cultural, and economic rewards. There is little doubt that graduates enjoy substantial advantages over non-graduates in the labor market. Lifetime incomes are typically much higher, unemployment rates much lower and the expected duration of unemployment is relatively short for those with higher education qualifications (Chapman, 1996). About the costs incurred, one has to note that, first of all, the general public will point at the fees and other direct costs of education such as study materials (books, personal computers, etc.). That is, of course, if fees are charged at all. However, the main cost category for individuals is foregone income while learning, that is what would have been earned in the absence of studying. This is the opportunity cost of studying. Putting the private benefits and private costs of higher education in an investment — that is, lifetime — perspective, one can calculate the private returns. The estimation of rates of return is one of the empirical applications of human capital theory. Rates of return analyses are very popular among labor economists and policy analysts (Psacharopoulos, 1981, 1994). Most of these studies show that on average investment in higher education is associated with high private economic returns. This would answer the question why people attend higher education. However, this human capital approach is challenged by the signaling (or screening) approach (Arrow, 1973; Spence, 1973). This view on college participation states that education primarily serves to reveal the innate ability of people. Natural ability and family background are considered to be the main determinant of individual productivity. While it cannot be observed directly, people can provide information about their productivity by investing in education. Thus, education helps to alleviate the information problem on the labor market. Having a degree, signals that the holders possess specific worthwhile characteristics, it signals to prospective employers that he or she is a high-productivity worker. Consequently, education may be a beneficial investment for individuals, even if it does not increase their productive capacity. The screening 252
Jongbloed: Tuition Fees in Europe and Australasia hypothesis questions the causal link, at least for post-primary education, between education and individual productivity, arguing that education is associated with increased productivity but does not cause it. A standard critique to the signaling approach is that higher education is a costly instrument to signal ability. Admission tests may be a much cheaper instrument to solve the information problem. A second objection to the so-called strong form of the screening hypothesis is that it fails where education includes professional training, for example, in medicine. What do the data say about the importance of the human capital versus the screening hypothesis? Hartog (1983) compares earnings of people who attended a higher education program but did not obtain a degree to earnings of people who completed the program. He finds a significant negative effect of the graduation gap, that is, the number of years short of graduation for those who did not complete their studies. Quantitatively, the effect of a year of non-graduation is in the same order of magnitude as the earnings gain of an additional year of higher education. This finding supports the human capital augmenting view of education, and is in contrast with the prediction of the screening hypothesis. Other evidence supporting the human capital model is presented in Groot and Oosterbeek (1994). However, according to Temple (2000) and Weiss (1995), the overall importance of signaling remains controversial and the results of natural experiments to test the correlation between earnings and schooling are not necessarily inconsistent with the signaling view of education. Returning to the rate of return analysis, we have to point out that this type of analysis does not capture the entire spectrum of benefits. First of all, education also generates non-monetary benefits. We already mentioned the consumption benefits of higher education. The consumption benefits are enjoyed not only during the course of instruction but over the rest of the student’s life. For example, an extensive knowledge of nature, culture, and society in general allows one to enjoy one’s life even more than would have been the case without a college degree. Furthermore, higher education is often believed to increase job satisfaction and job mobility (better job opportunities because of increased labor market search efficiency). Other examples of non-financial returns refer to non-wage labor market remuneration, intra-family productivity, quality of upbringing of siblings (level of education, cognitive development, health), own and spouse’s health, participation in social life, consumer choice efficiency, marital choice efficiency, attainment of desired family size, charitable giving, and savings (cf. Wolfe and Haveman, 2000). Table 7.2 presents an 253
HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Table 7.2: The Private and Social Costs and Benefits of Higher Education
Costs
Private
Social
Tuition fees
Operating costs of HE institutions Student support Foregone national production related to students
Study materials Foregone earnings Monetary benefits
Greater productivity Higher net earnings Employment Better job opportunities Higher savings Personal and professional mobility
Economic growth National and regional development Higher tax revenues More flexible labor force Increased consumption Reduced reliance on government financial support
Nonmonetary benefits
Educational consumption Improved working conditions Increased personal status Higher job satisfaction Healthier life style Improved quality of life (also for siblings) More informed decision making More hobbies and value of leisure Personal development
Social cohesion, appreciation of social diversity and cultural heritage Social mobility Reduced crime rates Improved health More donations and charity work Increased capacity to adapt to new technologies Democratic participation Improved basic and secondary education
Source: Based on World Bank (2002), Table 4.1, and Jongbloed and Vossensteyn (2002).
overview of the private (i.e., individual) benefits, both the monetary and the non-monetary benefits, and places them next to the benefits and costs to society, again distinguishing between monetary and non-monetary benefits. The non-financial private returns to higher education are far harder to measure than the financial returns. Wolfe and Haveman (2000) survey the literature on this issue, and conclude that non-market returns to schooling are substantial: conservative estimates of the value of non-labor market influences are in the same order of magnitude as estimates of the annual financial rate of return to schooling. However, even if one only takes into account the monetary benefits of higher education the private rate of return estimations are likely to be conservative. The reason is that in many countries students receive some form of financial support or other subsidies 254
Jongbloed: Tuition Fees in Europe and Australasia Table 7.3: Private Rates of Return to Tertiary Education 1999–2000 Men
Women
Australia* Canada Denmark France Germany Italy Japan Netherlands Sweden UK US
13.2 8.7 11.5 14.3 9.1 7.5 7.9 12.1 11.4 18.5 14.9
11.3 9.9 11.1 15.4 8.4 n.a. 7.2 12.5 10.8 16.1 14.7
Unweighted average**
11.6
11.8
* The figures for Australia are from Chapman and Withers (2002) and relate to the year 1994/95 and are for bachelor degree (4-year degree) holders; ** Excluding the figure for Australia. Note: The reported figures relate to the comprehensive rates, thus incorporating the effect of taxes, unemployment risk, tuition fees and public student support, but excluding the nonmonetary benefits of education. Source: Blöndal, Field, and Girouard (2002).
from their government. On top of that, most students take up small jobs while in college, although probably earning a lower wage than they would have earned had they been in full-time jobs. The combined effect of these facts means that these incomes should be subtracted from the foregone earnings to arrive at the real costs to students. While there are many shortcomings of private rate of return analyses, there are many studies that have tried to measure them. Table 7.3 shows the private internal rate of return to higher (or tertiary) education. The internal rate is equal to the discount rate that equalizes the real costs of education during the period of study to the real gains from education thereafter. The costs equal tuition fees, foregone earnings (net of taxes and adjusted for the probability of being in employment), minus the resources made available to students in the form of student support (grants and loans). It is good to note that the foregone earnings are usually approximated by the earnings of individuals holding an 255
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upper-secondary education degree. In other words, the rate of return analysis provides an estimate of the extra return on higher education compared to secondary education. The benefits of higher education are the gains in post-tax earnings adjusted for higher employment probability, minus the repayment, if any, of public support during the period of study (Blöndal et al., 2002, pp. 21, 22). The reported rate-of-return calculations abstract completely from any non-monetary benefits of education. Blöndal et al. (2002) show that the private rates of return differ significantly across the countries listed in Table 7.3. The average male private rate of return for a number of OECD countries lies around 12 percent. Returns for successful students range from 6.5 percent in Italy and 7.5 percent in Japan to 17.3 percent in Britain. The figures for women were slightly lower on average. Shorter university studies are one reason why returns are so high in Britain. Estimates for rates of return to education (not necessarily higher education) in the Netherlands vary from 3 percent to 8.6 percent (Hartog et al., 1999). For the Netherlands, Canton (2001) presents estimates for the private returns to an extra year of higher education. His study shows that for the vocationally oriented programs offered by the universities of professional education (the so-called HBO institutions) the rates are 6.7 percent, while for the traditional universities the rates are 9.2 percent. U.K. figures, submitted to the National Committee of Inquiry into Higher Education (the Dearing Committee), suggest that for the period 1989–95 the private rates of return from higher education for men on average varied between 9 and 11 percent, while for 18 year olds, they vary between 11 and 13 percent (Steel and Sausman, 1997). Ashworth (1997) obtains estimates of the average returns to higher education for the United Kingdom in the range of 9–21 percent, depending on assumptions with respect to economic growth, graduate unemployment and the type of student support. More recently, Blundell et al. (2000) estimate a rate of return to an undergraduate degree of around 17 percent for men and 37 percent for women. For Austria, similar calculations for the mid-1990s show private rates of return of around 12 percent (Biffl and Isaac, 2001). International estimates of the returns to an extra year of education lead to figures between 5 and 15 percent, depending on the time period and country in question. The large variation across countries is partly due to the earnings differentials within the country — that is, between those holding a college degree and those in possession of a diploma from upper secondary education — and the earnings differentials between degree 256
Jongbloed: Tuition Fees in Europe and Australasia holders from different countries. One has to note that the OECD estimates shown in Table 7.3 do take into account differences between countries in taxes, the length of education, unemployment risk, tuition fees, and student support. In other words, the rates are so-called comprehensive rates. For all studies mentioned here it is warranted to conclude that the private internal rate is higher than the real interest rate or the rate of return on other productive assets. This would imply that higher education is an attractive investment.
THE SOCIAL BENEFITS FROM HIGHER EDUCATION After having discussed the private benefits of higher education let us turn to the social benefits. The social benefits differ from the private benefits in that they take account not only of the benefits experienced by the individual but also of the benefits enjoyed by the rest of society. Looking at the cost side, social costs also take into account the costs borne by society (usually through taxes) in order that the individual can receive educational services. The cost of higher education now includes not only foregone earnings (i.e., the opportunity cost of having people not participating in the production of output, that is the loss of national production) but also the full cost of providing education (rather than only the cost borne by the individual through tuition fees). With respect to the latter we repeat that governments in Europe usually bear a very substantial share of the cost of education. The benefits to society, which are often referred to as “spillover” benefits, are usually argued to include (cf. Chapman, 1996, pp. 44–45): ●
●
●
●
●
the contributions to political democracy and stability, a more informed public debate and voting behavior, less crime, and more tolerance; the community benefits from research not completely captured by the individual, in part because of an (highly) imperfect patents system for knowledge; the benefits accruing to workers and others from the imitation of the skills of the highly educated, not reflected in graduates’ wages; higher tax revenue resulting from the higher productivity and wages of the more highly educated; improved prospects for increased competitiveness and economic growth through more highly educated people being able to adapt 257
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and adopt new technological progress, with returns not accruing just to graduates. The social returns to an educational investment indicate the desirability of this investment to society and — as we will discuss later on in this chapter — constitute an important reason for the government to invest in higher education. Two essential concerns for the government are: what are the social benefits and how much are they worth? Since the early 1960s it has been argued that in a world of rapidly changing information more highly educated workers have an advantage in adapting to different environments, in “dealing with disequilibria” — the capacity to adjust to unanticipated shocks (Huffman, 1974; Fane, 1975; Schultz, 1975). Nelson and Phelps (1966) emphasized the role of the human capital stock in creating and adapting new technologies. First, creating and adopting new technologies is more effective at higher levels of human capital. Second, learning (by-doing) is more effective with higher average human capital. Third, human capital accumulation is more effective within groups with the same level of prior human capital. This third externality is not related to the average level of human capital, but to the composition of human capital. The literature on human capital spillovers shows that more highly educated individuals are able to react productively to the emergence of new information and new technologies. In particular, new and improved agricultural inputs — such as fertilizers — are used more efficiently by more educated people. It is reasonable to suggest that this is because the process of learning associated with formal education results in people having increased capacities to understand and manage change. That is, learning how to learn is an important skill (Chapman, 2001). But for education to result in social as well as private gains requires that the rents from the process not be captured completely by the educated individuals or the firms employing them. This will be the case only if technological change flows easily from one workplace to the next (Romer, 1990). Lucas (1988) has suggested that high levels of education result in the increased dissemination of knowledge. Lucas conjectures that the human capital interaction within cities is a prominent channel, although empirical evidence for this externality is ambiguous. Rauch (1993), though, performs an analysis for the United States with the standard metropolitan statistical area as the relevant community and finds evidence for externalities. Bartel and Lichtenburg (1987) suggest that high levels of formal education seem to be necessary for the successful introduction of capital equipment. 258
Jongbloed: Tuition Fees in Europe and Australasia The belief that the most important social benefit from higher education is its contribution to technological change and, consequently, economic growth has been the topic of a growing research literature, known as endogenous growth theory (Romer, 1993). However, measuring the impact of education (let alone higher education) on economic growth is not straightforward. An important reason is that the growth impact of education on the skills of the labor force will be determined by both its quantity (higher schooling levels) and its quality (the amount of knowledge imparted at any given schooling level), and this distinction raises important measurement issues. Understandably, given data availability, most analyses focus on the former. Regressions of the level of GDP on the level of human capital fail to deliver a significantly positive relationship (Venniker, 2000). The role in economic growth of both the quality and the quantity of education internationally are compared in Hanushek and Kimko (2000). They test the extent to which educational quality as measured by standardized scores for mathematical and scientific literacy has contributed to economic growth differences averaged over 30 years across 139 countries. The test results are compared with the effect of changes in schooling quantities (as measured by the number of years of schooling). They find that increases in workforce quality have a profound influence on economic growth, and by much more than quantities — where these can be measured separately. For example, on average a one standard deviation increase in test scores adds about 1.0 percent to a country’s GDP per capita annual growth rate. By contrast, increases in the quantity of schooling required to match this growth rate change seems to be very much higher: that is, to achieve a one percent increase in the annual growth rate of a country’s GDP per capita would require on average that workers had nine additional years of education. The type of results produced by Hanushek and Kimko suggest that a country should watch its test scores and compare them to that of other countries. Governments, on their part, would need to examine trends influencing the quantity and the quality of education closely.
THE SOCIAL RATE OF RETURN OF INVESTMENT IN HIGHER EDUCATION The previous section suggests that there is a compelling economic case for the maintenance of important government subsidies for higher 259
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education. A difference between the private and social returns to education is a prime motivation for government intervention on the market for education. It is evidence of the fact that those having participated (or participating) in higher education do not reap the full benefits of their educational investment themselves. If higher education creates benefits to society over and above those to the individual this would represent a case of positive external effects. Such effects are known as externalities or spillover benefits, since they spill over to other members of the community. Spillover effects are a manifestation of market failure (Barr, 1998; Stiglitz, 2000) and point to a role for government in correcting the market by stimulating participation and investment in higher education. Negative external effects may occur if the government provides a degree of financial support that pushes participation to levels that are beyond the socially optimal level (i.e., private returns exceed social returns). The fact that rational, self-interested individuals do not take the more wider, social benefits of higher education into account in their investment decisions will lead to investments in higher education that are too low from a social perspective. While the human capital spillovers discussed will be difficult to measure, there is at least one strong external benefit that may be more easy to quantify (Barr, 2001, p. 165), that is the increased tax revenues received by the government. If education increases a person’s future earnings it increases his/her future tax payments. The investment in education thus confers a “dividend” on future taxpayers. In the presence of such an external benefit the resulting flow of private education investment will be less than optimal and, therefore, governments intervene by offering tax advantages for a firm’s investment in physical capital or an individual’s investment in post-secondary (or post-initial) education. For governments then the question is what is the appropriate level of spending on different types of education and what is the efficient level of taxpayer subsidy (Barr, 2001, p. 161)? Do the private and social returns to higher education differ, and, if so, by how much? Notwithstanding the difficulties in measuring social benefits and the critique on human capital theory expressed by proponents of the screening hypothesis, many studies have attempted to measure the social returns to education. However, the estimates vary widely, mainly because of the different ways of capturing the social costs and benefits of education. Some authors have identified positive externalities of education but few have been able to quantify them (but, see Weisbrod, 1964; Haveman and Wolfe, 1984).
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Jongbloed: Tuition Fees in Europe and Australasia Two studies — background reports to a government-commissioned study on the future of the higher education sector in the United Kingdom (National Committee of Inquiry into Higher Education, 1997) — have focussed especially on higher education (Gemmell, 1997; Steel and Sausman, 1997). The studies do not report strong evidence for the existence of externalities related to higher education. In particular, Gemmell (1997) writes: “The most likely source of reliable evidence is likely to come from comparing macro and micro estimates of rates of return to higher education. Present evidence is very limited; again it is suggestive of a small externality effect, at best, associated with higher education but a greater weight of evidence is required before firm conclusions can be stated.” Glennerster (1997, quoted in Barr, 2002) presents modifications of Steel and Sausman results, showing social and private rates of return to a degree. Glennerster is incorporating an “alpha factor,” which is the assumption about the extent to which the higher earnings of people with more education are attributed to that extra education. Thus alpha ⫽ 0.6 means that 60 percent of extra earnings are caused by extra education; by implication the remaining 40 percent is due to natural ability. If two countries differ in the extent to which other characteristics than education are translated into earnings, the value of alpha differs. For instance, the value for alpha may be related to the impact of social class on earnings. The social rates of return to education for 19-year old men estimated by Glennerster lie between 6 and 7 percent for alpha ⫽ 0.6 and between 7 and 9 for alpha ⫽ 0.8. For the early 1990s the returns seem to be slightly higher than for the mid-1980s. The difficulty of incorporating non-economic effects in rate of return calculations and translating these into monetary values, stands in the way of constructing comprehensive social rates of return. Therefore, the OECD, following up on a review of studies measuring the social benefits of education (OECD, 2001), has recently published so-called narrow estimates of social rates of return to education (Blöndal et al., 2002). The “narrow” adjective relates to the fact that the estimate of the social returns abstracts from any externality affects non-economic benefits and assumes that all wage gains from education represent associated gains in productivity. To the extent that there are sizeable positive externalities related to human capital investment by the average student, these estimates will thus be biased downwards. Table 7.4 shows the OECD estimates for tertiary education.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Table 7.4: Estimates of Social Returns to Tertiary Education, 1999–2000
Australia* Canada Denmark France Germany Italy Japan Netherlands Sweden UK US Unweighted average**
Men
Women
14.5 6.8 4.3 13.2 6.5 9.7 6.7 10.0 7.5 15.2 13.7
— 7.9 11.1 13.1 6.9 n.a. 5.7 6.3 5.7 13.6 12.3
9.6
8.4
* The figure for Australia is from Borland et al. (2000), table 2.6, and relates to the year 1997; is for men and women and is based on a 4-year bachelor degree; **Excluding the figure for Australia. Note: Reported figures related to so-called “narrow” rates of return, which exclude any possible positive external effects due to education. Source: Blöndal, Field, and Girouard (2002).
The social rate of return is calculated as the discount rate that equalizes future costs and benefits, where social cost is the opportunity cost of lost output plus the direct total (public and private) cost of providing education, and the social benefits are equal to the extra (unemployment risk-adjusted) earnings for tertiary educated persons (extra, in the sense of compared to the earnings of persons holding only an upper-secondary degree). The social rates of return are generally significantly lower than the private rates of return (Table 7.3), due to the fact that the social cost of education is higher than the private cost. Notwithstanding this, the social rates of return are on average 8–9 percent, which suggests that investment in tertiary education may often be a productive use of public funds. For the Netherlands, Canton (2001) reports social returns that are somewhat lower than the estimates reported by the OECD. For higher vocational programs the social return in 1997 was 4.3 percent, while for academic programs a social return of 6.6 percent was reported. 262
Jongbloed: Tuition Fees in Europe and Australasia Although the OECD calculations quoted here seem rather reliable, a recent review finds that empirical evidence on social returns is still inconclusive, providing only weak support for human capital spillovers (Venniker, 2001). Blundell et al. (1999) write: “The very few available estimates of the rates of return to education at the aggregate level do not, however, suggest that allowing for an externality effect adds very much to private rates of return based on earnings differences” (p. 15). It should be noted that private and social returns to schooling may differ for other reasons than the simple fact that the direct costs of education are borne to a large extent by the government. In general, apart from the already mentioned human capital spill-overs there is another important explanation for a divergence between the private rate of return and the social rate of return. Temple (2000), for instance, mentions signaling and rent-seeking activities (think of lawyers) as explanations for why the social return could be lower than the private return. The first explanation alludes to the argument that education merely acts as a signaling device and does not contribute to higher productivity. The second argues that more educated workers may have better access to those jobs in which workers share some of the rents earned by imperfectly competitive firms. As Temple argues, it remains worth bearing in mind that other mechanisms will have a positive effect on the social returns to education. On the other hand, the social return may exceed the private rate of return if an improved matching between workers and jobs leads to a more productive economy. In other words, even if education does act mainly as a signal (Arrow, 1973; Stiglitz, 1975), there should not be a presumption that education is therefore socially wasteful.
POLICY ISSUES Having looked at the costs and benefits of investing in higher education we now turn to policy-related issues. In principle, one of the key roles for government is to help ensure the production of optimal quantities of goods and services. For higher education, this means that government intervention on the market for education should ensure that society receives the appropriate level of higher education investment and there is no under-investment in higher education. Ideally, this requires public subsidies equal to the marginal value of the externality associated with higher education. However, as the previous section has argued, it is not currently 263
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possible to accurately quantify the extent of spillover benefits from higher education. Rate of return analyses, although still very prominent in the (higher) education literature and the policy research by the OECD and the World Bank (e.g., Psacharopoulos and Patrinos, 2002), therefore cannot be used as the single motivation for government policy aimed at ensuring an optimal level of higher education spending. Government policy and public investment in higher education will have to be guided by other indicators and motivations as well. Examples are indicators relating to the country’s potential in terms of research and development and innovation. The rate of return calculations show that returns on investment in higher education are generally well above the real interest rate and the rate of return on other productive assets. Even if we take into account the fact that the rates of return are subjected to considerable uncertainty (as indicated, inter alia, by the wide dispersion of earnings among the better educated (see Blöndal et al., 2002, p. 29) and that investors normally would require a risk premium that reflects this, the size of the estimated rates of return suggest that the market for highly educated workers shows a shortage of better-educated workers. This market failure would call for government intervention where government authorities try to enhance the incentives for investment in higher education. The rate of return perspective provides a number of ways by which a government can try to influence the levels of investment in higher education. From the way they are calculated it will be clear that the levels of the rates of return depend on a number of policy-related factors: (1) government subsidies, (2) financial support for students, (3) length of study periods, and (4) tax incentives. The first policy instrument is the level and extent to which the government finances the provision of higher education. In many European countries the government is heavily subsidizing public as well as private higher education providers. In other words, private tuition costs tend to be low and private individuals are thereby encouraged to invest in higher education. Table 7.5 illustrates that the average public subsidy rate in higher education ranges from less than 50 percent in Japan and the United States to close to 100 percent in some European countries. In Europe, the Netherlands and the United Kingdom are the countries where the presence of a tuition fee is reflected in a subsidy rate that is lower than for most other European countries. Second, most OECD governments have tried to stimulate investment in higher education by offering financial assistance to individuals during their studies. The student aid is supplied in the form of grants and 264
Jongbloed: Tuition Fees in Europe and Australasia Table 7.5: Subsidy Rates for Higher Education, 1999 Relative Proportion of Public Sources Australia Canada Denmark France Germany Italy Japan Netherlands Sweden UK US
53.5 61.7 97.7 88.0 91.8 86.5 44.5 79.7 88.4 73.9 46.9
Note: Share of direct public expenditure on tertiary education institutions and total public subsidies to households and other private entities in total sources of funds (public and private) for tertiary education. Source: OECD (2002), Education at a Glance, Table B4.2.
favorable loan arrangements. Increasing the generosity of the student financial support system directly translates in higher private rates of return for students. The rationale for offering student support lies not just in encouraging enrolments for efficiency reasons (i.e., addressing the underinvestment in education that is caused by externalities in the form of knowledge spillovers), but also in equity arguments, that is, equality of opportunity. We will return to equity arguments and data on student support later on in this chapter. The third government instrument that influences the rate of return and that might be used to raise participation in higher education is the length of the study period. Very long study programs will tend to discourage participation in higher education, because for students it leads to a higher level of foregone earnings. Therefore, reducing the time students would need to obtain a degree would act as an incentive to invest in higher education. A critical condition, of course, is that the reduction of the standard length of the education programs does not reduce the quality of the programs. In terms of the human capital theory, the reduction of the time to degree should not lead to a reduction in the student’s productive capacity and, therefore, the student’s earnings potential. Looking at the standard (i.e., the stipulated or official) length of first degree higher education programs in the OECD as well as the actual (or typical) length in the year 265
HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Table 7.6: Length (in years) of First-Degree Higher Education Programs in Selected OECD Countries, 1999
Australia Canada Denmark France Germany Italy Japan Netherlands Sweden UK US
Theoretical Length
Typical Length
3 4 3 3 5 4–6 4 4–5 3–4 3–4 4
3 5 3 3–4 6–7 4–6 n.a. 5–6 n.a. 4 5
Note: Data for non-European countries based on: OECD (1999), Classifying educational programmes. Manual for ISCED-97 implementation in OECD countries, 1999 edition. Paris: OECD. Source: CHEPS Higher Education Monitor.
1999, one can observe quite some variation between countries (see Table 7.6). In countries like Australia and the United Kingdom, the theoretical length is much shorter than in Germany or the Netherlands. If one looks at the actual time to degree, one observes an even more substantial difference in the length of study periods between the countries just mentioned. It should be noted, however, that after the adoption of the Bologna declaration, most European higher education systems have agreed to implement a more uniform system of tertiary degrees, based on a binary degree structure, with the first degree (the bachelor) taking 3 years and the advanced (master or professional degree) taking 2 years to finish. A system like this would enhance student mobility, increase transparency, and allow for the mutual recognition of degrees across country borders. For countries like the Netherlands, Germany, and Italy that used to have relatively long standard program lengths, this could lead to a shorter time to degree and raise participation in higher education. The fourth instrument, like the first one also relating to government finance, is the tax system. If income taxes are progressive, this implies that the increased earnings that are due to increased levels of human capital accumulation are “taken away” by taxes. The earnings of the bettereducated are taxed at a higher rate than the rate applied to the earnings of 266
Jongbloed: Tuition Fees in Europe and Australasia the less-educated. Thus, the tax system will discourage investing in higher education. A less progressive (i.e., a more proportional) tax regime can act as a stimulus for individuals to invest in higher education. Alternatively, making private contributions to higher education tax deductible acts as a similar instrument in encouraging human capital accumulation. The four policy instruments all have an effect on the private rate of return and — in combination — might be used to affect participation in higher education and, through this, produce benefits for society as a whole. Whether (potential) students are indeed reacting to financial incentives like the four instruments presented here is, however, another matter. The crucial parameter here is the price elasticity of the demand for higher education. We will return to the issue of the sensitivity of enrolment to price increases later on in this article, but first of all we will discuss one of them, student support, from the perspective of other market imperfections as well as the perspective of increasing equity in society.
STUDENT SUPPORT Redressing market failures like the under-investment in higher education that is due to human capital spillovers is one of the reasons why governments all over the world intervene heavily in the higher education sector. There are, however, other reasons why governments subsidize higher education and, in particular, provide financial support to students. The reasons can be grouped under the following headings: ● ● ●
credit market imperfections, risk/insurance market imperfections, equity concerns.
We will now briefly discuss the three reasons. Credit market imperfections form a first reason why governments provide student support (CPB and CHEPS, 2001, p. 38). They are yet another example of market failure. Students may need to borrow to finance their investment in human capital. They need to cover their living expenses and tuition fees during the time of their study. This is because their income and/or their parents’ income are insufficient to cover the expenses. However, student loans are rarely provided by private banks. Two factors account for the reluctance of commercial banks to offer study loans. First of all, there is no asset market for human capital. 267
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Therefore, human capital cannot serve as a collateral. The lender (i.e. the bank) has no security for the loan and, consequently is faced with significant risk and uncertainty. Second, the characteristics and behavior of borrowers are hard to monitor (or to predict) by the lender. Thus, the factors that influence the return on human capital investment are largely unobservable for the banks and, consequently, banks are not prepared to offer loans on good terms. Students that are more likely to default, irrespective of their behavior, are more inclined to apply for student loans, while students with very low default risks are induced to refrain from applying for loans because they do not want to pay the risk premium. This leads to the adverse selection problem; borrowers are better informed than the lender about the risks connected with the human capital investment. The result of this is that the average default risks of the students that still want to apply for loans are driven up, which in turn drives up the risk premium charged by banks and induces even more relatively low-risk students to refrain from loans. The end result may be that banks are unwilling to lend against commercial interest rates and there will be an amount of lending that is too low from a national point of view: the development of new and flexible skills for society is discouraged. In addition to this adverse selection problem, the fact that individual behavior is difficult to monitor could lead to the moral hazard phenomenon, in the sense that borrowers do not try all they can to finish their program in time and relieve the debt obligation. The appropriate type of government intervention to correct the problems of credit market imperfections is to make sure that students can borrow — either by governments issuing a bank guarantee of by direct public provision of student loans. Next to the risk and uncertainty facing lenders, there is the risk and uncertainty facing borrowers. This constitutes the second reason why governments intervene through student support. For (prospective) students, investing in higher education involves two types of risk. First, students may be unsure about the effect of higher education on their human capital due to the uncertainty about their own ability (he or she may fail to obtain a degree) and about the quality of educational services offered by higher education providers. Second, students may be unsure about the effects of human capital accumulation on their prospective income and employment opportunities. This is caused by the uncertainty about the future (composition of the) demand for labor. Although the average private rate of return to investment in higher education is positive (and sufficiently large, it 268
Jongbloed: Tuition Fees in Europe and Australasia would seem), there is considerable variance about that average (Barr, 2001, p. 176), so the borrower faces uncertainty and risk about the return to a particular qualification. The first risk is primarily idiosyncratic: due to the law of large numbers, pooling of the risk, resulting in a less risky portfolio of educational investments, is possible in principle. The sum of the individual investments is not risky for society as a whole. The second risk is a form of aggregate risk; one can think of recessions, shifts in labor demand and uncertainty with respect to skill-based technological change. For this type of risk, risk sharing is more difficult; its effect on individual decisions can only be limited by shifting risk from more to less risk-averse individuals (which is also possible for the first type of risk). Both pooling (reduction of risk) and shifting of risk will induce risk-averse people to increase their investment. However, markets fail to provide such insurance, due to moral hazard and adverse selection problems mentioned before. The resulting under-investment in education is generally expected to be particularly severe among students from poor backgrounds, who have to finance their education investments through loans and are afraid to be left with large debts they cannot repay. Before we turn to the equity argument as a reason for governments to offer student support, let us address the question of how relevant credit market imperfections are in practice. When liquidity constraints are important, one would expect parental income to have a positive impact on the enrolment decision. However, Oosterbeek and Webbink (1995) conclude from Dutch data that the effect of parental income on enrolment is not significant. Other authors have reached similar conclusions (cf. Shea, 2000). This does not imply that the government has no role in alleviating credit market problems. In fact, the observation that liquidity constraints do not seem to be very important in the current situation could indicate that government intervention is effective. A widely used government instrument is to lower the price of educational services through subsidies, which alleviate the liquidity constraints and the need to borrow. This policy is not very efficient: students from affluent backgrounds also benefit from these subsidies, while the poorest students may still not be able to finance their studies. A more efficient type of public action would seem to be to provide government loans to students or for the government to stand surety for student loans offered by commercial banks. One possible objection is that students from poorer backgrounds are less willing to incur debts. As will be argued later on in this chapter, income-contingent repayments will alleviate this problem. In that case, graduates repay their debt 269
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only when their income exceeds some threshold. A good example of such a repayment system is the Australian Higher Education Contribution Scheme (HECS). Government intervention of this (“Australian”) kind could also be the response to the above-mentioned absence of a private insurance market to address the risks and uncertainties facing students. Government can (partly) provide such insurance making repayments of student loans income-contingent. Again, this would seem to be a better policy than a system of offering income-contingent loans (ICL) that potentially distorts future choices that have an impact on earnings, like the labour supply decision, the choice of jobs and choices to invest in continuing education. A graduate tax, which is sometimes proposed by student unions and political parties as an alternative to a student loans system, also provides partial insurance. In the case of a graduate tax, each student receives funds (to pay for tuition fees and/or living expenses) and in return the government gets a claim on the student’s future income through a special income tax for graduates. A graduate tax introduces solidarity between successful and unsuccessful students. It has some possible drawbacks, however (Oosterbeek, 1995): the tax is based on total income, instead of the income that might be attributed to human capital accumulation, and the graduate tax may distort future labour supply and education choices. Furthermore, a graduate tax system could suffer from tax evasion, with the authorities unable to collect taxes from graduates who have left the country. The other basic argument for government intervention in private markets is establishing a more equitable society and striving for equality of opportunity. Equity concerns refer to the extent to which higher education does or should redistribute from rich to poor or between different social classes (Barr, 1998). In this sense, equity also relates to the distribution of educational outcomes, for example, whether poorer people end up with fewer qualifications and, as a result, with lower incomes. As argued by Barr (2001, p. 161), equity does not mean that everyone, for example, can go to university; it does not mean that anyone who wishes can go to university. But it does mean that if two people have identical abilities and identical tastes, they receive the same education, irrespective of factors that are regarded as irrelevant such as parental income. If, as suggested by the empirical evidence on social returns, society receives substantial gains from investing in higher education, governments should especially encourage talented individuals from economically disadvantaged families to realize their potential and climb up the social ladder. This would plead for 270
Jongbloed: Tuition Fees in Europe and Australasia targeting public support to those groups, instead of providing generic public support. When discussing equity, one has to distinguish between equity from a lifetime perspective and equity at the moment of attendance (Oosterbeek, 1998a). Looking from the lifetime perspective, one will have to realize that students probably belong to the people with the highest income earning potential. As such, subsidizing them with public money seems unfair (World Bank, 1994; Oosterbeek, 1998a), it would be a form of a regressive policy with people from better-off backgrounds consuming services that are funded from general tax income. However, equity at the moment of attendance refers to the idea that potential students from different socio-economic backgrounds may have unequal opportunities to enter higher education. It is feared that tuition fees and other private contributions particularly harm access of students from poorer and otherwise disadvantaged backgrounds, because they lack the ability of self-finance or to borrow against other collateral. Public support in the form of grants, loans, and tuition fee reductions may increase their likelihood to invest in higher education. If student support policies are formed on the basis of the current income situation of students, then the policies that increase the students’ ability to finance the cost of their higher education investment are likely to lead to grants and loans that depend on a student’s family income (Barr, 2001, p. 191). Alternatively, should the long-term perspective be taken, then support will be supplied in the form of a “study now, pay later” scheme. Examples of a strategy like this are student loans that are repaid on the basis of the graduate’s future earnings or graduate taxes. It will be clear that the approach of the government needs to be driven by long-term considerations. However, so far many European governments have not shown the audacity to accept the long-term perspective. The reasons for this most probably can be found in a fear to alienate key elements of the electorate. Looking at the role of student fees in financing higher education, Canton (2001) argues that equity arguments for government intervention in the setting of fees are subtler than it often seems in popular debates. Some people use the equity argument to plead for lower private contributions, while others use it to advocate tuition fee increases. The first group uses an income-redistribution argument, while the second points to the high private returns to justify a substantial tuition fee (see Oosterbeek, 1998b). 271
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The income redistribution motive is based on the idea that the income distribution is affected by participation in higher education. In particular, it has been argued that government support to higher education might help to reduce income inequality in the national economy (Goldin and Margo, 1992; Teulings, 2000). If government support leads to more highly educated workers in society, this will have a downward effect on their earnings. The so-called skill premium of graduates will decline and wages for the less highly educated workers will go up, leading to an income distribution that may more closely reflect social preferences with regard to equity. As Canton (2001) argues, using education subsidies instead of progressive income taxation to establish a more equal income distribution may be a rather ineffective instrument. This is because, on average, students are not very price responsive (as we will see later on in this chapter) and the effect of an increase in the supply of graduates on their wages is not well established. It is sometimes even claimed that there is a perverse relationship between supply and skill premium (Acemoglu, 2000; Nahuis and Smulders, 2000). Furthermore, it can be questioned whether a further subsidization of higher education is an equitable policy, as it implies an income transfer from the average taxpayer to tomorrow’s well-off — at least in the short run, when the effects on the skill premium are not yet visible. In this view, the equity argument is put forward by proponents of (introducing or raising) tuition fees. This type of argument will be discussed now, along with other pro-fee arguments.
THE CASE FOR TUITION FEES From the discussion earlier on in this article it will be clear that the individual student as well as society as a whole reap substantial benefits from investing in higher education. This implies that resources for higher education should come from the private purse as well as from the public purse, that is, the taxpayer. Public funds would need to be supplemented by private funds. Finding the right balance between the two, however, is the challenge that many governments are currently faced with, now that their countries for some years have experienced mass enrolments in higher education. Economic theory suggests that it is efficient if the student pays for his/her private benefit and that the government should finance higher 272
Jongbloed: Tuition Fees in Europe and Australasia education to the extent that the investment of taxpayers’ resources contributes to the social good. As far as the latter is concerned, the role of the government is to help ensure the production of the optimal quantity of higher education, and this objective is realized when the public subsidies are equal to the marginal value of the externality associated with higher education (Chapman, 2002). Earlier we have made it clear that the private rates of return as well as the size of the external benefits to higher education cannot be measured with a great degree of accuracy and, therefore, the optimal size of the higher education sector cannot be quantified satisfactorily. In other words, one cannot derive the optimal size of the public as well as the private investment in higher education. What we do know, however, is that each system of private contributions implicitly places a value on the externalities produced by higher education. Therefore, having no charge would suggest that the societal benefits of higher education at least equal the size of the subsidy, and, implicitly, that graduates receive no direct benefits (Chapman, 2002). Clearly, the empirical evidence tells us that this is a false statement; higher education delivers important private benefits to graduates. Moreover, from an equity point of view, a system without private charges is regressive and hence unjust. There is ample evidence that students in higher education are more likely to come from privileged backgrounds (middle class, professional backgrounds). Combined with the fact that graduates do well in the labor market this leads to the conclusion that a totally tax funded higher education system implies an income transfer to today’s and tomorrow’s well-off and, therefore, a zero charge system is unquestionably unfair. The argument that “free” higher education promotes access simply does not hold when looking at it from either an efficiency or an equity perspective. This conclusion is even more relevant for countries in Scandinavia and Germany where the higher education systems are maintained fully out of taxation. This situation, combined with the expansion of student numbers, has implied that governments, faced with fiscal constraints and competing claims on the public budget, have been forced to reduce the public funding per student. Funding higher education entirely from tax funding, therefore, is very likely to lead to a shortage of resources for higher education institution. However, it should be said that funding shortages also have arisen in countries where tuition fees are already in place. As we will see later on in this article, it is in some of these countries (most notably Australia, the Netherlands and the United Kingdom) that governments have considered 273
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raising or deregulating tuition fees, thereby giving institutions more room to raise additional revenues from the beneficiaries of higher education. Vossensteyn and Canton (2001) argue that tuition fees can help ensure that the decision to participate in higher education is taken more seriously by candidates. A private contribution encourages and motivates students to study seriously. Thus, the moral hazard risk is reduced. In addition, if students have to pay a price, they are more likely to demand value-formoney. As mentioned in the above section on tuition fees acting as (quasi) prices, the existence of a fee may stimulate competition in the system and induce higher education institutions to offer an attractive price-quality package (Eurydice, 1999). Moreover, tuition fees could help to filter out the less talented students who are taking up a higher education program even though, strictly speaking, they might not possess the competencies required for the program. Thus, fees may help to reduce the adverse selection problem and promote self-selection among students. Thus, there is a strong case for charging tuition fees (Oosterbeek, 1998a), and an equally strong case for continuing subsidization of higher education. However, the question of finding the balance between public resources and private contributions is still unresolved. Barr (2001, p. 194), argues that the way out of this problem is to deregulate the higher education system to a large extent. He proposes to leave decisions on the size of the system — the prices (fees) charged and the volumes (i.e., numbers of students) accepted — to students and higher education providers, while leaving the question on the size of public spending to the government. In his view, if public spending falls short of that necessary to meet the choices of citizens and universities, the difference will have to be made up with private spending. In his words (and emphasis): “the market decides on total spending, the government on public spending” (Barr, 2001, p. 194). However, to prevent potential students from under-investment in higher education, governments should safeguard student access. In other words, the Barr strategy does not merely imply a passive role for the government. Politicians and parliaments will always be worried about the possibility that a fee-based system prices some students out of the market and that students accumulate “disproportionate debt.” Governments therefore, will have a role in offering student support and promoting student access through non-financial means, including the provision of information. How a system of private charges and the accompanying system of student support may be designed is the topic of one of the following sections. However, because many government policies make use of financial 274
Jongbloed: Tuition Fees in Europe and Australasia instrument to increase (or decrease) demand for higher education, we will first of all address the topic of the price elasticity of demand.
TUITION FEES AND STUDENT DEMAND Earlier, we mentioned the tuition fee as one of the policy instruments that might be used by governments to influence the private rate of return to higher education investments. Taking a human capital theory perspective, raising (or introducing) tuition fees can be expected to have a negative influence on the students’ investment (i.e., participation) in higher education. The question is, however, whether students actually react to changes in tuition fees or, in other words, whether the price elasticity of the demand for higher education is significant. To what extent do higher tuition fees harm access, in particular for students from lower socioeconomic groups in society? This question is especially important now that many countries have experienced increases in the contributions students have to make to the cost of their higher education. One (but only one) of the causes of the rise in private contributions is the rise in tuition fees. For the European higher education systems, there are only a limited number of studies that contain insights into the effects of the rising cost of higher education. However, there is growing concern in many countries about the effects of increasing levels of student debt on participation in higher education. Most of the available research on price elasticities originates from the United States, a country in which paying for higher education has a much longer history and thus has a much longer time period over which data have been collected and analyzed. Leslie and Brinkman (1987) provide a meta analysis on student price responses in American higher education, updated in Heller (1997). Their major conclusion, quoted by Vossensteyn and Canton (2001), is that students are responsive to prices and that — ceteris paribus — for every $100 increase in tuition price one would expect the participation rate to drop by about 0.7 percentage-point. Vossensteyn and Canton (2001) state that for an average weighted tuition fee of $3,420 and a national higher education participation rate of 0.33 in 1982/83 (cf. Leslie and Brinkman, 1987), this corresponds to a price elasticity of ⫺0.73. Other authors (Manski and Wise, 1983; McPherson and Schapiro, 1991; Moore et al., 1991; Gladieux and Hauptman, 1995) add that particularly lowincome students are more sensitive to tuition price levels than higher 275
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income students. McPherson and Schapiro (1997, 1998a,b) stress that, though enrolment rates for all racial groups have risen, the gap between the enrolment rates of whites and other racial groups has widened. Heller (1997) also shows this variation in price sensitivity among different racial groups. In addition, Kane (1995) shows that increases in net costs over time are related to decreases in enrolment rates for low-income students in the United States. Contrasting to this, evidence shows that increases in net cost did not inhibit enrolment for more affluent students. However, middle-income students also seem to have reached a price threshold, particularly in the private sector institutions (Breneman, 1994; Campaigne and Hossler, 1998). Based on these findings, McPherson and Schapiro (1997) conclude that policies that call for cross-subsidization among students, such as the high tuition — high aid strategies, make sense from the viewpoint of economic efficiency (although targeted student support by the government would be a better policy instrument). The high tuition — high aid strategy comes down to a situation in which richer students pay a substantial part of the costs of education. This revenue is partly used for providing tuition discounts to poorer students. Notwithstanding this practice, there have been considerable increases in net tuition for low-income students, leading to a growing gap between enrolment rates for high- and low-income students and to an increased concentration of low-income students at the least costly institutions and programs (Duffy and Goldberg, 1998). Lowincome groups have become concentrated in public, low-status community colleges, contributing significantly to the growing stratification evident in the U.S. higher education system. Leslie and Brinkman (1987) address the quandary that participation rates have not gone down in the United States while tuition fees increased. They explain this phenomenon by noting that, over the period of analysis, tuition prices did not increase that much in real terms, and that financial support ameliorated access. In addition they note that demand is known to be affected not only by price but also by the money income of the buyer, by tastes and preferences, and by the value of the good from a consumption or an investment perspective. The McPherson and Schapiro (2000) paper relates to more recent research and takes into account the substantial increase in costs to students of participating in higher education and the trends in student aid that show more money being made available to students in the form of (repayable) loans rather than non-repayable grants. They also focus 276
Jongbloed: Tuition Fees in Europe and Australasia specifically on examining and explaining the seemingly paradoxical situation in the United States that was analyzed by Leslie and Brinkman. The primary cause of the phenomenon, having the highest enrolment figures coinciding with the highest levels of cost, appears to be that the increase in enrolment is not uniform across all groups. While participation is growing for all groups in absolute terms, relative enrolment levels are changing. This is evident in the enrolment trends for both income and ethnic groups and evidence of this is presented in the study of Kane (1995). The econometric analyses by Kane, and McPherson and Schapiro seem to support the conclusion that the “price sensitivity” is concentrated among low-income students. What the U.S. research suggests is that the disincentive effects of higher tuition costs and loan debt is linked to class position, but the relationship between the two is complex. It is not simply the case that low-income students are “debt averse” as is suggested in some literature. This view is not borne out by research data that shows there is little difference in loan take-up rates between social classes once enrolled in higher education. In research carried out for the Department for Education and Employment in Great Britain, Callendar and Kemp (2000) found that levels of borrowing, rather than borrowing per se, were associated with a student’s social class. Those eligible for the highest level of means-tested non-repayable government maintenance grants, that is, students from low-income households, had the highest levels of borrowing. This is a not unexpected finding given their likely familial financial resources. Debt aversion was found among all students, but most frequently among students enrolled for short courses (less than one year), students living at home with their parents, and Asian students (Callendar and Kemp, 2000, p. 79). A report commissioned by the New Zealand (Education and Science Committee, 2001), referring to another British research report (Connor and Dewson, 2001), goes as far as concluding that “although the research literature alludes frequently to incurring debt as a negative factor in decisions to participate, there is little research to suggest that this actually relates specifically to lower social class groups (Connor and Dewson, 2001, p. 15). Debt aversion as an explanation for lower rates of participation would appear to be somewhat out of date” (Education and Science Committee, 2001, p. 57). In addition to some students being debt averse, however, the New Zealand Committee’s report states that students are effectively deterred by the up-front costs of higher education, both in terms of tuition 277
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and living costs. If this is the case, the availability of student loans to fund higher education will not have the effect of encouraging enrolment from low income students. The obstacle for these students to overcome in order to enroll is the cost of tuition and/or living expenses, not merely the prospect of incurring debt (Education and Science Committee, 2001, p. 15). Whether such a subtle conclusion is justified cannot be answered here. More research into student choice and student attitudes towards debt is needed. Recent research from the United Kingdom (Callender, 2003) does indeed provide evidence that those most likely to be deterred by the financial disadvantages of student loans were from the lowest social classes and especially students from the lowest social classes expressed concerns about borrowing, debt, and repayments. However, Connor and Dewson (2001) show that concerns about the ability to afford the cost of study is only one issue in a range of factors that discourage students from entering higher education. The other factors being (1) the uncertainty about the future benefits of higher education, (2) not having enough information about the costs of higher education and the student support system, and (3) uncertainty about the likelihood of being able to earn income during term-time. What this list of issues points to is a stronger and more concerted effort by all parties concerned to communicate more effectively about the present and future costs and benefits of higher education programs. Financial instruments are only one type of policy instruments. For the Netherlands, where government imposes the level and increase in tuition fees, the scarce studies on the price sensitivity of student demand include Kodde and Ritzen (1984), Huijsman et al. (1986), de Jong et al. (1990), and Canton and de Jong (2002). Among other variables, these time series studies try to establish the impact of tuition fees on student enrolment. Oosterbeek and Webbink (1995), using micro-data on secondary school-leavers, find a statistically insignificant effect from tuition fees on student enrollment. Huijsman et al. (1986) report an elasticity with respect to tuition fees of ⫺0.003. This would imply that demand is fairly insensitive to the tuition fee level. de Jong et al. (1990) report that economic variables hardly affect the decision to enroll in an academic program. Bronneman-Helmers and Kuhry (1996) report price elasticities in the range of ⫺0.01 to ⫺0.1. A recent study by Felsö et al. (2000) indicates that students are not likely to change their program choice in cases where tuition fees were either increased or reduced by €454 (almost a third of the present day fee level). Finally, Canton and de Jong (2002) conclude that students are not responsive to tuition fees, but financial support, the 278
Jongbloed: Tuition Fees in Europe and Australasia college premium and the foregone labor market earnings are important in the enrollment decision. All in all, the Dutch evidence typically suggests that students hardly respond to tuition fee changes. This is in contrast to the findings in the U.S. and U.K. studies. However, the Dutch studies suffer from an important drawback, namely that they do not take into account that, over time, governments have compensated the increase in the tuition fee by a raise in the student financial support offered in the form of grants and loans. Fees and student support are policy instruments that are, however, in the hands of the government (i.e., parliament). What little room Dutch universities and HBO institutions do have (from the year 1996 on) to set their own levels for tuition fees is restricted to the charging of fees to part-time students and other students that do not — or no longer (due to long study periods) — qualify for student support. Neither universities nor HBO institutions seem to have experienced enrolment changes as a result of the little use they make of this freedom ( Jongbloed and Koelman, 1999a). The low elasticity of student demand with respect to tuition fees is typically weak and insignificant for the Dutch case. However, this makes sense from the viewpoint of the human capital model, as this direct cost component is very small when considered against the gain in lifetime income associated with an academic degree. Canton and de Jong (2002), however, do show a remarkable result in the sense that they report a positive elasticity of demand with respect to student financial support. This result may be useful in the debate on reform of the student support system. Options for reform recently proposed (CPB and CHEPS, 2001) include the introduction of a student loan scheme with income-contingent repayment rates, along the lines of the HECS and graduate taxes ( Jacobs, 2002). In the next section we will discuss the effects of HECS on student enrolments in Australia.
AUSTRALIA: THE HECS AND ITS EFFECTS ON ACCESS Australia is the fourth country for which research is available on the relationship between student contributions and student participation in higher education. Some of the features of the Australian higher education system and the way it has implemented charges to be paid by the beneficiaries of higher education will also be discussed later on in this chapter. Here, we will only discuss the issue of students’ price responsiveness. For regular (full-time Australian) students, the “price” that is relevant in 279
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this respect is the charge that is levied through the HECS, introduced in 1989 (see Chapman, 1997). HECS is a scheme through which (ex-)students pay for tuition fees. HECS was motivated by the sheer need to attract additional resources for the Australian higher education system in order to allow for further expansion in times of fiscal pressures for the government. Under the HECS system, students contribute approximately a quarter of the average cost of their training program, either by paying up-front (at the point of entry into higher education) or by taking out a loan and deferring repayment (through the tax system) until after graduation. The important condition for the HECS system was that the private contributions should not harm access to higher education, particularly not for people from disadvantaged backgrounds. In particular, the deferred payment option in HECS meant that students who could not or did not want to pay up-front were allowed to pay later (as a graduate). HECS was introduced by Minister John Dawkins as part of a larger package of funding reforms. Despite the strong arguments in favor of introducing fees, parliament and public opinion were very skeptical about it, fearing a worsening of access. However, the “package deal” tactic of the minister that included more public funds for universities did the trick. HECS applies to Australian and New Zealand students in undergraduate programs (bachelor’s degree) and master’s students in so-called master’s by coursework programs. Master’s by research students and Ph.D. students are not part of the HECS regime and fall under the research funding system. All foreign (overseas) students had to pay a cost-covering fee. The level of the HECS rate was determined by the Minister of Education and set to recover about 20 percent of the costs of an average university program. The rate was indexed to the cost of living and rose to 2,450 Australian dollar (A$) in 1996. Table 7.7 shows the level of the HECS charge (1 US$ is about 2 A$). Until 1997, the HECS charge was the same across all subjects and all universities. When paying the charge, the student has a choice of either paying upfront, attracting a discount on the HECS payment, or defer payment until after graduation. The discount on up-front payment was originally 15 percent but was later raised to 25 percent. In 1997, about 29 percent of students chose to pay up-front. In case students choose the deferred payment option, the Commonwealth (i.e., federal) government pays the charge for the students and the student incurs a debt that is repaid via the taxation system. The value of the outstanding loan is adjusted annually with the consumer price index to maintain the real value of the debt. Students that defer payment, therefore, receive an interest subsidy on their debt. The Australian Taxation Office 280
Jongbloed: Tuition Fees in Europe and Australasia Table 7.7: HECS Rates (in A$) for Selected Years 1989
1996
1997
1999
2003
Uniform rate: 1,800
Uniform rate: 2,450
Band 1: 3,300 Band 2: 4,700 Band 3: 5,500
Band 1: 3,409 Band 2: 4,855 Band 3: 5,682
Band 1: 3,680 Band 2: 5,242 Band 3: 6,136
Band
Disciplines
Band 1
Arts, humanities, social studies/ behavioral sciences, education, visual/performing arts, nursing, justice, and legal studies
Band 2
Mathematics, computing, other health sciences, agriculture/ renewable resources, built environment/architecture, sciences, engineering/processing, administration, business, and economics
Band 3
Law, medicine, medical science, dentistry, dental services, veterinary science
Source: Australian Department for Education, Science and Training (DEST).
(ATO) administers the debt and collects repayments. The (at that time) innovative characteristic of HECS is that repayments are income-contingent. Therefore, HECS sometimes is termed a system of income-contingent loans.2 In 1989 the income threshold for repayment was A$27,700 per annum. At this level of income graduates had to pay 2 percent of their taxable income each year, with payments rising to 3 or 4 percent at higher levels of income. These proportions have since been increased. The Australian Higher Education Contribution Scheme is operationally distinct, compared with conventional student loan schemes in most other countries, which offer what are often called “mortgage type” loans. The obvious difference is that in the case of mortgage type loans the repayments do not depend on former students’ incomes. The difference between HECS and subsidized bank loan schemes of other countries is 2
Please note that it is not the loan that is income contingent, but the repayment. This makes the system resemble a graduate tax system. However, the name graduate tax is not correct. In fact, HECS is a system of fees and loans with income contingent repayments.
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that the latter typically offer assistance to a minority of students, with eligibility depending on a range of factors, including family income and age (Chapman and Ryan, 2002, p. 6). HECS has no eligibility criterion — it is offered to all prospective students. The third difference between HECS and other student loans systems is that HECS is only about the repayment of deferred tuition charges and not about the repayment of loans that cover the student’s living expenses. The Australian Higher Education Contribution Scheme brought in significant revenues for the Australian universities. In 2001 students provided over A$800 million in terms of up-front payments and income contingent repayments through the tax system. This is about 20 percent of total recurrent cost of higher education in Australia (Chapman and Ryan, 2002, p. 10). When a new (conservative) government came to power in 1996, HECS was reformed. Charges were increased substantially (by about 40 percent on average) and their structure changed, so that they varied by subject but not by university. Three fee “Bands” were created (see Table 7.7) containing disciplines that attracted low, middle, and high HECS charges. This new charging scheme can be characterized as a hybrid of a teaching cost-related system and an expected future earnings (i.e., private rate of return) system (Chapman, 1997). As such, the most expensive tier not only included expensive courses like medicine, but also law, which is one of the cheapest subjects in terms of teaching costs. Other inexpensive programs, such as economics and business, attracted a medium charge. Turning to the effect of HECS on student participation, we start by mentioning that Parliament imposed a system of monitoring to ensure that access and equity claims were tested annually. Chapman (1997), summarizing a number of studies, claims that “the introduction of HECS does not seem to have had any discernible effects on the socio-economic composition of the student body” so that “there is no evidence of HECS diminishing access to higher education of the disadvantaged” (Chapman, 1997, p. 749). Also the 1997-changes to the HECS have hardly changed the rates of return and, as such, were unlikely to reduce the attractiveness of higher education (Chapman and Salvage, 1997). Andrews (1999) measured changes in the proportion of first year higher education students from relatively poor backgrounds. While the causes for lower participation rates for low socio-economic status (SES) groups are likely to be complex and include social, cultural, and attitudinal factors as well as financial, he points out that for low SES groups HECS appears to have been a minor influence on decision making. Evidence for 282
Jongbloed: Tuition Fees in Europe and Australasia the lack of deterrent effect is seen in the fact that participation rates for low SES groups have not worsened since the introduction of HECS. Overall the number of undergraduates doubled between 1989 and 1998. While numbers may not have dropped, the general expansion and availability of funding to participate does not appear to have improved the socioeconomic composition of the student population either. Vossensteyn and Canton (2001) in their review of studies that have evaluated the effects of HECS, come to the same conclusion, stressing the role of non-financial factors such as values and attitudes in determining student choice. One of the founding fathers of the HECS, Bruce Chapman, presents the following summary of findings from research looking at the effects of HECS on access for the disadvantaged (Chapman and Ryan, 2002, p. 13): (a)
The relatively disadvantaged in Australia were less likely to attend university even when there were no student fees. This provides further support for the view that a no-charge public university system (that is financed by all taxpayers) is regressive, (b) The introduction of HECS was associated with aggregate increases in higher education participation, (c) HECS did not result in decreases in the participation of prospective students from relatively poor families, although the absolute increases were higher for relatively advantaged students, (d) The significant changes to HECS introduced in 1997 were associated with increases in the participation of individuals irrespective of their family wealth.
LESSONS FROM INTERNATIONAL EXPERIENCE: GERMANY Germany is a perfect example of a country where the tradition of free (that is zero tuition fee) higher education has led the higher education system into a state of under-funding and confusion about its future. For the state to finance the rapid expansion of student numbers and accommodate the increased diversity of the higher education system from tax sources alone has proven to be unsustainable in an environment of fiscal restraint. With no private higher education sector to speak of, the system is overwhelmingly public, with (in 2002) 1.8 million students studying at some 90 universities 283
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and 140 other (more vocationally oriented) institutions. For a large number of years the heavily regulated German system has been experiencing a funding crisis, with debates on the topic of funding reforms concentrating on the charging of tuition fees. These debates have been very emotional and ideological (Ziegele, 2001) and so far have not led to funding reforms. Where students and some institutional leaders stress the potentially negative effects of introducing fees, others expect to solve all of higher education’s problems with the imposition of fees. Opponents of fees predict an end to the open access character of German higher education and fear that fee revenue would merely be used as a way to reduce grants to institutions. The proponents of fees stress the fact that tuition free higher education is to be regarded as a subsidy for a group of well-off academics financed by all taxpayers. Apart from pointing at the private rate of return (see Table 7.3), they point at the fact that a family’s socio-economic status plays a very large role in who has access to and attends higher education. 59 percent of students enrolled in higher education came from either an upper- or upper-middle class background whereas only 13 percent of students came from lower class families (Albrecht, 2003). Clearly the challenge is to introduce fees in combination with a larger package of complementary reforms in the field of student support and non-financial instruments aimed at disadvantaged or otherwise underrepresented groups. This could ensure that fees do not harm access and actually could bring in resources that improve access and quality. The Hochschulrahmengesetz, The Framework Act for Higher Education, is the overarching federal law that guides higher education policy in Germany and, among other things, gives each state in the Federal Republic of Germany the responsibility to fund its institutions. Enacted in 1976 and last amended in 1998, the Framework Act provides the federal guidelines which all state-run institutions of higher education must follow. Passage of the Framework Act Amendments in 1998 was seriously delayed over the issue of whether or not a ban on charging tuition fees should be included in the Act. The fight was lost due to the fact that if the prohibition were included, the states would certainly challenge it in the courts. The exclusion of the ban on charging tuition in the Framework Act ultimately gave states the power to assess tuition fees to students. Some states have introduced special, selective forms of tuition fees. Three main models have recently emerged: (1) tuition fees for “slow-lane” students, (2) tuition fees for degree holders, and (3) administrative enrollment fees. 284
Jongbloed: Tuition Fees in Europe and Australasia Students in the “slow-lane” as it is termed are a common problem in German universities. While university students are expected to complete their degree in 4–5 years, the average duration is almost 7 years. “Slowlane” fees would charge students tuition fees each semester that they enrolled after the 13th semester (i.e., the normal duration plus 4 semesters) and thus constitute a punishment for long-term students. Slow-lane fees are meant to act as an incentive for efficient student behavior. In July 2001, a German court upheld the ability for the state of BadenWürttemberg to charge a €550 penalty fee per semester for “slow-lane” students. Baden-Württemberg, the most publicized German state for the introduction of fees, initiated the penalty fee in 1996. The new rule requires students to pay a fee after their 12th semester (depending on the area of study). Preliminary findings have shown that the penalty fee has decreased the number of students studying longer than thirteen semesters by onehalf. The remaining “slow-lane” students are obviously still a problem because students who are holding on to these seats at the university are denying the ability for new students to enter. Baden-Württemberg has not been the only state to introduce fees; the city-state of Berlin passed a law in 1994 to charge students fees and introduced a nine-semester limit for most academic majors. The exception was natural science and engineering majors who were allowed 10 semesters. In January 2003, the government of Nordrhein-Westfalen approved the charging of tuition fees to students after their fourteenth semester, after which time they will be charged €650 per semester. The states of Saarland, Hamburg, and Thüringen, all run by the same political party as BadenWürttemberg also plan to introduce tuition fees to “slow-lane” students (Albrecht, 2003, p. 12). With respect to the second and third fee types we observe the following: in the states of Bavaria and Saxony, the state governments have introduced fees to be paid by students that already hold a degree from a higher education institution. The fee (some €500 in Bavaria and €300 in Saxony) is intended to limit the tuition-free period to a first higher education degree. In a number of other states (e.g., Berlin, Lower Saxony, Brandenburg) governments have implemented fees as a user charge to recover some of the administrative cost of institutions. Common features of these models are their very limited objective and scope. Moreover, they have been implemented without accompanying changes in student support mechanisms. Ziegele (2001) criticizes the fee models and the absence of accompanying support schemes. He puts 285
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forward the recommendation to introduce fees for all students, along with a system of income-contingent loans. The current German fee systems in place do not establish a better functioning higher education market. The slow lane fees do not act as a quasi price as described earlier on in this article. Probably the only positive effect is the dropout of the students who are only enrolled to benefit from certain social advantages of the student status (such as free public transport). While the logic behind the charging of fees for second studies may be acceptable, the effects are minimal. In fact, there may even be an incentive to design courses according to the preferences of the paying students, meaning a disadvantage for the “normal” student whose needs are not backed by payments.
LESSONS FROM INTERNATIONAL EXPERIENCE: THE NETHERLANDS While perhaps not as harsh as in Germany, the students and the higher education institutions in the Netherlands also are experiencing the effects of shortfalls in government funding. As in Germany, current debates address the various options for reforming the tuition fee and student support arrangements as well as the more general mechanisms of public funding for the traditional universities (13 in total) and the universities of professional education (some 50 in total). A prominent feature of the Dutch higher education system is the trend towards cost sharing (Vossensteyn, 2002). While the (public as well as private) institutions and their students are heavily subsidized by the government, there has been a trend of increasing tuition fees, reducing the subsidies to students and their families, and a stronger emphasis on student loans in the student support system. Tuition fees have been a longstanding feature of the Dutch higher education system. The fees are set by the government and are the same across all institutions (universities, offering academic programs, and the so-called HBO institutions offering vocationally oriented programs) and all programs. Initially the level of the fee was moderate, in the period 1945 to 1971 students were paying only €90 a year. After an initial increase to €450 in 1972 and 1973, the level was set at €230 between 1974 and 1980. Since then, tuition fees have gradually increased up to a level of around €1,400 per year. The fee increase outpaced the rate of inflation. 286
Jongbloed: Tuition Fees in Europe and Australasia The student support system underwent several changes. It transformed from a system consisting of family allowances and tax benefits to a system of grants and loans. From 1986 on, the system consists of three components: the basic grant, the supplementary grant, and a student loan. All students receive a basic grant, independent of parental income. The supplementary grant is based on a parental income test. The loans, which are not means-tested and can be taken up on a voluntary basis, bear a marketbased interest rate from 1992 onward. They are of a mortgage-type, meaning that repayment takes place in fixed installments over a fifteen-year period. Repayments do not depend on the income of the (former) student. Loans are not very popular with students; the take-up rate is low and students prefer taking on part-time jobs during their studies. Over the years, the amount of the basic grants (available to all fulltime students) decreased, partly compensated by increases in the supplementary grant. The supplementary means-tested grant also compensated for tuition fee increases. Underlying this was the wish to maintain the open access type character of Dutch higher education, particularly for students from disadvantaged backgrounds. Supplementary grants are available to about 25–30 percent of all full-time students. To stress cost sharing, the duration of the grant was reduced. This had a large impact on students because (like in Germany) most students exceed the nominal duration of the program. Average times to degree declined, also because of other changes in the student and institutional support mechanisms. The role of loans gained in importance. The maximum amounts were increased, also partly to compensate increases in tuition fees. Interestingly, from 1996 on, both the basic and the supplementary grants are given to the student as a loan (hence the name performance-related grant), which is converted to a grant if students meet necessary performance criteria, the most important being that they obtain their qualification within a specified duration. Earlier (in 1993) performance requirements had already been attached to the grants, but since 1996 they are felt to be more intense. The reason to sketch the tuition fee system as well as the student support system is that they are connected in the sense that Parliament has compensated the increases in fees by means of adjusting grants and loans. Moreover, both are regarded as instruments in achieving the aim of efficient study behavior among the student population and both have (at least in theory and in public opinion) an impact on the decision to participate in higher education. 287
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In 1999, the Dutch Ministry of Finance commissioned a research institute to look into the reactions and potential effects of a system of deregulated and differential fees, set by the higher education institutions themselves ( Jongbloed and Koelman, 1999b). The effects on programmatic diversity were to be particularly addressed. The question was, whether such a system could be effectively combined with a system of student loans offered by private banks. Instead of the conventional approach of governments backing the loans, the idea was that the loans were to be guaranteed by higher education institutions, giving them an incentive to create successful graduates. From an expert group discussion that was organized on the basis of two scenarios the following outcomes were generated. Institutional leaders (i.e., university presidents), when given the freedom to set their own fees, will make relatively little use of this. They will set differential fees mainly to reflect differences in program cost, especially the mode of delivery, and the demand expressed by the market (i.e., students and employers). The former relates to the way in which the program is offered to the students (intensive versus less-intensive modules, reflecting the institution’s educational profile and the students’ wishes to receive a specific type of instruction). The latter relates to the question of what the market can bear. In all of this, the institutional leaders observed that student demand in the Netherlands was relatively price-inelastic. The administrators also mentioned they would use the fees to compensate for the cutbacks in government allocations. Where students were very skeptical about was the proposal of differentiated tuition fees; the private banks expressed a willingness to participate in such a system, provided that the scale of the operation (the number of loans to be handed out, the number of institutions participating) was sufficiently large. The banks did not see a lot of reason to have a guarantee on the loan and the institutional leaders found the guarantee totally unacceptable. Some of the difficulties that were mentioned in the focus group discussions were that the higher education cost structure is very obscure, due to capital costs and cross-subsidies, and that a relationship between tuition fees and cost could not be well grounded. Other outcomes of the experiment also were mentioned in a research report compiled by a group of officials from five Dutch ministries, including the Ministry of Education, the Ministry of Economic Affairs, and the Ministry of Finance (IBO, 2003). The group was assisted by two academics acting as experts. This IBO (Interdepartmental Research Group) report also addresses the topic of tuition fee deregulation and comes up with 288
Jongbloed: Tuition Fees in Europe and Australasia a number of recommendations for improving the tuition fee and student support system. The report investigates the possibilities and options for introducing flexible fees in the Netherlands. Before presenting the report’s conclusions, it is good to remember three things: ●
●
●
The Netherlands is emerging from a situation with (still very) modest uniform fees for all programs and all institutions. Until August 2002, separate bachelor’s and master’s tracks did not exist in the Netherlands; all programs were leading to a type of master’s degree. After 2002 bachelor’s and master’s programs are in place and the debate about the extent to which each should be funded respectively by the taxpayer and the student has begun only recently. For fear of creating elite programs, the previous Parliament scrapped initiatives by the then minister of Education to allow institutions to charge more for specific high quality programs.
The IBO group proposed — in a unanimous decision — to the Cabinet a choice of three options: ●
●
●
Allow fee differentiation up to a maximum for high quality master’s programs Allow fee differentiation (up to a maximum) for all (publicly funded) master’s programs Allow fee differentiation (up to a maximum) for all bachelor’s and master’s programs.
Implicitly, the IBO group suggested implementing the first option (the research masters and some professional masters), then broaden the system (option 2) to all masters, and finally (in option 3) extend it to all undergraduate and postgraduate programs. It was left to the (recent — 2003 — installed) Cabinet to decide whether it wanted to go forward with any of the options. The signs are that this time there is a bigger chance of introducing flexible fees, especially because members of Parliament expect that fees will not just rise, but also decline for socially relevant programs in areas like nurse training and teacher training. The chances of implementing fees will heavily depend on the accommodating policies (student support, changes in the funding system, information supply, monitoring of events). A “package deal” (see the HECS introduction) will probably be necessary. 289
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The arguments for fee differentiation mentioned in the IBO report were that it would stimulate the emergence of a differentiated system of program supply, allowing more choices for students, and a market that is functioning better (restoring the price signal). However, accommodating policies were also deemed necessary, especially with respect to: ●
●
●
the student support system (a review is presently being carried out by another committee); the funding system (more differentiation in funding rates — not like the present two/three categories, but more closely reflecting costs and externalities); the system of providing ‘consumer’ information (quality, labor market effects, etc.).
One of the recommendations was also to make a distinction between tuition cost and living expenses in the student support system. This would send out a clear signal to students about the purposes of the support budget and to the higher education community in general about what it is the government actually subsidizes.
LESSONS FROM INTERNATIONAL EXPERIENCE: THE UNITED KINGDOM As in the Netherlands, the issue of differential fees, set by the higher education institutions themselves, was also a central element in the recent proposals presented in a 2003 White Paper by the British government (Department for Education and Skills/DFES, 2003). Earlier in this article it was mentioned that tuition fees have been in place in the United Kingdom for quite some time, but until 1997/98 they were paid by the government authorities on behalf of the (full-time) student. Partly as a result of the Dearing review (National Committee of Inquiry into Higher Education, 1997), full-time undergraduate students were asked to pay a fee, set by the government and to be paid according to parental income. Until 1998/99 the students’ living expenses were covered by a mixture of a tax-funded grant, a loan with mortgage-type repayments, and (voluntary) parental contributions. The grant was means-tested and dependent on whether the student was independent or lived with his/her parents. Loans were available for all. Since 1998/99, there has been an up-front fee, irrespective of subject or university; there is no loan to cover the fee; living expenses are met by 290
Jongbloed: Tuition Fees in Europe and Australasia a mixture of parental contributions and an ICL. The ICL is a loan with repayments calculated as a percentage of the borrower’s subsequent earnings, collected alongside the income tax. Similar to Australia, the ICL attracts no real interest fee. Student grants were more or less abolished (exceptions are for students in hardship situations). Students in postgraduate programs cannot receive student support and, on top of that, have to pay a tuition fee that is set by the institution itself (see Table 7.2). Students in research master’s or Ph.D. programs, though, can apply for grant support (scholarships) from research councils. The government’s proposals, released in its White Paper (DFES, 2003) contain the following proposals: ●
●
● ●
from 2006 universities will be free to set fees between £0 and £3,000; the system of income-contingent loans will continue in its current form to cover living costs but will extend to cover all fees, that is, it will be a system of deferred charges; grants for poor students will be restored; student numbers will rise, increasing participation from 43 to 50 percent.
With respect to the last element, it is important to note that the government (in fact, the Funding Council, an intermediate body) only funds a restricted number of students in each university or college. In this sense, the British system is centrally planned, comparable to the Australian system. The rationale for the White Paper, as in the two countries mentioned in the previous sections of this article, lies in concerns about the quality of the higher education system (the fear of losing out to other national systems that lure away students and academics), the size of the system (the still comparatively low participation rate in the United Kingdom) and, the level of resources per student (real funding per student has fallen over the years). Recently (January 2004) the government’s reform package was passed by a narrow majority in the House of Commons after heated debates that in particular focused on the potential effects of the deregulated fees on access. In Parliament the Tories launched a proposal to abolish all tuition charges and to keep participation at its current levels. The analytical arguments in favor of tuition fees have been presented elsewhere in this article. Barr (2003) forcefully supports the government proposals and argues that flexible fees are necessary and desirable for addressing a diverse, mass higher education system. Today, he argues, the necessary variation in funding is much 291
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greater than formerly and the problem is now too complex for a central planner to have the sole power of decision about how resources should be divided between institutions and what the funding levels for different institutions and programs should be. Thus, institutions should have the freedom to set their own fee levels. He does make clear that that freedom could be constrained and he is not against a fee cap. However, the cap should not be placed at too low a level. Fees could rise, freeing up the necessary private resources to halt the quality decline and to improve access for the disadvantaged. Without higher fees, he argues, quality will continue to be eroded and, given flat fees, quality would erod most at the best institutions. Therefore, as he continues, flexible fees benefit all tertiary institutions, not just the best ones.
LESSONS FROM INTERNATIONAL EXPERIENCE: AUSTRALIA Earlier, we touched upon Australia when we gave a description and assessment of the Australian student charging system and its effects on participation. Therefore we now can be brief on most of the fee-related aspects of the system. While HECS (described above) was most probably the right system of freeing up additional resources for a much-needed expansion, today’s differentiated HECS system has come under substantial criticism. Again, the reason is that government funding per student has gone down, quality is in danger of declining, and increased student demand cannot be accommodated by the public system of universities. The HECS reforms in 1996 that introduced three fee bands and higher fee levels, like the recent UK White Paper proposals, did not mark the end of central planning. In particular, the federal government continued to set the levels of the fees as well as the numbers of (HECS-liable) students it was prepared to fund at each university. As part of the reforms in the second half of the 1990s, the federal government allowed institutions that had filled their quotas of publicly funded students to recruit (at maximum) an additional 25 percent of students as “domestic full fee paying undergraduates.” The institutions were allowed to set the fee levels for this category of students, but were not receiving the full funding per student as for the other (HECS-liable) students. The only public grant universities were receiving for these students was a so-called “marginal funding for 292
Jongbloed: Tuition Fees in Europe and Australasia over-enrolled places” (equal to 75 percent of the Band 1 HECS rate: A$2,700 in 1998). The fees charged were full-cost fees. In 2002, the number of fullfee paying Australian undergraduates was 6,500 and in 2003 their number had risen to 9,300 (2 percent of the total number of 531,000 students). The full fee paying students did not qualify for HECS loans and therefore constituted a separate category of clients for the institutions, next to the students that studied in a government-funded and HECS-liable “slot”. Clearly, this dual structure is distortionary and inequitable, allowing less bright students from wealthy families to get into top universities on the basis of wealth rather than ability (Barr, 2001, p. 210). Although an earlier review committee had produced an assessment of the Australian funding system and proposed a more demand-driven funding system (the West Committee), the present (2003) government organized a new review in 2002. The federal ministry of education produced a discussion paper (Higher Education at the Crossroads) and invited public comment. In May 2003 the minister of Education, Science and Training released his plan (Nelson, 2003). Part of the plan is to make a kind of HECS available for students in recognized private higher education institutions as well as students who are paying full-cost fees in public universities. The system is called FEE-HELP (Higher Education Loan Programme) and also intends to cover the system of loans that was introduced (in 2001) to help postgraduate students pay for their fees. The latter system (PELS: Postgraduate Education Loan Scheme) was targeted at students in public universities who were studying for a master’s by coursework program (a taught — that is, non-research — master’s degree) and enabled students to take up an interest-free loan to cover the postgraduate fee, the level of which was set by the university itself. PELS was introduced because postgraduate students did not qualify for HECSloans (a situation comparable to the United Kingdom). Unlike HECS, PELS did not provide for a 25 percent discount on the fee rate should a student wish to pay up-front. The introduction of PELS led to a rise in the number of coursework master’s students and a rise in the loans taken up. In the recent (2003) plans of the minister, HECS and PELS are modified. The new system, called HECS-HELP, however, is based on the same principles as HECS. However, the following changes are proposed, apart from the changes already mentioned: ●
universities can set the fees for their undergraduate students up to a maximum that differs according to the ‘Band’ in which the 293
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●
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program is categorized. HECS-HELP has the same categories as the differentiated HECS system; the income threshold that sets off the debt repayments is increased and the repayment rates are slightly increased; the discount of 25 percent on the up-front payment of fees is lowered to 20 percent of the fee rate; the FEE-HELP loan (for full-cost fee paying students in public and private institutions) attracts an interest rate that is 3.5 percent above the rate of inflation; PELS is replaced by FEE-HELP; learning entitlements (i.e., a right to study) for a maximum of 5 years in a government-supported place will be introduced.
The maximum levels to which universities can set their student contributions from the year 2005 on are as follows: ● ● ●
Band 1 maximum ⫽ A$5,010 Band 2 maximum ⫽ A$7,137 Band 3 maximum ⫽ A$8,355
The maximum is set at a level that lies 30 percent above projected HECS rates. As a last comment on the Australian system we mention that the feature of allowing institutions to recruit two types of students, viz. full-fee paying students and students paying capped fees will stay in place. Finally, we stress the fact that HECS-HELP and FEE-HELP do not cover the students’ living expenses. Youth Allowances and Austudy grants are available for undergraduate students.
LESSONS FROM INTERNATIONAL EXPERIENCE: NEW ZEALAND The New Zealand (NZ) experience in terms of fee setting is interesting, because fee-setting was at the discretion of the providers over the period of 1992–2000. Furthermore, fees and students’ living expenses are covered by loans. The loans are fully income-contingent, with repayments collected by the tax authorities and loans carrying a market or near-market interest rate. In the years following the introduction (in 1992) of fee deregulation, the average tuition subsidy per student paid by the government to the
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Jongbloed: Tuition Fees in Europe and Australasia institutions decreased significantly. The average fee over that period increased (approximately) by the decrease in the level of tuition subsidy, after inflation was taken into account. Thus there is a close link between levels of public tuition subsidy and the student fees charged by the institutions. The government was thus able to exercise indirect influence over fee setting by varying the levels of public funding. An important corollary of this ability however is that, unless government funding is increased it is likely that student fees will continue to increase. Fee-setting practices are driven by both supply and demand factors. The strategies for fee-setting in New Zealand vary between providers. Some providers appear to have taken a relatively simple approach wherein fees represent the difference between the cost of delivery and government subsidies. Most providers have taken more complex approaches to fee setting and these have resulted in commensurably complex fee structures (TEAC, 2001). In some cases relatively low fees have been set (at times discounted below average cost) in areas where a provider faces direct competition or is attempting to attract a greater share of available students in a particular program. Some providers offer free courses to attract more students, and one provider basically offered all of its courses free (to utilize the economies of scale implicit in higher education). Provider behavior in terms of fee-setting was such that providers were very concerned about the potential loss of students (knowing that the vast majority of funding was paid on a per student basis), and providers tended to be very aware of what other providers were doing in terms of fees. Thus the incentive to keep fees low was strong. In other cases it appears that providers may have set fees at a level much higher than course costs would indicate — because of high demand for the course, price inelasticities, or a lack of competition. In the latter part of the period 1992–2000, providers were tending to be more sophisticated in terms of their fee-setting behavior. One could witness more differentiation in the market. There was some evidence of higher priced providers emerging in the market, and there certainly were some higher priced courses (e.g., MBAs where the fee was very high by New Zealand standards — reflecting demand for the courses and the fact that often employers paid the fee, not the student, etc). One interesting feature is that providers tended to cross-subsidize internally from their so-called “cash cows” to maintain relatively low fees
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in less popular courses. The areas where providers tended to make money were often commerce and business, where the number of students enrolling was high. This was a fairly consistent pattern; providers tended to want to protect their offerings in less popular areas (and were trying very hard to attract as many students as possible in these areas). A further feature is that it is clear that the price elasticities were not high — the evidence is that students were making study choice decisions on the basis of likely labor market outcomes rather than price of study. There was a high level of concern amongst the general public with increases in student debt, and a major element of this was the increase in fees over the 1990s. This may be due primarily to the decrease in the per student tuition subsidies, and not the fact that fee setting was deregulated per se. The decrease in per student tuition subsidies of course allowed the large increase in participation in higher education that New Zealand enjoyed over the 1990s, within acceptable fiscal limits for successive governments. From 2000 on, the government was committed very much to stabilizing fees and ensuring that the cost of tuition to students did not significantly rise. The present government has stabilized fees by linking per student funding (“tuition subsidies,” as they are known in New Zealand) to the freezing of tuition fees. Reforms in 2000 increased the subsidy on interest rates charged on student debt. New plans, recently revealed, show that New Zealand is moving closer towards the Australian system, with the government setting the maximum fee levels up to which institutions may set their fees.
FLEXIBLE FEES: CAN THEY WORK? The international experience set out in the previous section shows that in many states the higher education providers and their students are experiencing the effects of prolonged periods of under-funding by their national governments. In light of this funding crisis, many proposals for reform have been put forward to remedy deficiencies and prepare the sector for the challenges ahead. In the financing options under discussion, student contributions are becoming an increasingly important issue. In countries like the United Kingdom, Germany, the Netherlands and Australia, there have been heated debates about the need to promote greater institutional autonomy and flexibility with respect to student charges. 296
Jongbloed: Tuition Fees in Europe and Australasia Allowing institutions — not governments — to set the levels of the tuition fees has been put forward as an option in the countries just mentioned. It was suggested that price discretion is an instrument that will enable institutions to tap into new sources of revenue, allowing tuition fees to bear a closer relationship to the different costs of providing different subjects, while allowing fees to reflect the different financial returns that students (once graduated) get depending on the institution attended and subject studied. Recapitulating, the effects of flexible fees can be grouped into two broad categories of expectations. The main positive effects are: ● ● ● ●
●
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increased income from students, increased diversity in program supply and delivery, increased competition between providers, enhanced decision-making by students on the basis of pricequality trade-off, a closer relationship between the student and the higher education institution, the institution’s prices increasingly reflect its circumstances, goals, and opportunities.
Some of the negative effects are: ●
●
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student choices are increasingly driven by financial motives at the expense of intrinsic motivation, an increased focus by providers on profitable programs at the expense of unpopular ones, geography and history give some institutions a commercial advantage over others, students (especially those living in border regions) will be attracted to providers abroad that charge less than domestic ones, the increased charge burden may deter students from disadvantaged backgrounds to participate in HE or from enrolling in the institution of their first choice.
For a market-based system of flexible fees to work successfully it may be argued that some conditions need to be met in order that the positive effects become real. To combat the potential negative effects on variety and access, while strengthening the desired outcomes, some critical considerations will need to be addressed. It may be argued that (at least) 297
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six related critical conditions need to be fulfilled. These relate to: 1. 2. 3. 4.
the student support system, the availability and adequacy of information, the government’s communication strategy, the presence of government-imposed capacity limits on funded places, 5. the relationship between public funding rates and program costs, 6. the relationship between public funding and student numbers. Since some of the students would not have the resources to pay the fees, they would need financial assistance of some sort — either from their parents, the government, their employer, or other sources. The first condition for differentiated fees to work, therefore, is the existence of a well-designed student support system. Thus prospective students without sufficient financial resources will be able to enroll in a degree program. A student support system gives students access to government loans or guaranteed (i.e., government-backed) bank loans. Much has been written already about the design of the student support system (by authors like Bruce Chapman and Nicholas Barr), and the key lesson seems to be that the best way for students to pay is via a deferred payment system such as the Australian HECS system. Income-contingent payment gives students (or rather graduates) the possibility to defer payment till after graduation. Levies are in proportion to a graduate’s income (above some income-threshold), and are collected by tax authorities. The second condition refers to the availability of recent information that informs students about the quality of education, and the likely outcomes from their education. The information should relate to the quality of different degrees at different institutions. This must include outcome measures, such as subsequent employment rates, salaries, etc. The availability of information might be considered a “conditio sine qua no” for any education system, but it is likely to be more important in a fee-deregulated environment. The third criterion points at the government’s (or department’s) “public relations strategy.” Before it can consider introducing flexible fees, the government needs to communicate effectively to students and providers the rationale for a differentiated fees system and the changes to the various ingredients of the accompanying student support and institutional support system (see items 4 and 5, below). A lot of the public resistance towards fee deregulation in countries like the Netherlands, the 298
Jongbloed: Tuition Fees in Europe and Australasia United Kingdom, New Zealand, and Australia has been because people (including members of Parliament) focus on the headline (e.g., €10,000), without realizing that income-contingent loan repayments are — from the students’ point of view — little different from income tax. The fourth criterion is that there should not be limits on the numbers of students who will be funded at particular providers. Basically, if there is fee-setting autonomy, the risk should be in place that providers will lose students (and income) if the fee rise is unacceptably high. If there are limits on the number of funded places at each provider, providers do not experience this risk, and there will be a natural tendency for providers to increase their costs when they come under pressure from whatever cost drivers they face. This does not mean that governments cannot place limits on the total number of places that they fund. Governments can still choose to fund only a certain number of places, so long as they do not limit the number of funded places at particular providers. The fifth criterion is that there should be some relation between cost of provision and level of underpinning subsidy. This allows some room for providers to cross-subsidize, but if there is too much difference between cost of provision and subsidy differentials then the incentive not to crosssubsidize would be high, thus endangering less popular areas, and also endangering provision in areas where the underpinning subsidy is much lower (relative to other disciplines or levels of study) than the cost of provision. The sixth criterion is that a reasonable amount of payment to providers should be based on a per student basis. The consequences of losing students because of high fee levels is high if the bulk of the money being paid to providers is paid on a per student basis. This adds to the incentives to keep fees down. In addition to items 5 and 6 it can be mentioned that, if (a) a government thinks it is important that subjects like classics, music, drama, etc. are taught and (b) universities find it hard to support such subjects, then it is open to government to subsidize (i) particular subjects and/or (ii) particular institutions and/or (iii) particular students. This suggests that flexible fees can only work successfully if governments — in agreement with other players — implement reforms in many areas at the same time. Private charges, funding mechanisms, student support, information supply and public relations all need to be addressed. Neglecting one of these issues is likely to decrease the chances of a successful attainment of goals. The New Zealand case illustrates the 299
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problems of rapid deregulation. Barr (2001, p. 211) has termed it a “big bang” introduction. This presents the danger that fees and student indebtedness could rise sharply, without giving people the time to adjust to the new arrangements.
CONCLUSIONS This chapter has looked at student contributions and especially tuition fees. Fees were placed in the larger spectrum of the costs and benefits of investing in human capital. As such, the human capital theory and the screening theory were discussed. Fees were also examined by comparing them to market prices paid for commercial products on competitive markets. Looking at the empirical evidence on the private and social returns to investment in higher education and the international evidence presented in the form of five case study sections discussing fee policies in Europe and Australasia, one can arrive at the following conclusions with respect to the financing of higher education from the public and — in keeping with the topic of this article — the private purse. The most important conclusion is that a private contribution, in addition to the income foregone by students, appears justified. Efficiency as well as equity arguments have been put forward to explain this, the arguments revolving around the labor market effects and the externality effects of higher education investment. This does not mean that higher education should be fully funded by the private purse, but it does mean that funding should be a shared responsibility of the student (or rather, the graduate) and the taxpayer. From earlier sections in this chapter it will be clear that the nature and size of the non-financial benefits to higher education investments is still largely unknown and the subject of ongoing research in higher education. It was argued that higher education should not be free, but it should be free at the point of entry. This relates to our second conclusion, which is the answer to the question — if there should be a charge, how should it be paid? The answer is that the best way to pay for this charge is through income contingency — that is, wait for students to graduate and then have them pay in proportion to their earnings. There should be a loan facility to make this possible and up-front payment of fees should be eliminated. The private bank sector or the government might provide loans, but without 300
Jongbloed: Tuition Fees in Europe and Australasia governments guaranteeing the repayment of the debt in case of default, bank loans will not be provided. Most loan systems, therefore, must be government administered, also for reasons of minimizing transaction costs. The Australian and New Zealand cases demonstrated the success of such “study now, pay later” schemes. However, attractive as they may seem, one should not forget that the design of loan schemes (as reflected in the arrangements for eligibility, interest rates, repayment, etc.) is crucially important and further research on this matter is needed. Loans, however, are only one way to cover (part of the) college costs, and college costs consist not just of tuition fees. Recent research carried out by Ma (2003) looks into the effects of arrangements that allow students and their parents to save in advance for college expenses through Education Savings Accounts. Dedicated savings incentives, however, are rarely used in Europe and — like tax incentives — their potential for stimulating human capital investment remains unknown. The issue of access provides another rationale for governments to intervene and provide student support. It is a fact that students from low socio economic status groups are underrepresented in higher education. Research shows that they are both price- and debt-averse and this impacts their human capital decisions. This justifies targeted government policies aimed at providing grants, scholarships, soft loans, and tax facilities. However, it also calls for action on non-financial areas, such as providing information, changing attitudes, offering learning facilities, adjusting curricula, addressing parents, etc. While policy action is called for on areas like these, again the effects are still largely unknown. While it may be argued that an important policy goal is to encourage students to go to college, it may be equally important to affect the student’s decision about which college he/she attends (university, higher vocational education, community college, etc.) or to affect the timing and type of attendance (full-time, part-time, early or later on in life). As Hoxby (2003) argues, it is not college attendance that is interesting, but college choices. The appropriate amount of the private contribution is difficult to determine and is dependent upon finding an appropriate balance between public and private financing, with the level of public financing necessarily left to politicians as representatives of all stakeholders in society. The level of the tuition fee, being part of the private investment in higher education, is often set by government. This is the case in Europe and Australia. Our review of the international evidence suggests that, from efficiency and equity points of view, the decision on fees should be left to the 301
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institutions. A deregulated, thereby differentiated fee structure, was argued to be the only feasible long-term outcome of debates on the level of the tuition fee. However, if institutions set the level of the fees, the immediate question that arises is how they determine the appropriate level. While this is largely a matter of how the institutional management perceives the supply and demand in the market for graduates (cf. the New Zealand case) and its reputation in the market, it does make our attention turn to (potential) students and the information they use to guide their decisions on human capital investments. If fees differ across institutions, individuals will need access to reliable information on the returns they can secure from studying various subjects at different institutions. While this chapter has shown the average private returns to be high, it should be noted that averages often hide wide disparities across fields, institutions and — even — students. However, while research on the rates of return to additional years of education exist, evidence on the returns to specific qualifications is scarce and largely non-existent outside Anglo-Saxon countries. Recent research by Conlon and Chevalier for the United Kingdom shows that there are increasing returns associated with increasing qualification attainment (Chevalier et al., 2002; Chevalier and Conlon, 2003). However, the returns associated with degree level qualifications vary substantially according to the type of institution attended, the subject studied and the social class of the individual in possession of the qualification. The high degrees of variance in returns to degrees implies that the risk/reward equation differs considerably for different students. Again, this underlines the importance of research on the determinants of student (or college) choice. It also has important implications for policy and practice aimed at influencing decision-making by students. While differentiated fees may be desirable, a system of fees set by the institutions themselves can only work if a number of important conditions are met. If not, the market will fail and a great deal of harm may be done. The necessary conditions for an efficient higher education market have been presented in this article and relate not just to the design of the fees system, but also to student support and the system through which government funds the providers of higher education. Higher education researchers will have to help identify which conditions are crucial and how they should be shaped in order to contribute to the desired policy objectives. This calls for more evaluation research into the effects of the various types of intervention instruments used by governments and it calls for interdisciplinary research on the drivers of student choice. Policies will 302
Jongbloed: Tuition Fees in Europe and Australasia need to be informed by research that identifies the incentives that shape behavior. And, quoting a recent report (CPB and CHEPS, 2001) that analyzed a number of case studies in the area of higher education policy, getting all the incentives right is the challenge that lies ahead.
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Jongbloed: Tuition Fees in Europe and Australasia M. Bateman (eds.), Condemning Students to Debt, College Loans and Public Policy. New York: Teachers College Press. Canton, E. (2001). Should tuition fees be increased? CPB Report 2001 No. 2, 50–56. Canton, E., and de Jong, F. (2002). The demand for higher education in the Netherlands, 1950–1999. CPB Discussion Paper. The Hague: CPB Netherlands Bureau for Economic Policy Analysis. Chapman, B. (1996). The rationale for the Higher Education Contribution Scheme. Australian Universities’ Review 1: 43–50. Chapman, B. (1997). Conceptual issues and the Australian experiences with income contingent charges for Higher Education. Economic Journal 107: 738–751. Chapman, B. (2001). The higher education financing debate: Returns to educational investments, current pressures and some suggestions for reform. Paper presented to the National Press Club, October 16, 2001. Chapman, B. (2002). A Submission on Financing Issues to the Department of Education, Science and Training Inquiry into Higher Education Reform. (Submission 317.) Canberra: Australian National University. Chapman, B.J., and Salvage, T. (1997). Changes in the costs for Australian higher education students from the 1996/97 budget. In J. Sharpman and G. Harman (eds.), Australia’s Future Universities. Armidale: University of New England Press. Chapman, B., and Ryan, C. (2002). Income-contingent financing of student charges for higher education: Assessing the Australian innovation. Centre for Economic Policy Analysis Discussion Paper No. 449. Canberra: Australian National University. Chevalier, A., and Conlon, G. (2003). Does it pay to attend a prestigious university? London: Centre for the Economics of Education, London School of Economics. Also available on-line at: http://cee.lse.ac.uk/publications.htm. Chevalier, A., Conlon, G., Galindo-Rueda, F., and McNally, S. (2002). The Returns to Higher Education Teaching. London: Centre for the Economics of Education, London School of Economics. Also available on-line at: http://cee.lse.ac.uk/publications.htm. Connor, H., and Dewson, S. (2001). Social class and higher education: Issues affecting decisions on participation by lower social class groups. Institute for Employment Studies/Department for Education and Employment. Research Report No. RR267. CPB and CHEPS (2001). Higher Education Reform: Getting the Incentives Right. The Hague: SDU. Also available on-line at: http://www.cpb.nl/pub/bijzonder/29. Department for Education and Skills (2003). The future of higher education. Cm 5735. London: The Stationery Office. Also available on-line at: http://www.dfes.gov.uk/highereducation/ hestrategy/. Duffy, E.A., and Goldberg, I. (1998). Crafting a Class: College Admissions and Financial Aid, 1955–1994. Princeton: Princeton University Press. Dynarski, S.M. (1999). Does aid matter? Measuring the effect of student aid on college attendance and completion. National Bureau of Economic Research Working Paper, No. 7422. Education and Science Committee of the New Zealand Parliament (2001). Inquiry into Student Fees, Loans, Allowances and the Overall Resourcing of Tertiary Education. Wellington: House of Representatives. Available at: http://www.clerk.parliament.govt.nz/content/28/i2c.pdf. Eurydice/European Commission (1999). Key Topics in Education, Volume I: Financial Support for Students in Higher Education in Europe. Trends and Debates. Luxembourg: Office for Official Publications of the European Communities.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Fane, G. (1975). Education and the managerial efficiency of farmers. Review of Economics and Statistics 57: 452–461. Felsö, F., van Leeuwen, M., and Zijl, M. (2000). Verkenning van Stimulansen voor het Keuzegedrag van Leerlingen en Studenten. SEO Report No. 545. Amsterdam: Stichting voor Economisch Onderzoek. Gemmell, N. (1997). Externalities to higher education: A review of the new growth literature, Report 8. In The National Committee of Inquiry into Higher Education, Higher Education in the Learning Society. London: HMSO. Also available on-line at: http://www.leeds.ac.uk/ncihe/. Gladieux, L.E., and Hauptman, A.M. (1995). The College Aid Quandary: Access, Quality, and the Federal Role. Washington D.C.: The Brookings Institution. Glennerster, H. (1997). Education. In H. Glennerster and J. Hills (eds.), The state of welfare: The Economics of Social Spending. Oxford: Oxford University Press. Goldin, C., and Margo, R.A. (1992). The great compression: the wage structure in the United States at mid-century. Quarterly Journal of Economics 107: 135–164. Groot, W., and Oosterbeek, H. (1994). Earnings effects of different components of schooling; Human capital versus screening. Review of Economics and Statistics 76: 317–321. Hanushek, E.A.., and Kimko, D.D. (2000). Schooling, labor force quality, and the growth of nations. American Economic Review 90: 1184–1208. Hartog, J. (1983). To graduate or not. Does it matter? Economics Letters 12: 193–199. Hartog, J., Odink, J., and Smits, J. (1999). Private returns to education in the Netherlands: A review of the literature. In R. Asplund and P.T. Pereira (eds.), Returns to Human Capital in Europe: A Literature Review. ETLA: Helsinki. Haveman, R.H., and Wolfe, B. (1984). Schooling and economic well-being: the role of nonmarket effects. Journal of Human Resources 19(3): 377–407. Heller, D.E. (1997). Student price response in higher education, an update to Leslie and Brinkman. Journal of Higher Education 68(6): 624–659. Hoxby, C.M. (2004). College Choices: The Economics of Where to Go, When to Go, and How to Pay for It. Chicago: University of Chicago Press. Huijsman, R., Kloek, T., Kodde, D.A., and Ritzen, J.M.M. (1986). An empirical analysis of college enrollment in the Netherlands. De Economist 134(2): 181–190. Huffman, W.E. (1974). Decision making: The role of education. The American Journal of Agricultural Economics 56(1): 85–97. IBO (Interdepartmental Policy Research Committee) (2003). IBO Collegegelddifferentiatie. The Hague: Netherlands Ministry of Finance. Jacobs, B. (2002). An investigation of education finance reform: Graduate taxes and income contingent loans in the Netherlands. CPB Discussion Paper, No. 9. The Hague: CPB Netherlands Bureau for Economic Policy Analysis. Johnes, G. (1993). The Economics of Education. London: MacMillan. Johnstone, D.B. (1998). Tuition fees. In Clark, B.R., Husén, T., Postlethwaite, N. and Neave, G. (eds.), Education: The Complete Encyclopedia. Oxford: Elsevier Science (CD ROM). Jong, U. de, Oosterbeek, H., Roeleveld, J., Teulings, C.N., and Webbink, H.D. (1990). Wel of Niet Verder Studeren? Beleidsgerichte studies hoger onderwijs en wetenschappelijk onderzoek, No. 26. Zoetermeer: Ministry of Education, Culture and Science. Jongbloed, B., and Koelman, J. (1999a). Het retributiebeleid van instellingen voor hoger onderwijs. Beleidsgerichte studies hoger onderwijs en wetenschappelijk onderzoek, No. 60. Zoetermeer: Ministry of Education, Culture and Science.
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Jongbloed: Tuition Fees in Europe and Australasia Jongbloed, B., and Koelman, J. (1999b). Collegegelden en Studieleningen. Een Scenariostudie naar meer Differentiatie in het Nederlandse Hoger Onderwijs. Utrecht: Lemma. Jongbloed, B., and Vossensteyn, H. (2002). Financiering masters: argumenten en arrangementen. Enschede: Center for Higher Education Policy Studies. Kane, T.J. (1995). Rising public college tuition and college entry: How well do public subsidies promote access to college? National Bureau of Economic Research Working Paper No. 5164. Kodde, D.A., and Ritzen, J.M.M. (1984). Integrating investment and consumption motives in a neoclassical model of demand for education. Kyklos 37: 598–608. Leslie, L.L., and Brinkman, P.T. (1987). Student price response in higher education. Journal of Higher Education 58(2): 181–204. Lucas, R. (1988). On the mechanics of economic development. Journal of Monetary Economics 22: 3–42. Ma, J. (2003). Education saving incentives and household saving: Evidence from the 2000 TIAACREF survey of participant finances. In C.M. Hoxby (ed.), College choices: The Economics of Which College, When College, and How to Pay for it. Chicago: University of Chicago Press. Manski, C.F., and Wise, D.A. (1983). College Choice in America. Cambridge: Harvard University Press. McPherson, M.S., and Schapiro, M.O. (1991). Does student aid affect college enrolment? New evidence on a persistent controversy. American Economic Review 81(1): 309–318. McPherson, M.S., and Schapiro, M.O. (1997). Demand for American higher education: Prices, college attendance, and federal policy. In P.W. Miller and J.J. Pincus (eds.), Funding Higher Education: Performance and Diversity. Canberra: Department of Employment, Education, Training and Youth Affairs. McPherson, M.S., and Schapiro, M.O. (1998a). The Student Aid Game, Meeting Need and Rewarding Talent in American Higher Education. Princeton: Princeton University Press. McPherson, M.S., and Schapiro, M.O. (1998b). Financing lifelong learning: trends and patterns of participation and financing in higher education. Higher Education Management 12(2): 131–156. McPherson, M., and Schapiro, M.O. (2000). Financing lifelong learning: trends and patterns of participation and financing in higher education. Higher Education Management 12(2): 131–156. Moore, R., Studenmundt, A., and Slobko, T. (1991). The effect of the financial aid package on the choice of selective college. Economics of Education Review 10: 311–321. Nahuis, R., and Smulders, S. (2000). The skill premium, technological change and appropriability. CPB Research Memorandum, No. 169. The Hague: CPB Netherlands Bureau for Economic Policy Analysis. National Committee of Inquiry into Higher Education (Dearing Committee) (1997). Higher Education in the learning society: Main Report. London: HMSO. Nelson, R.R., and Phelps, E.S. (1966). Investments in humans, technological diffusion and economic growth. American Economic Review 56(2): 69–75. Nelson, B. (2003). Our Universities. Backing Australia’s Future. Canberra: Department for Education Science and Training. OECD (1998). Human Capital Investment, An International Comparison. Paris: OECD. OECD (2001). The Well-being of Nations. Paris: OECD. Oosterbeek, H. (1995). Sociaal leenstelsel voor financiering van studie. Economisch Statistische Berichten, 19 April 1995, 376–379.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Oosterbeek, H. (1998a). An economic analysis of student financial aid schemes. European Journal of Education 33(1): 21–29. Oosterbeek, H. (1998b). Innovative ways to finance education and their relation to lifelong learning. Education Economics 56(3): 367–380. Oosterbeek, H., and Webbink, D. (1995). Enrolment in higher education in the Netherlands. De Economist 143(3), 367–380. Psacharopoulos, G. (1981). Returns to Education. Amsterdam: Elsevier. Psacharopoulos, G. (1994). Returns to investment in education: A global update. World Development 22: 1325–1343. Psacharopoulos, G., and Patrinos, H.A. (2002). Returns to investment in education: A further update. World Bank Policy Research Working Paper No. 2881. Washington: World Bank. Also available on-line at: http://econ.worldbank.org/files/18081_wps2881.pdf Rauch, J. (1993). Productivity gains from geographic concentration of human capital: evidence from the cities. Journal of Urban Economics 34: 380–400. Romer, P. (1993). Ideal gaps and object gaps in economic development. Journal of Monetary Economics 32: 338–369. Romer, P. (1990). Endogenous technological change. Journal of Political Economy 98(5): S71–S102. Schultz, T.W. (1961). Investment in human capital. American Economic Review 51: 1–17. Schultz, T.W. (1975). The value of the ability to deal with disequilibria. Journal of Economic Literature 13(3): 827–843. Shea, J. (2000). Does parents’ money matter? Journal of Public Economics 77: 155–184. Spence, M. (1973). Job market signalling. Quarterly Journal of Economics 87: 355–374. Steel, J., and Sausman, C. (1997). The contribution of graduates to the economy: Rates of return, Report 7. In The National Committee of Inquiry into Higher Education, Higher Education in the Learning Society. London: HMSO, also available on-line at: http://www. leeds.ac.uk/ncihe/. Stiglitz, J.E. (2000). Economics of the Public Sector (3rd edn.). New York and London: Norton. Stiglitz, J.E. (1975). The theory of ‘screening’, education, and the distribution of income. American Economic Review 65: 283–300. Temple, J. (2000). Growth effects of education and social capital in the OECD countries. OECD Economics Department Working Papers No. 263. Paris: OECD. Tertiary Education Advisory Commission (2001). Shaping the funding framework. Wellington: Ministry of Education. Also available on-line at: http://www.teac.govt.nz/ffamework.htm Teulings, C. (2000). Onderwijs: een nuttige maatschappelijke investering? Socialisme en Democratie 57(9): 405–410. Venniker, R. (2000). Social returns to education: a survey of recent literature on human capital externalities. CPB Report 2000, No. 1, 47–50. Vossensteyn, H. (2002). Shared interests, shared cost: student contributions in Dutch higher education. Journal of Higher Education Policy and Management 24(2): 145–154. Vossensteyn, H., and Canton, E. (2001). Tuition fees and accessibility: the Australian HECS. In CPB and CHEPS, Higher Education Reform: Getting the Incentives Right. The Hague: SDU. Weisbrod, B.A. (1964). External Benefits of Education. Princeton University: Industrial Relations Section. Weiss, A. (1995). Human capital vs. signalling explanations of wages. Journal of Economic Perspectives 9(4): 133–154.
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8. TOWARD MASSIFICATION: HIGHER EDUCATION DEVELOPMENT IN THE PEOPLE’S REPUBLIC OF CHINA SINCE 1949 Rui Yang Monash University
It hardly needs stating that what China is and how it will develop is of major importance for all of us. China is not only a culture that has contributed in different ways over a long period to world cultures, but is today one of the most populous and potentially powerful countries in the world (Price, 1997). It is now experiencing rapid, profound socio-economic transformation. Against such a background, mass higher education system is beginning to emerge in China. With enormous recent increase in participation levels, China’s higher education is moving fast to become one of the largest systems in the world. Its intake of students, for example, is very close second to that of the United States, in terms of sheer numbers of students. However, its proportion of students enrolled is still far behind OECD countries. As the integration of China’s higher education system into the world community is important and urgent to both China and the world higher education circle (Yang, 2002), it is necessary to have a full understanding of the Chinese system. This chapter aims to provide an overview of the development of Chinese higher education and to put it into the relevant context of massification. The paradigm shift in focus from elite to mass higher education was originally promoted by Martin Trow (1973) to analyze the explosive growth of higher education first in the United States then in some major European
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countries. The discussion was furthered in the early 1980s and the mid1990s. The idea of an elite-mass paradigm shift has since become the standard account of how higher education systems develop (Scott, 1995). The notion provides a useful perspective to examine China’s higher education development. It is in this sense that this chapter employs the concept to explain the transition from elite to mass forms of higher education. While the rapid higher education expansion after World War II is an often-told and well-documented story, and the term “mass higher education” has been widely used, surprisingly there are still too few studies of the transitional process grounded in detailed examination of particular historical and geographical times and spaces. Comparative studies in less developed countries are especially lacking. This chapter is built on the existing English and Chinese literature on massification of higher education. It delves deeply into the historical traditions, current practices and likely future changes of Chinese higher education to contribute to identifying effective approaches to mass higher education. By so doing, this study also tests and further modifies the existing literature on mass higher education. The notion of mass higher education has never been more relevant. Many countries have seen a doubling or tripling of post-secondary enrollments in the last few decades, along with increased participation rate for young people. In most middle-income countries today, between 25 and 45 percent of young people enroll in higher education (El-Khawas, 1998, p. 4). Similar trends have emerged in China. Since the establishment of the People’s Republic of China (PRC), its higher education has expanded considerably. In 2000, a total of 3,768,000 first-year students studied in post-secondary education, with 2,206,000 in regular higher education institutions.1 The number of enrolled students in Chinese regular and adult higher learning institutions (9,399,000) in 2000 was 80 times that (117,000) in 1949 (China Education Daily, June 23, 2001, p. 2).
1 China’s post-secondary higher education institutions can generally be divided into two sectors: regular and adult higher education. The regular sector is the mainstream including 4-year university (benke) and 3-year specialized college (zhuanke) programs, leading to a Bachelor’s degree and diploma respectively. The adult sector includes 2- and 4-year diploma programs of study. Students in the regular sector are overwhelmingly full time, while students in the adult sector are usually part-time. A substantial proportion of adult higher education is offered by regular higher education institutions. See Du Zhuo-run and Xiong Qing-nian (eds.), (1999) Zhonghua Renmin Gongheguo Jiaoyu Zhidu, pp. 108–109, 188–189 for more detailed discussion.
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From 1999 to 2001, graduate students increased by 97.7 percent to 194,000, undergraduate students increased by 105 percent to 2,745,000, and students enrolled in 3-year specialized colleges increased by 76.6 percent to 2,775,000. The goal set in the Action Plan to Vitalize Education in the 21st century (Mianxiang Ershiyi Shiji Jiaoyu Zhenxing Jihua) issued by the Ministry of Education in 1999 to achieve a gross enrollment ratio of 11 percent was overachieved (Ministry of Education, 1999, p. 4). With the rate of increase, China will be well ahead of the target goal to achieve a gross enrollment ratio of 15 percent by 2010. Those who had received examination-based self-study higher education increased from 147 in 1984 to 488,900 in 2000,2 totaling 3,320,000. Numbers of applicants for these examinations in 2000 reached the enormous figure of 13,691,300 (China Education Daily, February 29, 2001, p. 1). Such developments, although impressive, have not brought China mass higher education in the usual sense. The percent of gross enrollment in China in 2000, for example, at about 11 percent, lags much behind the world average of 16.7 percent in 1996. Among economically developed countries, the percentage is as high as 50.5 percent, reaching close to the universalization of higher education (UNESCO, 1998, p. 11). In an era of the knowledge-based information economy, higher education is seen as the core of nation-building projects in modern societies (Bell, 1976; Gibbons, 1998). China’s modernization relies heavily on higher education (Min, 1999), as is clear in the phrase, kejiao xingguo (to make China prosperous and powerful through education and science) (Li, 1996, pp. x–xi). In the following sections, a historical review of China’s higher education development is presented first, with particular focus on the achievements
2
Examination-based self-study higher education in China is the result of some special socio-historical circumstances. After the open and reform policy was adopted in late 1970s, regular higher education institutions could not supply the huge societal demand for more professionals. The Sate Council approved an application by the Ministry of Education to experiment with examination-based self-study higher education policy in January 1981. By 1985, all provinces had established their examination-based self-study higher education systems. By passing examinations set by the national government, candidates can obtain corresponding educational qualifications. The examinations cover many specialized areas, and are at diploma and Bachelor’s degree levels. All Chinese citizens are eligible to apply. After more than 20 years practice, examination-based self-study higher education has been proved a much-needed countermeasure in meeting the development needs in the rapid expansion of China’s higher education. From 1988 to 1997, for example, applicants totaled 53,000,000. Among them 1,730,000 succeeded, covering 425 specialized fields. For more discussions on examination-based self-study higher education in China, see Liu Hai-feng (ed.), (2001) Gaodeng Jiaoyu Zixue Kaoshi Bijiao Yanjiu.
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since 1949, especially since the adoption of the Open Door policy.3 Then comes a detailed discussion of the current practice, set against an international background. Finally, some tensions within the process of higher education massification are examined critically.
THE CONTEXT: HISTORICAL ROOTS AND CURRENT SYSTEM By the close of the 18th century, China had perfected one of the world’s most durable political systems during 2,000 years of its imperial history and had developed a unique civilization that had deeply influenced the culture of its neighboring countries. China’s higher education had evolved according to its own logic and never deviated from its developmental path, despite external influences. Higher education circles confined their dissemination of knowledge to the provincial level and persisted in disregarding knowledge about anything in the rest of the world. Over such a long historical process, a unique set of scholarly values arose in China. There was no institution in Chinese tradition that could be called a university. Instead, the imperial examination system4 and the academies or shuyuan5 were key elements of ancient Chinese higher learning. As Hayhoe (1996, p. 10) writes: On the one hand there was the civil service examination system and its cognate institutions — the Hanlin Academy, the college for the sons of the emperor (guozijian), the institution of supreme learning (taixue), and the whole system of institutions at provisional, perfectural, and county levels that made possible a “ladder of success” through a series of examinations, culminating in the palace examination in the presence of the
3
After being closed to international intercourse for decades, China adopted its policy of opening to the outside world at the Third Plenary Session of the Eleventh Central Committee of the Communist Party of China held in December 1978. 4 The imperial examination system began to take form around 400 C.E. and reached its full institutional development in the Tang dynasty (618–907 C.E.). During the Song (960–1279 C.E.), it crystallized into patterns that were to last right up to 1911. For more information, see Ruth Hayhoe (1996) China’s Universities 1895–1995, p. 10. 5 The academies or shuyuan took their definitive forms in the Song dynasty, as what had been originally libraries or centers for scholarly discussion developed into academies that provided a structured learning environment separate from, yet interacting with, state institutions associated with the civil service examination system. See also Ruth Hayhoe (1996) China’s Universities 1895–1995, p. 11 for more information.
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Hayhoe (1996, p. 15) goes on to point out that the 19th century saw the diffusion of the European model of the university throughout much of the world, under conditions of imperialism and colonialism, which might be understood as an integral part of the history of capitalism. As both a crucial gateway to the world and a means to social development, China’s higher education could have taken the lead in introducing and assimilating advanced culture, science and technology in order to promote social and economic development. Yet, due to its exclusivity, Chinese higher education continued to train traditional Confucian scholars with little knowledge of the outside world. Although Western higher education models had already demonstrated their strength, China’s communication with the West was thus intentionally hindered. Chinese higher education within the period laid stress solely on the training of scholars with an encyclopedic knowledge based on Confucian values, which in practice served only the aristocracy. The Confucian scholars acquired the cultivation that symbolized their social status. Although occasionally there were some exceptions, the civilian participation in ancient Chinese higher learning was much less than in the equivalent European model. As China became enmeshed in the West-centered global historical process, officials who had had to deal with Westerners realized that the Chinese needed to acquire the weaponry of the West to ward off the West. In order to better learn Western science and technology, reformers suggested to “give up courtesy to the barbarians” and to invite Western instructors into Chinese institutions (Zheng, 1994, p. 19). Starting from the 1860s, Western style professional schools were founded to train technicians. Among them were many language schools, which trained translators from Western languages into Chinese. One of these professional schools, Beiyang gongxue, was established in 1895 and later became the first modern Chinese university (Chen, 1986). Reforms of traditional higher learning institutions were started thereafter. A number of modern institutions were also established. However, the impact of these institutions was minimal. The traditional examination system did not change its emphasis on Confucianism and continued to 315
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produce a conservative, backward-looking intelligentsia (Teng and Fairbank, 1961). The “Great Reform” of 1898, however, placed much hope on education. Higher education became a major concern (Shu, 1981). Educational reform was indeed the most revolutionary in its effect on China. Emperor Guangxu decreed that a countrywide hierarchy of schools, topped by universities, be established to teach modern as well as classical subjects; that students be sent abroad for education; and that current affairs and other Western subjects be incorporated into the imperial examinations. By 1905, the traditional examination was finally abolished. Women’s schools — normal and vocational were founded. More students were sent abroad for training, mainly to Japan, the United States and Europe. Education was the area in which the reforms succeeded most (Bastid, 1988, p. 89). The 1911 revolution which soon followed was thus a product of reformist as well as revolutionary forces. A modern educational system was ostensibly established in such a context. The new republican government decreed a major reorganization to create an education system in 1912 more in tune with prevailing world trends. A foundation was laid to build a new higher education system. The classics were ordered to be eliminated from the curriculum. The new educational law stipulated length of terms for universities, classified branches of study as humanities, science, law, business, medicine, agriculture and engineering, and required that universities establish graduate schools, offer preparatory courses, and organize appraisal meetings. In 1912, there was 1 university, 10 preparatory schools, 94 professional training colleges, 12 normal colleges, and 5 “others” (Pan and Liu, 1993, p. 803). Within this period, foreign missionaries played a significant role in higher education. By 1917, 80 percent of the student population was accommodated by missionary universities. By the 1922–23 academic year, there were 35 university-level institutions of higher education, 68 provincial training colleges, 8 normal colleges, and 14 “others” (Zhou, 1934, p. 225). However, universities developed in a rather lopsided fashion nationwide. For instance, there were 638 students of law, 376 students of engineering, but only 74 students of science. In addition, 11 industrial colleges of industry, agriculture, medicine, and business were also established with a population of 4,000 strong students, while law schools numbered 32 with at least 8,000 students (Gao, 1992, p. 227). Students still strongly regarded becoming an official as the only purpose for getting an education. 316
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The lack of central government from 1911 to 1927 provided Chinese higher education with the possibility of vigorous experimentation. The period, as Hayhoe argues (1996, p. 43), saw the first real effort to establish a “university” in the sense of the defining values of autonomy and academic freedom. Within the period, a tremendous range of new higher education institutions also developed and flourished. Different strands of China’s own evolving traditions linked up with various foreign influences, with America replacing Japan as the most favored source of influence. Chinese scholars who returned from Western countries and Japan played a key role in the development of higher education. Educational thought gradually matured, with eclectic foreign influences, particularly from America and Europe. The Japanese invasion in 1937 inflicted heavy losses on China’s higher education. By 1936, China had had 108 higher education institutions, of which 91 were damaged significantly from July 1937 to August 1938. Students decreased to 25.6 percent from 41,922 in 1936 to 31,188 during 1937. With constant bombing by Japanese fighters, many institutions could not maintain order. They were forced to move to remote mountaineous districts, and sustained great losses of finance, personnel and library collections. Nevertheless, in the regions that were not occupied by the Japanese troops, higher education even grew during these years. By the end of the Anti-Japanese War (1937–45), there were 141 higher institutions, with an enrollment of 83,498 students. The development during this period was much imbalanced among disciplines, with the biggest growth in education and commerce. The numbers of students in natural and social sciences dropped dramatically. From 1912 to 1949, the university continued to go through a process of adaptation and indigenization that might be compared to the development of American universities in the 19th century. During this period, the Chinese university developed into a mature institution, which achieved a balance between its Chinese identity and its ability to link up to a world community of universities. The Chinese Communist Party (CCP) came into power and founded the PRC in October 1949. Western policies to isolate the newborn communist China led to the leaning to the Soviet Union. The first national higher education conference held in June 1950 demanded attention be paid to the socialist Soviet model, the dominant slogan in China until the mid-1950s was “learn from the Soviet Union.” Mao Ze-dong announced in the 317
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summer of 1949 that the CCP must “lean to one side” (Mao, 1991, pp. 472–473). Russians replaced departing Americans and Europeans, some 700 Soviet “experts” serving in Chinese higher learning institutions in the early 1950s. From 1952, the Chinese higher education system simulated Soviet administration, teaching methods, textbooks, and even classroom design. The experience of other countries, especially those of the West, was rejected. Based on Russian experience and advice, the First Five-Year Plan (1953–1957) focused on the development of heavy industry. Plans to reform institutions of higher education so as to emphasize technical education were finalized in 1951 (People’s Daily, September 24, 1952, p. 2). To ensure that the restructured system performed the function intended, it was reinforced within unified sets of plans for student enrollment, job assignment, and curriculum content. The Eighth National CCP Congress in 1956 again emphasized the role of higher education in national reconstruction. It required universities and colleges to absorb the latest technology developments in the world and send teachers and students abroad for study. This conference, however, was followed by an assessment of educational achievement since the founding of the PRC, which concluded that (in the context of the Cold War) higher education should be geared to the tit-for-tat struggle between classes and lines (socialism and capitalism). Bourgeois educational views were bitterly criticized (Schram, 1974). From the Great Leap Forward (1958–1966) to the end of the 1970s, expertise was not given a wide edge over political understanding. Whichever way one looks at the Great Proletarian Cultural Revolution (1966–76), with hindsight it must be seen as a terribly costly failure, perhaps partly because of its passionate rejection of foreign influence. Higher education was devastated along with the fortunes of a generation of teachers and students. Institutional administration was paralyzed and classes suspended. Maoists eliminated age limits and entrance examinations for universities and colleges, reduced the number of school years needed for graduation, and eliminated the examination-based grading system. As time passed, it became increasingly obvious that this egalitarian approach to education would not produce the high-quality technicians and scientists China needed for its modernization program. The closing down of universities for some years in that period also left a gap in the educated class that is still proving to be a handicap in China’s efforts to modernize. 318
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When Deng Xiao-ping and the “pragmatist” faction reversed Maoist policies in late 1976 and set China on a more rational, economic-oriented path to modernization, one of the first tasks undertaken was restoration of the educational system (Reed, 1988). Although Deng’s reform agenda was officially inaugurated at the Third Plenum of the Eleventh Central Committee held in December 1978, changes in the education sector had preceded it. By that time, almost all the decisions necessary to recreate the regular education system in its pre-1966 state had already been announced, and implementation was well under way (Pepper, 1990). Entrance examinations to colleges and universities were re-introduced, and professional standards and expertise were made respectable again. These post-Maoist changes in educational policy saw the re-emergence of the old “regular” system with its residues of foreign models (Hayhoe, 1984). The Chinese higher education system has long been highly centralized, with education provided by the central and local governments, respectively, under their direct administration. It has been viewed as a disadvantage of the system that the state undertook too much responsibility and the schools lacked flexibility and autonomy to provide education according to societal needs. The central departments and local governments provided education separately. The structure of education was segmented with overlapped disciplines and very low efficiency of institutional operation. Therefore, structural reform has been the core of China’s higher education reforms in recent decades. At the same time, in line with international practice, significant progress in implementing the reform agenda is also seen in other aspects of the higher education sector. The costs of higher education are increasingly shared with students and families via tuition and fees. Means-tested grants and student loans are now available, and are on the Chinese higher education policy agenda. Private sector institutions continue to grow where they are not prohibited by the law. Cost-effective, market-responsive learning is widely occurring in most institutions. The financing of universities is taking into account measurable output indicators, and the government is devolving expenditure authority to the universities, and entrepreneurship is growing fast within every university at the institutional, departmental, and individual faculty levels. The reform and development of higher education in the last two decades has resulted in significant achievements. A higher education system which encompasses basically all branches of learning, combines both degree and non-degree education and integrates diploma, undergraduate 319
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and graduate education has taken shape. In 1998, there were, altogether, 1,984 higher education institutions, among which 1,022 and 962 were regular and adult higher education institutions, with a total enrollment of 3,408,700. The total number of graduate students was 198,885. Chinese private higher education (the minban system) is also developing rapidly. The Chinese expression minban literally means “popularly run” or “run by collectives and individuals”. Essentially, minban institutions are those run by non-state sectors, including privately and collectively owned institutions. Private higher education has a long history in China dating back to ancient dynasties. It disappeared in 1952, and has been resurrected as an offshoot of the country’s new economic diversification. China’s first minban higher institution, Zhonghua Shehui University, was established in March 1982. Since then minban institutions have been struggling to gain legitimate status within the Chinese system, something that they have attained only gradually. Minban institutions have further developed especially since 1997 when the State Council issued its Regulations of Education Run by Social Forces (Shehui Liliang Banxue Tiaoli), which further legitimized their role. There were 1,095 minban institutions nationwide in 1995, with a student intake of 1,190,000. The number of institutions grew steadily to 1,230 in 1996, 1,252 in 1997, and 1,277 in 1999 (Mok, 2000). Let us have a glance at the current Chinese higher education system. Chinese higher education is provided by institutions of various types including general universities (natural and social sciences and humanities), technical universities, specialized institutions (medicine, agriculture, foreign languages, etc.) and teacher-training colleges. Graduate schools, attached to 4-year colleges, universities and national scientific research institutions with the authorization of the Ministry of Education, are responsible for the management and organization of graduate education. The State Council and the Ministry of Education are responsible for policy-making, development planning, reforms and the direction of higher education at the national level. The Chinese system comprises 4-year undergraduate programs in universities or colleges, which lead to a Bachelor’s degree, while study at medical colleges and some technology institutes requires 5 years. Students can obtain a Master’s degree after 2–3 years of successful study and completion of a dissertation. Students are required to study courses in the first half of the study term. They can only enter the dissertation preparation 320
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stage if they have completed all required courses and obtained the required minimum of credits. Doctoral degree requirements can be completed in a minimum of 3 years. A dissertation must be presented proving that the candidate possesses the ability to undertake independent research and has made a significant contribution to the field. Until 1955 no graduate study facilities were available, and students mostly went to the former Soviet Union for graduate studies. In 1955 the qualification of Associate Doctor was established, but few were awarded. Graduate study was not re-instituted until 1978 after the Cultural Revolution. Since 1982, the Chinese government has instituted a number of educational development programs to raise academic standards and has introduced a wide range of research courses in universities. One important part of the present Chinese higher education is the non-formal system. Non-formal studies are offered by radio and television universities, whose courses are accredited by the Ministry of Education. The Central Broadcasting and Television University (CBTVU) in Beijing, for example, offers numerous 3-year courses, including mathematics, physics, engineering and electronics, management and agriculture, and Chinese language. Graduates are granted a diploma. There are about 50 provincial television-based universities nationwide working closely with the CBTVU. Spare-time colleges have been established by factories and trade unions to offer 4-year courses in various fields and/or short advanced courses. These institutions are regarded as universities. There are some other forms of non-formal higher education. The People’s University of China, for instance, offers special classes to enable students to make up any deficiency in their secondary education; these normally continue for 2–4 years. There are also evening schools and advanced training programs for adults attached to regular universities and colleges. Diplomas or certificates are awarded on the basis of completion of required courses and passing the examinations. The overall structure of Chinese higher education has changed significantly, particularly within the past 50 years from the single emphasis on undergraduate education to a more reasonable distribution at various levels. In 1950 the ratio between two/three-year training specialized colleges, undergraduate and graduate programs was 0.1 : 1 : 0.01. It became 0.83 : 1 : 0.08 in 1978, and 1.23 : 1 : 0.07 in 1999 (Ministry of Education, 1999, p. 47). Taking examination-based self-study higher education students into account, the ratio then was 1.65 : 1 : 0.066. This means students 321
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enrolled in two/three-year specialized college programs have occupied 62 percent of the total, forming a pagoda-shaped structure for the system of higher education, with many more at the bottom than at the top.
THE TRAJECTORY OF HIGHER EDUCATION EXPANSION IN THE PRC THE INITIAL STAGE OF THE PRC (1949–57) During the initial stage of the PRC, full-scale reconstruction was under way. Based on socialist public ownership and the development goals of a planned economy, the Chinese communist government took over both public and private institutions of higher learning from the previous Nationalist government, as well as the institutes run by foreign missionaries. Meanwhile, the then Soviet style was modeled as a basis for China’s nationwide higher education reorganization. Chinese higher education grew rapidly thereafter, especially from 1955 to 1957. First, the communist government took over all 205 higher learning institutions left over by the governments at various levels under the Nationalist Party (124), private agencies (61) and foreign missionaries (20) (Ministry of Education 1979, p. 42). The new government saw the remolding of foreign missionary institutions as an integral part of its political campaign to resist imperialistic cultural invasion. It was reiterated clearly by Ma Xu-lun, the then Minister for Education, that foreigners were not allowed to run schools in China. In this regard, it is interesting to see how the Chinese government later welcomed foreign participation in providing education after a few decades of administration, as shown later in this chapter. While the change of political power was violent, regular operation of colleges and universities was maintained with remarkable little disruption. In consideration of the fact that foreign missionaries had substantially reduced providing funds, the then Government Administration Council decided to transfer all missionary institutions to public ownership on December 29, 1950. By 1950, the communist government had taken over 20 foreign missionary institutions, of which 17 were American, with 14,536 students, 3,491 teaching and administrative staff, and 1943 security guards. Meanwhile, the Ministry of Education issued Provisional Regulations of Private Higher Institutions Administration (Sili Gaodeng Xuexiao Zanxing Tiaoli) and began 322
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to subsidize private post-secondary institutions (Yu, 1994, pp. 15–16). While these changes were evidently due to political considerations, higher learning institutions became much more accessible to some of the Chinese population with middle, lower middle and working class origins. Second, the Chinese government realized that there was a huge gap between the industrialization demand for highly skilled and educated workers and the actual supply generated by those left over institutions from the previous government which were the small-scale, single-leveled with imbalanced foci on arts, humanities and social science.6 A campaign of remolding the “old” education began. The restructuring of higher education institutions was a major event aiming at the needs of national construction. As the Minister of Education pointed out, the fragmented political and economic situation was reflected in higher education, which was in an extremely anarchic state, with each government department operating in its own way (People’s Daily, June 14, 1950, p. 1). Thus, a nationally united and centralized leadership needed to be gradually established. Higher education must be geared to the need of national construction. The existing system should be strengthened and adjusted adequately and gradually, or new departments need to be created. Such work starts from North and East China regions. (He, 1998, pp. 92–93)
With a view to meeting the needs of economic construction, steps were taken gradually to strengthen and readjust the departments and colleges within higher education institutions. The departments of the engineering colleges were the first to be readjusted, and new departments added. As early as the end of 1949, the central government and various administrative regions searched into ways of achieving the proposed adjustment, and conducted some experiments. In November 1951 a national conference of the presidents of engineering colleges discussed the first draft of a national higher education adjustment. According to the conference, the major problems of the national distribution of engineering colleges were: an imbalance in terms of geographical distribution; a dispersion of teachers and facilities which led to uneconomical practices; impractical programs that failed to train specialized personnel; and
6 Immediately before the CCP came into power, there were 49 comprehensive, 28 engineering, 18 agricultural, 22 medical, 12 teacher training, 11 foreign languages, 11 finance and commerce, 7 law and politics, 2 physical education, 18 art higher learning institutions and 27 others. For more detailed information, see Ministry of Education (1979) Sanshinian Quanguo Jiaoyu Tongji Ziliao, 1949–1978, p. 42.
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a shortage of students. The conference made a plan that centered on the restructuring of engineering colleges in North, East and the Central South China. The Ministry of Education issued a draft of a report on national higher education adjustment in May 1952. It required institutions to keep the existing needs of national construction, and their own strengths in mind, and to do their work in order of importance and urgency. The main task of 1952 was to reorganize institutions in Beijing, Shanghai, Hangzhou, Nanjing, Wuhan, Changsha, Guangzhou as well as in some big cities in Anhui and Shandong provinces. The institutions included comprehensive universities, specialized institutes and two/three-year specialized colleges. The content was adjusted and consolidated according to the decrees issued by the central government. In each administrative region there was to be at least one comprehensive university to train scientific research personnel and teachers. Engineering institutes were the main concern at this time. The principle was to reduce the number of polytechnic institutes, and increase the number of specialized engineering institutes. Agricultural institutions were required to be established, with only one to three in each administrative region. There were to be one to three teachers’ colleges in each administrative region to train senior secondary school teachers, while the training of junior secondary school teachers was left to the provincial governments (Zhongguo Jiaoyu Nianjian Editorial Committee, 1984, p. 233). It was clear that the main task of this adjustment was to develop specialized colleges, especially engineering institutes, with the adjustment and consolidation of comprehensive universities as a supplement. In May 1953, the Government Administration Council decided to continue the restructuring of higher education, building on the work of 1952. This time, the focus was on the Central South region, together with the adjustment in the North, East and the Northeast China areas, and some in the Northwest and Southwest regions. The main targets were on the one hand, to reform the old universities which were thought to have disorderly specialties, and which had not yet been re-organized. On the other hand, institutions of technology, and some teacher-training colleges were to be strengthened and increased. Institutions of finance and administration, politics and law were merged and consolidated. By 1953, a wholesale reorganization of Chinese higher education had been accomplished, providing the basis for further development of the next 50 years. 324
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After the adjustment, there was a total of 182 higher learning institutions, including 14 comprehensive universities, 38 engineering institutes, 31 teachers’ colleges, 29 agricultural and forestry institutions, 29 medical and pharmacy institutions, 6 institutions of finance and economics, 4 institutions of politics and law, 8 foreign language institutes, 15 institutions of art, 4 physical education institutions, 3 institutions for minority groups, and 1 meteorology institution (Yu, 1994, pp. 39–40). The reorganization in the early 1950s, together with the take-over of public institutions from the previous government and the transference of the foreign missionary universities into public ownership, combined to lead to a rapid expansion of China’s higher education during the initial years of the PRC. Enrolled students increased 69 percent from 1949 to 1952. During the First Five-Year Plan period, the annual increase rate of student intake in higher education reached 18.2 percent (Zhongguo Jiaoyu Nianjian Editorial Committee, 1984, p. 963). THE GREAT LEAP FORWARD AND THE “HARD LANDING” AFTERWARD (1957–66) The good times in the early 1950s did not last long. China’s higher education circle soon turned dizzy with success. Ma, still the Minister for Education, summarized the situation in his speech entitled “New China’s Higher Education in the Past Five Years” in October 1954: Due to the rapid development of our national construction, neither the quantity nor the quality of higher education can satisfy our societal demands. . . . In consideration of the limited numbers of secondary graduates, higher education institutions have difficulties in recruiting sufficient number of students. In order to solve such a problem, our principle is to concentrate our strength on key projects. To achieve this, we must create conditions proactively, and at the same time, facilitate ourselves with revolutionary enthusiasm and methods to bring our latent potentialities fully to fulfill our task to train cadres for our country. (He, 1998, p. 391)
As a matter of fact, the number of the students enrolled for higher education in 1954 was already 135 percent of secondary school graduates. This was seen as entirely appropriate within the atmosphere during the Great Leap Forward, which required China to catch up with the United Kingdom and the United States within 15 years. The Central Committee of the CCP and the State Council released Instructions in Education Work 325
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(Guanyu Jiaoyu Gongzuo de Zhishi) on September 19, 1958, which pointed out: We should devote our major efforts to developing secondary and higher education to achieve the goal that all our young people and adults can receive higher education when they meet certain requirements on a voluntary basis. We will universalize higher education within 15 years, and then spend another 15 years on its improvement. (National Education Research Institute, 1984, p. 232)
The plan to universalize higher education within 15 years drove China’s higher education into its own great leap forward. Higher education institutions increased from 229 in 1957 to 1289 in 1960. New enrollments grew from 105,000 to 323,000. The total number of students in higher education increased rapidly from 440,000 to 960,000 (Yu, 1994, p. 63). In fact, the year 1958 witnessed the birth of two institutions every three days. For several years consecutively, higher education recruited more students than secondary school graduates, as shown in Table 8.1. By early 1961, the Chinese government realized the necessity to put a brake on this rapid expansion. On June 6, 1961, when commenting on the adjustment of higher education institutions and upper-level specialized colleges in Beijing, the Ministry of Education pointed out: The number of higher education institutions in Beijing increased from 31 in 1957 to 90 at present. Students increased accordingly from 77,000 to 132,000. This growth is too fast, and needs to be checked. The overall scale should be in more control. (He, 1998, p. 1033) Table 8.1: Higher Education Institutions and Secondary School Graduates, 1954–1960 (thousand)
Year 1954 1955 1956 1957 1958 1959 1960
General Secondary School Graduates (GSSG)
Higher Education Institutions Enrolments (HEIE)
68 99 154 187 197 299 288
92 98 185 106 266 274 323
Source: Ministry of Education (1979), pp. 14–17.
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Percentages of HEIE on GSSG (%) 135 99 120 57 135 92 112
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The Ministry of Education then proposed the Adjustment, Consolidation, Enrichment, and Improvement (ACEI) policy, and required higher education institutions to take measures to control their scale, reduce student numbers, merge with each other, and even move out of Beijing to other regions if needed. By August 10, the Ministry of Education officially issued a national adjustment policy, and set a national enrollment limit between 160,000 and 180,000. In order to ensure teaching and research quality, 882 (68.4 percent of the total) institutions were closed from 1961 to 1963 (Yu, 1994, p. 70). Teachers were dispatched. Students who originally came from factories and rural areas were sent to countryside. Such a “hard landing,” although compelled by the circumstances, caused huge waste of human, financial and material resources (Xie, 2001, p. 143). Many students had to discontinue their studies. The whole higher education system was greatly undermined. The emergence of evening universities, correspondence learning, radio, and television universities during this period deserves our attention. Their establishment was regarded as a compliment to the regular system. Since China’s first television university was established in Beijing in March 1960, many provinces built up their own radio and television universities (Yu, 1994, p. 61). From 1957 to 1965, students enrolled in such modes of higher education increased from 70,000 to 790,000 in 1960. These forms of educational provision were not much affected by the readjustment in the early 1960s. By 1965, at least 400,000 students were still enrolled in such modes (Xie, 2001, p. 145). It took China a few years to bring order out of the chaos caused by the impact of the Great Leap Forward on higher education. By the 1964–65 academic year, the national situation had largely returned to normal. China’s economy had also overridden great difficulties: the GDP began to climb again with increase rates of 10.2, 18.3, and 17 percent, respectively in 1963, 1964, and 1965. This was the time when people began to forecast another fast growth both in the economy and in higher education. What followed was the Cultural Revolution, a disastrous man-made calamity, whose impact still lingers on today. HIGHER EDUCATION DURING THE CULTURAL REVOLUTION (1966–76) The official verdict of the Cultural Revolution by the Central Committee of the CCP after it was over (1982, p. 811) was that it was a period of 327
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“civil strife.” During the 10 years in which it ran its course, China’s economy and higher education suffered unprecedented losses. In 1967 and 1968, for instance, China’s GDP fell 5.7 and 4.1 percent consecutively. Over those 10 years, misery and suffering characterized the experience of those in higher education. By 1971, there were only 328 higher learning institutions. Students numbered 48,000 in 1970, 59 percent less than the intake of 1949, and almost equal to that (44,000) of 1939, as shown in the Figure 8.1. This backlash formed a sharp contrast to the Great Leap Forward period in the early 1960s. Beginning from March 1970, the resident Mao Ze-dong Thought propaganda teams formed by workers and People’s Liberation Army soldiers and the revolutionary committees at Peking and Tsinghua Universities submitted a joint request to the Central Committee of the CCP for student recruitment. Their report pointed out: According to Chairman Mao’s teaching, university students should be selected from workers and peasants with practical experience, as illustrated by the case of Shanghai Machine Tool Plant. They study at universities for several years, and then go back to practice again. Our two universities plan to recruit 4,100 students from the first half of this year. Their length of study will be 2–3 years. In order to be admitted, they must be workers, peasants or soldiers, have completed their junior secondary education, and be under 20 years of age. (National Education Research Institute, 1984, pp. 433–434)
The request was approved on June 27. The central government asked universities nationwide to follow suit with consideration of their local circumstances. Chinese higher education institutions, after four years suspension, recruited their first batch of 41,870 “workers, peasants and soldiers students” (WPSS) in 1970 (Xie, 2001, p. 148). The recruitment of WPSS continued to 1976 when students totaled 560,000, equivalent to the intake in 1957. During the early 1970s, spare-time higher education institutions grew fast from 127 in 1972 to 13,436 in 1976 with a student intake of 1,300,000. Though the quality of students and teaching in both regular and sparetime higher education institutions was extremely questionable (Shanghai Higher Education Research Institute, 1989, p. 23), this was part of the recent history of Chinese higher education. Considering this, WPSS are treated the same as other university students in the above figure in order to delineate an overall picture of China’s higher education development in the past half century. 328
329
49 19
0
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
14,000,000
16,000,000
1
2 95
1
5 95
Student numbers 18,000,000
58 19
61 19
1
4 96
67 19 70 19 73 19 1
6 97
79 19
1
2 98
85 19
1
8 98
91 19
94 19
97 19
00 20
Figure 8.1: Students in China’s Higher Education, 1949–2001
Year
Total
Students in examination-based self-study higher education
Graduates from examination-based self-study higher education
Post-graduate students
Students in adult higher education institutions
Students in regular higher education institutions
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REGULATION IN THE NAME OF REFORM SINCE THE LATE 1970S Deng Xiao-ping started his regulation of education immediately after the Cultural Revolution. In August 1977, Deng said at a national symposium of science and education that “this year we should make a resolution to recruit university students directly from senior secondary graduates. . . . Such direct recruitment in my view is a good way to turn out talents and produce results” (National Education Research Institute, 1984, p. 499). On October 12, 1977, the State Council and the Ministry of Education issued two policy documents respectively concerning the recruitment of undergraduate and graduate students. In the winter of 1977, some 5,700,000 candidates sat for higher education entrance examinations, with 273,000 being admitted. Candidates increased to 6,100,000 in 1978, with 402,000 actually enrolled, which was another peak year in history (National Education Research Institute, 1984, p. 519). At the initial stage of the open and reform practice in the late 1970s, Deng Xiao-ping made a series of speeches emphasizing the crucial roles of science, education and intellectuals in China’s modernization (see, e.g., Deng, 1994, pp. 85–90, p. 108). His views were implemented into national policies. In December 1978, economic construction replaced class struggle to be identified as the central work by the CCP. From 1978 to 1999, China’s GDP increased five times with an average annual rate of 9.58 percent. Over the period, China’s higher education grew accordingly. Students in regular and adult higher learning institutions and in examinationbased self-study higher education increased six times from 1,320,000 to 9,530,000, with an average annual rate of 9.9 percent. Higher education enrollment ratios increased from 1.56 percent in 1978 to 11.2 percent in 1999. By 1999, the ratio of students in higher education to those in secondary schools was 1 : 7. This has been termed as the “pre-mass” stage between the extreme elite and mass higher education (Knowles, 1978, pp. 2770–2773). In the late 1970s, the Chinese government realized the widening gap between the increasing societal demand for higher education and its limited financial capacity to provide sufficient funding for such education. One way to solve this problem was to further build up radio and television universities. For this purpose specifically, China bought a communication satellite in 1978. By 1997, China had established a national television higher education system, with the CBTVU at the top and 44 institutions at provincial level, 831 branches at prefectural level, and 1,699 branches at county level. 330
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Another means to overcome the difficulty was to rely on examinationbased self-study higher education. The system came into being on the initiative of the State Council and the Ministry of Education in late 1980 and early 1981, and became popular nationwide between 1983 and 1987, and has grown further since 1988 when the central government issued specific regulations. Graduates from examination-based self-study higher education increased from 1,478 in 1984 to 422,000 in 1999. Considering the fact that it takes candidates 5 years on average to finish their studies, one graduate from examination-based self-study higher education is equivalent to five enrolled students in regular higher education, and the contribution of examination-based self-study higher education to the national total number of enrollments was 211,000, occupying 22 percent (see Figure 8.1). Third, despite the annual increment of government investment in the early 1980s, resources for higher education were far from sufficient. In order to supplement inadequate public sector and state finance, minban higher education arose as the times required. Within the Ninth Five-Year Plan (1996–2000), China’s intake of students in higher education continued to grow substantially (Table 8.2). There was a considerable increase of university student numbers per 100,000 population. The increase rates of higher education enrollment in 1999 and 2000 were substantially higher than the average 8.5 percent over
Table 8.2: Higher Education Growth in the Ninth Five-Year Plan (1996–2000) with Comparison to 1990 and 1995 Year Higher education gross enrollment ratio Post-graduate students (thousand) Adult education students (thousand) Numbers of higher education student in every 100 thousand population
1990
3.4 93
1995
1996
1997
1998
1999
2000
7.2
8.3
9.1
9.8
10.5
11
145.4
162.3
176.4
198.9
233.5
301.2
1666.4 2570.1 2655.7 2724.2 2822.2 3054.9 3536.4
326
457
470
482
504
Source: National Center for Education Development Research (2001), p. 11.
331
594
723
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the previous 24 years since China adopted its Open Door policy. In 2000, students totaled 9,399,000 in China’s 1,041 regular and 772 adult higher education institutions, 2.4 times more than the total number in 1990. The average annual increase rate within the period of 1990–2000 reached 9 percent. Other aspects of higher education also developed considerably within the Ninth Five-Year Plan period (Table 8.3). Graduate students in 2000, for example, totaled 301,000, 3.2 times more than that in 1990 (National Center for Education Development Research, 2001, p. 11). Growth continued in 2001. More than 1,500 Bachelor and Diploma programs were newly launched (Table 8.4). In order to further drive economic development, the Chinese central government lifted the longstanding restrictions on marital status (required to be single) and age (below 25 years of age) of student examinees. In 2001, 4.5 million candidates
Table 8.3: Development of Full-Time Higher Education during the Ninth FiveYear Plan (1996–2000) in China with Comparison to 1990 and 1995 Year
1990
1995
1996
1997
1998
1999
2000
Numbers of higher education institutions 1,075 1,054 1,032 1,020 1,022 1,071 1,041 Average student numbers of each higher education institution 1,919 2,758 2,927 3,112 3,335 3,815 5,289 Staff number (thousand) 1,004.5 1,040.6 1,035.8 1,031.5 1,029.6 1,065.1 1,112.8 Teacher-student ratio at regular higher education institutions — 9.83 10.36 10.87 11.62 13.37 16.3 Note: “—” Means statistics unavailable. Source: National Center for Education Development Research (2001), p. 12.
Table 8.4: Enrolled Students in Regular Higher Education 1998–2001 (thousand) Year
1998
1999
2000
2001
Total student intake Graduate students Undergraduate students Diploma students
6430 199 2576 3655
7422 234 3208 3980
9399 301 4118 4980
21244 393 5354 6397
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1998
1999
2000
2001
Total enrollment Senior secondary school graduates Ratio of students in higher institutions to those in senior secondary schools
2,085 5,210
2,755 5,467
3,768 6,021
4,642 7,091
40%
50%
62.6%
65.5%
sat for university entrance, and 16,265 of them were over 25 (Table 8.5). Among these many were married. With such an increase in participation levels, the national government has recently readjusted its state planning and is determined to increase gross higher education enrollment ratio to 15 percent by 2005. To summarize, both gains and losses have been outstanding in the past half a century trajectory of Chinese higher education development. While the Great Leap Forward warns that higher education cannot be divorced from the bearing capacity of the economy, the Cultural Revolution upheaval showed stability as a prerequisite for mass higher education. The relatively smooth growth since the late 1970s has been based on a variety of factors. First, with only limited financial resources, the central government alone can never satisfy pressing societal demands for education. Sources of funding for China’s higher education have been increasingly diversified. The state’s role as the sole provider or a reliable guarantor of educational services has been transformed to a regular or service purchaser in order to alleviate the pressure on the government’s finances and to strengthen the institutions’ capacity for self-reliance (Mok, 2001). This move is in a direction that has been evident in many developed and developing countries (Rhodes, 1997). Individuals and social groups are encouraged to participate in running education. In 1999, for example, minban post-secondary institutions accommodated 123,000 students (China Education Daily, October 18, 2000, pp. 1–2). Even public institution funding sources have been greatly diversified, relying heavily on the “multiple-channel” approach, which includes government funding, education tax revenue, tuition and fees, university-run enterprise deductions, donations and foundations. In 1995, for example, the funds for public higher education institutions includes government investment (70.12 percent), education tax revenue (0.52 percent), contribution by 333
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university-run business (9.82 percent), education running expenditure from individuals and social groups (0.23 percent), donations (1.02 percent), tuition and fees (13.16 percent), and others (5.07 percent) (Shanghai Institute of Intellectual Development, 1997, pp. 92–93). Second, since China adopted the Open Door policy, the scale and expansion of its higher education sector has matched the growth of its national economy with a high correlation between their indexes. The correlation coefficient between higher education enrollments and China’s GDP was 0.95 during the period of 1978–99 (Xie, 2001, p. 153). Third, in order to provide sufficient higher education services to satisfy heightened social aspirations and parental expectations, China has gradually restructured its higher education system with a variety of higher education provision modes, including forms of full-time, part-time, radio and television, and examination-based self-study higher education. By 1999, China had approached closely to what has been defined as the threshold of mass higher education (Trow, 1973). Accordingly, the functions of the university have changed substantially, bringing formal and non-formal higher education even closer. This resembles the development of mass higher education in modern industrial societies after World War II, which exhibited a rapid growth of enrollments, both in absolute numbers and in the proportion of the traditional age cohorts (Gibbons, 1998).
DYNAMICS FOR MASS HIGHER EDUCATION The development of mass higher education is not an isolated, autonomous phenomenon. The larger changes in the nature of society and in the structure of the economy and the shifts in intellectual culture and in science and technology are integral parts of the story of mass higher education (Scott, 1995). This explains why mass higher education and the path to it are the major questions at issue in Chinese academic circles. Before we examine any of China’s specific strategies, let us first look at the current societal calls for mass higher education. A FAST-GROWING ECONOMY The growth of the world economy in 2001 featured significant slowdowns, with various developed countries plunging into economic 334
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recessions or economic downturns simultaneously. Against this context, China was able to maintain a 7.3 percent growth. A simple direct comparison of economic growth of all countries shows that China exceeded all the others. The most prominent feature of China’s economic growth over the past few years is that the growth rate has been maintained at a 7–8 percent level for four successive years. From 1989 to 1999, calculated according to the current price, the growth rate of China’s GDP increased from 4.1 percent in 1989 (close to low-ebb years) to 14.2 percent in 1992 (highgrowth years), and then decreased to 7.1 percent in 1999, 8 percent in 2000, and 7.3 percent in 2001. Over the past two decades, China has succeeded in obtaining an average annual growth of about 10 percent, while the average annual inflation rate was kept under 3 percent. China’s GDP growth is predicted to remain steady at about 7 percent in 2002 (Liu, Wang and Cheng, 2002, p. 9). Such rapid economic growth has amazed the whole world. Most recently, whether China can maintain such growth in the years to come has been the subject of a lively debate inside and outside China. Judged by the overall situation of economic growth, China experts tend to predict that China’s economy will keep on growing (see, e.g., Lardy, 2002), especially with China’s reformist leaders moving along with the global economy in a liberal direction. Chinese household income has increased substantially. Measured by purchasing power parity, the present per capita GDP is between US$1500 to US$2000. By 1998, China’s private saving was 40,000 billion yuan (US$1 艐 8 yuan), of which most was used for education. Once Chinese households have achieved relatively comfortable standards of living, expansion of the higher education sector can be easily justified. This will reduce the immense pressure caused by young people’s demand for further education on the one hand, and provides the society with educated manpower, especially scientists and engineers on the other hand. Within the past 20 years, Chinese residents’ income has more than doubled. Starting from the mid-1980s to the 1990s, however, the rural– urban income gap began to widen. Income disparities among regions were also on the rise, as economic growth in coastal China was more rapid than inland areas. While the relative gap between the per capita GDP in different regions is being narrowed, the absolute gap continues to widen. Income disparities within both rural and urban China have become less equitable. Within regions, substantial disparities exist between urban and rural areas. In Guangdong, a province that has been well documented 335
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as being one step ahead of the rest of China (Vogel, 1989), the per capita GDP in Zhuhai (the wealthiest city) was 16.4 times more than that of Heyuan (the poorest county) in the mid-1990s. According to the State Statistical Bureau, while 33.1 percent contribution to GDP was made by end consumption, rural residents contributed 15.8 percent only, which decreased 9 percent compared to the 24.8 percent contribution in 1998. Moreover, 63.91 percent of Chinese population lives in rural areas (Population Census Office, 2001). In a word, China’s economic growth has provided its higher education sector with both a huge demand and a solid basis for expansion. Within the process of higher education massification, however, special attention needs to be paid to income disparities between urban and rural areas and between different social groups. The process will be greatly affected if the 63.91 percent Chinese rural population does not raise their consumption level.
INTERNATIONAL COMPETITIVENESS IN SCIENCE AND TECHNOLOGY China’s recent accession to the World Trade Organization (WTO) has been hailed as the “biggest coming-out party in the history of capitalism”. WTO supporters predict that its membership will eventually contribute to higher standards of living for its citizens and increased growth for its economy. At the same time, China realizes it should prepare itself well in science and technology, especially by pioneering frontiers of advanced and emerging technology. According to a timetable released by the Chinese Minister for Science and Technology at the annual national conference on science and technology in January 2002, China plans to launch research into key technologies in a fight against foreign competitors’ monopoly in strategic advanced technologies. China is setting patent management and the establishment of technical standards to cope with increasing world competition in science and technology. The Ministry poured 450 million yuan ($54.2 million) in 2001 into improving conditions for research and making industrial use of scientific discoveries (People’s Daily, January 10, 2002, pp. 1–2). There is an irony in that China’s competitiveness in science and technology is still not strong enough to cater for the keen international competition. The Global Competitiveness Report of the International Institute for Management Development (April, 2002) has ranked China’s 336
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competitiveness the world as 31st in 2002, 33rd in 2001, downgraded from 28th in 2000, 25th in 1999, and 13th in 1998. China’s decline in ranking is mainly due to the relatively small amount of funds put aside for research and development. Only by making greater efforts in science and technology can China catch up with the developed countries in competitiveness. Although ancient China contributed significantly to the development of world science and technology, today’s China lags far behind industrialized countries. The primary reason lies in the international knowledge system — the people and institutions that create the knowledge edge, and the structures that communicate knowledge (Altbach, 1998, p. 193). The worldwide scientific communications system is still centered in and dominated by the research-producing nations. The most recent innovations in scientific communications, databases, and information networks are also located in the industrialized nations, especially in the United States. On the other side of the fence, China is a science and technology giant among developing countries with relatively well-developed basic scientific and technological infrastructures including scientific laboratories, universities, a network of scientific journals, and large numbers of scientists and researchers. China has, particularly recently, promulgated ambitious scientific plans and has taken scientific development seriously. By focusing on extending its scientific base and supporting scientific research and higher education, China’s scientific research has been sustained at a reasonable level (Thulstrup, 1992). Since the reopening to the outside world, China’s representation in the international scientific community has grown rapidly. The number of papers by China’s scholars that appeared in prestigious mainstream journals in sciences and social sciences was 1,293 in 1981 but, had climbed to 11,435 by 1995. The number of citations was only 8,517 in 1981–85, but had reached 77,841 by the 1993–97 period (World Bank, 2000, p. 124). These encouraging achievements of Chinese researchers are closely related to China’s recent economic growth and the increasing investment on science, technology and education. The Chinese government is aware of the fact that it remains an arduous task for China to catch up with the world in cutting-edge science and technology. It is equally aware that knowledge accumulation has been one of the major factors in economic development and is increasing at the core of China’s competitive advantage. The weapons in this new war of global economic competition 337
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are high technology and human skill. Higher education institutions are therefore in the frontline.
A SOLID FOUNDATION OF BASIC EDUCATION Mass higher education has evolved from mass elementary education. The historical order of the development of mass education is from elementary to secondary and further to higher education. This order is irreversible. As noted above, China’s premature plan to universalize higher education in the late 1950s with a reversal of post-secondary education enrollments and senior secondary school graduates could only lead to twists and turns, resulting in great losses in education and the economy. How far China can move towards mass higher education also depends on the compacted thickness of its basic education. China’s citizens were better educated at the end of the 1990s, however, than at the beginning. The growth of the population with secondary and higher education was particularly rapid. Middle school graduates rose from about 23 for every 100 persons in 1990 to 34 in 2000. Those with any higher education remain a tiny elite, but a fast growing one. Those attending junior college or above jumped from 1.4 to 3.6 percent of the population in the decade. The illiterate population also continued its long decline. In 1964 nearly one-third of Chinese aged 15 or over were illiterate or semi-illiterate, a number reduced to 15.9 percent in 1990. By 2000 this had fallen to 6.72 percent. According to the national education statistics released by the Ministry of Education ( June 3, 2002), China had 491,300 primary schools by 2001, with 19,442,100 primary students and an enrollment rate of 99.05 percent. Junior secondary graduates numbered 22,878,500 with a gross enrollment ratio of 88.7 percent. Half of the age cohorts graduated from senior secondary school, totaled 22,460,500. The gross enrollment ratio of the whole secondary education was around 82 percent. Based on the previous experience of other countries, mass higher education starts when higher education gross enrollment ratios reach 15 percent, a time when secondary education gross enrollment ratios reach 50 percent. This shows that the stress on the universalization of 9 years compulsory education laid by the Chinese government in recent decades has paved the way for forms of mass higher education. China’s higher education will and should have a rapid growth in the coming decades. 338
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THE WORLD’S LARGEST POPULATION Compared to some of its neighbors such as Japan and Korea, China lags behind in the participation of its population in higher education. As early as the 1950s, India had already built up one of the largest higher education systems in the world with gross enrollment ratios of 1 percent in 1950 and 8.19 percent in 1970. From 1970 to 1996, Indian higher education student numbers increased three times. Within the same period, students increased 2.2 times in Japan and 1.8 times in the United States. However, the gross enrollment ratios increased 159 and 71 percent in Japan and the United States, respectively, while they decreased 6.9 percent in India. The reason was directly linked to population growth: while the age cohorts declined in Japan and the United States, they climbed in India far more rapidly than the increase of university student numbers. India would have long reached mass higher education stage if the Indian population had grown less rapidly. The Indian past could also represent the Chinese prologue. China currently has the world’s largest population. However, according to the 2000 Census of China, only 36.09 percent of the Chinese population live in urban areas (Population Census Office, 2001). By 2000, five million were still in poverty, particularly in rural regions. Although China has maintained a fairly rapid economic growth, its urbanization proceeds relatively slowly, with huge amount of surplus labor to be transferred. At the same time, a large number of laid-off workers from state-owned enterprises are waiting for reemployment in urban areas. All these demand careful management, with control over population growth on the one hand and rapid development of post-secondary vocational–technical education on the other. Any strategic decision on massification of higher education in China will need to take population factors into serious account. As a developing country with a large population, the path to mass higher education is doomed to be rough and bumpy.
STRATEGIC CHOICES Currently, there are heated debates in China in relation to the appropriate approaches to a smooth transformation from elite to mass higher education. While it is widely accepted that mass higher education is approaching fast, issues including the structure, financing, expansion and 339
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regional balance in higher education are open to question. A further scrutiny reveals that even at a more fundamental level, the arguments are in diametric contradiction to each other. For example, while some insist that mass higher education does not suit China because of China’s less solid national strength, many others criticize this viewpoint and see China’s adoption of mass higher education as “a strategic choice”, or even “the only way” (Xie, 2001, pp. 2–3). Other issues such as the relationship between higher education expansion, economic growth, and funding sources for higher education are also contested. Some key issues identified by the Chinese are reported and analyzed below, together with some disparities and similarities compared to the practice in other countries. These are suggestions about potential strategies. SHIFTING TOWARDS VOCATIONALISM It has been shown by the previous experience of various countries, developed and developing, that mass higher education aims primarily at training professional personnel to meet societal demands. The vocational function of higher education has introduced mass and universal higher education into society, at the same time draws elite higher education institutions closer to practical needs, and thus has strengthened the adaptability of the whole higher education sector. The service function of mass and universal higher education institutions caters for the rising social demand for higher education opportunities on the one hand, and protects teaching and research usually conducted in research universities at higher levels. The shift toward vocationalism and mass forms in higher education echo each other to demonstrate the demand of new modes of economic production in what is referred to as the “knowledge society”. China’s secondary school graduates who do not score highly enough to gain admission to a 4-year, degree-granting university may opt to enter a variety of other post-secondary education institutions. Non-university post-secondary institutions in China are a new type of regular institutions. They resemble American community colleges to some extent. Such institutions include workers’ colleges, upper-level specialized colleges (dazhuan) and vocational–technical colleges (gaodeng zhiye jishu xueyuan). Most have a two/three-year program designed to be terminal in nature, leading to a diploma. China’s post-secondary vocational–technical education did not start to take root until the early 1980s when many localities established their 340
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post-secondary institutions to train skilled professionals, technicians and managers badly needed by regional economies at the intermediate level and in the localities.7 Before the 1980s, neither the national nor the provincial institutions would consider the need for these types of jobs. The non-university institutions possess some unique features that differ from other Chinese higher education institutions. They are locally administrated and primarily financed at the city level, with comprehensive curricula and short-cycle programs that are vocational–technical in nature. Their programs are closely linked to local industry and business needs and include optometry, tourism, horticulture, industrial arts and crafts, commodity inspection and maintenance, and nursing, to name only a few. Knowledge of a particular field and demonstrated applied skill in the field are the required dual qualifications for faculty members at these institutions. Most of the institutions have found it difficult to recruit sufficient qualified full-time faculty, and therefore employ many part-time members. The funding sources for these institutions are various. Annual appropriation from the city governments based on student head count is the major one, together with tuition and fees. Other non-regular financial supports come from business sectors, overseas Chinese and international organizations. They also depend on individuals for donations of books, facilities and other teaching-related materials. Most recently, funds generated from providing training services to local enterprises are a growing source of support. After over 20 years construction, China had 161 post-secondary vocational–technical institutions with 234,000 enrollments in 1999. These institutions join adult post-secondary institutes and 3-year specialized colleges to enroll about one-third of the post-secondary student population, totaling 3,986,000 in 1999 (Table 8.6). China’s Tenth Five-Year Plan (2001–2005) attached greater importance to the high-tech industry. Within a wider pattern of global economic competition, China’s effective participation relies heavily on how it manages the interaction between information technology, knowledge production,
7 The contemporary cities in China are ranked in three kinds according to their administrative levels: the county level, the prefecture level and the province/autonomous region level. The size of the cities at the prefecture level is medium. These cities play a significant role in regional development. They are thus called zongxing chengshi (central cities). In the 1980s of the last century, many new types of post-secondary institutions emerged in these cities, particularly in more developed provinces such as Guangdong. The institutions are under the jurisdiction of the local city governments.
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Type
First-year Total Enrollments Graduates Enrollments Institutions (thousand) (thousand) (thousand)
Adult higher education
772
1,561.5
880.4
3,536.4
Three-year specialized programs Upper-level specialized college
442
486.86
178.46
1,008.69
Upper-level vocational–technical
184
194.33
42.45
361.77
1,398
2,242.69
1,101.31
4,906.87
77.11%
41.17%
60.17%
52.21%
Total Proportion to the whole higher education
Source: www.edu.cn/20011219/3014655.shtml on October 11, 2001.
human resources, and institutions. The new modes of China’s economic production will be increasingly dependent on knowledge and information technology. If knowledge is the electricity of the new information international economy, then Chinese institutions of higher education will be the power sources on which a new development process must rely. At present, vocational–technical institutions have a particularly significant role to play. China’s authorities now place great value on vocational–technical education. The Action Plan to Vitalize Education in the 21st century requires that vocational and adult education be further developed to train a large number of junior- and middle-level professional and skilled workers (Guangming Daily, February 25, 1999, p. 3). However, while Chinese societies have been well known for their emphasis on education, Chinese parents and students generally view vocational–technical colleges as a second choice to universities. Compared to the traditional elite higher education, post-secondary vocational–technical education often meets frosty reception in the upsurge of university enrollment expansion. In Henan, for example, only about half of those who received admission notice from post-secondary vocational–technical institutions registered finally in 1999. The percentages were similar in 342
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Shaanxi and Jilin (China Education Daily, January 10, 2000, p. 3). When postsecondary vocational–technical institutions in Beijing planned to recruit 1,755 students to 3-year specialized college programs in 2000, they only received 1,100 applications (China Education Daily, June 14, 2000, p. 1). There are some direct reasons for the depressing state of postsecondary vocational–technical education. First, many post-secondary vocational–technical institutions started hastily. Little is known about them. This is especially the case with those vocational–technical programs offered by universities. In early 1999, for example, many universities received notice to start the programs within that year. Second, there has been a deviation in enrollment policy. Vocational–technical institutions were required to recruit students after other institutions, leaving the populace with an impression of inferiority. Third, tuitions of Chinese post-secondary vocational–technical institutions are unreasonably high, often two to three times more than the average annual tuition for undergraduate education at a university. Fourth, many vocational–technical institutions emulate universities in designing their programs, which are not sufficiently vocational–technical, and even become the compressed undergraduate programs. Fifth, vocational–technical education at diploma level lacks integration with undergraduate and graduate programs. The above-mentioned factors collectively exert a strong impact on China’s post-secondary vocational–technical education. The present situation is that while the government hankers for expansion in the vocational–technical part of post-secondary education, response from the society has been cold. Overall, post-secondary vocational–technical education oriented to societal demands walks haltingly on its way to growth. A further scrutiny into the unimpressive development in China’s postsecondary vocational–technical education reveals some reasons for their slow growth at more fundamental levels. First, vocational–technical institutions that are designated to be oriented to societal needs and to train skilled technicians who will develop, implement, operate and maintain the new technologies in a knowledge society still adhere to the elite intellectual and scientific culture that only benefits the privileged (Scott, 1995). Many vocational–technical institutions are offering programs leading to a diploma, but they call themselves a university.8 If given the choice, 8
By the close of the 1980s, the Ministry of Education urged 2/3-year specialized colleges, of which many had named themselves as a university, to rename themselves as colleges. Many of them, however, still translate their names as universities in their English version web sites, for example.
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directors of these institutions would choose to upgrade themselves to 4-year universities, rather than to become 2-year colleges. Such a mindset has its deep roots in the Confucian culture. Second, post-secondary vocational–technical education is still much divorced from localities whether or not to expand and to what extent they are in the control of the central government. With all the rhetoric of decentralization and institutional autonomy, the Chinese higher educational system remains highly centralized. For example, within the 47 percent enrollment expansion in 1999, while many 4-year universities including those research-intensive key institutions were assigned specific overload quotas,9 many vocationally oriented institutions, private or public, could not recruit a sufficient number of students. Third, Chinese post-secondary vocational–technical education has not been well integrated with other parts of the whole higher education sector. The practice of transferring from these institutions to universities does not exist in China, although there is discussion about its merits. There are, however, some encouraging signs of new developments. In 2000, Anhui recruited 5,000 students in an experimental 5-year vocational program built on a post-secondary vocational–technical program (China Education Daily, June 9, 2000, p. 1). Shanghai accepted students from vocational–technical institutions to join undergraduate classes in regular higher learning institutions in the middle of courses (China Education Daily, May 31, 2000, p. 1). Jiangxi has removed the obstacle to entry into undergraduate programs from vocational–technical diploma programs (China Education Daily, June 21, 2000, p. 1). In Tianjin, local communities are increasingly encouraged to participate in the development of post-secondary vocational–technical education (China Education Daily, April 3, 2000, p. 1). DIVERSIFYING POST-SECONDARY EDUCATION SYSTEM A diversified system has proved to be a necessary approach to strengthening the shift from elite to mass higher education by the practical experience of different nations. In response to mass higher education, 9
Overall, the administration of higher education institutions follows “vertical” and “horizontal” patterns of general public administration in the PRC. There are institutions all over the country that are administered in the “vertical” system by ministries of the central government. Most of these institutions are designated as key institutions. Another system is the “horizontal” system where institutions within a locality are administered by the local authorities mainly the provincial government.
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greater diversity of educational offerings has emerged in most countries, where different types of institutions, different lengths of study programs, and varying modes of instructional delivery have been introduced as ways to accommodate rapid enrollment expansion (El-Khawas, 1998). It is a lifelong learning system in which every sub-sector at different levels is linked to each other, with a variety of students and curricula. A completely diversified higher education system serves different purposes: (1) it provides lower strata with easier access to post-secondary education at a lower unit cost, and therefore softens tensions between classes; (2) it increases the participation of traditional disadvantaged groups in post-secondary education; (3) it raises the education level of the masses and further improves their employability. Research has shown that education level is in inverse proportion to unemployment. Modern mass higher education teaches people not to become too closely devoted to one occupation or a single set of skills. It prepares them for changes (Gibbons, 1998). A diversified post-secondary education system then pushes massification of higher education to become a central focus of the society. There is a shift from elite to mass forms of higher education. It has led to the erosion of the elite intellectual and scientific culture. Mass higher education systems necessarily have lower unit costs than elite systems because they have to cater for much larger numbers of students and because they cannot make the same claim to privileged treatment. It is in this vein that Martin Trow (1973) criticized the modern British elite higher education model. A diversified higher education system both safeguards and substantializes massification of higher education. A diversified post-secondary education system is a practical option necessarily determined by China’s national conditions. In 1999 alone, China admitted some 2.8 million new students into higher education. China claims that it educates one-quarter of the world’s students on 1 percent of the world’s education budget (National Center for Education Development Research, 2001, p. 4). According to the experience of various countries, the growth of mass system is taking place against a background of socioeconomic transformation that is both rapid and profound. Mass higher education is more than the linear successor of elite higher education because sociologically and epistemologically it represents a break with past continuities (Scott, 1995, p. 172). New institutions emerge in the process of massification, reflecting the participation of new social forces in higher education and demonstrating varying demands from the mass for higher education. 345
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Although China’s higher education is only in the transitional premass stage between elite and mass higher education, most of the education models and ideas originated in industrialized nations have already been introduced into China. As a latecomer massification of higher education, China can select from a wide range of successful practices in other nations, shorten its exploratory period, and create its own model to achieve mass higher education. A diversified post-secondary education system should be based squarely on the current condition of China. To achieve this goal, two major strategies have been identified. Particular Functions Performed in Different Directions The global economy is altering the nature of research, touching the heartland of the university, its modes of organization, and its core values. For a long time, universities have sought to establish themselves as the prime institutions for carrying out basic research, while applied research was left to government or industrial laboratories. Now the global nature of knowledge production is rendering this institutional division of labor less and less relevant (Gibbons, 1998). The tendency to vocationalism is especially evident in mass higher education systems. To be oriented to vocationalism, mass higher education needs to target directly socio-economic needs. While it is true that universities still retain their role as the “conscience of society”, the critical function of universities have been displayed in favor of a more pragmatic role in terms of the provision of qualified manpower and the production of knowledge. Chinese universities are increasingly required to be relevant. Such a view, judged primarily in relation to their contribution to economic development, constitutes a major shift in perspective and values from the perspective presented to an earlier age by the likes of von Humboldt and Newman in the West and Confucius and Cai Yuan-pei in China.10 10
Cai Yuan-pei was one of the most influential figures in Chinese modern history of higher education. He succeeded first in passing the Chinese imperial examination. Then he went to study in Europe, mainly in Germany, for many years. Upon his return to China, Cai was briefly the minister for education in 1912, and then the Chancellor of Peking University from 1917. When he was in these positions, he embarked on a series of reforms with substantial historical significance. Peking University under Cai was the first real university. During his service at Peking University, Cai introduced the ideas of university autonomy and academic freedom, and the Humboldtian university model. For a thorough discussion, see William Duiker (1977). Ts’ai Yuan-p’ei: Educator of Modern China. University Park and London: Pennsylvania State University Press.
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As the entire post-secondary education system becomes more diversified, Chinese higher institutions themselves become more differentiated, with the inclusion of new faculties and departments representing subjects formerly excluded from traditional universities, preparing students for new or semi-professions. At present China has 1,000 strong vocational–technical institutions at junior secondary, diploma and undergraduate levels, with an intake of some 4 million students. This is a reasonable scale. Yet there have been two worrying signs in recent years: the employment difficulty faced by the graduates from these institutions, and the surprisingly low registration rate of the admitted students. The post-secondary vocational–technical education built up under the planned system has increasingly demonstrated its clumsiness to suit ever-changing demands from the rapid industrial structural adjustment in China’s transitional economy. The role of vocational–technical education within China’s postsecondary education system has not been defined clearly. This is indeed where the problem arises. Various sub-sectors and institutions of different types in higher education system need to identify their dissimilar locations and orientations. By performing their particular tasks they foster their unique sectoral and institutional characteristics: research-intensive universities tie themselves in with high-tech enterprises;11 provincial teaching universities partner regional trades in varying industrial collaborative projects in the light of local conditions; vocational–technical institutions work closely with enterprises to provide the much-needed training to produce skilled technicians to support technological and industrial development. Attacks on Segmentation Like many developing countries where the higher education system is at crossroads between an elite higher education and a completely mass higher education system, such as Brazil (Eisemon and Holm-Nielsen, 1995) and Chile (World Bank, 1998), China’s higher education system is still fairly segmented. Transfer between the different institutional levels is limited, hampering the aspirations of learners and affecting equity, as well as linkages with the public sectors, and regional development. 11 At present, such a tie often takes the form of building up scientific parks. However, many of these parks have failed to attract investment from high-tech companies as shown similarly by the American experience from 1975 to 1985.
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A diversified higher education system, however, has begun to take shape in China, with a wide range of post-secondary institutions from public to private institutes covering regular, adult, television and radio institutions, and examination-based self-study higher education. Nevertheless, a coherent linkage between them is still lacking. In addition to the aforementioned impasse for graduates from vocational–technical specialized colleges to enroll for university undergraduate programs, there has been little link at the diploma level between adult, television and radio institutions, and examination-based self-study higher education. In effect, such a close system drives most secondary school graduates to swarm towards traditional elite universities with little regard to vocational–technical institutions. In 2000, for example, while public universities had to raise entrance ranks to sift out large number of candidates, many vocational–technical and private institutions could hardly find sufficient number of applicants. One private university planned to recruit 400 students into its undergraduate programs, only 6 candidates applied. Such a fact has substantially reduced the function of non-regular institutions to relax the tension between societal demand and higher education supply. At the same time, research universities are forced to overtake students, while their teaching and research work are much affected. Such a system further strengthens the “malposition” phenomenon: while institutions at lower levels strive to reach university status and even deliver postgraduate education to heighten their social reputation, universities, including some prestigious ones, exploit their brand effect to offer programs at lower levels to attract tuition and fees from students. This will inevitably affect China’s massification of higher education by bogging it down in a quagmire in an “expansion of traditional elite higher education”. As shown particularly clearly by the modern British history of higher education, there could be sharp conflicts between the notions of mass and elite higher education. Higher institutions oriented to utilitarian needs were established, assimilated later by traditional elite universities, and then upgraded to become traditional universities. As a result, the massification of British higher education was substantially delayed. Such a historical lesson has much to teach the Chinese. Special attention needs to be given to societal practical demands and individual students’ development. Obstacles to the linkage between various sub-sectors in higher education must be removed. Graduates from vocational–technical institutions should have opportunities to further their studies if they wish. Such measures can 348
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benefit the development of vocational–technical institutions by increasing their student numbers and by strengthening their contributions to local needs. In a nutshell, once the diversity of educational offerings has been expanded, the adaptability of the higher education sector will be enhanced and the rapid expansion of higher education scale can be maintained. It is also important to note that such a diversified, internally opened system cannot be sophisticated overnight. Its implementation also relies on the equilibrium of supply and demand, and on the harmonization between quantitative and qualitative development. TRANSFORMING MODES OF GOVERNANCE The increasing interdependence and connectedness of nation-states have made the state a declining autonomous decision-making body (Mok, 2001). The role of the nation-states has had a fundamental change from a “provider of welfare benefits” to a “builder of market roles” (Sbragia, 2000). Introducing market principles and practices to manage the public sector has inevitably transformed society into an “audit society” (Power, 1997), or “performative society” (Ball, 2000), turning the traditional welfare states into “competitive states” (Cerny, 1996), or “evaluative states” which attach importance to effectiveness, efficiency, and economy in public sector management (Henkel, 1998; Kogan and Hanney, 2000). It is against such a global policy context that higher education has become a tool for achieving an integrated global system along market lines (Ball, 1998). The change in governance ideology in higher education has altered the ways in which universities are managed (Slaughter and Leslie, 1997; Braun and Merrien, 1999). Due to the influence of supranational organizations including the World Bank and with China’s recent entry into the WTO, market ideologies are becoming popular in the Chinese higher education circles, regarded either as correct or as inevitable. Proponents of such ideologies believe that no government is able to pay fully for the transition from elite to mass and from mass to near universal higher education, so that for quality to be maintained institutions are going to have to generate an increasing amount of resources either from students or from other private sources. However, this is just not accurate. There are a number of countries now defying these ideas and thus create space for more skepticism about market ideologies. Norway and many European countries, for instance, 349
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have free higher education and have mass education systems. Norway’s enrollments are now greater than the United States. Germany has in its constitution to provide free education. German universities cannot even charge foreign students. France also has very small tuition fees. Both France and Germany have large populations with very high enrollments, almost reaching the US levels. In spite of the striking differences, the experience of many countries has generally indicated a necessary combination of private and public funding sources in the process of higher education massification. For example, the United Kingdom and the United States both chose to rely on public funding after World War II to strengthen the role of the state in order to quicken their steps toward mass higher education. The proportion of British government contribution to higher education funding increased from 35 percent in 1940 to 72 percent in 1965, and 78 percent in 1975 (Trow, 1978, p. 42). In the United States, the proportion of government funding was 31.6 percent in 1909–10, 37.5 percent in 1939–40, 58 percent in 1969–70, and 51.3 percent in 1989–90 (National Center for Education Statistics, 1993, p. 89). Japan and Korea, however, relied much on private higher institutions to achieve massification of higher education. This was not achieved by altering traditional universities. Instead, new types of institutions were established to suit the massive demand from society. Furthermore, their reliance on private institutions was on condition that public higher education had been the dominating force in the societies. These different experiences show that within the process of higher education massification, new forces emerge to work together with, rather than replace, traditional forces. Mass higher education demands contributions made by a variety of forces in a society. For China, a developing country still restricted strongly by the lingering impact of longstanding “socialist” public ownership, one practical approach to mass higher education is to diversify its channels for resources. Therefore, private institutions are bound to play a significant role. Based on historical lessons and practical conditions, China started to transform from elite to mass higher education in the late 1950s with fixed targets and clearly defined plans. The motive force was socialist construction, in which the state was almost the single provider of funding. China’s previous experience in the 1950s and 1960s admonishes us of the insolvency of the state alone to bear this task. One major reason for the relatively smooth development in the 1980s and 1990s is the diversification of 350
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resource channels via donation from society, enterprises, public institutions, and individuals. Universities are increasingly urged to cooperate with the private sector, and respond to market needs (World Bank, 1997, p. 43). Indeed, the private sector is becoming increasingly evident in China both within and without higher education (Bray, 1998). Another crucial restricting factor of mass higher education development in China is its current national condition. China has 1.265 billion people as of November 1, 2000, of which about 10 percent are full-time students and 63.91 percent are in rural areas (Population Census Office, 2001). The PRC accounts for approximately 21 percent of the human population. China is still the most populous nation, a title it will not cede to India for another 4–5 decades. Millions of Chinese are still living below the absolute poverty line. Meanwhile, under the impact of global market forces, there has been a general trend toward the reduction of per capita public funding to higher education, despite the continuing increase in student enrollments (Johnstone, 1998). Money everywhere is scarce. For example, state appropriations for higher education, the single largest source of public funding for higher education in the United States, has declined a whopping 8.7 percent in just over a decade. China is no exception. The burden of funding higher education is being shifted more and more to the shoulders of the individual. Nongovernmental funding sources are becoming crucial. Private institutions are resurging like bamboo shoots after a spring rain, as it is often referred to in China. There are already over 1,400 minban colleges and universities serving over 1 million students. However, only 37 are permitted by the Ministry of Education to confer diplomas, and of these, only 4 can confer Bachelor degrees, while 157 have been allowed to experiment in providing higher education (Xie, 2001, p. 184). Although those that have been accredited by the central government only consist of a small part, the total number of private institutions is growing fast, and their status is becoming increasingly legitimate. In consideration of future goals and current conditions, China has adopted the following specific approaches to mass forms of higher education. Their long-term repercussions, however, remain to be seen. First, individuals and enterprises are encouraged more to establish postsecondary institutions. At present, when a private institution is founded, it is hard to attend to each and every aspect of a matter. It is the responsibility of the Chinese governments at various levels to give support to improve the 351
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institution’s operation. To achieve this, some specific policies and regulations are called for. With the newly issued Higher Education Law (Gaodeng Jiaoyu Fa), China has made a good start in this regard. Second, within one single institution, it is now possible to operate on a basis of one university two systems. A private institution can be built up with affiliation to a public university. By so doing, the parent university can be directly involved in the quality assurance at its affiliated private institution, while graduates from the institution can be conferred qualifications by the parent university. By 2000, there had been more than 10 such institutions scattered in Guangdong, Jiangshu and Zhejiang, with Shichuan and Fujian following suit closely. Third, education shares are being tried out. The stock market is closely associated with the free market economy. Education shares have been reported as an effective way to raise education funds. Some private institutions are operated as businesses. According to a few publications in China, this can improve teachers’ morale and help maintain the stable development of these institutions. One typical example is Hualian University at Guangzhou, which successfully solved its funding problems and has financially benefited its shareholders (Xie, 2001, p. 186). In 1998, Zhejiang formulated a policy to specifically allow funds to be raised by means of education shares.
GIVING EFFICIENCY THE HIGHEST PRIORITY Disparities in receiving higher education between different geographical areas and social classes are evident in the process of massification in many countries. At present, while 30–40 percent of the age cohorts in major cities has an opportunity to receive higher education, the percentage in remote areas is between 3 and 5 percent. Historically, disparities between urban and rural areas and between the rich and the poor have been a longstanding issue in China. According to 1931 statistics, 80 percent of the 103 higher institutions were concentrated in the coastal provinces in the east, the two biggest cities, Shanghai and Beiping (Beijing), both had 37 (36 percent), only 9 (8.7 percent) institutions were in Western provinces including Guangxi, Guizhou, Shichuan, and Suiyuan (Inner Mongolia) (Xie, 2001, p. 208). At the initial stage of the PRC, when the communist government worked out its plans for national construction and education development, 352
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the whole nation was divided into coastal and interior regions. Some departments in the big cities in the coastal east were moved to inland medium-sized cities during the 1950s reorganizations. The reform was targeted at reducing disparities and at ensuring that higher education was available to students from workers’ and peasants’ families (He, 1998, pp. 92–93). Within the period, Shanghai higher institutions decreased from 37 in 1949 to 15 in 1953, while institutions in Guangdong and Fujian changed from 12 to 7 and 8 to 4, respectively. Meanwhile, inland institutions increased considerably, from 3 to 7 in Shaanxi, 2 to 4 in Inner Mongolia (Ministry of Education, 1979, p. 214). As a result, the gap in higher education development between the coastal and inland areas was reduced. More opportunities were created for cadres and youth from workers’ and peasant families. The People’s University of China, for example, recruited 2,981 such students (He, 1998, p. 92). According to a national survey, in the 1950s and 1960s, university students from workers’ and peasants’ family backgrounds increased substantially: the proportion of university students from peasants families to the national intake changed from 16.5 percent in 1952 to 39.5 percent in 1960, and 53.8 percent in 1965 (Ministry of Education, 1979, p. 85). Starting from the 1960s in the last century, from a national defense point of view, the Chinese government divided the whole country into three lines: the frontline were coastal eastern provinces, the second and the third lines included Hunan, Sichuan, Guizhou, Guangxi, Hubei, Shaanxi, Ganshu, Ningxia, Hebei, and 10 other provinces. About 62.7 percent of the national infrastructure construction was transferred to the third line. Despite its lower economic effectiveness, such a strategy acted as a strong dynamic to promote higher education growth in the inland, with the highest in the far west region. Since the late 1970s, China set its targets at modernization. The geographical advantage of the coastal east was again exploited. Accordingly, policy privileges were given to the east. From 1985 to 1995, 87.3 percent of national foreign investment was in the east, while only 8.5 and 4.2 percent went to the central and western regions, respectively (Wei, 1997, pp. 10–11). Meanwhile, great disparities also existed among western provinces. Correspondingly, higher education development was again imbalanced. This was further fuelled by two factors: first, education reforms have been aimed at devolution and decentralization. With regional economic development, higher education development was linked closely to 353
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the regional economic situation, and therefore widened the gap between different regional higher education systems. For example, while the proportion of students grew rapidly in Beijing, Shanghai and Tianjing from 1978 to 2000, the difference between these major centers and the remote areas including Tibet, Ganshu, Qinghai, Ningxia and Guizhou, is widening even more strikingly than that of 1931. Second, the move towards marketization has increased the capacity of local governments in exercising their influence on higher education development, especially via financing. The funding for every student differs considerably from region to region. Those in more affluent areas such as Shanghai and Guangdong are often three times more than that in the inland provinces (Xie, 2001, p. 215). This has contributed greatly to imbalanced regional higher education development. Within the Chinese academic circle, regional higher education development has been a matter for debate. Despite the ongoing controversy among academics, disparities have become a serious concern of the government as a threat to social stability. Under the intervention of the central government, a variety of measures have been taken to promote higher education development in the west. They are further enhanced by China’s current ambitious plan to develop its western region (China Education Daily, April 27, 2000, p. 1; March 5, 2001, pp. 1–2; June 13, 2001, p. 2). However, due to various historical and contemporary reasons, the situation cannot be changed overnight. It may even become worse before it gets better. Nationwide, higher education will develop far more vigorously in the thriving export-oriented coastal zones than that in the interior. In consideration of the great variation across provinces according to available human, financial and material resources, the central government will not try to restrain the rapid higher education growth in the east, while giving special regard to the development in the west, a strategic plan commonly referred to as “efficiency claims precedence and fairness is to be taken into consideration also” (xiaolü youxian jiangu gongping). To achieve this, two measures were adopted: First, major efforts were being devoted to developing examinationbased self-study higher education. The education opportunities provided by regular universities are normally for the youth with urban family background, only one-sixth were rural youth. Research has revealed that city youth were, respectively, 9.6–12.8 and 5.8 times more likely to receive higher education than their peers in rural areas in the 1980s and 1990s (Xie, 2001, pp. 218–219). For female rural youth, chance is even slimmer. 354
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In order to improve the participation of socially disadvantaged groups, to simply rely on government special enrollment policy does not suffice. New creative methods are in great demand. Examination-based self-study higher education is certainly a realistic, effective way. According to a survey in 2001, the percentage of female candidates for examination-based self-study higher education reached 58.6 percent. Also, an overwhelming proportion of examination-based self-study higher education candidates are from low-income family background. In terms of their profession, half of the candidates in 2000 were workers, peasants and unemployed youth (Xie, 2001, p. 222). All these show collectively that examination-based self-study higher education functions effectively to reduce disparities in higher education provision between geographical areas and among social classes. Second, in line with international trends, an expansion of educational offerings by distance learning was a response to mass higher education to accommodate rapid enrollment growth (El-Khawas, 1998). The Chinese government has taken distance education seriously as a means of providing higher education to the masses. The Ministry of Education plans to have 5 million students in 50–100 online colleges by 2005 (Walfish, 2001). By using modern information and communication technologies, distance education can provide more people with better access to education at various levels and more locations. These features suit China’s vast territory and striking regional disparities. In view of this, China has recently built up a distance education network in the west covering 12 provinces. China has also been trying to fully exploit the potential of the Internet since mid-1980s. The Chinese Education and Research Network (CERNET), for example, was established in 1986 to deliver qualified education all over China, with special targets at rural and remote areas.
PARADOXICAL MOVEMENTS With the recent accession to the WTO and the exponential use of the Internet, China is accelerating its integration with the rest of the world. Chinese higher education, while being ascribed as a key supporting role in the drive to modernize the nation, is gaining stronger links with the international community (Yang, 2002). It is no longer immune from international forces, and thus has to confront new challenges. One of them is to reconcile the local and the global (Yang, 2000). Against such a context, 355
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a series of paradoxical movements have been demonstrated within its present march toward mass higher education. OPPORTUNITIES LOST IN THE MASSIFICATION OF HIGHER EDUCATION The expansion of higher education scale has greatly relaxed the longstanding gap between social demand and higher education supply. Many Chinese people, especially those in affluent areas such as major cities and coastal areas, benefit much from such a rapid growth in higher education. In Beijing, for example, the municipal education commission declared that it would raise its higher education participation rate in 2001 to 70 percent of senior secondary school graduates (China Education Daily, March 24, 2001, p. 1). According to Wenhui Daily (August 16, 2001), higher education enrollment in Shanghai has reached 38.8 percent of the 18–22 ages cohort, 372,000 students are currently studying in either regular or adult higher education institutions in Shanghai, and 232 of every 10,000 Shanghai residents have received post-secondary education. In Jiangsu Province, the student population in higher education reached 480,000 with a gross enrollment ratio of 15 percent by the first half of 2001, and was over 700,000 later in the year with an intake of around 220,000 new students. At the current annual growth of 10 percent, Jiangsu is expected to have over one million university students by 2010, and thus will become China’s first province to start the transition from elite to mass higher education. Gradually, the situation that a large number of senior secondary school graduates go to various institutions to receive their post-secondary education has begun to take shape nationwide. The tension caused by thousands of senior secondary school graduates competing for a very limited number of places in universities has been lessened. However, the groups that are located at the bottom of social resource distribution with the lowest living standards are obviously losing their opportunities in this massive expansion of higher education. Enrolled Students from Poor Families China is now in transition. The transformation of its social structure has brought fast changes to social stratification (Bray and Borevskaya, 2001). This has thrown a spotlight on the disadvantaged social groups who 356
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have remained in the dark corners of China for some time. One fundamental feature of such groups is poverty (Townsend, 1979). According to a study conducted by the Chinese Academy of Social Sciences, the population of the disadvantaged social groups totaled over 80 million, 7 percent of China’s overall population (Jiang, 1996, p. 9). The issue of some university students as a disadvantaged group started in 1997 when Chinese universities began to charge students tuition and accommodation fees. This was against the background of strikingly imbalanced economic developments in different regions. In Jiangxi, 10.5 percent of the total student population within its 32 higher education institutions were from poor families, of which 5 percent of families totally lost their capacity to support their children. Similarly, 11.8 percent of the students on 27 campuses in Helongjiang were from poor families, and 4.9 percent of students were from families in absolute poverty. Such students occupied 10 percent of the total national university student population (Jiang, 1996). In teacher-training institutions, their proportion is often much larger. This is because the Chinese government has subsidized those who choose to become teachers. Such support, however, is greatly offset as Chinese universities face increasing financial difficulties and are required to raise their funds. As China’s transformation from the planned to a market economy, the workers laid-off from the previous state-owned enterprises and some people from remote areas are much disadvantaged. By the late 1990s, when student fees were considered relatively low, a student needed at least 10,000–10,500 yuan annually for a 10-month academic year. Such an amount was already astronomical to many families. Only 8 percent of students’ families could cope with the whole amount on their own, 22 percent could only manage half of the amount, and 44 percent could afford less than onethird, and 10 percent of students felt absolutely helpless with the amount (China Education Daily, March 28, 2001, p. 1). Chinese parents are well known for being hard savers for their child’s education, and the hardships they experience are often unimaginable for many of those living in affluent, industrialized nations. However, as many families are in absolute poverty, they have no way to save money and it is hard for them to borrow. In such cases, assistance from universities, although vital, cannot suffice. Without sufficient financial support, these students’ lives are under threat. The straitened circumstances also exert strong impacts on such students’ mental and social life. While many of these students face their 357
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economic difficulties courageously, some are often under great mental pressure. The Chinese governments at various levels and higher education institutions have worked together to develop some policies. Yet, within a globalized context of increasing competition, corporate managerialism, efficiency, and accountability in higher education worldwide (Tierney, 1999), “efficiency” has been given the highest priority in China. University students from poor families will continue to be a knotty issue well into the coming years. Opportunities for Receiving Higher Education in Less Developed Regions Globalization has never created global equality. In effect it makes the rich richer, guarantees the perpetuation of privilege, and maintains the caprices of the moneyed, over the very survival of those without it. Gaps between rich and poor, the haves and the have-nots, the overdeveloped and underdeveloped regions, have grown exponentially. For example, the income gap between one-fifth of the world’s people living in the richest countries and one-fifth in the poorest was 74 to one in 1997, up from 60 to one in 1990 and 30 to one in 1960 (UNDP, 1999, p. 31). Inequality has also been rising within many countries since the early 1980s. In China, disparities are widening between the thriving exportoriented coastal zones and the provinces, especially those in the interior (World Bank, 1997): the human poverty index is just under 20 percent in coastal provinces, but more than 50 percent in inland Guizhou (UNDP, 1999, p. 3). In 1995–96, while local education expenditure in China’s 8 western provinces was 3.37 percent of GDP on average, it was 1.98 percent in the costal region. The average per capita education expenditure from 1988 to 1996 was 67.59 yuan in the inland, and 210.02 yuan in major cities. China’s illiterate population remains huge. By 1994, 22.5 percent of the 430 million rural people were either real or functional illiterates. The percentages of those with primary (years 7–12), junior secondary (years 13–15) and senior secondary (16–18) education were, respectively, 38.67, 31.43 and 6.81 percent. Over 60 percent of the rural population had an education lower than six years primary education, concentrating especially in the impoverished areas largely in the far west (Zhang, 1998, pp. 47–49). Under such a scenario, it is not surprising that higher education development is poor quantitatively and qualitatively in China’s less developed areas. Despite recent spectacular economic development, 6.7 percent of the Chinese still live in poverty. They can be found in most parts of the 358
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country covering 25 of China’s 31 provinces, concentrating more in far west, where agricultural economy still dominates. In Guizhou, for example, agricultural products occupy 30.1 percent of its GDP, and 35.7 percent of the population live in poverty. Similarly, Qinghai’s agriculture weighs 23.6 percent of its GDP (Zhang, 1998, pp. 5–6). The average per capita annual income in such areas was 1,000 yuan (about 123 US dollars) in the mid-1990s. It was only 248 yuan in one county in Guizhou. While the county’s financial income was 6,280,000 yuan, its budget reached 48,490,000 yuan (Zhang, 1998, pp. 92–93). Within such underdeveloped regional economies, the best possible local investments in education are often not good enough. University fee policy, then, does not favor those living in remote areas with little money. As higher education is getting more and more expensive, the gap of higher education opportunities between the poor and the developed areas is rapidly widening. Rising tuition fees have substantially increased the difficulties of poorer families in sending their children to universities. A survey shows that many Shanghai parents are budgeting well over an annual amount of 10,000 yuan for their child’s university education based on the current expenditure (China Education Daily, March 28, 2001, p. 1). Such an amount is incredibly astronomical to many families in China’s vast less developed areas. Even for those already enrolled, it is extremely difficult to finish their university education. The widening regional gap most affects impoverished areas, which are often minority regions too. For instance, by the end of 2000, the number of students studying in higher education institutions in Tibet was 5400, whereas in 2001, 38.8 percent of the 18–22 age cohorts went to universities in Shanghai, and 70 percent of senior secondary school graduates went directly to universities in Beijing. Regional imbalance becomes even more serious as the market economy further settles in China. Nonetheless, social justice issues are not the first priority of the current strategy for higher education development (Price, 1997). Such a policy orientation seems to be justified in an international context that central governments devolve authority to lower levels in the hierarchy to “pass the buck” (Bray and Borevskaya, 2001). To make the situation in poorer areas worse, China is still practicing a discriminative university student admission policy, which gives preferences to students from major cities (China Education Daily, March 9, 2002, p. 1). Top institutions adopt a quota system and admission requirements that favor local students. Such a quota system has existed in China for 359
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many years. Nowadays, as academic qualifications become more important in China’s job market, this discriminative admission policy further widens the gap of receiving higher education in different regions (South China Morning Post, August 8, 2001, p. 3). SCHOLARLY ADVANCEMENT WITHIN A MARGINALIZED RANGE China was once an ancient giant in world science and technology. In the contemporary international knowledge system, however, China has been much marginalized. The overall picture of China’s research strength in the system is mixed, [a “giant periphery” as Altbach (1998, pp. 189–197) has referred to]. While China is catching up rapidly with the world cutting-edge in some academic fields with an increasing number of internationally active scholars, its scholarship is still largely unrecognized, and far from integrated with the world mainstream. Government-Initiated Projects To catch up with and surpass the world’s advanced levels has long been the fundamental theme in many spheres of China’s modernization. It is neither a wholly novel, nor primarily contemporary social phenomenon in the higher education sector. Nevertheless, there are striking novelties in the officially defined target to build up world-class universities in China. “Worldclass university” has already become a buzzword within the past five years or so. On the campuses of major Chinese universities, pictures and slogans on this theme can hardly be missed at university main entrances, on the wall of major buildings, and even along crane arms at university construction sites. Such endeavors have been legitimized since President Jiang Ze-min’s calls to have quite a few first-rate universities of international advanced level in his speech at the conference celebrating Peking University’s centenary. Towards this end, Chinese governments at different levels have taken various administrative and financial initiatives. Among them, the most prominent are the “211 Project” and the plan to build up key national bases for humanities and social sciences research in regular higher education institutions. The “211 Project” The “211 Project” is the Chinese government’s recent endeavor aimed at strengthening about 100 institutions of higher education and key 360
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disciplinary areas as a national priority for the 21st century. It is an important measure to facilitate the development of higher education in the context of the country’s advancement in social and economic fields (Christiansen, 1996). Primarily aiming at training high-level professional manpower to implement the national strategy for social and economic development, the project consists of three major components for development: the overall institutional capacity, key disciplinary areas, and public service systems of higher education (China Education Daily, December 7, 2001, pp. 2–3). The implementation mode of the “211 Project” deserves our particular attention in understanding China’s march toward mass higher education. The project is mainly oriented to economic development. Its focus has been almost exclusively on research-intensive universities. A small number of key disciplinary areas and other development projects are accommodated in other institutions of higher learning. The project is under the direct guidance of the Central Committee of the CCP and the State Council, and with the coordination of the State Planning Commission, and the Ministries of Education and Finance. The funding required for the project can be generated through a cofinancing mechanism involving the State, local governments and higher educational institutions. In line with the existing administrative system of higher education, funding mainly comes from the central departments and the local governments that have the jurisdiction over the universities concerned. So far, 98 institutions of higher learning nationwide have gone through sector preliminary examination as scheduled; 602 key disciplinary areas have been identified; among them, 62 (10.1 percent) are from social sciences and humanities, 57 (9.5 percent) economics and law, 89 (15 percent) basic science, 42 (7 percent) environmental resources, 255 (42.4 percent) industry and hightech, 66 (10.6 percent) medicine and nursing, and 31 (5.1 percent) from agriculture. The overall investment during the Ninth Five-Year Plan was 110.37 billion yuan. In addition, 73.32 billion yuan complimentary investment on construction and facilities was raised. By August 31, 2000, the actual investment reached 150 billion yuan (China Education Daily, February 8, 2001, p. 1). Building up Key National Bases for Humanities and Social Sciences Research When confronted with an international context, one urgent task for Chinese universities is to improve their levels of internationalization in the 361
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humanities and social sciences. Due to the varied ideologies, paradigms, and discourses inherent in these fields and the high dependency on language to convey their meanings, dialogue with the international community is needed. The integration of social studies with the international community has attracted the government’s attention with its move to restructure research strengths and infrastructure in humanities and social sciences. In June 1999, the Ministry of Education issued the Plan to Build up Key National Bases for Humanities and Social Sciences Research in Regular Higher Education Institutions (Putong Gaodeng Xuexiao Renwen Shehui Kexue Zhongdian Yanjiu Jidi Jianshe Jihua). The plan included a selection of about 100 leading research centers in the country, chosen for their relevance to economic and social development and to higher education reform; provision of spadework for future development by reforming the existing administration system — including initiating major projects, allocating funds and grants, and supervision; and improvement of the overall research capacity of these listed centers to cutting-edge level, and thus ensuring a substantial international reputation. To achieve these targets, three stages have been scheduled to implement the plan. Step one (1999–2000) focused exclusively on identifying 103 centers of research excellence. Step two (2001–05) includes comprehensive policy implementation. This stage aims in particular to ensure that the overall research strength of the selected centers achieves leading level within China by 2005. Those failing to do so will be excluded from the plan, and new centers with recent excellent performance in similar areas will be added. The final stage will start in 2006. The plan has been in operation for two years and has yielded intense competition among universities, which is welcomed by the Chinese government. This echoes the global paradigm shift in public management, as manifested by a more individualistic, competitive, and entrepreneurial approach (Robertson and Dale, 2000). According to the Ministry of Education, such competition helps use financial and human resources at different levels where they are needed most. Those 103 listed centers are spread across 40 universities, of which 27 are under direct administration of the Ministry, and 13 are under other ministries and provincial governments. The plan echoes an international trend in educational restructuring: ongoing devolution in finance and administration with increasing central government influence in curricula (O’Donoghue and Dimmock, 1998). This major initiative to promote research deserves our particular attention 362
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as China’s scholars in the humanities and social sciences have achieved far less international visibility than their colleagues in engineering and the natural sciences. The humanities and social sciences, however, serve as a more accurate barometer of the extent of China’s progress in the internationalization of higher education (Yang, 2003). Achievements, Burden and the Road Ahead Within the past two decades, China has had a great leap forward to a substantial role in the hierarchy of international scientific powers, competitive with Spain, Switzerland, and Sweden by the late 1990s (Zhong, 1998, pp. 61–62). In 2001, there were altogether 1,399,776 sci-tech theses published in the world. Among them, 49,678 were produced by scientists from mainland China, an increase by 7.6 percent ranking the world 8th (People’s Daily, February 1, 2002, p. 1). China’s edge is in the quality of its students. Chinese universities draw from a huge gene pool. Some seven million Chinese apply for places annually. Every year, about 20,000 students from mainland China enter top-notch overseas universities. Increasingly they return home to help build a modern economy, a phenomenon the government is trying to foster. Many Chinese universities target the world’s leading Chinese researchers to attract them back to their institutions. Internationally active scholars are not rare to find. With such considerable achievements, it is worth asking how China’s higher education institutions rate against their international rivals. Asiaweek’s (2002, p. 2) recent ranking reveals that in research and international recognition, Chinese universities are lagging behind some of their Asian counterparts, not to mention how they compare to world leading universities in industrialized countries. Life science as one of the most important part of the contemporary science and technology can serve here as a stark example. To date, Chinese scholars have produced very few research articles in the leading journals in this field. Reasons are many, including their lack of English language proficiency, and the likely prejudices of Western editors. It is, however, the low-level research capacity and the shortage of creative thinking that are to blame. In 2000, Nature published 205 articles from Germany, 105 from Japan, 62 from Switzerland, 49 from Australia, 35 from Sweden, 17 from Austria, and 7 from China. Science published 71 articles from Japan, and 7 from China. In 2001, five mainland and three Hong Kong scholars published articles in the most prestigious life science journals: three 363
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appeared with Science, three in Nature Genetics, and one in Nature Neuroscience (Rao, 2002, p. 91). These numbers show that on one hand researchers from mainland China have made encouraging achievements, which are closely related to China’s recent economic growth and the increasing investment in science, technology, and education. The fact that most of these articles came from a handful of institutions shows the direct association with various Chinese government-initiated projects to promote knowledge innovations. On the other hand, these numbers demonstrate that catching up with the world cutting-edges in science and technology remains an arduous task, and arguably, except for a few special cases, a far dream in present China. Within China, the situation is highly differentiated. Internal differentiation among various disciplines demands attention. The aforementioned achievement is largely confined to natural sciences and technology. China’s humanities and social sciences scholars have not achieved the emerging visibility of their natural sciences and engineering peers in the international community. The numbers of publications reported by international citation indices, which have become increasingly important in the assessment of research at institutional, departmental, and individual levels, however, have not been popularly employed as an effective means in the social sciences precisely because too few publications produced by Chinese social scientists appear in internationally reputable journals (Yang, 2003). Within the current framework of international knowledge system, any knowledge that does not belong within the system is not knowledge, simply because it is not circulated internationally. This explains why indigenous Chinese scholarship is not treated seriously. To avoid being marginalized yields the following dilemma for Chinese scholars: on one hand there is no effective way to avoid marginalization except by joining the world community which leads to reliance on foreign scholars and returned students in the process of knowledge transfer and intellectual contacts; on the other hand, this yields increased dependence on the international knowledge network, and in some ways reinforces China’s peripheral status, by emphasizing the mainstream international knowledge (Altbach, 1998), at the expense of indigenous forms of scholarship and understanding. Chinese researchers in the social sciences and humanities, in particular, face a challenge of paradigm shifts from the traditional Chinese to the most internationally accepted Western. This does not mean negation 364
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of Chinese traditions; but even the further development of Chinese research traditions should be on the grounds of a mastery of the Western tradition too (Yang, 2003). The transition will certainly not be easy. Indeed the difficulty has caused some to flinch (The Australian, January 23, 2002, p. 29).
FINANCIAL STRINGENCY WITH HEAVY INVESTMENTS Under the impact of globalizing market forces, higher education is being asked to be more accountable for how its diminishing portion of public financial support is spent (Altbach and Peterson, 1999). A major change has occurred in the evaluation of university performance, with a government initiative toward a more competitive allocation of operation funds (Taylor et al., 1998). Parallel to financial cuts is the move to privatization (Smolicz, 2000, p. 122). China’s higher education cannot immunize itself against the international context. While investment still relies heavily on national funds, diversification via donations from society, enterprises, public institutions, and individuals is being encouraged. Universities are increasingly urged to cooperate with the private sector, and respond to market needs. Students are required to pay their tuition fees. Universities are asked to raise funds from various income producing sources (Bray, 1998), and to generate their revenues as shown in Table 8.7. The professoriate is seen as a means to raise income for academic institutions. The need for universities to operate profit-making enterprises is increasing.
Table 8.7: Funding Sources for Regular Higher Education Institutions, 1998–2001 (hundred million Yuan)
Year
1998
1999
2000
2001–1998 2001 increase (times)
1. Total Percentages 2. Government investments Percentages 3. Revenues generated by higher institutions Percentages
544.8 100.0 342.6 62.9
704.2 100.0 429.5 61.0
904.2 100.0 512.7 56.7
1,166.6 100.0 613.3 52.6
1.8 ⫺0.1
202.2 37.1
274.7 39.0
391.7 43.3
553.3 47.4
2.7 0.1
365
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Unlike many countries, however, China is now investing heavily on higher education in one sense. This has taken two forms: one is through national key programs, as shown by the above-mentioned “211 Project” and the plan to build up key research centers in the humanities and social sciences. There are some other governmental initiatives including the 863 High-Tech Programs and the National Natural Sciences Fund. Many ministerial and provincial/city governments also have their projects and grants to promote research and development. A substantial proportion of such resource goes to universities. The other form is its highly discriminative policy of focusing its investment on a handful of elite universities. In 1999, Peking and Tsinghua Universities each received an extra $36 million. For the current year, each will have twice that amount on top of their regular $14.5 million allotments (South China Morning Post, August 1, 2001, pp. 2–3). The extra resources are meant for new research spending, special stipends, and housing. Such special allotments, however, are generally confined hierarchically to the prestigious universities, and geographically to those institutions in affluent coastal areas. It is now a common practice for many universities to pay selected professors extra stipends every month, with those setting up laboratories getting more. Universities often have to be in partnership with the business world to offer better welfare for their members, for instance, building apartment units for teachers and students. All of this requires resources. The government wants universities to shoulder half of their budget. The gap will have to be filled by private-sector endowments, consultancies and commercial spin-offs. Such a task is only achievable for the more prestigious universities as they have a strong research capacity to attract investment from the industry. The story of provincial universities, which form the mainstay of China’s higher education, is totally different. One direct effect of the massive enrollment increment is the huge gap between student demands and the actual operating conditions in many universities. The continuous increase of student numbers for more than a decade, particularly since 1999 has put great pressure for funding. Yet funding increase lags far behind, leaving most Chinese universities with overloading operation. Student dormitories are often dark and worn down by years. Many universities have daily problems with water, gas, and electricity facilities, let alone other demands such as library collection, laboratory facilities, and the Internet access. Under such scenario, education quality has to be compromised. 366
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Another effect is the increasing differentiation within higher education sector. First is among different universities, while Peking and Tsinghua Universities are in great delight to receive the special favor from the central government, other equally qualified universities feel they are given the cold shoulder. Nanjing University, for instance, while boasting its top ranking for recent years, has not been equally fortunate in winning the privilege from the national government. Its president even resigned in protest. Another form of internal differentiation is the regional differences. As shown above, China’s imbalanced regional development has been a social problem for thousands of years. It is being aggravated, rather than reduced, by the current transformation from the planned to a market economy, and by the shift of regional development policy since 1978. Higher education development, as both a stimulus for and an outcome of change, differs from region to region due to very different socio-economic conditions and tasks. Regional financial disparity has an evident effect on universities. Higher education institutions in better-developed areas are much more likely to receive significant assistance and investment from various organizations, particularly the private sector. Institutions in poorer areas, by contrast, often feel helpless. A further element of differentiation is across disciplines. Different financial situations have provided various departments even within one institution with very different bases for their future developments. Overall, the process of increasing integration with society has seen technosciences make considerable progress. This has led to new problems within various faculties even departments. In some faculties, a criterion for performance assessment with the central focus on economic benefits has been implemented. This is a dangerous, if not mistaken, conception, and stands in direct conflict with the nature of a university, whose task is “the methodical discovery and the teaching of truths about serious and important things” (Shils, 1997, p. 3). It also undermines the university as an integrated whole and causes tensions among its staff.
CONCLUDING REMARKS Despite some concerns for the modes of implementation and specific timing, the move toward massification of higher education has been well acclaimed in China, with pushes from below and pulls from above. 367
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China’s trend toward the massification of higher education is neither a simple continuity of its unique traditional higher learning, nor a wholesale transplant of foreign experience. While disparities are obvious, China’s initial practices have demonstrated some similarities with the practice of other nations. It is then necessarily appropriate to set Chinese practice in the international context. Chinese higher education institutions are on the horns of a dilemma: while they are playing a crucial role in China’s economic and social development, they still find themselves at a disadvantage in the international knowledge network. The problems of looking outward and inward at the same time are substantial, particularly when combined with immense pressures to contribute directly to national development and to participate in the international system (Altbach, 1998). Such a predicament is felt on a daily basis, especially by China’s major universities within the preliminary stage of massification of higher education. Higher learning in China has traditionally been the privilege of the elite, a phenomenon often referred to as xuezaiguanfu. Only rarely was it successfully used by the few talented with lower middle- and workingclass origins to gain infiltration into high society. In this regard, the ongoing massification of higher education in China is historically significant in providing increasing Chinese population with access to education at an unprecedented level, and therefore with more life choices. Chinese preparation for a take-off in the massification of its higher education system reminds us of the often-neglected fact that higher education is by its very nature an elitist system. Only a few selected in a given population have access to the pinnacle of any higher education system. Even in mass higher education systems, there is a high degree of selectivity that ensures that access to the top institutions in the hierarchy of institutional forms is controlled, and possible only to elite performers, as demonstrated persuasively by Brown and Bok (1998), using the admission to highly select American four-year colleges as an example. Without exception in the Chinese higher education system, while the participation rate is becoming higher, institutional differentiation is increasing. As knowledge production moves out of the university into the larger society, so the society’s diverse values move in. The boundaries of the university are increasingly blurred by both tendencies (Gibbon, 1998). The total mission of higher education has become fuzzier and more diverse, more difficult to define and defend. Universities increasingly serve a growing variety of functions from the most abstract research to the most 368
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utilitarian training force. The socio-economic significance of mass higher education is therefore increasingly prominent. One pressing issue in contemporary China is that there is a determinist element in Chinese higher education that puts a particular model of institution at the top and creates conditions that offer almost insuperable barriers to lower ranked institutions emulating the higher ranked. This is aggravated by the still highly centralized administration. The question that needs to be asked of the system is how do the institutions with less social prestige define a role for themselves that allows them to focus on achievable goals.
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9. THEORY AND RESEARCH ON THE DEVELOPMENT OF MORAL REASONING AMONG COLLEGE STUDENTS Patricia M. King and Matthew J. Mayhew University of Michigan
Moral development has been a central purpose of American higher education since its inception (e.g., Reuben, 1996). College mission statements today continue to refer to purposes that include a moral dimension, such as preparation for citizenship, civic engagement, character development, moral leadership, service to society, and responsible participation in a diverse democracy. Several professional organizations have recently sponsored national reports on higher education, such as those by the National Association of State Universities and Land-Grant Colleges (1997) and the Association of American Colleges and Universities (2002) have recently reaffirmed this purpose and called for a more central role for moral education. Higher education policymakers have also identified the development of moral character as a matter of national interest, and Congress has passed federal legislation that emphasized the need for moral education. For example, in the 1998 Amendments to the Higher Education Act of 1965, Congress voted to “support and encourage character building initiatives in schools across America and urge colleges and universities to affirm the development of character as one of the primary goals of higher education” (Higher Education Act, 1998). Embedded within the emphasis on the moral and ethical dimensions of education is the assumption that colleges and universities are wellpositioned to serve these purposes, and that they provide educational
J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XIX, 375–440. ©2004 Kluwer Academic Publishers. Printed in The Netherlands.
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experiences for students to develop their moral capacities. This review organizes and summarizes a wide variety of studies that examined moral development among college students; this body of research provides an extensive array of evidence about moral development as a collegiate outcome, and updates a review published in this volume 15 years ago by Nucci and Pascarella (1987). The available evidence on this question rests heavily on findings from one major instrument, Rest’s (1979a,b) Defining Issues Test (DIT). As a result, this instrument has played a major role in shaping our understanding of the development of moral reasoning among college students. Although Rest himself (1984) noted that the domain of morality was much broader than moral reasoning, and even mapped out a conceptualization of several other components (presented below), the vast majority of studies on college student moral development has used the DIT, and therefore, most available research has focused on the moral judgment domain. In this chapter, we first describe the theoretical assumptions about the development of morality on which the DIT is based, and then explain the structure, rationale, and scoring of this approach to assessment of moral judgment. These discussions set the stage for the major focus of this chapter, a review of the development of moral reasoning among college students. We initially identified over 600 such studies, and then selected those that met given criteria. First, we limited our review to studies using the DIT since it is the overwhelming choice as a measure of moral development. Second, given our focus on undergraduate students, we selected only studies that used samples of college students. (For a review of the use of the DIT in professional education, see Bebeau, 2002.) Third, we limited our search to studies that sampled students attending U.S. colleges and universities because a discussion of international students and their universities, along with effects of translating the DIT into different languages, was beyond the scope of this chapter. Last, with the exception of Rest’s original studies (Rest et al., 1974; Rest, 1979a,b), we included only studies published since 1980 since many of the findings from Rest’s early articles are subsumed and/or replicated by more recent studies. This procedure yielded the 157 studies that comprise the current review. We have organized these into four major sections; the first of these summarizes studies that examined the effects of participation in formal education on the development of moral reasoning. We turn next to studies that provide explanations for these effects, dividing these studies into two major categories, those that examined student characteristics, and 376
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those that examined collegiate contexts and experiences. Last, we summarize studies that have examined the relationship between moral reasoning and other collegiate outcomes (cognitive, identity, and social outcomes). We conclude by offering a critique of the contributions and limitations of DIT research in higher education, and make suggestions for future research that we derived from this review.
EVOLVING THEORETICAL CLAIMS ABOUT THE PSYCHOLOGY OF MORAL DEVELOPMENT This section examines three major approaches to scholarship on the psychology of moral development. Each is theoretically grounded, has a substantive research base, and informs the interpretation of studies designed to assess moral development in the college years. These three are the Four Component Model developed by James Rest, Lawrence Kohlberg’s theory of moral judgment development, and a successor to Kohlberg’s theory, the “neo-Kohlbergian” approach proposed by Rest and his colleagues. MAPPING THE MORAL DOMAIN: FOUR COMPONENT MODEL OF MORALITY Many approaches and theoretical traditions have been used to study moral development (for an introduction, see Kurtines and Gewirtz, 1995), and a few attempt to integrate scholarship across traditions. Rest (1983) proposed one of the early integrative approaches in an attempt to organize the scholarship on morality as a psychological construct. He identified four different approaches to answer the question, “What processes or functions must have occurred in order for an individual to perform a moral act?” (Rest, 1986, p. 3). Rest referred to each approach and its associated psychological processes as a “component” of morality and emphasized that moral behavior is the result of several processes with distinctive functions, not a unitary process: A person who demonstrates great facility at one process is not necessarily adequate in another. We all know people who can render very sophisticated judgments but who never follow through on any course of action; we know people who have tremendous follow-through and tenacity but whose judgment is simple-minded. (Rest, 1986, p. 4)
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The four components are not intended to depict a linear sequence of processes, a point highlighted by research on the interactions among components. Rest also asserted that in producing moral behavior, cognition and affect work together, abandoning the familiar categories among cognition, affect, and behavior with their separate tracks of development. “I take the view that there are no moral cognitions completely devoid of affect, no moral affects completely devoid of cognitions, and no moral behavior separable from the cognitions and affects that prompt the behavior” (Rest, 1986, p. 4). Table 9.1 describes the purpose and functions of each component and factors that influence the process being described, listing some of the many factors (empathy, moral standards, ego strength, etc.) that are involved in the production of moral behavior. As Rest (1984) pointed out, “Deficiency in any process can result in moral failure. Although one process might interact and influence another process, the processes ought to be distinguished from each other as performing different functions, all of which are necessary for the production of moral behavior” (p. 27). This model has been used to frame a theoretical approach for character education (Bebeau, Rest, and Narvaez, 1999; Rogers, 2002) and to stimulate the development of new measures and research programs (Rest, Narvaez, Bebeau, and Thoma, 1999a). Component 2 processes are the focus of the DIT; the schema that guide these processes are described in detail in the following sections on Kohlbergian and neo-Kohlbergian approaches. Although the most prominent theory of moral reasoning is that proposed by Kohlberg and his colleagues (Colby and Kohlberg, 1987; Kohlberg, 1981, 1984), this is only one model or interpretive system that informs moral judgment. Other systems are contained within Component 2 as well, such as social conventions and religious prescriptions (Thoma, 1994). KOHLBERG’S APPROACH TO MORAL DEVELOPMENT Kohlberg’s keen and sustained interest in moral psychology stemmed from his experiences during and after World War II, including time served in a concentration camp after being arrested for trying to help Jewish refugees immigrate to Israel. His rejection of moral relativism and the search for a universal morality came from his observations of the devastating effects of the relativistic view of morality that tolerated horrific injustice during the Nazi holocaust (Kohlberg, 1991). 378
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For Kohlberg, moral philosophy guided not only the study of moral development, but the special, prominent role he ascribed to moral judgment in the larger domain of morality. Gielen (1991) summarized this role as follows: For [Kohlberg], morality includes feelings, thoughts, and actions, but it is moral reasoning that gives the actions their specifically moral quality. Moral reasoning focuses on normative judgments prescribing what is obligatory or right to do. They are judgments of value, not descriptive judgments of fact. They contain universalizable prescriptions about rights, duties, and responsibilities and are not merely value judgments of preference or liking. Moral judgments tell us what we should do in situations where the claims of various persons are in conflict with each other. When people make moral decisions in situations of conflict, their reasoning frequently refers to normative rules and principles, welfare consequences for the various people in conflict with each other, the search for fair solutions, the balancing of perspectives, and the search for personal and group harmony. These moral concerns center, directly or indirectly, on issues of justice. (p. 24)
As Kohlberg attempted to describe the evolution of moral judgment, he considered not only a particular dimension of morality, but a particular aspect of moral judgment, which Rest, Narvaez, Bebeau, and Thoma (1999a) call macromorality: how people think about “the formal structures of society (laws, roles, institutions, general practices) instead of personal, face-to-face relationships in particular, everyday dealings with people” (p. 2). Although caring for others, being courteous, kind, polite, helpful, and even punctual might be considered moral behaviors, this is not the aspect of moral development described by Kohlberg’s theory. Kohlberg used a structured interview format, the Moral Judgment Interview (MJI; Colby, Kohlberg, Speicher, Hewer, Candee, Gibbs, and Power, 1987) and to learn about the structure of people’s moral reasoning. The interviews focused on different problems of justice: distributive justice (e.g., whether communities distribute tangible and intangible societal goods, such as wealth or privilege based on merit, equity, special circumstance, etc.), commutative justice (e.g., problems relating to contracts and agreements), and corrective justices (e.g., problems of restitution and retribution). For these interviews, Kohlberg identified six distinctive structures, which he called stages of moral development. These have been described in detail elsewhere (Kohlberg, 1969, 1971, 1981, 1984). Gielen (1991) summarized the stages as follows: at the preconventional level (Stages 1 and 2), “societal 379
380 Determining what a person ought to do ● Deciding which course of action is morally right ● Formulating a plan of action that applies a moral standard or ideal (e.g., fairness, justice).
To formulate what a moral course of action would be; to identify the moral ideal in a specific situation
To select among competing value
Component 2: Defining the Morally Ideal Course of Action
Component 3: Deciding What ●
●
Evaluating possible courses of action for how they would
Ambiguity of people’s needs, intentions, and actions ● Familiarity with the situation or the people in it ● Time allowed for interpretation ● Degree of personal danger and susceptibility to pressure ● Preoccupation with other component processes ● Sheer number of elements in the situation and the embeddedness of crucial cues ● Complexity in tracing out cause-effect chains ● Presuppositions and prior expectations that blind a person to notice or think about certain aspects ● Factors affecting the application of particular social norms or moral ideals, or their activation ● Delegation of responsibility to someone else ● Prior conditions, promises, contracts or expectancies that affect role responsibilities, reciprocity, or deservingness ● Particular combination of moral issues involved; preempting of one’s sense of fairness by prior commitments to some ideology or code ● Factors that activate different motives other than moral motives ●
Being aware of the moral dimension within the situation (that an individual’s actions could affect other people’s interests or well-being) ● Recognizing how possible courses of action affect all parties involved ● Recognizing how interested parties would regard these effects on their welfare
To interpret the situation in terms of how one’s actions affect the welfare of others
Component 1: Interpreting the Situation as Moral ●
Influences
Functions
Purpose
Process
Table 9.1: Rest’s Four-Component Model of Morality
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To execute and implement what one intends to do
Component 4: Executing and Implementing a Moral Plan of Action ●
Acting as one intended to act, and requiring attributes such as perseverance, resoluteness, strong character, the strength of one’s convictions, how much energy you have for the task, etc.
serve moral or nonmoral values (political sensitivity, professional aspirations, legality, public relations impact, perceived level of vindictiveness, etc.) ● Deciding what one actually intends to do
Mood states that influence decision making Factors that influence estimates of costs and benefits ● Factors that influence subjective estimates of the probability of certain occurrences ● Factors that affect one’s self-esteem and willingness to risk oneself ● Defensively reinterpreting the situation by blaming the victim, or by denying need or deservingness ● Factors that physically prevent one from carrying out a moral plan of action ● Factors that distract, fatigue, or disgust a person ● Cognitive transformations of the goal, and timing difficulties in managing more than one plan at a time ●
●
Sources Rest, J.R. (1984). The major components of morality. In W.M. Kurtines and J.L. Gewirtz (eds.), Morality, Moral Behavior and Moral Development. New York: John Wiley and Sons. Rest, J.R. (1986). Moral Development: Advances in Research and Theory. New York: Praeger.
outcomes of ideals, the one to act on; deciding whether or not to try to fulfill one’s moral ideal
One Intends to Do
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expectations remain external to the self. The perspective is the perspective of a concrete individual actor who follows roles in order to avoid trouble, satisfy needs, and maximize his or her interests” (p. 27). At the conventional level (Stages 3 and 4), “conventions, rules, obligations, and expectations are experienced as being part of the self. The self identifies with and voluntarily subordinates itself to personal and impersonal (societal) mutual obligations and expectations” (p. 30). At the postconventional level (Stages 5 and 6), “a person has abstracted general principles of freedom, equality, and solidarity from more specific societal or interpersonal expectations, laws, and norms. The self is differentiated from the expectations of others” (p. 30) and is subordinate to principles that apply to all. Each level (indeed, each stage within a level) reflects a qualitatively different approach to reasoning about moral issues. Noteworthy among the distinctions across levels is that the concept of justice expands from an egocentric to a societal perspective. That is, what is considered to be fair or morally right expands from a system that serves oneself (preconventional), to one that serves one’s close friends and family (conventional), and finally, to one that also serves strangers (postconventional). Courses and programs designed to promote moral reasoning encourage college students to see moral problems from broader societal perspectives. THE NEO-KOHLBERGIAN APPROACH: THEORETICAL ASSUMPTIONS UNDERLYING THE DIT As a protégé of Larry Kohlberg and a scholar with an independent research agenda, James Rest was uniquely positioned to both evaluate and respond to the criticisms directed toward Kohlberg’s theory. His work on the DIT (Rest, 1979b, 1987) was a distinct departure from the Kohlbergian approach to assessment, and provided the means to evaluate underlying assumptions of Kohlberg’s approach that were problematic (e.g., simple stage theory and its description of development as step-like and hierarchical). Over time, Rest’s approach not only yielded a new measure, but evolved into a theory of its own. In 1999, Rest and his closest colleagues (Rest, Narvaez, Bebeau, and Thoma, 1999a,b) offered a major new synthesis of ideas based on emerging theoretical models (especially schema theory) and the extensive body of DIT research. Although Rest et al. (1999a) make different claims based on different assumptions than did Kohlberg, they honor the “very wise and useful things [that Kohlberg had to say] about the nature of morality” (p. 292), by calling their approach “neo-Kohlbergian.” 382
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In this new approach, cognitive schemas rather than stages are used to describe how individuals organize (i.e., assimilate and structure) new information. Rest et al. (1999a) proposed three developmentally ordered schemas through which people make sense of moral situations. The first schema, Personal Interests, develops in childhood and has elements similar to Kohlberg’s Stages 2 and 3, in particular, that “it justifies a decision by appealing to the personal stake that an actor has in the consequences of an action” (Rest et al., 1999b, p. 305). This schema does not reflect an understanding of society as an organized entity. The Maintaining Norms schema was derived from Kohlberg’s Stage 4, and is characterized by the acknowledgment of the need for normative rules and role systems to address common needs in ways that are reliable and provide for safety and coordination among community members. Formal laws, rules, and norms that are known by and applied to all members are seen as means that help assure society-wide cooperation among members who are not only close friends or associates, but with and among strangers and competitors. Where this approach becomes morally inadequate is when the social order is protected at the expense of basic human rights and civil liberties. By contrast, a major element of the Postconventional schema is that moral criteria (such as respect for human rights) have primacy over social conventions (such as laws, roles, contracts) in making moral decisions. Since there are many possible social arrangements, members’ duties and rights derive from the moral purpose of the arrangement, not from its existence per se. The postconventional schema appeals to ideals for organizing society (e.g., majority rule, minority rights), ideals that are sharable and open to scrutiny by others. For an extended discussion of the similarities and differences between the underlying assumptions of this model and Kohlberg’s, see Rest et al. (1999a). The links between theoretical assumptions and descriptions of a construct affect how instruments are designed to measure the construct, but these links are not always transparent. In the next section, we note these links as we discuss the design and rationale for the DIT, the instrument on which a great deal of our understanding of moral reasoning is based.
MEASURING MORAL REASONING: THE DIT James Rest became interested in developing an alternative measure of moral judgment while reflecting on his experiences when conducting Kohlbergian interviews for his dissertation (Rest, 1969; described in Rest, 383
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1986). The measure he created, the DIT has become the most widely used measure of moral development in studies of college students (King and Mayhew, 2002). The DIT “is designed to measure how concepts of justice influence the process of moral judgment” (Rest, 1986, p. 152); for a detailed history and rationale of its construction, see Rest (1979b). In the remainder of this section, we describe the DIT, present its scoring indices, and summarize the validation studies that have been conducted on it. THE STRUCTURE OF THE DIT The DIT is based on the premise that people at different points of development interpret moral dilemmas differently, define the critical issues of the dilemmas differently, and have different intuitions about what is right and fair in a situation. Differences in the way that dilemmas are defined therefore are taken as indications of their underlying tendencies to organize social experience. (Rest, 1983, p. 196)
After reading a story that includes a moral dilemma, respondents are first asked to choose which of two possible actions they think the protagonist should take (e.g., “Should a principal of a high school stop a student from publishing a controversial student newspaper?”). The central task for individuals completing the DIT is to then assess the moral importance of a series of 12 issues that might be considered when responding to each of six stories (dilemmas). For example, in the famous case of whether Heinz should steal a drug to save his dying wife’s life if he can get the drug no other way, the issues coded as preconventional (Stages 2 and 3) include: “Is Heinz willing to risk getting shot as a burglar or going to jail for the chance that stealing the drug might help?” “Isn’t it only natural for a loving husband to care so much for his wife that he’d steal?” Conventional level items are: “Whether a community’s laws are going to be upheld” and “Whether the druggist’s rights to his invention have to be respected.” Items designed to reflect Postconventional moral reasoning are: “What values are going to be the basis for governing how people act toward each other?” and “Whether the law in this case is getting in the way of the most basic claim of any member of society.” The issues were derived from an extensive set of interviews and scoring guides and converted into response items. Respondents are then asked to indicate which issues are important in making a decision about what ought to be done in each situation and to rank order the top four of these. The issues are generally based on Kohlberg’s theory of moral development, and reflect the different considerations associated with different schemes of fairness (i.e., moral judgment 384
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stages). Respondents must weigh the importance of these schemes. The logic here is that if a person consistently selects items coded at a given stage across dilemmas, it is plausible to infer that the concept of justice associated with that stage is a prominent feature of the person’s thinking. More recently, Rest and his colleagues (Rest, Narvaez, Bebeau, and Thoma, 1999a) turned to schema theory to explain how the DIT works as a reliable measure of moral judgment. The DIT is a device for activating moral schemas (to the extent that a person has developed them) and for assessing them in terms of importance judgments. . . . As the subject encounters an item that both makes sense and taps into his or her preferred schema, that item is rated and ranked as highly important. Alternatively, when the subject encounters an item that either doesn’t make sense or seems simplistic and unconvincing, the item receives a low rating and is passed over for the next item. . . . In the DIT, we are interested in knowing which schemas the subject brings to the task (are already in his or her head). Presumably, those are the schemas that structure and guide the subject’s thinking in decision making beyond the test situation. (p. 6)
This version of the DIT was used from the 1970s to the 1990s, and it was apparent in the later years that specific references within the test were out of date. Rest and his colleagues considered changing the test many times, but decided that it was more important to establish a stable record of research based on the same instrument: “the DIT has remained unchanged so that a record of validity and generality could be established over the years during a full cycle of research” (Rest et al., 1999a, p. 61). However, an updated version of the DIT has recently been developed called the DIT2 (Rest, Narvaez, Thoma, and Bebeau, 1999b). It is shorter, updates language and references to historical events, has less stringent consistency checks (allowing researchers to retain larger samples), and uses a new scoring index, N2 (described below). The vast majority of studies described here have used the DIT; we indicate where the DIT2 has been used.1 SCORING THE DIT Several approaches to scoring the DIT have been tested, based on both theoretical and methodological advances in understanding and measuring moral judgment. Since most are described in detail elsewhere, here we try 1
Information about permissions, ordering, and scoring the DIT2 is available at: http:// education.umn.edu/csed/
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to offer only enough detail so that readers can adequately interpret the research results reported below that use these scores. P-Score The most commonly-used score of the DIT reflects the relative importance that respondents give to items that reflect principled (hence, the P in P-score) moral reasoning. It is calculated by summing the number of times respondents rank Stage 5 and 6 items as first, second, third, and fourth most important, and then weighting these ranks by 4, 3, 2, and 1, respectively. It is typically expressed as a percentage, which can range from 0 to 95. For a more detailed discussion, see Rest (1979b, 1983; Rest et al., 1999a). N2 This is a relatively new DIT index score; a key feature is that higher stage reasoning is prioritized and lower stage reasoning is rejected (Rest, Thoma, Narvaez, and Bebeau, 1997). It accounts not only for the ranked items that reflect principled moral reasoning, but also for the rated items that reflect respondents’ preferences for higher versus lower stage reasoning. Rest et al. (1997) conducted a series of studies comparing N2 to P-scores and concluded that the N2 index is “generally better than the P index” (p. 505). D-Score Davison created a score based on latent-trait, unfolding models of scaling theory that take into account selection of principled items as well as lower stage items. It is described in Rest (1979). Evens (1995) conducted an extensive investigation of the utility of the D-score, and concluded that the P-score was the stronger measure. U-Score Thoma (1994; Thoma, Rest, and Davison, 1991) created a utilizer score (U-score) to examine the degree to which concepts of justice are utilized in moral reasoning and behavior. Thoma observed that certain items implied given action choices, and sought to identify the relationship between the implied and actual action choices they made. He reasoned that when these were consistent, “then it is reasonable to assume that a single interpretative 386
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system — justice reasoning — is driving both decisions” (Thoma, 1994, p. 205). (See Derryberry and Thoma (2002) for a description of how the U-score was used to develop moral typologies.) M-Score This score was developed as an internal validity check on respondents “who endorse items because of their complexity and pretentiousness rather than their meaning” (Rest, 1979b, p. 91); these meaningless items appear in each of the DIT stories. An example from the Heinz dilemma is: “Whether the essence of living is more encompassing than the termination of dying, socially and individually.” These indices were theoretically- and mathematically-based to maximize the utility and the efficiency of the DIT. We next note studies conducted to test the validity of the DIT as a measure of moral reasoning using these indices. VALIDATION Since the 1970s, Rest’s program of research emphasized studies that addressed validation questions surrounding the use of the DIT to examine the development of moral judgment. These questions have been organized and summarized in detail by Rest (1979b, 1986; Rest, Narvaez, Bebeau, and Thoma, 1999a) who offer summaries from hundreds of published studies that provide evidence of the validity of the DIT; we suggest that interested readers check these sources for a detailed review. This section provided readers with information about the rationale, design, and scoring of the DIT and how these reflect assumptions about the development of moral reasoning on which it is based. The sheer number of studies reflected in this review provides testimony to the availability and widespread use of the DIT as a measure of moral reasoning. We turn now to a more detailed review of these studies.
EFFECTS OF PARTICIPATION IN HIGHER EDUCATION ON MORAL REASONING We start this review by examining how participation in higher education affects moral reasoning. We then try to explain this effect, looking 387
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at two sets of studies, those that examined student characteristics, and those that examined collegiate contexts and experiences. What is the relationship between participation in higher education and the development of moral reasoning in college students? This central question has been the topic of at least 45 studies, with striking results: almost 90 percent reported a significant relationship between level of formal education2 and moral reasoning (Biggs and Barnett, 1981; Bouhmama, 1988; Borduin, and Baumstark, 1992; Buier, Butman, Burwell, and Van Wicklin, 1989; Burwell, Butman, and Van Wicklin, 1992; Cannon, 2001; Clouse, 1991; Felton, 1984; Finger, Foster and LaForce, 1999; Gfellner, 1986; Glover, 1994; Gongre, 1981; Hay, 1983; Hood, 1984; Icerman, Karcher, and Kennelley, 1991; Jeffrey, 1993; King and Kitchener, 1994; Kitchener, King, Davison, Parker, and Wood, 1984; King, Kitchener, and Wood, 1985; Loviscky, 2000; Mentkowski and Associates, 2000; Mentkowski and Strait, 1983; Mustapha and Seybert, 1990; McNeel, 1994; Paradice and Dejoie, 1991; Ponemon and Glazer, 1990; Rest, Cooper, Coder, Masanz, and Anderson, 1974; Rest, 1979a,b; 1987, 1988; Rest and Thoma, 1985; Shaver, 1985, 1987; Stroud, 2000; Thoma, 1994; Thoma and Ladewig, 1993; Walker, Rowland, and Boyles, 1991; Whiteley, 1982). Only six studies (Bonawitz, 2002; Cohen, 1982; Cummings, Dyas, Maddux, and Kochman, 2001; Galotti, 1989; Quarry, 1997; Shaub, 1994) reported no significant relationship with formal education. Instead of reviewing all the studies listed above, we focus on those that used design strategies that most directly test the effects of participation in formal education on the development of moral reasoning. The first of these are longitudinal studies, which are essential for the validation of any developmental model. A series of longitudinal studies have examined the effects of age and education on the development of moral reasoning. Across these studies, students’ use of conventional level reasoning decreased during college, and their use of postconventional moral reasoning increased (Burwell, Butman, and Van Wicklin, 1992; Foster and LaForce, 1999; King and Kitchener, 1994; King, Kitchener, and Wood, 1985; Mentkowski and Strait, 1983; Rest, 1979b; Shaver, 1985, 1987; Whiteley, 1982), offering evidence that collegiate experiences promote the development of moral reasoning among undergraduate students. 2 DIT P-scores by educational levels are as follows: Junior high students ⫽ 21.9; senior high students ⫽ 31.8; college students ⫽ 42.3; moral philosophy and political science graduate students ⫽ 65.2 (Rest, 1994).
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However, since students age as they attend college, age and education are frequently confounded in longitudinal designs. Controlling for age by using same-age non-college comparison groups can test whether gains in moral reasoning are due to education, age, or the interaction between them. Rest (1979b) and Rest and Thoma (1985) tracked the course of moral reasoning development of participants from the end of high school to 6 years beyond high school; some attended college and others did not. At the third testing, Rest (1979a) reported that for the 38 college students attending college, DIT scores continued to increase; for the 18 participants not in college, scores were stable. At the fourth time of testing, Rest and Thoma (1985) divided the groups into low-education (less than 2 years of college) and high-education (more than 2 years of college) categories. Two years after leaving high school, both groups showed increases in P-scores; 4 years later, the 23 students in the high education group still showed gains, while the scores of the 13 individuals in the low education group were stable (Rest and Thoma, 1985). Collectively, these studies provide strong evidence that participation in formal education promotes the development of moral reasoning among undergraduate students. Our findings are consistent with those reported by Rest et al. (1999b), who concluded that formal education is “by far the most powerful demographic correlate of DIT P-scores, typically accounting for 30 percent to 50 percent of the variance in large, heterogenous samples . . .” (p. 70). Thus, intentionally or unintentionally, there appears to be a moral “curriculum” in higher education. In the next section, we use Astin’s (1993) Inputs–Environments– Outputs model to organize the empirical literature concerning moral reasoning in college. Here, the inputs factor refers to student characteristics that contribute to students’ levels of moral reasoning. The environments factor includes general collegiate contexts and specific experiences that influence the development of moral reasoning during the college years. The outcome factor for this analysis is moral reasoning as measured by the DIT. Figure 9.1 shows the list of variables in each category that have been studied in relation to moral reasoning, and provides an organizing template for this literature review. We wish to note here that this framework was designed to organize the factors that have been studied related to moral reasoning in the college years. It was not designed as a conceptual model of factors related to the development of moral reasoning and how these are related; we leave this important task to a subsequent essay. The far right-hand column of Figure 9.1 summarizes the last section of this review, how moral reasoning is related to three other sets of collegiate 389
• • • • • • • • •
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Age Ethnicity Gender SES Aptitude/Intelligence Political identification Religious identification Personality traits Other student characteristics
Student Characteristics
• • • • Institutional type Academic discipline Curricular experiences Co-curricular experiences
Collegiate Contexts
Moral Reasoning
Personal epistemology Academic achievement Logical reasoning
Ego Ego identity status Other identity measures Locus of control Values Religiosity/Spirituality
• •
Understanding others Behaviors toward others
Social Outcomes
• • • • • •
Identity Outcomes
• • •
Cognitive Outcomes
Figure 9.1: Research on the Relationship Between Student and Collegiate Factors Affecting Moral Reasoning and on its Relationship to Other Collegiate Outcomes HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX
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outcomes (cognitive, identity, and social outcomes). The dashed lines connecting moral reasoning to other outcomes are intended to portray a relationship that is conceptually related rather than causal or directional. One of the most challenging aspects of completing this review was deciding how to organize it, especially regarding the related outcomes. Shulman (2002) recently encouraged scholars to be playful when arranging and rearranging their organizing frameworks; we took his advice when deciding how to organize these variables, and encourage others to do so in ways that suit their purposes.
STUDENT CHARACTERISTICS THAT AFFECT MORAL REASONING How are student characteristics related to students’ capacity for postconventional moral reasoning? In this section, we examine age, ethnicity, gender, and socioeconomic status, aptitude, intelligence, and political and religious orientation, and the effects of personality and other factors on the development of moral reasoning. Age Studies that used age to predict moral reasoning scores among traditionally aged college students (Armstrong 1993; Cummings et al., 2001; Gongre, 1981; Mason and Mudrack, 1997; Quarry, 1997; Schaub, 1994; Stepp, 2002) found no significant relationship between age and moral reasoning. The two studies that yielded significant relationships between age and DIT scores sampled nontraditionally aged students (Bonawitz, 2002; Cannon, 2001). Because education and age are often confounded in student populations, especially among traditionally aged college students, it is useful to control for age to test for the impact of college, which has been done in numerous studies (Benixden, Schraw, and Dunkle, 1998; Borduin, and Baumstark, 1992; Cummings et al., 2001; Finger, Gfellner, 1986; Icerman, Karcher, and Kennelley, 1991; Kitchener, King, Davison, Parker, and Wood, 1984; King, Kitchener, and Wood, 1985; Mentkowski and Strait, 1983; Paradice and Dejoie, 1991; Rest, 1979a, 1980, 1987, 1988; Rest and Thoma, 1985). These studies indicate that participation in higher education makes a substantial contribution to development in moral judgment beyond that attributable to age alone. 391
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Ethnicity Several studies have examined the relationship between race and ethnicity, and the development of moral reasoning. Only two (Gongre, 1981; Locke and Tucker, 1988) directly investigated differences in moral reasoning by race or ethnicity; the others reported differences in moral reasoning by race or ethnicity as they related to other research questions ( Johnson, Insley, Motwani, and Zbib, 1993; Katz, 2001; Loviscky, 2000; Lupfer, Cohen, Bernard, and Brown, 1987; Murk and Addleman, 1992). For a detailed review of these studies, see King and Mayhew (2002); they could discern no clear pattern of results concerning the differential effects of race and ethnicity on the development of undergraduate students’ moral reasoning. Gender Many studies have focused on questions relating to gender differences in moral reasoning (Walker, 1984). The majority of the studies reviewed here reported that women scored higher than men on the DIT (Abdolmohammadi, Gabhart, and Reeves, 1997; Bendixen, Schraw, and Dunkle, 1998; Boss, 1994; Clouse, 1991; Glover, 1994; Guthrie, 1985; Hay, 1983; Kilgannon and Irwin, 1992; Mullane, 1999; Olejnik and LaRue, 1980; Plueddemann, 1989; Pratt, 2001; Pressley, Schmierer, and Hope, 1980; Renwick and Elmer, 1984; Shaub, 1994; Shaver, 1985; St. Pierre, Nelson, and Gabbin, 1990; Stepp, 2002; Tennant, 1991; Thoma, 1986; Walker, Rowland, and Boyles, 1991; Whiteley, 1982). These findings are consistent with the meta-analyses reported by Thoma (1986) and Walker (1984). The next largest group of studies showed no differences in DIT scores between men and women (Armstrong, 1993; Bonawitz, 2002; Cohen, 1982; Cummings et al., 2001; Galotti, 1989; Gfellner, 1986; Gongre, 1981; Murk and Addelman, 1992; Quarry, 1997; Rotenburg, Hewlett, and Siegwart, 1998; Stroud, 2002; Thoma, 1993, 1994; Wright, 2001; Wygant and Williams, 1995; Zarinpoush, Cooper, and Moylan, 2000). Only two studies (St. Pierre, Nelson, and Gabbin, 1990; Whiteley, 1982) reported that men scored higher than women on the DIT. Although some scholars have expressed concerns about the possibility of gender bias in Kohlberg’s theory (most prominently, Carol Gilligan, 1977), this collection of studies demonstrates no such bias using the DIT, as women consistently scored higher than men in these studies. For an excellent discussion of this issue, see Brabeck (1983). 392
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Socioeconomic Status (SES) Researchers interested in understanding the effects of SES on moral reasoning scores have measured SES in a variety of ways, including father’s education, mother’s education, father’s occupation, mother’s occupation, and/or family income. Studies on the effects of SES on students’ capacity to develop moral reasoning (Biggs and Barnett, 1981; Felton, 1984; Finger, Borduin, and Baumstark, 1992; Gfellner, 1986; Gongre, 1981; Mentkowski and Strait, 1983; Rest, 1979; Stepp, 2002) consistently revealed no predictive relationship between SES and DIT score. Aptitude and Intelligence Many researchers have investigated the impact of aptitude and intelligence on DIT scores, especially among entering college students; a variety of measures have been used for this purpose. Aptitude measures include scores on the SAT (SAT; Quarry, 1997; Sanders, Lubinski, and Benbow, 1995), the ACT (Gongre, 1981; Hendel, 1991; Stepp, 2002), Raven (Sanders, Lubinski, and Benbow, 1995), and the PSAT (Hendel, 1991). Intelligence measures include high school class standing (Hendel, 1991; Stroud, 2002), high school grade point average (GPA) (Green, 1981; Mentkowski and Strait, 1983; Quarry, 1997; Stepp, 2002), performance on written assignments ( Johnson, Insley, Motwani, and Zbib, 1993), and Terman’s (1973) Concept Mastery Test (King et al., 1984; King, Kitchener, and Wood, 1985; King and Kitchener, 1994; Kitchener and King, 1981). With the exception of SAT scores reported by Quarry (1997) and high school GPA, all these measures of aptitude and intelligence shared a significant relationship with DIT scores: students who scored higher on these measures also scored higher on the DIT. Political Identification There is a considerable body of research investigating the relationship between political attitudes and moral reasoning. Most of this research does not address political identification as an input variable, but either as a threat to construct validity or as a related domain (see Footnote 4). Most of the studies that examined political identification as an entering characteristic asked students to rate themselves on a Likert scale, indicating the degree to which they believe themselves to be either conservative or 393
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liberal. Students who enter college with more politically liberal political orientations tend to exhibit higher levels of moral reasoning than students entering college with more politically conservative orientations (Barnett, Evans, and Rest, 1995; Elmer, Renwick, and Malone, 1983; Elmer, PalmerCanton, and St. James, 1997; Fisher and Sweeney, 1998; Murk and Addelman, 1992; Narvaez, Getz, Rest, and Thoma, 1999; Thoma, 1993). Religious Identification Research that examined the relationship between religious orientation and moral reasoning of entering college students often used Likert indicators to assess levels of religious conservatism and liberalism (Clouse, 1985; Foster and LaForce, 1999; Holley, 1991; Murk and Addelman, 1992; Richards, 1991; Stepp, 2002). With the exception of Holley’s (1991) study, students with more liberal religious orientations were more likely to use postconventional moral reasoning than were students from more conservative religious orientations. In addition, a number of studies used other means for assessing students’ religious orientations; among these are religious affiliation (Glover, 1997; Gongre, 1981; Hay, 1983; Mentkowski and Strait, 1983; Quarry, 1997; Richards and Davidson, 1992; Stepp, 2002; Wahrman, 1981); church attendance during high school (Stepp, 2002; Wahrman, 1981), and religious training (Wahrman, 1981). No differential effects on moral reasoning scores were found using any of these indices. Personality Traits Three studies (Faucett, Morgan, Poling, and Johnson, 1995; Redford, McPherson, Frankiewicz, and Gaa, 1995; Ritchie, 1991) found that higher levels of postconventional moral reasoning were used by students who used intuitive approaches to gathering data and making judgments as measured by the Myers–Briggs Type Indicator (Myers and McCaulley, 1985). The same pattern was found among students who were open to new experiences as measured by Costa and McCrae’s (1992) NEO-Five Factor inventory (Dollinger and La Martina, 1998). Other Student Characteristics Several other characteristics were examined in addition to those listed above: previous work experience (Cannon, 2002; Felton, 1984), family 394
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structure (Stepp, 2002), urban versus rural residence (Biggs and Barnett, 1981; Gongre, 1981), parental control and warmth (Finger, Borduin, and Baumstark, 1992), amount of discipline at home (Gongre, 1981), marital status (Mentkowski and Strait, 1983) and geographical region of origin (Quarry, 1997). None of these variables shared significant relationships with postconventional moral reasoning scores. Summary of Student Characteristics that Affect Moral Reasoning Students enter collegiate environments with a number of characteristics that may influence their capacity for moral reasoning. Findings from this review suggest that gender, aptitude, intelligence, political identification, and certain personality traits are more likely to affect moral reasoning scores than age, ethnicity, SES, or religious identification. What is less clear is how these characteristics individually and collectively contribute to moral reasoning as an outcome of higher education. For example, few studies examined the possibility of interaction effects (e.g., race by gender) between student characteristics as possible determinants of students’ propensity to develop moral reasoning during college. Further, many studies sampled too few students within subgroups to make meaningful comparisons between subgroups (e.g., by ethnicity). Two findings from this section of the review are noteworthy. First, there is no evidence of gender bias favoring men in the DIT; in fact, women tend to score higher on the DIT than men. Second, research investigating the relationship between race and ethnicity and moral reasoning development as measured by the DIT remains underdeveloped; this finding is surprising given the extensive cross-cultural research on Kohlberg’s theory and the strong interest in diversity-related issues in higher education. COLLEGIATE CONTEXTS AND EXPERIENCES THAT AFFECT MORAL REASONING We now turn to a review of studies that have investigated the effectiveness of specific collegiate contexts and experiences on students’ moral reasoning. In this section, we attempt to identify more specific factors within collegiate environments that are associated with the development of moral reasoning, such as the kinds of collegiate experiences that both promote and inhibit moral development. We clustered studies that inform these questions into six categories, each of which reflects either a general environmental variable (e.g., institutional type) or a more specific type of 395
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experience that has been examined for its association with moral reasoning (e.g., classroom interventions). Institutional Type American higher education is characterized by a wide variety of types of collegiate institutions that vary by size, public or private control, mission, etc. Institutional types range from large public universities with multiple constituencies and missions to small private colleges serving specific student subgroups with distinctive missions. Accordingly, institutional type is a common research variable in higher education research, including research on moral reasoning (Burwell, Butman, and Van Wicklin, 1992; Good and Cartwright, 1998; McNeel, 1991, 1994; Pascarella and Terenzini, 1991; Shaver, 1985, 1987, in preparation). Across these studies, the only institutional type with consistently large effect size was found for liberal arts colleges. While these studies reveal a clear trend, they do not explain why liberal arts environments are effective in promoting moral reasoning. Obtained institutional differences may be a result of factors such as student self-selection (whether those who are more open to thinking about moral dilemmas are inclined to select a liberal arts college), access to opportunities for direct involvement, smaller classes with more discussion of societal issues or the role of values in students’ lives, opportunities to practice reasoning about moral issues, or a liberal arts curriculum that stresses examining many issues from multiple perspectives. In terms of understanding what types of contexts influence the development of moral reasoning, institutional type (as has been historically defined) may be too gross an indicator to identify more specific factors that are directly related to changes in the development of moral judgment. Academic Discipline Does study within certain academic disciplines differentially affect moral reasoning scores? Most studies of this topic reported no significant differences (Cummings et al., 2001; Ponemon and Gabhart, 1994; Snodgrass and Behling, 1996; St. Pierre, Nelson, and Gabbin, 1990; Zeidler and Schafer, 1984). Three reported variability within disciplines (e.g., accounting versus non-accounting business majors) (Icerman, Karcher, and Kennelley, 1991; Jeffrey, 1993; Paradice and Dejoie, 1991), but indicate no clear patterns of results. 396
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Like institutional type, academic discipline is a broad category of educational environments, made more problematic when the factors that characterize or distinguish given disciplines as they pertain to moral reasoning are not explicated. Further, as a unit of analysis, it lacks the specificity needed to identify individual factors or experiences that facilitate growth in moral reasoning. We turn next to specific kinds of collegiate experiences that may be more directly related to moral judgment development, and which provide more fruitful avenues for research on pedagogies that foster moral judgment. Curricular Experiences The DIT has been used to examine the effects of participation in courses or course-related experiences that were intentionally designed to promote the development of moral reasoning among college students. These vary widely in content and process, as shown below. Alverno College’s distinctive ability-based curriculum has been the subject of a massive research effort to evaluate elements of its curriculum for deep and durable learning in college and beyond (Mentkowski and Associates, 2000; Mentkowski and Strait, 1983; Rogers, 2002). One of the eight ability areas at Alverno is Valuing in Decision-Making, and is taught through courses within each discipline. Students’ development in moral reasoning (Rogers, 2002) was related to progress through Alverno’s developmentally sequenced curriculum (for a summary of the causal model explaining this progress, see the cognitive outcomes section). Analysis of student interviews showed that the curriculum and the campus culture helped broaden students’ moral perspectives; Mentkowski and Associates (2000) concluded that students “came to appreciate and understand differing values because they were repeatedly asked to examine and discuss them” (p. 130). Nevin and McNeel (1992) investigated the effects of a college-wide faculty development program (SPECTRUM: Scholars Pursuing Educational Competencies to Raise Undergraduate Maturity) on student moral reasoning development. SPECTRUM faculty designed and implemented their own interventions in a course they chose, based on theories of both personal development during the college years and of developmental instruction concepts. Forty-four students were sorted into groups based on the number of SPECTRUM courses they had taken during their first two years of college: a “low contact” group, a “moderate contact” group, and a “high 397
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contact” group. The low contact group showed no significant postintervention gains in P-scores (from 40.9 to 43.6); students in both the moderate (from 36.4 to 49.8) and the high (from 34.1 to 41.2) contact SPECTRUM groups showed significant change. These findings suggest that gains in student moral reasoning were facilitated by the faculty development program that “included but did not center on the area of moral development, and that did not prescribe set procedures to be applied in the classroom” (p. 17). Not surprisingly, ethics course have been used in several studies as the context in which to promote the moral judgment of students (Armstrong, 1993; Bonawitz, 2002; Boss, 1994; Ponemon, 1993). These typically included direct instruction in ethics in a one-term course. However, the results are mixed: significantly higher moral judgment scores were reported for ethics students by Bonawitz (2002), Armstrong (1993), and Boss (1994), but not by Ponemon (1993). Courses on social diversity and social justice also include content that is directly related to topics requiring moral judgment, with mixed results. The course evaluated by Adams and Zhou-McGovern (1994) focused on racism, anti-Semitism, sexism, homophobia, and disability oppression. By the end of the course, DIT scores had increased significantly. The course that served as the context for Katz’ (2001) study was an intergroup dialogue course that consisted of 13 weekly face-to-face sessions, where students explored “attitudes, perceptions, and beliefs about other social identity groups” (p. 12); he found no pre-/post-differences for the 42 students enrolled in the course. (For other results, see the Identity Outcomes section.) Similarly, Tennant (1991) reported no significant differences between pre- and posttest measures of DIT scores for his sample of 42 students enrolled in a psychosocial course for entering freshman students in a residential liberal arts college. Service learning has been advanced as a powerful pedagogical technique for helping make academic learning more meaningful for students. Service learning is distinguished from community service in that service is explicitly linked to issues studied in a course (Eyler and Giles, 1999). Several studies have examined the effects of service learning on moral reasoning. For example, Boss (1994) compared two sections of the same ethics course, one with and one without a service component; the average pretest P-score for the two sections (n ⫽ 65) was the same. Students in the service learning section (who had completed 20 hours of community service and kept a journal of these experiences) demonstrated higher levels of moral reasoning than those in the section without these components, even after 398
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controlling for class size, instructor, class exercises, and text used across the two sections. On the posttest, 51 percent of the service-learning group and only 13 percent of the comparison group used postconventional moral reasoning. Gorman, Duffy, and Heffernan (1994) adopted a similar design (but with fewer controls) comparing scores of students in two courses, “Perspectives on Western Culture,” and “Person and Social Responsibility.” The latter included field projects that “put the students into direct contact with examples of social injustice” (p. 426) and opportunities to reflect upon and discuss field experiences. Again, posttest DIT scores were higher for students in the section with the service component. However, no statistical procedures were reported to test for differences in pre-test scores for the two sections, so obtained differences could be an artifact of selection. To what can the effectiveness of these experiences be attributed? Are particular pedagogical strategies more effective than others in teaching students to make more sophisticated moral judgments? Several studies have attempted to disentangle the component parts of specific educational experiences in an effort to guide educators to develop curricula that help students develop their capacities to reason about moral issues. Rest (1987, 1988) and Rest and Deemer (1986) attempted to identify experiences related to development of moral reasoning by comparing experiences of those whose DIT scores had shown greater rates of increase with others who showed less increase, using data from his longitudinal sample (this sample is described in the formal education section above). When asked to identify what they thought had influenced their moral thinking, respondents cited a wide range of experiences. “Spending more time contemplating issues” was cited more often by those who showed a greater rate of increase than those not citing it, suggesting again that reflection is a key factor in promoting moral thinking. Three studies used the DIT not only to measure individuals’ moral reasoning, but as the topic of discussion where groups of students were asked to come to a consensus on DIT ranking (Abdolmohammadi et al., 1997; Carey, 1988; Nichols and Day, 1982). All three studies first administered the DIT individually; they randomly assigned students to two (Carey, 1988) or three (Abdolmohammadi et al., 1997; Nichols and Day, 1982) member groups and asked them to come to a consensus response for each of the questions on the DIT. Carey (1988) matched high moral reasoners (i.e., students who scored in the first and second quartiles on the DIT) with low moral reasoners (i.e., students who scored in the third and fourth quartiles) and found that students who were exposed to moral reasoning above their own 399
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level changed more than those exposed to lower levels of reasoning, and that the rate of change was greater towards higher than lower levels of reasoning. Nichols and Day (1982) and Abdolmohammadi et al. (1997) reported that group scores were higher than the average P-scores of individuals comprising the group. Abdolmohammadi et al. (1997) also checked for differential effects of group discussion on moral reasoning scores by gender. In the individual administration, P-scores of female students were significantly higher on the DIT (M ⫽ 49) than were the scores of the male students (M ⫽ 38). However, in the group administration, the scores of the women declined (M ⫽ 44) while the scores of the men increased significantly (M ⫽ 43). Collectively, these results reveal differences in individual versus group decision-making, and gender-related effects of group interactions on reasoning. They are also provocative in that they speak to the effects of group learning on moral reasoning scores, and that these effects were positive for men and negative for women. Not all courses that are effective in promoting moral reasoning explicitly address moral content, such as the outdoor education course studied by Smith and Bunting (1999), and a psychosocial course for entering freshmen (Tennant, 1991). The authors of these studies attribute growth in moral reasoning to opportunities that these courses provide for students to engage in active learning and decision-making activities. Mustapha and Seybert (1990) compared the effects of enrollment in a traditional and multidisciplinary (integrated) general education curricula in an effort to test the effects of decision-making on moral reasoning. The multidisciplinary curriculum was organized around the central idea of decision-making, used small seminar groups, Socratic inquiry, and active learning approaches, and required students to formulate many kinds of decisions, including decisions related to moral issues. Both studies report higher P-scores for students participating in the multidisciplinary decisionfocused curriculum than for students participating in the traditional curriculum. This study suggests that moral reasoning development may be attributable to how students learn rather than what they learn; irrespective of content, pedagogical strategies to enhance decision-making may help students develop their capacities for postconventional reasoning. Similarly, three experimental studies examined the effects of different pedagogies on helping students develop their capacities for postconventional moral reasoning. DeWolfe and Jackson (1984) investigated modeling as an influence on growth in moral reasoning; findings from this study suggest that teaching at advanced moral reasoning levels appears to be 400
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effective for all students, regardless of their existing levels of moral reasoning. Rholes, Bailey, and McMillan (1982) examined the role of cognitive dissonance in moral reasoning; they found that “mere exposure to advanced moral arguments was not sufficient for acceptance” (p. 534) and that moral behavior will be likely to promote growth in moral reasoning if it “occurs under circumstances that promote cognitive dissonance” and if “advanced moral ideas are made salient during the dissonance reduction process” (p. 523). Reall, Bailey, and Stoll (1998) compared the moral reasoning of 118 upper-division business students first in a noncompetitive situation, then in a competitive game, using a test based on the DIT that yields a “moral reasoning during competition” score; although the average P-score was low for college students, M ⫽ 37 (see Footnote 2), the level of moral reasoning was significantly lower for students during the competitive game in this study. To summarize, the majority of studies in this section reported significant increases in moral judgment as a result of participation in these courses. In addition, it appears that the effectiveness of these interventions in promoting moral reasoning is not solely due to the content of the courses; rather, it appears to be determined by the pedagogical strategies used within these courses, such as encouraging students to reflect, to make decisions, to wrestle with diverse perspectives, and to participate as agents in their learning experiences. Co-curricular Experiences Research in other domains has documented the powerful effects of student involvement in co-curricular activities (Kuh, Schuh, Whitt, and Associates, 1991; Pascarella and Terenzini, 1991) on the achievement of student outcomes. We turn now to a review of the studies that examine the effect of co-curricular activities on moral reasoning development. Like service learning (but without the link to course enrollment), community service also provides opportunities for students to gain broader perspectives about social issues through experiential learning. In the Boss (1994) study described above with students enrolled in an ethics class, the community service component of the class served as the critical factor in facilitating growth in moral reasoning. Wright (2001) and Pratt (2001) found no significant differences between pre- and post-test DIT scores for students who participated in community service from those who did not; however, they found differential effects for participation in 401
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community service by gender; P-scores for men increased dramatically as a result of participating in these service-learning opportunities, while P-scores for women either slightly increased or stayed the same. These gender effects are consistent with scores reported for Boss’s (1994) and Abdolmohammadi et al.’s (1997) samples, but not for Gorman et al.’s (1994) sample. These studies suggest that certain experiential learning environments may have differential effects on moral reasoning scores for men and women. Three studies examined the influence of membership in Greek organizations on the development of moral reasoning. Kilgannon and Erwin (1992) administered the DIT to 209 women and 162 men at the beginning of their freshman year and at the end of their sophomore year. At Time 1, there were no differences in DIT scores between entering freshmen who chose Greek affiliation from those who did not choose this affiliation; at Time 2, non-Greek women had higher P-scores (M ⫽ 43.4) than Greek women (M ⫽ 40.6) and non-Greek men (M ⫽ 40.2) had slightly higher Pscores than Greek men (M ⫽ 38.7). Sanders (1990) administered the DIT to male freshmen at the beginning of the fall term (n ⫽ 195) and 9 weeks later at end of the term (n ⫽ 101). Independents scored significantly higher than fraternity members on both the pre- and post-test; however, P-scores for both groups are remarkably low, M ⫽ 10.0 and 8.6, respectively (see Footnote 2). Cohen (1982) tested fraternity and sorority members in various leadership positions (23 executive committee members and 111 presidents) and 141 other individual members. She found no differences by membership category, gender, or year in school; all had low mean P-scores, in the high 30s. These studies capture a few of the wide variety of co-curricular experiences that influence the development of moral reasoning in undergraduate students. Experiential learning environments can promote moral reasoning, but may be more influential for developing men’s capacity for moral reasoning than women’s. Providing opportunities where students can see moral theory in context seems to have an impact on students’ capacity to engage in postconventional moral reasoning. Perhaps students become more aware of their own moral reasoning processes when confronted with experiences that challenge their own values. Perhaps experiences that force students to evaluate situations using multiple perspectives make learning more salient and therefore, more accessible to students when asked to take the DIT. Alternatively, these learning experiences may provide opportunities for students to have meaningful interactions with 402
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others — interactions that motivate students to approach moral issues from a variety of different perspectives. Whatever the reason, it appears that providing experiential learning leads to greater capacities for postconventional moral reasoning than relying solely on didactic approaches. Are there particular social dynamics that make these contexts more effective than others in promoting postconventional moral reasoning? Identifying the elements of specific educational experiences associated with growth in moral reasoning could help educators more effectively develop their capacities to reason about moral issues. We have identified three studies that investigate the influence of social experiences on the development of moral reasoning. Thoma and Ladewig (1993) conducted a study that examined how the quality of students’ peer relationships would affect their moral reasoning development during college. Using a sample of 156 college students, they found that both DIT scores and the number of close college friends increased for each class level from freshman to senior years. Students with close friendships who had multiple independent friendship groups (that is, those whose friends were not necessarily friends with one another) had higher P-scores than other students. These findings suggest that diverse friendships may provide a context for challenging students to consider issues of fairness from different perspectives. Alternatively, it may be that those who seek multiple friendships are more open to developmental challenges. Although the links between types of friendships and development of moral reasoning have not yet been explicated, this line of research bears much promise. (For a review of the literature on friendship and moral judgment, see Derryberry and Thoma, 2000.) In a study designed to examine the correlates of moral judgment development in college students, Finger, Borduin, and Baumstark (1992) administered the DIT as one of many instruments to 159 undergraduate students (67 men, 92 women) from all grade levels (Mean age ⫽ 19.7); they found that after controlling for age, SES, and relationship with family, educational level and frequency of informal social activities significantly predicted moral judgment development. The authors suggest that “social activities with friends and other acquaintances may encourage and stimulate role-taking and group problem solving and may ultimately promote more mature moral judgment” (p. 222). Endicott, Bock, and Narvaez (2003) studied 70 undergraduate students from a large, Midwestern university to examine the effects of multicultural experiences on the development of moral judgment as 403
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measured by the DIT2. No significant relationship was found between breadth of multicultural activities and moral judgment; however, the “depth” of the multicultural experience (e.g., multicultural reading, speaking, working, friendships, courses, amount of time spent in another culture, and degree of commitment to intercultural growth) was significantly related to Maintaining Norms subscores (r ⫽ 0.28, p ⬍ 0.05) and to Postconventional subscores (r ⫽ 0.24, p ⬍ 0.05), suggesting that the intensity of the multicultural experience may be the critical factor in promoting moral judgment among undergraduate students. To summarize, it appears that the quality or nature of college students’ experiences with other students affects their moral development. Research that investigates the impact of social relationships on moral reasoning shows that the intensity and depth of the social experience have a greater impact on the development of moral reasoning than the quantity or breadth of the social experience. Some collegiate environments may foster close friendships with diverse others and therefore foster moral perspective-taking (see Endicott, Bock, and Narvaez, 2003), while others may foster close friendships that reinforce stereotyping or perpetuate nonmoral values and behaviors, which can lead to higher or lower moral judgment scores (see Kilgannon and Erwin, 1992). These findings are consistent with research that investigates how college students influence each other’s learning and development; in his national study of some 500,000 students, Astin (1993a,b) concluded that “the student’s peer group is the single most potent source of influence and growth and development during the undergraduate years” (p. 398). Summary of Collegiate Contexts and Experiences that Affect Moral Reasoning This section has examined the impact of different collegiate environments and experiences on the development of moral reasoning. These studies suggest that liberal arts colleges are more conducive to promoting the development of moral reasoning than are other types of institutions. However, details about the learning environments (beyond basic categories of institutional type and academic discipline) are largely missing. These traditional categories may yield indicators that are at too gross a level to yield more specific factors associated with changes in the development of moral judgment. The educational programs reported here vary widely in form and content; however, it does appear that most curricular-based interventions and 404
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many co-curricular interventions are effective in promoting moral reasoning. More specifically, interventions with experiential learning components and pedagogical strategies that encourage experiential learning, reflection, group work, active learning, and decision-making are generally more effective in promoting moral judgment than those that use more traditional pedagogies. For co-curricular interventions, it appears that creating contexts and experiences for students to engage in positive interactions with other students may facilitate the development of moral reasoning. While some collegiate environments may enable students to develop friendships with diverse others and thereby facilitate moral perspective-taking, others may encourage relationships that reinforce stereotyping or perpetuate nonmoral behaviors; each in turn can lead to higher or lower moral reasoning scores. For educators to create environments that are effective in promoting moral reasoning, they will need data from studies that use a more finegrained level of analysis when examining learning environments.
THE RELATIONSHIP BETWEEN MORAL REASONING AND OTHER COLLEGIATE OUTCOMES Desired collegiate outcomes (see Bok, 1986; Boyer, 1987; NASULGC, 1997) include not only mastery of disciplinary content, but outcomes that are associated with maturity, including cognitive complexity, a refined sense of one’s self and one’s values, intercultural sensitivity, and sociopolitical awareness. In this section, we ask, “How is moral judgment related to other collegiate outcomes?” We have clustered studies addressing this question into three major categories of collegiate outcomes, cognitive, identity, and social outcomes. COGNITIVE OUTCOMES Rest (1970) argued that moral reasoning is a distinct element of cognitive complexity and not simply the application of more complex cognitive structures to moral content; the studies described below offer evidence on which this claim may be evaluated. Three distinct types of cognitive outcomes have been studied in relation to moral reasoning. The first of these is called “personal epistemology,” a term recently coined by Hofer and Pintrich (2002) to provide an umbrella concept for research on 405
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epistemological assumptions and learning. The other two are more common cognitive outcomes, academic achievement and logical reasoning. Personal Epistemology The most rigorous test of Rest’s (1979a) claim that moral judgment is a distinct element of cognitive complexity was reported in King and Kitchener’s 10-year longitudinal study of reflective judgment (King and Kitchener, 1994; King, Kitchener, Wood, and Davison, 1989). This study used the DIT in conjunction with the Reflective Judgment Interview (RJI), which measures how people reason about complex, controversial problems by examining their underlying assumptions about the nature and certainty of knowledge. RJI and DIT scores correlated moderately (0.46–0.58), and remained positive when the effects of age, education, and verbal ability were statistically controlled. These findings suggest that although reflective judgment and moral reasoning may share common underlying developmental structures, they are conceptually distinct. Bendixen, Schraw, and Dunkle (1998) examined syllogistic reasoning skill, epistemic beliefs and moral reasoning among 154 undergraduates enrolled in an introductory educational psychology class. The authors developed two measurements used in this study, the 32-item Epistemic Beliefs Inventory (EBI) and a 12-item test of syllogistic reasoning (TSR). Four of the five epistemic beliefs comprising the EBI collectively explained more variation in P-scores than did gender, age, education, or syllogistic reasoning. Walker, Rowland, and Boyles (1991) administered the DIT and the Attitudes About Reality (AAR) questionnaire (Unger, Draper, and Pendergrass, 1986) to a sample of 98 university students. The AAR was designed to measure personal epistemology on a continuum from social constructionism (the belief that society determines outcomes for individuals and society as a whole) to logical positivism (the belief that the individual determines her or his own and society’s outcomes). Second order partial correlations controlling for educational status and age were nonsignificant for women (n ⫽ 57) and yielded a negative correlation between P-scores and AAR for men (r ⫽ ⫺0.32, p ⬍ 0.05, n ⫽ 41); that is, men who scored high on the DIT tended to endorse social constructivism. Mentkowski and Associates (2000) investigated causal relationships among many constructs, including role responsibilities, integration of self in context, moral reasoning, and critical thinking. DIT scores were significantly 406
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related to role responsibilities (r ⫽ 0.52, p ⬍ 0.05), integration of self in context (r ⫽ 0.53, p ⬍ 0.05), and critical thinking (r ⫽ 0.53, p ⬍ 0.05). Two years later, the moral reasoning construct was significantly related to two entrance scores, the DIT (r ⫽ 0.59, p ⬍ 0.05) and critical thinking (r ⫽ 0.23, p ⬍ 0.05), and three Year 2 scores: critical thinking (r ⫽ 0.05, p ⬍ 0.05), integration of self in context (r ⫽ 0.16, p ⬍ 0.05), and progress throughout the curriculum (r ⫽ 0.18, p ⬍ 0.05). All of these correlations were embedded within the context of this causal model, where every construct was measured in relationship to all other constructs. After controlling for age and integration of self in context at both points in time, moral reasoning and critical thinking were significantly related. Academic Achievement Eight studies used students’ GPA as a measure of academic achievement in conjunction with the DIT. Seven reported low to moderate positive relationships with moral reasoning, ranging from 0.18 to 0.33 (Clouse, 1991; Dollinger and LaMartina, 1998; Hendel, 1991; Johnson, Insley, Motwani, and Zbib, 1993; Muhlberger, 2000; Murk and Addleman, 1992; Taylor, Waters, Surbeck, and Kelley, 1985); the remaining study reported a nonsignificant correlation (Quarry, 1997). While there is no a priori reason to believe that that GPA and DIT scores would be highly correlated, these studies indicate that at best, GPA makes a modest contribution to DIT score. Also, as noted above, measures of aptitude and intelligence are positively correlated with DIT scores, so positive DIT/GPA correlations may reflect a shared variance among all three measures (ability, GPA, and DIT scores). Hendel (1991) examined two cognitive outcomes, the College Outcome Measures Program (COMP; American College Testing Program, 1988) and the Academic Profile (Educational Testing Service College and University Programs, 1988), along with the DIT using a sample of 118 students. The COMP was designed to assess students’ ability to apply skills and knowledge in ways important to adults outside of the classroom; the Academic Profile was designed to measure general education outcomes in four skills areas: college-level reading, college-level writing, critical thinking, and mathematical data. The DIT positively correlated with both the COMP (r ⫽ 0.49, p ⬍ 0.01) and the overall Academic Profile (r ⫽ 0.41, p ⬍ 0.01), which Hendel interpreted as evidence of convergent validity and similar outcome dimensions among these measures. 407
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Logical Reasoning Several studies have investigated the relationship between DIT scores and the tests of Piagetian formal operations. LaRue and Olejnik (1980) tested introductory psychology students (n ⫽ 36) who were randomly assigned to three experimental conditions (formal operational priming, concrete operational priming, or control) and given tasks to induce different cognitive conditions. P-scores for participants in the formal operation priming condition (M ⫽ 43.9) were significantly higher ( p ⬍ 0.01) than P-scores in both the control (M ⫽ 28.5) and the concrete operational priming conditions (M ⫽ 26.5). The authors posited that procedures that stimulate formal operational thinking can be used to influence moral reasoning. Two studies assessed the relationship between moral reasoning and logical reasoning using the DIT and the How Is Your Logic test (HIYL; Gray, 1976), a paper-and-pencil questionnaire that requires students to perform tasks that demonstrate competencies in both concrete and formal operations. Santilli and Hudson (1992) tested 17 students enrolled in an interpersonal communication training course at two times during the semester and found that formal reasoning is a necessary precursor to the development of postconventional moral reasoning. Young, Cashwell, and Woolington (1998) administered the HIYL to 152 undergraduate students and found no significant correlation between these measures. Two studies used Lawson’s Classroom Test of Formal Reasoning (CTFO; Lawson, 1978) for this purpose. Wanshaffe (2001) administered the CTFO and the DIT to 237 students. Significant differences were found between groups: of the 48 participants using concrete operations, none used principled moral reasoning, six used transitional moral reasoning, and 42 used conventional moral reasoning: of the 37 participants using formal operations, five used principled moral reasoning, 12 used transitional moral reasoning, and 20 used conventional moral reasoning. Taylor, Waters, Surbeck, and Kelley (1985) also used the CTFO to understand how cognitive, psychosocial, and moral development predict pre-service teachers’ ability to analyze child behavior using a sample of 141 juniors and senior education majors. The correlation between the CTFO and the DIT was moderate, r ⫽ 0.35, p ⬍ 0.05. Stepp (2002) examined the relationship between critical thinking and moral development by administering the DIT and the Watson–Glaser Critical Thinking Appraisal (WGCTA; Watson and Glaser, 1980) to 121 first-year college students from a private, Christian, liberal arts college. P-scores were low (M ⫽ 25.6) and significantly related to WGCTA scores (r ⫽ 0.23, p ⬍ 0.01). 408
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Summary of Cognitive Outcomes The vast majority of studies noted here reported positive relationships between the DIT and measures of cognitive outcomes among college students. Higher levels of principled moral reasoning appear to be associated with more sophisticated epistemic belief systems and reasoning strategies, academic achievement, and logical reasoning. Higher order reasoning associated with the achievement of cognitive outcomes may share common developmental structures or be a precursor to developing higher levels of moral principles. Perhaps the development of cognitive complexity that underlies higher order reasoning enables students to see multiple social perspectives inherent in complex moral problems. From a cognitive schema perspective (e.g., Derry, 1996), an increased capacity to engage complex reasoning skills may enable students to more readily access principled moral reasoning schemas when making a moral decision, or to use multiple schemas to organize information surrounding moral issues. Few of these studies attempted to identify underlying influences in the cognitive domain that might affect moral reasoning (or vice versa); doing so would help explain why the relationship between cognitive complexity and moral reasoning is so strong. IDENTITY OUTCOMES The role of colleges in promoting identity development has been a topic of scholarly inquiry since at least the mid-1960s (Chickering, 1969; Erikson, 1968; Loevinger, 1966; Marcia, 1966; Sanford, 1966). More recently, scholars have continued to argue the need to pay more attention to identity-related outcomes in higher education (Baxter Magolda, 2003; Chickering and Reisser, 1993; Palmer, 1998). The construct of identity encompasses a broad range of attributes related to a person’s sense of self, including locus of control, ego development, sense of purpose, religious values, etc. These identity outcomes are discussed below as they are related to moral judgment. Ego Development Many studies have been conducted based on Loevinger’s (1976) comprehensive model of ego development from childhood to adulthood, using the Sentence Completion Test of Ego Development (SCT; Loevinger and 409
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Wessler, 1970). This model consists of nine stages (the middle three of which are common among traditional-age college students) that describe major changes in impulse control, character development, interpersonal style, conscious preoccupation, and cognitive style. Loevinger (1976) interpreted ego development as the “master trait” (p. 41) of personality, seeing ego as the organizing construct into which other aspects of development were subsumed (an assertion strongly disputed by Kohlberg, 1976). We turn to studies examining both ego and moral development to inform this question. Six studies have used the SCT (Loevinger and Wessler, 1970) and the DIT to investigate the relationship between identity and moral reasoning development among college students. All six reported low to moderate positive relationships with moral reasoning, ranging from 0.13 to 0.44 (Dixon and Hudson, 1982;3 Gfellner, 1986; King, Kitchener, Wood, and Davison, 1989; Lutwak, 1984; Mentkowski and Associates, 2000; Whiteley and Associates, 1982). Findings from these studies suggest that although conceptually and structurally related, moral, and ego development are distinct complementary college outcomes. Ego Identity Status Several identity outcome studies have used Marcia’s (1966) model of identity development, which was based on Erikson’s (1959/1980) concepts of the successful resolution of life crises. He identified four identity statuses based on whether or not the individual had experienced a decisionmaking period (a crisis) and made a personal investment in a decision (a commitment). The statuses are: identity diffused (no crisis, no commitment); identity foreclosed (no crisis, commitment); identity moratorium (crisis, no commitment) and identity achieved (crisis, commitment). These statuses are not necessarily progressive, but those who have reached the identity achieved status are characterized as “strong, self-directed, and highly adaptive” (Marcia, 1980, p. 161). Three studies used Marcia’s model of identity development in conjunction with the DIT to assess the relationship between identity status and moral reasoning. Burwell, Butman, and Van Wicklin (1992) and Foster and LaForce (1999) conducted longitudinal studies of changes in moral and 3
Dixon and Hudson (1982) examined ego development using a short form of the SCT (4 of the 26 stems); interpretations from this study must be made with caution given the unknown reliability of this short form.
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ethical decision-making among college students at Christian liberal arts colleges; in both, identity achievers had the highest P-scores and identity foreclosed students had the lowest. These findings suggest that experiences of crisis (the process of decision-making) may stimulate change in moral reasoning. Wanshaffe (2001), however, found no significant relationship between moral reasoning and identity status. Other Identity Measures Other measures of identity have also been used in conjunction with the DIT. For example, Simmons (1983) asked 99 general psychology students to complete several measurement inventories, including the DIT and The Identity Achievement Status Scale (IAS; Simmons, 1970), and created two groups using a median split on the IAS scores. The high IAS group (those scoring above 14) produced significantly higher P-scores ( p ⬍ 0.01) than did students from the low IAS group. Katz (2001) administered the Collective Self-Esteem Scale: SelfEvaluation of One’s Social Identity (CSES; Luhtanen and Crocker, 1992) and the Multigroup Ethnic Identity Measure (MEIM; Phinney, 1992) to students enrolled in an intergroup dialogue course (described in Curricular Experiences section). In the CSES, participants evaluate their own group relative to other groups; higher scores indicate higher group-esteem ratings. The MEIM measures the degree to which one identifies with his or her own ethnic group; higher scores indicate higher identification. These measures were administered to students at the beginning (n ⫽ 74), and at the end of the course (n ⫽ 42). P-scores were negatively correlated with CSES scores (Time 1: r ⫽ ⫺0.34, p ⬍ 0.05; Time 2: r ⫽ ⫺0.36, p ⬍ 0.05) and with MEIM scores at Time 1 (r ⫽ ⫺0.37, p ⬍ 0.05), but not at Time 2. Katz concluded that the CSES and MEIM may measure a sort of group pride or “group-centrism” (p. 110) and that, as this orientation towards group centrism increases, one’s orientation toward justice on a macro-social level decreases. “In essence, as individuals attain an orientation of justice, they are able to cast a wider net around people and groups to whom they owe ethical duty; self-interest bows to fairness, and one’s inner circle is subsumed by the greater human community” (p. 110). Taylor, Waters, Surbeck, and Kelley (1985) administered the DIT and Constantinople’s Inventory of Personality Development (CIPD; Constantinople, 1969) to 141 pre-service teachers and found no significant relationship. Green (1981) used Haymes and Green’s (1982) Needsort to 411
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measure the relative clarity of an individual’s psychosocial, safety, and belongingness needs, and found that for the majority of the 139 pre-service teachers in his sample, satisfying safety needs was a “necessary element” (p. 142) for moral reasoning. Walker, Rowland, and Boyes’ (1991) study (noted above in the cognitive outcomes section) included a measure of “the need for varied, novel, and complex sensation and experiences and the willingness to take physical and social risks for the sake of such experiences” (Zuckerman, 1979, p. 10); no significant relationships between this measure and P-scores were found. Rotenburg, Hewlett, and Siegwart (1998) administered the Selfmonitoring scale (SMS; Snyder, 1974) and the DIT to a sample of 226 students enrolled in an introductory psychology course. The SMS consists of 25 items with three factors: extraversion, acting (e.g., liking to entertain and speak and being good at both) and being other-directed. P-scores were low but significantly related to scores on the Acting subscale only (r ⫽ 0.15, p ⬍ 0.05). Curtis, Billingslea, and Wilson (1988) also examined personality correlates of moral reasoning and attitudes toward authority among 105 undergraduate psychology students. They administered the DIT, the socialization (the extent to which an individual has internalized the rules and norms of society) and empathy scales of the California Psychological Inventory (CPI; Megargee, 1972), and a questionnaire designed to elicit participants’ feelings about authority figures. P-scores were positively correlated with socialization scores (r ⫽ 0.43, p ⬍ 0.05) and empathy scores (r ⫽ 0.69, p ⬍ 0.05), and were negatively correlated with evaluations of both impersonal authority figures such as police officers (r ⫽ ⫺0.60, p ⬍ 0.05) and personal authority figures such as a parent (r ⫽ ⫺0.37, p ⬍ 0.05). Locus of Control Rotter (1966) posited that people hold different perceptions of how internal and external factors govern behavior and events in their lives, and suggested that locus of control could be mapped on a continuum from internal to external. An external orientation reflects a belief that some source outside the self such as fate, chance, or an external being controls the outcome of a situation. Five studies have examined the relationship between locus of control and moral reasoning. Four of these studies (Guthrie, 1985; Felton, 1984; Murk and Addleman, 1992; Whiteley and Associates, 1982) report significant relationships between the DIT and the Internal–External scale, with correlations 412
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ranging between ⫺0.22 and ⫺0.14. These findings indicate that people who are more internally oriented use higher levels of principled moral reasoning when confronted with a moral decision than people who are externallyoriented. By contrast, Ritchie (1991) reported that postconventional moral reasoners were more likely than conventional moral reasoners to have external rather than internal locus of control orientations. Values Mullane (1999) explored the relationship between college students’ perceptions of the procedural fairness and educational value of the disciplinary process and moral reasoning among 73 students at a private university. P-scores were significantly related to the perceived educational value of the disciplinary process (r ⫽ 0.41, p ⬍ 0.01). Mason and Mudrack (1997) administered Froelich and Kottke’s (1991) measure of societal well-being to 115 undergraduate business students. They found that students with higher levels of principled moral reasoning value the interests of wider society to a greater degree than the interests of an organization, but only for the D-score (r ⫽ 0.31, p ⬍ 0.001), not the P-score. Two studies examined the relationship between values and moral reasoning by administering the DIT and a version of Rokeach’s Value Survey Form. Simmons (1982) used Form E (Rokeach, 1973) with 99 students enrolled in a general psychology course. P-scores were low (Md ⫽ 17) and negatively and significantly associated with the terminal value of Mature Love (t ⫽ ⫺2.25) and the instrumental values of being capable (t ⫽ ⫺3.68), imaginative (t ⫽ ⫺3.22) and logical (t ⫽ ⫺2.81). These scores were positively associated with the terminal values of A World at Peace (t ⫽ 2.14) and the instrumental values of being clean (t ⫽ 3.99, p ⬍ 0.05), obedient (t ⫽ 3.79) and polite (t ⫽ 2.91). Using Form G (Rokeach, 1983), Frost, Michael, and Guarino (1997) administered the DIT and the Rokeach Value Survey Form G (Rokeach, 1983), and found no significant relationships to P-scores among a sample of 66 undergraduate students. Two studies examined moral reasoning as it relates to open/closed thought by administering the DIT and Rokeach’s (1960) Dogmatism Scale. Nichols and Stults (1984) studied the responses of 81 introductory psychology students and found that the DIT was negatively correlated with the Dogmatism Scale (r ⫽ ⫺0.33, p ⬍ 0.01). Wahrman (1981) found a similar relationship in his study of 124 students (r ⫽ ⫺0.15, p ⬍ 0.05). 413
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Galotti (1989) asked 64 undergraduate students: “When faced with a moral dilemma, what issues or concerns influence your decision?” Students were equally divided by gender and class (first and second or third and fourth year). Four raters coded these responses, and identified six “feminine-oriented” themes (i.e., what others would think/feel, effect on others, situation specifics, effect on self, personal guilt, and gut feeling) and seven “masculine-oriented” themes (i.e., religious teachings, greater societal good, legal issues, general principle, personal code of ethics, reasoning systematically, and rights of others). The 13 themes shared a low but significant correlation with DIT scores (r ⫽ 0.20, p ⬍ 0.01). Religiosity/Spirituality Clouse (1985) examined the relationship between moral reasoning and the Politics–Religion (P–R) Attitude Scale among 371 students enrolled in an undergraduate psychology course. The P–R attitude scale includes 28 statements designed to assess participants’ agreement with political issues (e.g., free enterprise, communism, patriotism) and with religious issues (e.g., deity of Jesus Christ, life after death, importance of a religious experience). Higher mean scores on the P–R attitude scale reflect more conservative attitudes. Students who were conservative in their Christian faith scored lower on the DIT than did students who were liberal in their religious beliefs. Clouse (1991) later examined how religious experiences, beliefs about religion, and moral reasoning are interrelated. A sample of 393 students enrolled in education courses took the DIT, indicated whether they had ever had a religious experience and whether this experience was with Christianity or another religion, and then took the P–R (described above). A low but significant negative correlation was found between P-scores and conservative religious beliefs (r ⫽ ⫺0.12, p ⬍ 0.05). Burwell, Butman, and Van Wicklin (1992) administered the DIT and the 18-item Religious Problem-Solving Scale (Pargament et al., 1988) to 75 students at the Christian liberal arts colleges at the beginning of their firstyear in college and again at the end of their senior year. The only significant findings occurred at Time 2: deference to God for problem solution was negatively correlated with DIT scores (r ⫽ ⫺0.29, p ⬍ 0.01). Young, Cashwell, and Woolington (1998) examined the relationships among spirituality, cognitive and moral development, and existential sense of meaning in an exploratory study of 152 undergraduate students. 414
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Instruments used in this study included: the Human Spirituality Scale (HSS; Wheat, 1991), the DIT, and the Purpose in Life scale (PIL; Crumbaugh and Maholick, 1981). The HSS consists of 20 items designed to provide a global measure of spirituality; the PIL scale measures the degree to which individuals perceive life as meaningful. The DIT shared significant positive relationships with the HSS (r ⫽ 0.35, p ⬍ 0.01) and the PIL (r ⫽ 0.27, p ⬍ 0.05). In contrast, Simmons (1982) found no significant relationships to PIL scores among 99 students enrolled in a course in general psychology. Summary of Identity Outcomes Studies of the relationship between moral judgment and identity outcomes reviewed here illustrate the breadth of the construct of identity. There are several close conceptual links between these two domains: the common emphasis on social identity issues (how one relates to others), similar descriptions of how development unfolds over time (e.g., a shift in locus of control from external to internal) and descriptions of mature levels of development. Looking specifically at studies of ego development, positive relationships were consistently obtained, even though a variety of analytical strategies were used. This may be explained by the structural similarities between Loevinger’s (1976) and Kohlberg’s (1981) theories and the fact that each describes developmental changes from childhood to adulthood. A similar pattern of findings was obtained in the locus of control studies, where those with an internal locus of control typically earned higher DIT scores than their externally controlled counterparts. The development of internal control may facilitate movement to postconventional reasoning, enabling students to weigh social norms but not use them as absolute dictates. The pattern of results was less clear for Marcia’s (1966) ego identity status, in part because the four statuses are not developmentally ordered prior to identity achievement, which makes both conceptual and analytical comparisons more difficult. However, students in the identity achievement status did tend to score higher on the DIT, even though several instruments were used to measure the construct. As the section on values shows, there are many values (even educationally relevant values) other than moral values. Two findings are consistent with the moral values of postconventional reasoning. These are the positive relationship between DIT scores and valuing the broader interests of society over organizational interests found by Mason and Madrack 415
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(1997) and Mulane’s (1999) finding that students who scored higher on the DIT were more likely to acknowledge the educational value of the campus judicial processes, which tend to emphasize an individual’s responsibility to larger social groups. Are religious beliefs, motivations, ideologies, and experiences related to moral judgment as defined by the DIT? A wide variety of measures and approaches have been used to examine these relationships. Students who hold conservative religious views tend to score lower on the DIT, and may be relying more on church teachings than on moral principles when making moral judgments. Just as blind deference to authority and dogmatic thinking (often associated with fundamentalist religious beliefs) do not reflect advanced levels of cognitive development, similar approaches as applied to religious content are not consistent with the assumptions of postconventional reasoning. The finding of lower than average scores of religious students attending religious institutions is consistent with that reported by Rest (1986) over 15 years ago. It may be that these settings emphasize the maintenance of specific social norms in ways that hinder the development of postconventional thinking (e.g., by discouraging students from stepping back from their own views to consider broader social interests), or that these settings attract religious students who do not use postconventional moral reasoning. Just as religious institutions in these studies are heavily represented by conservative Christian colleges, by far, the dominant religion represented here is Christianity; studies of moral judgment among students of other religious belief systems are largely absent. Within Christian denominations, it appears that the quality of one’s religious experience (not affiliation alone) appears to affect one’s moral judgment, not affiliation or presence of religious experiences per se. SOCIAL OUTCOMES Perhaps more than any other domain of collegiate outcomes, the relationship between social outcomes and moral reasoning is clear and explicit. This is reflected in higher education’s community focus so eloquently described by Boyer (1987), to help students “go beyond their own private interests, learn about the world around them, develop a sense of civic and social responsibility, and discover how they, as individuals, can contribute to the larger society of which they are a part” (pp. 67–8). We have organized the studies in this section according to two major clusters of social outcomes as they relate to moral judgment. The first 416
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section is understanding others, which includes studies of empathy as well as contemporary cultural issues including intercultural sensitivity, tolerance for diversity, and prejudice. The second includes a discussion of what is arguably the ultimate social outcome, moral behaviors.4 Understanding Others Reeves, Bowman, and Cooley (1989) used the Empathy Understanding Scale (EU; Carkhuff, 1983) to assess the empathy of 27 upper-level undergraduate and beginning level graduate students. They found that counseling students with higher levels of moral reasoning demonstrated more empathy for clients who used low moral reasoning than for clients who used higher levels of moral reasoning. In her investigation of the factors that influence voluntary community service in undergraduate students, Hudec (2002) examined the relationship between empathy and moral reasoning of two groups of students. Using Jackson’s (1994) Personality Inventory-Revised, she surveyed those who volunteered for community service (n ⫽ 83) and those who did not (n ⫽ 129). No significant correlations between moral reasoning and empathy were found for either group of students. Endicott, Bock, and Narvaez (2003) studied 70 undergraduate students from a large, midwestern university to examine the relationship between the development of moral judgment as measured by the DIT2, and the development of intercultural sensitivity using the Intercultural Development Inventory (IDI; Hammer and Bennett, 1998). Higher scores on the IDI reflect higher orientiation toward intercultural sensitivity. The correlation between DIT2 scores and the composite measure of intercultural sensitivity was r ⫽ 0.24, p ⬍ 0.05. The authors concluded that the relationship between moral reasoning and intercultural sensitivity is rooted in cognitive flexibility, “the ability to understand, consider, and weigh multiple frameworks or schemas” (p. 16), that considering moral frameworks requires flexible moral thinking, and that considering cultural frameworks requires flexible intercultural thinking. 4
A third cluster that arguably belongs here is political attitudes. Although moral and political reasoning share a common focus on the adequacy of socio-political arrangements, we excluded this body of research from this review due to space constraints and the question of whether political attitudes should be considered as an intended collegiate outcome. General reviews (not specific to college students) have been written by Rest et al. (1999a), Thoma (1993), and Narvaez et al. (1999).
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Glover (1994) examined how moral reasoning predicted prejudice among 207 university students by administering the Katz–Hass Attitude Value Scale (Katz and Hass, 1988) and the McConahay, Hardee, and Batts (1981) measure of traditional and modern racism. Higher DIT scores were significantly related to positive attitudes toward minorities (r ⫽ ⫺0.28, p ⬍ 0.01; items for attitudes toward minorities were reverse scored). Regression analyses used the DIT in conjunction with age, education, cognitive complexity, and commitment to humanitarian-egalitarianism to predict positive attitudes toward minorities and expressions of traditional racism; these showed that principled moral reasoning was not a significant predictor of either of these outcomes. Eyler (1980) investigated the relationship between principled thinking and tolerance for conflict and diversity. She administered the DIT and a questionnaire containing items that measure students’ positions on minority rights to 120 first-year college students. Among the high moral reasoning group, 88 percent endorsed issues pertaining to minority rights, compared to 61 percent of the low moral reasoning group who endorsed these rights. These results suggest that higher levels of principled moral thinking may facilitate the individuals’ capacity to endorse the rights of people from minority groups. Longsdon, Thompson, and Reid (1994) examined the relationship between level of moral judgment and attitudes toward illegal software copying. A sample of 373 students (of whom 120 were undergraduates) enrolled in business and engineering courses, were administered the DIT and a measure of respondents’ attitudes toward copying behavior (ATTBEH; Swinyard, Rinne, and Kengkau, 1990). The ATTBEH consisted of the sum of the responses to four statements about copying behaviors, with higher scores indicating that a respondent would not copy software. A significant correlation was found between the ATTBEH and D-score, but not for the P-score. The authors suggested, among other explanations, that software piracy is not perceived as “morally intense.” Perhaps this finding reflects Component 1 in Rest’s (1986) model, that students do not perceive software privacy as having a salient moral dimension. Behaviors toward Others Many scholars (e.g., Blasi, 1980) have argued that morality ultimately lies in action and that assessment strategies intended to measure morality should use action as its final criterion. For these reasons, many studies 418
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have focused on observable moral behaviors and their relationship to moral reasoning. Several comprehensive literature reviews have been published to examine whether moral judgment as measured by the DIT predicts moral behaviors (Blasi, 1980; Rest et al., 1986; Thoma and Rest, 1986; Thoma, 1994). King and Mayhew’s (2002) review specifically examined the relationship between moral reasoning and moral behaviors among undergraduate college students. They reported that students with higher postconventional moral reasoning scores were more likely to: engage in “whistle-blowing” under conditions that made it more difficult to ascertain truth (Brabeck, 1984), claim conscientious objector status in regard to being drafted into the military (Hay, 1983), cast “not guilty” votes as jurors at a simulated trial (Lupfer et al., 1987), demonstrate competencies in nursing clinical performance (Duckett and Ryden, 1994) and in business writing (Cartwright and Simpson, 1990). Such students were less likely to engage in academic misconduct (Cummings et al., 2001; Malinowki and Smith, 1985), exhibit aggression in athletics (Bredemeier and Shields, 1984), or engage in risky sexual behaviors (Hubbs-Tait and Garmon, 1995). Only three studies (Cartwright and Simpson, 1990; Ponemon, 1993; Taylor et al., 1985) failed to show that moral reasoning significantly predicted moral behaviors. Here, we add two studies to the list of those described above. Muhlberger (2000) presented a model of moral reasoning sophistication that examined the effects of moral reasoning on the weight 119 students placed on moral versus nonmoral considerations when they decided whether or not to participate in public interest groups. Respondents with high P-scores stressed morally relevant considerations (e.g., sense of responsibility to contribute to group goals) over nonmoral considerations (e.g., “How good would I feel about myself if I acted on these goals?”) (p. 672) and selective incentives: “Will I make friends, will I benefit materially?” (p. 672). Respondents with lower P-scores considered nonmoral over moral considerations when deciding whether or not to participate in public interest groups. Participants with higher P-scores had a higher probability of leaving phone numbers so they could be contacted to participate in the public interest group and had a higher probability of attending the group meeting. These findings suggest that moral reasoning does affect political engagement. Hudec (2002) investigated moral reasoning as related to college students’ participation in voluntary community service. Students in this sample completed a required service-learning experience during their first 419
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semester in college and were tested three times over the course of one year. An analysis of covariance controlling for the DIT score Time 1 showed that post-test P-scores significantly predicted whether or not students participated in subsequent voluntary community service, F(1, 212) ⫽ 38.88, p ⬍ 0.01. In addition, DIT scores increased from 27.2 to 34.1 (n ⫽ 83) for those who chose to participate in volunteer community service after their service learning experience and stayed the same for those who chose not to participate (n ⫽ 129). These findings suggest that participation in service learning requirements positively affects moral reasoning, which may serve as a mediating variable on students’ choices to engage in voluntary community service. Summary of Social Outcomes Is the achievement of collegiate social outcomes (e.g., productive citizenship, skills associated with participation in a democracy, moral leadership) associated with the development of moral judgment? The studies in this section illustrate the wide variety of ways this general question has been studied and the variety of social outcomes that have been examined in relation to moral judgment. A major developmental advance that lies at the heart of many findings in this section is the shift from conventional (or maintaining norms in neo-Kohlbergian terms) to postconventional reasoning. The significance of this shift is that it reflects the ability and inclination to examine the fairness of social systems, and the understanding that social systems are cultural constructions that can be changed. In the first category of social outcomes, understanding others, several findings suggest that moral judgment plays an important role in the achievement of diversity outcomes, such as the positive relationships found between DIT scores and attitudes toward minorities (Glover, 1994), minority rights (Eyler, 1980), intercultural sensitivity (Endicott, Bock, and Narvaez, 2003), and lower levels of traditional racism (Glover, 1994). Although it would seem that empathy would be closely related to moral judgment, the studies reviewed here do not offer compelling evidence in this regard, perhaps because empathy is a Component 1 attribute while moral judgment is a Component 3 attribute (see above discussion of Rest’s Four-Component Model). Given the pressing nature of contemporary social issues in general and diversity issues in particular, coupled with a surge of scholarly output around diversity issues in the last two decades, 420
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the paucity of research relating moral judgment to social outcomes such as these is also striking. A stricter test of whether moral judgment is related to collegiate social outcomes is provided by studies that link moral judgment to behavior toward others, the second category of social outcomes. In his detailed review of the relationship between moral judgment and moral action, Thoma (1994) observed that understanding moral action is “the acid test” (p. 199) of the usefulness of research on morality; a similar observation may be made about behaviors demonstrating the usefulness of a college education. Thoma’s evidence, that reported by King and Mayhew (2002), and the additional studies summarized here all point to a strong relationship between moral reasoning and civic behavior. In the additional studies summarized here, this link was seen in taking a stand for civil liberties (Derryberry and Thoma, 2002), stressing moral considerations when deciding whether or not to participate in public interest groups (Muhlberger, 2000), and in the predictive value of P-scores on students’ decision to participate in community service activities (Hudec, 2002). The production of moral behavior is obviously a complex process affected by many factors, from empathy and moral motivation to community expectations and standards; what this body of research shows is that moral judgment in general and postconventional thinking in particular clearly affect one’s engagement in moral actions.
CONCLUSION Moral development has been an aim of higher education since its inception, and there has been a resurgence of interest in this domain of college outcomes in the last few years. At a time of increased national interest in character education, educators, researchers, and policy makers need information that helps them understand the nature, the assessment, and the mechanisms underlying moral development. In particular, they need to know how college students develop along moral dimensions, and how institutions can create and evaluate educational experiences for this development to occur. This review has attempted to address this need by providing a comprehensive review of the literature on the development of moral reasoning among undergraduate students. We found strong evidence that significant growth in the use of postconventional moral reasoning does occur in college, and that this growth is not solely attributable to general maturation. This finding may be gratifying 421
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to educators and policy makers who have directed their efforts to promoting prosocial values such as civic responsibility and social justice and the skills to reason complexly about topics with social consequences. Perhaps the general intellectual and social milieu of colleges and universities fosters the exchange of ideas, exposure to multiple perspectives regarding social issues, the development of academic values of truth-seeking and careful reasoning, and institutional values of academic integrity and personal responsibility. We found that students enter collegiate environments with a number of pre-college experiences and characteristics that appear to influence their capacity for moral reasoning. In particular, being female, having higher aptitude/intelligence, being politically liberal, and being open to new experiences were found to be positively related to postconventional reasoning, but SES, ethnicity, and religious affiliation were not. We also found that certain types of collegiate environments and experiences influence the development of moral reasoning, but that evaluating the effectiveness of some of these environments using the broad categories of institutional type and academic discipline provided little information about how these contexts influence moral reasoning. Studies that examine more specific experiences that contribute to growth in moral reasoning offer a finer-grained analysis and more informative findings. For example, these studies indicate that pedagogical strategies that encourage experiential learning, reflection, group work, active learning, and decision-making are more effective in promoting moral judgment than those that use more traditional pedagogies. The quality and intensity of students’ experiences with other students also appears to have a positive impact on moral reasoning. This review differs from prior reviews in that it examined moral reasoning in relationship to other college outcomes, organized by cognitive, identity, and other social outcomes. Many of the studies found that moral reasoning is positively related to cognitive outcomes, such as using more sophisticated epistemic belief systems and reasoning strategies. However, although cognitive complexity and moral reasoning may share common theoretical derivations and developmental structures, they are conceptually distinct. Perhaps the development of cognitive complexity makes students more aware of the moral dimension of problems that require higher levels of reasoning for their resolution. From a cognitive schema perspective, perhaps increases in cognitive complexity allow the boundaries of schemas used to organize information about moral issues to become more flexible. This allows information that used to be considered morally irrelevant to become relevant and integrated into the moral schema. Alternatively, it may 422
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be that the development of cognitive complexity facilitates the use of multiple schemas to organize information surrounding moral issues. Findings regarding the relationship between moral reasoning and identity outcomes are less conclusive because of the breadth of the identity construct itself, the wide array of instruments used to measure identity-related characteristics, and the fact that some are developmentally grounded (e.g., ego functioning) and others are seen as traits (e.g., Myers–Briggs preferences). Personal values that emphasize an individual’s roles and responsibilities in broader social systems are consistent with underlying principles of postconventional moral reasoning, so they would be expected to yield a stronger relationship with moral reasoning. For a more complete picture of how these two constructs relate, it might be necessary for scholars to specify domains of identity development as Rest (1984) did for the four major domains of moral development. The relationships described here between moral judgment and other social outcomes are of interest because of their shared emphasis on many attributes related to outcomes such as civic engagement and democratic values, and more specifically, evaluating the formal structures of society (laws, roles, institutions, legal, and social practices). Postconventional reasoning enables a person to evaluate the fairness of these structures not only from the perspectives of those affected, but based on moral principles that supercede individual perspectives. This level of evaluation is at the heart of the studies grouped here in the category of understanding others. In addition, if the production of moral behavior is the proverbial “proof of the pudding” in terms of the importance of moral judgment, then the findings demonstrating the links between postconventional reasoning and moral actions are reassuring. Indeed, if complex, postconventional reasoning somehow enables moral action, then efforts designed to assist students to reason from broader perspectives of fairness based on moral principles may be well placed.
RECOMMENDATIONS FOR FUTURE RESEARCH A major finding from this review is that significant growth in the use of postconventional moral reasoning does occur in college, is not attributable solely to general maturation, and is evident even after controlling for age and entering level of moral judgment. At the same time, many questions remain concerning the influences on development in moral reasoning that 423
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are associated with collegiate participation. What will be needed in the next phases of research to better understand the nature and mechanism of moral development in adults who are engaged in study in collegiate settings? First, Figure 9.1 shows the variety of variables that have been used in studies that have addressed some aspect of moral development with college students. This is an empirically derived figure (i.e., what has been studied), but has the potential to inform the development of a conceptually derived map of this domain. Given the complexity of variables that play a role in students’ moral development, our first recommendation is that larger scale studies be conducted utilizing more sophisticated statistical techniques to better discern factors that lead to the development of moral reasoning. Few of the studies reviewed here partialled out the effects of student demographic, pedagogical, or curricular covariates. Only one (Mentkowski and Associates, 2002) used causal modeling to indicate how different factors and experiences work together to explain how educational contexts influence moral reasoning, and none used hierarchical linear modeling to identify and weigh nested contextual effects on moral development. In addition, case studies and ethnographies are needed to capture information concerning ways in which institutional characteristics, cultures, and subcultures (both curricular and cocurricular) affect the moral reasoning of undergraduate students. Mixed methods approaches that use these in conjunction with measures of moral reasoning might be especially insightful in explaining why some educational contexts are effective in promoting moral reasoning while others are not. For example, administering the DIT to students before and after an intervention and then conducting in-depth interviews in a way that would allow comparison on the basis of gain scores might provide rich information on which students characteristics’ or features of the experience set the conditions for this growth. Studies that more carefully examine the conditions for growth are needed. Are liberal arts colleges more successful in this regard because they attract students who are more open to thinking about moral dilemmas? Does their smaller size provide greater access to opportunities for direct involvement and positions of responsibility for others? Are smaller classes better used for discussions of social issues? Or are these learning environments more effective because they more fully examine the role of values in students’ lives, offer more opportunities to practice reasoning about moral issues, or provide a curriculum that stresses examining social issues through the lens of moral philosophy? Similarly, studying the 424
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subcultures of those environments that do not appear to promote moral development (e.g., fraternities and accounting courses) may be enlightening. Do such subcultures attract those for whom prosocial attitudes or behaviors are less central? Do the formal and informal practices in such learning environments give higher value to non-moral attributes? Addressing these questions might also create a fruitful line of research. The interventions reviewed here offer other promising approaches for identifying important influences on moral development. However, many of these studies employed research designs that do not allow the reader to confidently attribute growth in moral reasoning to the intervention. Specifically, such studies would be strengthened by meeting experimental research design criteria, such as carefully selecting control or comparison groups, employing sampling strategies that allow for the control of selection effects, providing detailed descriptions of the major features of the intervention, designing conceptually grounded interventions, and testing for stability in change scores after the post-tests. Is moral development enhanced by the kinds of good practices being espoused by professional associations and scholars of learning and development, such as connecting the curriculum to personally meaningful topics, providing opportunities for reflection, practice, and feedback, having substantive interactions with other students, especially with diverse peers, and interacting more frequently with faculty? A large body of research has documented the powerful effects of student involvement in co-curricular activities (Kuh, Schuh, Whitt, and Associates, 1991; Pascarella and Terenzini, 1991), yet this context is minimally reflected in this review. The effects on moral reasoning of student involvement in study abroad programs, community-outreach activities, campus judicial systems, leadership positions, and peer conflict mediation programs remain largely unexplored. The dearth of studies that investigate moral reasoning as it relates to other democratic outcomes (i.e., intercultural sensitivity, multicultural competence, etc.) is alarming, especially given recent research efforts that suggest how institutions are increasingly recognizing the educational value of diversity in the classroom and its role in positively affecting studentlearning outcomes (Gurin, Dey, Hurtado, and Gurin, 2002). Future research is needed to address these relationships; for these studies, we think it would be important to incorporate more research using sampling strategies that enable the participation of students from many racial and ethnic backgrounds. 425
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In this collection of studies, we identified several limitations that impeded interpretation or otherwise diminished the value of the studies for the purpose of this review. In addition to the need for more carefully designed intervention studies noted above, two other limitations merit comment here, sampling and data analysis. First, several studies provided inadequate sample descriptions (e.g., “college students”), masking variability by age, class level, and other variables that are relevant when interpreting the impact of college on the moral reasoning of students. In addition, many studies appeared to use college students as convenience samples or as proxies for reasonably bright adults, with no particular emphasis on college as an educational context nor on college students as a purposeful sample. Moreover, several studies used samples that relied heavily on first- and second-year students from psychology pools; this strategy has the potential of skewing findings toward students who are younger and near the beginning of their college experiences. Samples that are limited to students from these pools risk underestimating moral reasoning development compared with samples that include younger students and/or older students with more life experiences. Second, many studies used stage score as the dependent variable instead of P- and D-scores. This violates the theoretical assumptions underlying the construction of the DIT by classifying respondents as being “in” a stage. In addition, many studies performed median splits on their student samples in an effort to categorize and compare high versus low groups of moral reasoners. This procedure can be misleading; in several studies, it yielded a cluster of “high” P-scores which were higher than average for that sample, but quite low relative to college norms and to the scales of moral development on which the DIT is based. Comparing low and high groups this way can easily lead to misinterpretation, especially when making recommendations that are differentiated for high and low scorers. The final recommendation we make for improving our understanding of moral development among college students is to conduct a meta-analysis of these findings, combining samples across studies to investigate the factors affecting moral reasoning using more robust data analysis techniques. This would allow for the studies of growth in moral reasoning over the last 20 years to be compared to changes in student values that have been reported using large national data sets. For example, Thoma (personal communication, 11–7-02) suggested examining the effect size for moral reasoning across successive cohorts and relating this to the well-documented 426
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(Astin, 2002) decline in entering students’ espoused goal of developing a meaningful philosophy of life in college. Creative studies like these would add depth and new insights to the already substantial literature on moral reasoning as an intended outcome of college.
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10. FACULTY PROFESSIONAL DEVELOPMENT FOR THE 21ST CENTURY Christine A. Stanley Texas A&M University
In 1981, Jack Lindquist wrote, “Eric French is a 46 year-old full professor of English, more precisely of English Romantic Poetry. And he is in a midlife quandry. He has 30 articles and a textbook behind him, but no new topic catches his fancy. Indeed, he is wondering whether it was all worth the effort. He sees little more career climbing to do. He has been active in the Modern Language Association and in the Faculty Senate and is glad to be free of those political hassles. He has no interest in chairing the department or becoming a dean. Most of his teaching consists of upper-division and graduate courses in his specialty, but he has been doing those courses for years and is weary of the same material, the same student essays, the same class discussions. That weariness shows in declining student ratings. There are no great traumas at home, but even there the routine is getting pretty dull. The same office, the same chitchat, the same house, the same daily search for parking, the same petty squabbles and budget threats in the department, the same social circuit, the same lousy weather? Is that all there is? Mean while, over in Biology, Geneva Westgate stews over an impending tenure decision. Now 34, she went straight into teaching from graduate school. The university is her life. She has completed her dissertation and has published four well-received articles, but she has not published in the last two years. Instead, she has discovered undergraduate students and has found introductory biology and bioethics exciting vehicles for aiding their intellectual development. To become more skilled in teaching, she has attended faculty development workshops, and she is now serving on a team that is trying to get a formal
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faculty development program going. Yet there have been two troubling consequences for her new enthusiasm. One is that her growing assertiveness, born of her own developmental need for self-esteem and autonomy, seems to be making her husband and colleagues uncomfortable. The other problem is that her colleagues in the biology department have intimated, though not directly said, that all this attention to undergraduate student development, while laudable, is not helping the department build a reputation for graduate education and research. What if she fails to get tenure? What if her marriage breaks up? How can she pursue her own development and that of her students in a system that appears to be thwarting both? Down the hall, Dean Elinor Jackson finds her mind wandering from the curriculum committee discussion. How these committees can drone on! She sits on six different standing committees, ex officio, and has another four special task forces going, and none of them seem to get anywhere. Costs continue to spiral, educational problems mount, and the faculty union gets more obstreperous by the day. There must be a better way to run this college, but nothing in Elinor’s background as a professor of political science has prepared her for this mess. Worse, the job demands 60 hours a week reacting to everyone else’s agendas, she seems to have become the enemy of her faculty colleagues, and she is beginning to lose her patience in the office and at home. What is she doing in this impossible job? Is there a way to become more effective in administrative leadership and even to enjoy it? Is she ready to give up the status, the salary, the perquisites, the aspirations to a college presidency? Sitting in the faculty lounge is George Miller, who likes to think of himself as a professor of nineteenth-century American history, with a special interest in Emerson and Thoreau. He calls himself a “humanist.” But the administrators seem to think of him as a teacher of remedial reading and writing. The few students who enroll in his classes seem to think of George as a foggy and irrelevant white male chauvinist. To his colleagues in the faculty lounge he rails against administration and students alike. “Philistines all! Disco dancers on the grave of Western civilization!” But left to himself, he worries that he is not able to teach reading and writing; that he may be prejudiced against women and minority races; that he cannot present his subject in ways that excite today’s students; that his position will be cut if he cannot attract more students” (Lindquist, 1981, pp. 730–731). When I came across these scenarios in a chapter on “Professional Development” by Jack Lindquist in The Modern American College, I could not help but be amazed at how little the composite characters of these faculty and their experiences have changed since 1981. Here I am, at the writing of 442
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this chapter in 2002, and the halls of academe are still occupied with faculty and with very similar challenges, such as the ones presented here by “Eric French,” “Geneva Westgate,” “Elinor Jackson,” and “George Miller.” Like Jack Lindquist, I too, have come across these individuals in various faculty professional development activities such as consultations on teaching, workshops and seminars on teaching, new faculty orientations, and teaching retreats. In these characters I see similar, yet new, faculty development challenges faced by institutions in higher education as we enter the 21st century. When asked to write a chapter for this Handbook, I was excited, nervous, and yet humbled. I was excited because I thought of this as an opportunity for me to discuss the research I have been engaged in, as well as the work of others, on a topic that has consumed the greater part of my scholarly life. I was also nervous, because of the audience and company in which I would be keeping, and humbled, because I know that I have much to learn on the topic as well. When I think of senior scholars who have made and continue to make an impact on the field of faculty professional development the names of William Berquist, Jack Lindquist, Robert Diamond, Richard Tiberius, Robert Menges, Ann Austin, Nancy Chism, Marilla Svinicki, Kay Herr Gillespie, Wilbert McKeachie, and Mary Deane Sorcinelli, to name a few, come immediately to mind. I approach this topic somewhat differently, as a faculty development specialist of color, with a relatively long period of time observing the evolution of this emerging field. In this chapter, I will attempt to provide an overview of faculty development in higher education. Included in this overview, I would like to focus on its past and current context, the teaching development of the future professoriate, the process of development in college teachers, and then pose new reasons for concern, new possibilities for faculty professional development, and some measures for assessing faculty competence. In particular, I would like to examine, within the changing context of higher education, faculty vitality and competence in the context of the broader scholarship of faculty work framed by Ernest Boyer — the scholarship of teaching, the scholarship of discovery, the scholarship of integration, and the scholarship of application (Boyer, 1990).
HISTORY OF FACULTY DEVELOPMENT: AN OVERVIEW Faculty development and the development of professional competencies for faculty has been an integral force in higher education for some time. 443
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The pathway to the professoriate is through the attainment of a terminal degree in some disciplinary area at a recognized university. Knowledge of one’s disciplinary area and the contribution and demonstrated impact of new knowledge to the field are key criteria for promotion and tenure in institutions of higher education. It is not surprising then that faculty development came to mean the development of expertise in one’s discipline. In order to support faculty in their endeavor to remain current in their fields, colleges and universities created opportunities such as sabbatical leaves, allocated resources for travel to professional conferences, and designated funds for conducting research. These professional activities are now commonplace in faculty development programs in institutions of higher education (Gaff and Simpson, 1994). While faculty professional development encompasses faculty work in teaching, research, and service, the primary focus of this chapter will be on the development of faculty as teachers. It was not until the 1960s and 1970s that institutions of higher education began to pay particular attention to “more purposeful and intentional faculty development, and our knowledge and understanding of this emerged field has steadily increased over the years” (Gillespie, 2002, p. ix). The 1970s saw the creation of new approaches to the professional development of faculty. These new approaches emphasized teaching. Faced with the enrollment of college age baby boomers and retrenchment from the recession of the 1970s, institutions of higher education could not help but pay attention to the improvement of teaching. For example, student protests during the late 1960s and early 1970s criticized college curricula and teaching, in particular, the irrelevancy of certain courses, and the quality of teaching (Mathis, 1982; Gaff and Simpson, 1994). “Since the protests took place at universities with the greatest concentration of leading scholars, they exposed the myth that, all that is required to be a good teacher is to know one’s subject” (Gaff and Simpson, 1994, p. 168). The rising numbers of nontraditional graduate students also challenged traditional teaching methods, with many of them calling for more creative and relevant approaches to their learning experiences. At the same time, the average of the faculty began to rise and the importance given to teaching also increased (Mathis, 1982; Menges and Brinko, 1990). In the 1980s, faced with these challenges, colleges and universities established instructional development programs (Toombs, 1983; Clark and Lewis, 1985; Eble and McKeachie, 1985). Many of these programs were developed with the assistance of grants from private foundations and agencies such as the Danforth Foundation, the Lilly Endowment, the W.K. Kellogg 444
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Foundation, the Exxon Education Foundation, and the Andrew W. Mellon Foundation. Federal agencies such as the National Endowment for the Humanities, National Science Foundation, and the Fund for the Improvement of Postsecondary Education (FIPSE) were very supportive of faculty development efforts in higher education (Gaff and Simpson, 1994; Diamond, 2002). Reports from the National Endowment for the Humanities (Bennett, 1984), the Association of American Colleges and Universities (1985), Ernest Boyer of the Carnegie Foundation (1986), and the National Education Association (1996) identified pressing issues in higher education. Specifically, these reports called attention to the lack of breadth in the content of courses and curricula, the overspecialization in the preparation of faculty, and the quality of teaching and learning in colleges and universities (Diamond, 2002). As a result of these reports and external pressures, institutions of higher education began to explore ways in which they could improve the quality and effectiveness of academic programs and teaching and learning (Gaff and Simpson, 1994; Diamond, 2002a). The efforts used to improve the quality of teaching and learning have been conceptualized as faculty, instructional, and organizational development (Berquist and Phillips, 1975; Gaff, 1975). In earlier, more traditional definitions of faculty development, the term usually referred to support for research, scholarship, and sabbatical leaves (Lunde and Healy, 1991). Another view of faculty development came from the perspective of life-span developmental psychology recognizing the needs of unrecognized faculty — women academics, late entry academics, dual career couples, and retirees (Hodgkinson, 1974; Cytrynbaum, Lee, and Wadner, 1982). In the 1970s, the term was reexamined to include a broader and deeper level of understanding to capture the approaches used by institutions in higher education to improve the quality of teaching and learning (Lunde and Healy, 1991; Diamond, 2002a). Faculty development has often been referred to as “an amorphous process” and the terms, “vitality” and “renewal” have been used frequently to describe the purpose of faculty development efforts (Menges and Mathis, 1988). In a report of the status of 11 campus faculty development centers in southern universities as they were organized in 1976, Crow, Milton, Moomaw, and O’Connell (1976) defines faculty development as “the total development of the faculty member — as a person, as a professional, and as a member of the academic community” (p. 3). In general, efforts to enhance the quality of teaching and learning in higher education have been referred to as faculty development. The term, 445
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“professional development” is used loosely and sometimes interchangeably with three approaches — faculty development (focus on the faculty member), instructional development (focus on student learning outcomes through course and curriculum development), and organizational development (focus on the institutional climate and reward system for teaching) (Diamond, 2002a). The three approaches, although different and overlapping in the types of activities emphasized, have very specific outcomes. Faculty development emphasizes enhancing the teaching skills of individual faculty members. Institutions of higher education have long recognized, research demonstrates, and faculty readily admit as teachers, that faculty tend to teach the way they were taught or learned. It is not surprising then, that many faculty enter academia without any formal preparation in teaching or that seasoned faculty need occasional “booster shots.” Furthermore, with the changing demands on higher education, coupled with an ever-changing student population, the need to remain current and vital in one’s teaching and learning approaches is imperative. Every year, for the last 5 years I have taught the college teaching course in my department, for example, there are consistent comments on my student evaluations of teaching that resonates, “This course should be a core course in the graduate curriculum.” Bill McKeachie, Professor Emeritus of Psychology, who has studied and researched faculty development, methods of college teaching, and faculty evaluation using quantitative and qualitative methods since 1948, asserts, among the several lessons learned in training college teachers, is that faculty value teaching and find it to be rewarding when they do it well. Most ineffective teaching results not from lack of motivation, but from anxiety and feelings of incompetence. He also states that if we are to improve teaching, we need to help faculty develop a repertoire of effective skills for facilitating student learning. Peers can be an invaluable resource in these efforts by providing emotional and motivational support (McKeachie, 1990, 1993). Common approaches to enhancing the teaching skills of faculty include interventions such as classroom observations of teaching by faculty development professionals, colleagues helping colleagues, individual consultation on teaching, workshops and seminars, and the use of multimedia to analyze presentation skills and teaching styles. Classroom observation of teaching is probably the most widely used faculty development intervention to gather feedback on teaching for summative and formative decisions on teaching. According to Evertson and Holley (1981), “classroom observation gives us a view of the climate, rapport, interaction, and functioning of 446
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the classroom available from no other source” (p. 90). Though it is a timeconsuming process, it can provide a wealth of information about what is affecting the teaching and learning process (Lewis, 1997). Also, without some knowledge of what is occurring in the classroom, it is difficult to interpret, for example, comments one might read on student evaluations. The research on instructional consultation, for example, support the conclusion that consultation over student evaluation of teaching data improves teaching (Levinson-Rose and Menges, 1981; Murray, 1984). An instructional consultation may involve a visit to the faculty development consultant’s office to discuss the results of mid-course or end-of-semester student evaluations. The most effective discussions focus on the instructor’s behaviors. Focusing on specific, individual, and observable behaviors enables the consultant to provide feedback that is concrete to effect change in teaching and learning (Murray, 1984; Wilson, 1986; Stanley, Porter, and Szabo, 1997). A review of the research on instructional interventions and their efforts to improve instruction reveal that “more research needs to be undertaken” to support the “wisdom of practice and the voice of experience” present in the literature (Weimer and Lenze, 1997). The teaching improvement process is a highly individualized, voluntary, and confidential process. What works for one faculty member will not work for another. The most important outcome of the teaching improvement process is that it is focused on the faculty member’s needs (Brinko, 1993; Stanley, Porter, and Szabo, 1997). Typically taking place over the course of a semester or the amount of time it takes to effect change, the process includes four phases: (1) assessment of teaching and learning through interventions such as student interviews, classroom observation, videotape of classroom teaching, student feedback, and selfassessment, (2) analysis of the information presented from data gathered through these interventions to identify strengths and areas for improvement, (3) formulating plans and goal setting for improvement through cycles of experimentation and feedback, and (4) a final review and analysis to observe and document changes (Sorcinelli, 1997). Research and practice show that mandatory improvement programs for teachers who are perceived as having difficulties in the classroom do not work (Sorcinelli and Cunningham, 1991). While some faculty are able to improve their teaching after feedback in isolation, a deeper change is more likely if a consultant or more knowledgeable colleague can help interpret information, provide challenge and support, and suggest alternative ways of knowing and thinking about teaching and learning (Sorcinelli, 1997). Erickson and 447
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Erickson (1979) evaluated the effectiveness of the teaching consultation process by comparing results of an experimental group and a control group of volunteer faculty at one institution. Results of this study and a later follow-up study showed that “volunteer faculty who use the teaching consultation process consider it useful and well worth their time and effort, and that it resulted in significant, positive, and lasting changes in their classroom teaching performance” (p. 683). Peer review of teaching might also be a part of the faculty development approach. Arguments made in the literature on peer review of teaching have focused on the responsibility of the profession to monitor itself. The concept of “teaching as community property” proposed by Lee Schulman of Stanford University, for example, leads us to a discussion about the various kinds of collaborative activity among faculty, such as team teaching, the teaching seminar that is often used in the faculty interview and hiring process, course materials, libraries of course syllabi, and research papers on college teaching. Many scholars have argued for peer review to be a permanent part of the faculty development structure in college and universities (Hutchings, 1996; Quinlan, 1996). “The rationale is that faculty must be continually engaged in discussing teaching in order to both nurture new teachers into the community of teacher-scholars and to render the process of making personnel decisions (who gets hired, who gets tenured, who gets merit pay)” (Chism, 1999, p. 6). An often overlooked area in peer review of teaching is preparing colleagues to assess each other’s teaching. Such preparatory sessions can be facilitated by a faculty development consultant, a skilled member of the department, or a faculty member from another department (Chism, 1999). Peer review of teaching as a faculty development initiative requires institutional, college, and departmental leadership. According to Diamond (2002a,b), “When an institution has clear faculty development plans and opportunities for faculty, it sends the message that there is concern for the individual” (p. 4). Desirable outcomes of the faculty development approach include increased scholarly productivity, a focus on student learning outcomes, and an improved attitude toward teaching excellence. There is agreement in the faculty professional development literature that the instructional development approach to teaching and learning emphasizes the improvement of courses and curricula through curriculum development and enhancement, implementation, and evaluation. The appropriate use of instructional technologies is also a part of this approach. 448
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Abedor and Sachs (1978) contend that instructional development is a systematic method for identifying, modifying, or developing innovations in teaching. The process focuses on the design, development, implementation, and evaluation of instructional materials, lessons, courses or curricula in order to improve teaching and learning. Desirable outcomes include the potential of these activities to increase student recruitment and retention, faculty and student satisfaction with courses and curricula, a focus on student learning, and an overall improvement of academic effectiveness and efficiency (Diamond, 2002). Finding, modifying or developing innovations in teaching is only a small part of the process of influencing change in teaching. Abedor and Sachs (1978) argue that it is also necessary that innovations be valued by the individuals and the organizations who will use them. Faculty and universities are complex entities. Each has a number of characteristics that can affect the degree to which an innovation in teaching is adopted. The characteristics which appear to be the most influential in affecting instructional change are: (1) attitudes about self and how this influences teaching and learning, (2) values placed on the importance of teaching, (3) beliefs that efforts to enhance teaching are worthwhile, (4) skills needed in teaching, and (5) knowledge of the subject matter, teaching, teaching methods, and strategies (Abedor and Sachs, 1978). Organizational development emphasizes the climate and reward system for teaching and learning. Activities may include workshop, seminars, retreats, and individual consultation for academic administrators and faculty. Simply put, organizational development activities seek to change the university’s structure, policies, and overall environment in which teaching takes place. Desirable outcomes include the diagnosis of institutional problems, clarification of institutional goals, improvement of the institutional climate for teaching and learning, and enhancement of communication and feedback among academic departments and colleges (Diamond, 2002). In order to effect change in teaching and learning, universities should create an environment that nurture group problem-solving, encourage open communication and exchange of ideas, disseminate rewards to faculty for their efforts, support teaching innovations, provide resources to support professional development, and develop policies that permit faculty to engage in these activities. The scope and dissemination of faculty, instructional, and organizational development approaches are often accomplished through a centralized unit on a college or university campus such as a teaching and learning center. 449
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TEACHING AND LEARNING CENTERS Given these three approaches, it is not uncommon for some faculty development programs or teaching and learning centers to concentrate their efforts on one or a combination of these efforts. It is important to emphasize that the three approaches are not mutually exclusive (Gaff and Simpson, 1994; Diamond, 2002). For example, some faculty professional development programs focus on the individual faculty member and seek to help faculty learn more teaching and learning, student development, or their institutions; acquire innovative instructional strategies; gain feedback on their teaching; explore their philosophy about teaching and learning; or apply principles of learning theory in their courses. Other programs might focus on the instructional process and work with faculty to develop course goals and learning outcomes and objectives; design alternative learning experiences; and incorporate multimedia in teaching. An often compelling argument is that “teaching and learning should occur within a supportive environment by training department chairs and establishing clear policies, such as the importance of teaching in the reward system” (Gaff and Simpson, 1994, p. 169). Often the mission and goals of the faculty development unit are implied in its title (Diamond, 2002). For example, a detailed look at the membership directory of the over 1200 Professional and Organizational Development (POD) Network in Higher education, the North American organization that exists to support practitioners and leaders in higher education dedicated to enhancing teaching and learning, reveals that members represent offices with titles such as Center for Teaching Excellence, Center for Research on Learning and Teaching, Center for Instructional Development and Research, Instructional Design and Technology, Faculty Center for Professional Development, Office of Faculty and TA Development, and the Center for Educational Development and Research. The placement and emphases of the work of these units within the institutional structure varies. Many faculty development professionals argue that the placement of the unit sends a message about the institution’s value and concern for teaching. Robert Diamond (2002) makes this point succinctly. “The higher the unit is in the hierarchy of the institution and the more central it is to the structure of the university or college, the greater is its potential impact” (p. 6). Many teaching and learning centers report to the equivalent of a President, Provost, Vice-Provost, or Dean. The work that each unit emphasizes “is a consideration of the needs and priorities of the 450
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institution within the context of its mission, the benefits or outcomes that can be reasonably expected from a particular approach, and the balance between costs and benefits. The best approach for one institution may not be the best for another” (Diamond, 2002, pp. 6–7). Typically, leaders of teaching and learning centers were respected faculty members who took on the role while still fulfilling their faculty responsibilities (Gaff and Simpson, 1994). Today, the majority of this leadership is provided by full-time professional staff (Graf and Wheeler, 1996). In many instances, the staff of teaching and learning centers are hired with tenure and/or are offered tenure-track appointments in an academic unit (Stanley, 2001). In order to provide administrative support, directors of teaching and learning centers usually report to the chief academic officer. To encourage confidentiality and to foster a climate of support and improvement, these centers were removed from the formal authority structure and from the performance review process, such as personnel and promotion and tenure decisions. To foster faculty ownership, centers usually had faculty advisory committees and were responsive to the needs and concerns of the faculty (Gaff and Simpson, 1994). In the 1980s, a variety of academic challenges that centered on the curriculum impacted the work of teaching and learning centers. These challenges included enhancing the quality of general education; strengthening and assessing academic majors; multicultural curriculum transformation; incorporating global perspectives; and teaching skills, such as writing and critical thinking across the curriculum (Gaff and Simpson, 1994). Being attentive to these changes in the curriculum required a shift in faculty development efforts from working with individuals and their needs to empowering groups of faculty to work together to fulfill their interests within the context of the department or institution. These changes were achieved through workshops, seminars, and retreats designed to get faculty to think deeply about learning outcomes and curriculum development. After the development of curriculum frameworks, faculty were then given an opportunity, for example, to learn how to incorporate multicultural content in courses, design interdisciplinary courses, and use appropriate multimedia for student learning. Sometimes these programs were operated out of the Dean’s office or offices charged with curricular components such as a writing center. In other cases, the teaching and learning center might provide leadership for these activities or they might be given resources to serve this institutional priority. During the 1980s “faculty development and curriculum change 451
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were the two sides of the same coin” (Gaff and Simpson, 1994, p. 170). Today, the faculty professional development programs that are a part of an institution’s structure can be traced to these phases. A comprehensive faculty professional development program will have some or all of these activities (Schuster and Wheeler, and Associates, 1990). Teaching and learning centers today are primarily driven more by the needs of the faculty than by the motivation of administrators. Some earlier teaching and learning centers tended to reflect the mission and goals of the president or provost. The teaching and learning centers that have made and are making an impact on the institution are those that are “meeting the multidimensional and ever-changing needs of the faculty. The best operations today enjoy support from the central administration and are guided by grassroots support from the faculty” (Gaff and Simpson, 1994, p. 171). In a historical overview of educational development, Tiberius (2002) argues four belief systems about teaching and learning centers that shape practice — “teaching as content mastery,” “teaching as a performance aimed at making learning happen,” “teaching as facilitation of learning,” and “the teacher–student relationship as a vehicle for learning.” A closer look at each of these belief systems reveals the stages, progression, and characteristics of faculty development from the 1960s to the current period. “Teaching as content mastery characterizes the academic period of the mid-1960s to the present.” During this period, professional development funds were given to professors to support sabbatical leaves, travel to professional meetings, for research support, and contracting guest speakers. Teachers were viewed as experts and masters of the content. The philosophical beliefs of the period could be captured in statements such as, “teachers are born, not made; teaching is an art, not a science; a professor’s classroom is his castle; and hire good people and get out of the way” (Gaff, 1975, cited in Tiberius, 2002, p. 21). Some of these philosophical beliefs are still being argued today. The first faculty development center began with the Center for Research on Learning and Teaching at the University of Michigan in 1962. During this period books on college teaching appeared beginning with Wilbert J. McKeachie’s, Teaching Tips: A Guidebook for the Beginning College Teacher (McKeachie, 1951). Faculty development professionals were few and far between until the early 1970s. “Teaching as performance aimed at making learning happen” was characteristic of the mid-1960s to the present. It was the coming of age of faculty development professionals. Administrators assumed responsibility and support for educational development efforts. Faculty development 452
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units or teaching and learning centers were increasingly staffed “by a new group of researchers and practitioners who could translate research for teachers. We called ourselves ‘developers’ ” (Tiberius, 2002, p. 24). The commonly held belief of the period was that learning could happen if teaching skills were applied to students. Teaching and learning centers provided workshops, consulting, research literature on teaching, and training sessions for faculty to enhance faculty knowledge, skills, and strategies. Faculty developers could help faculty teach better by teaching them skills. The dominant teaching theories were the metaphors of transfer, shaping, and molding. “Learners were vessels to be filled, or clay to be molded into shape” (Tiberius, 2002, p. 25). McKeachie’s 6th and 7th editions of Teaching Tips appeared in 1969 and 1978 (McKeachie, 1969, 1978); and other publications focused on teaching such as The Chronicle of Higher Education (1966); Change: The Magazine of Higher Learning (1969); Higher Education (1971); and Research in Higher Education (1973). The POD Network in Higher Education was formed in 1975. The philosophical stance of teaching as skilled performance is still being used today. “Teaching as facilitation of learning” required faculty to see the teaching and learning process as a reciprocal relationship. Teachers learned that it is important to listen, understand, and receive feedback from students. Faculty developers not only helped faculty to interpret research results on teaching, but were also contributing to research and collaborated on research. Teaching progressed from the transfer theory of teaching to “teaching as conversation” (Tiberius, 2002). Constructivism, the view of connecting learning material to the previous knowledge and experience of students to appropriate social contexts took hold during the 1980s and continues to the present. “The teacher–student relationship as a vehicle for learning” operates from the philosophy that building rapport and understanding between teacher and student are helpful to learning. Tiberius (2002) further argues that the history of faculty development and teaching are guided by these four belief systems. FACULTY DEVELOPMENT BY COMMITTEE The charge of doing faculty development on a college or university campus does not always rest with the establishment of a centralized unit like a teaching and learning center. Often a committee is formed and given this charge. The purpose, function, and activities of faculty development 453
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committees vary. Faculty development committees are found on most campuses and are situated in departments, colleges, and other academic units. In 1991, members of the POD Network in Higher Education conducted a study of the work of faculty development committees (Lunde and Healy, 1991). In the 1970s, faculty development committees were established in more than 40 liberal arts colleges participating in the faculty development training program sponsored by the former Council for the Advancement of Smal Colleges (now renamed the Council of Independent Colleges) (Quehl and Berquist, 1977). In a study of 408 4-year institutions, Centra (1976) reported that 62 percent of these institutions had faculty development committees. In 1986, Erickson, in a study of 630 institutions, reported the same number of committees in existence. However, only 14 percent (88) of these were active in providing services. Boice (1989) surveyed 330 members of the POD Network in Higher Education. Thirty-four percent of the respondents in his study reported that their campus had a formal faculty development committee. Faculty development committees currently exist in colleges and universities of all sizes. These committees are often initiated at the request of a college administrator. Some committees are formed and instructed to explore and develop guidelines for improving the climate for teaching and learning (Lunde and Healy, 1991). Lunde and Healy (1991) reported that 70 percent of faculty development committees listed the improvement of instruction as a major goal of their work. These activities included offering workshops and seminars on teaching, advising the Dean on instructional activities, creating a climate where teaching is valued and rewarded, providing non-threatening services for faculty to enhance teaching and learning, developing print publications on teaching, improving student learning outcomes, and determining the instructional needs of faculty. Sixty-five percent of the faculty development committees in this study reported the need to provide professional development opportunities for faculty as another goal. These activities include assisting faculty in research and service, addressing faculty renewal, developing and overseeing an orientation program for new faculty, facilitating leadership workshops for faculty, supporting the holistic concept of faculty development, and creating a climate of collegiality. Thirty-five percent of the faculty development committees identified the allocation of professional development funds for faculty as an important goal. For example, funds might be used for research and scholarly activity, travel or training, and professional leaves or absences or sabbaticals. Still another 30 percent of these committees 454
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reported the need to coordinate campus faculty development activities as a goal. The goals of faculty development committees are a unique combination of approaches and activities. In fact, some of these activities are similar to those of teaching and learning centers. When a teaching and learning center exists, there is likely to be a relationship between that center and the faculty development committee. Lunde and Healy (1991) found that some faculty development committees serve in an advisory capacity to the center, and the center’s director chairs the committee, or serves as member. In other cases programs of a center and of a committee are the same or independent. In addition to a designated teaching and learning center, there are others units or offices that might offer faculty development services. These offices include the office of the president, the provost, the faculty senate, and deans. A growing number of academic units such as the professional schools in colleges and universities (law, medicine, nursing, dentistry, pharmacy, veterinary medicine) have created faculty development committees.
THE TEACHING DEVELOPMENT OF THE FUTURE PROFESSORIATE Many administrators, faculty, and faculty development professionals have come to realize the value of preparing the faculty of the future to teach (Bowen and Sosa, 1989; Nyquist, Abbott, Wulff, and Sprague, 1991; Ronkowski, 1993; Richlin, 1995). Funding agencies like the U.S. Department of Education Fund for the Improvement of Postsecondary Education and the Pew Charitable Trusts, for example, have been extremely generous in their financial support of graduate teaching assistant (TA) development programs. The growth of TA development programs surged in the 1980s. Research on the graduate TA experience revealed that they faced challenges with their training and supervision, time and funding, and how they were evaluated (Ervin and Muyskens, 1982; Diamond and Gray, 1987; Davis, 1987a, Piccinin et al., 1993). In 1987, the first National Conference on the Employment and Education of Teaching Assistants was convened at the Ohio State University in Columbus, Ohio. This grew into a biannual conference with other universities taking the lead for conference leadership — 1989, the University of Washington, Seattle; 1991, the University of Texas, Austin; 1993, the University of Illinois, Urbana–Champaign; 1995, 455
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the University of Colorado, Boulder; and in 1997, the University of Minnesota, Twin Cities. In a study of faculty identity and socialization to the professoriate, Sorcinelli (1985) found that only 20 percent of those interviewed knew that they wanted an academic career prior to coming to college. Faculty often do not see a direct path to college teaching. She discovered that there were two career decision points: one for the discipline and a later one for the academy. There are many arguments made for supporting the teaching development of graduate students. Some of these arguments are based on changing faculty scholarship, the preparation of future faculty, and employment practices. Moving from the all too often debate of “research vs. teaching” to the more multidimensional aspects of scholarship, Scholarship Reconsidered: Priorities of the Professoriate by Ernest Boyer (1990) proposed four interrelated components: “the scholarship of discovery; the scholarship of integration; the scholarship of application; and the scholarship of teaching” (p. 16). Boyer stated that the implementation of these scholarships will depend on broadening graduate study to prepare the “new generation of scholars” for this task. He further argued that teacher training be incorporated into all graduate programs. He stated that, “Teaching assistant programs, perhaps more than any other, are crucial in the preparation of future teachers” (p. 71). The current attention to undergraduate education strongly suggests that graduate programs need to select and prepare graduate students interested in becoming teacher–scholars. Unfortunately, when we select candidates for admission to a Ph.D. program, most doctoral programs have not yet begun to select students who would be good college teachers (Richlin, 1995). When asked on a survey if potential university teaching ability or interest was considered in the graduate student admission process, department chairs’ comments included: “Not a criterion at admissions”; “Not even taken into account”; “We don’t select on that basis”; and “Why should we select future teachers?” (Richlin, 1991). Graduate students about to embark on the professorial job market in higher education are sometimes asked by prospective employers to provide evidence of their teaching. How is this evidence documented? Graduate students and faculty have found it useful to document their teaching accomplishments in a teaching or professional portfolio. How is this evidence used? In the early years of graduate school, for example, the portfolio can “stimulate the collection of scholarly artifacts pertaining to teaching and research; promote reflection about initial teaching and other 456
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professional experiences; and encourage discussions about professional activities with faculty mentors.” In later graduate school years, the portfolio can “stimulate thinking about a philosophy of teaching and a future research agenda” (Froh, Gray, and Lambert, 1993, p. 105). Seven years ago, Richlin (1995) offered six recommendations for designing future faculty professional development programs: (1) “consider the academy of the future with its rapidly expanding knowledge, increasing use of technology, and the increasing diversity of the undergraduate student population,” (2) “match the training to the needs of future faculty,” (3) “build mandatory, and centrally-organized core programs for graduate teaching assistants,” (4) “support the development and presentation of discipline-and course-specific programs in the departments,” (5) “encourage TAs to document their teaching scholarship and skills in addition to documenting their research with the dissertation and publications,” and (6) “assess the impact of faculty development programs on the improvement of teaching by TAs.” It is difficult to address the professional development of faculty in higher education without attention to how college teachers develop in their knowledge and practice in teaching.
THE PROCESS OF TEACHING DEVELOPMENT IN COLLEGE TEACHERS Faculty develop as teachers in a variety of ways. Chism (1988, 1996), describes this in terms of development at the individual level, where there are incremental episodes of growth that lead to changes in teacher’s perceptions, skills, knowledge, and practices (Chism and Szabo, 1996). This process occurs at such a low level of awareness that most teachers have a difficult time articulating how they have grown as teachers even though they have experienced and can describe what they did to change a particular area of practice. For teachers who are open to growth, the process goes on continually. For the most part, faculty pursue these efforts alone. Sanders (1978) developed a model that describes individual episodes of growth. He suggests that growth occurs in immediate concrete experience and begins when a person encounters some issue or “hitch” in their teaching. Faculty developers can facilitate this growth by providing challenge and support (Sanford, 1967; Perry, 1970; Sanders, 1978; Myers, 1980). Sanders and McCutcheon (1986) described this process of development as teachers selecting and using practices that they think will be successful in 457
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that situation. They may modify a new or existing practice or way of thinking to better fit the circumstances under which they are teaching. Stanley (2000), in a case study of 10 university professors who were clients of the university teaching and learning center, found that the teaching improvement experiences reported by these faculty were similar to those described by the Sanders and McCutcheon and Chism models. Her study supports the observation that faculty rely on personal reflection and sensitivity to the dynamics of the classroom environment for effective action and improvement of teaching. Junior faculty preparing for review and tenure were especially eager to make an effort to enhance their teaching. Senior faculty, particularly those at mid-career, sometimes find themselves in a “rut.” They want to try new methodologies and some aspire to change the climate and reward system so that teaching is more visible in their departments (Boice, 1991). Faculty in the case study were enabled to make changes in their teaching as a result of a personal commitment towards change. These research clearly show that faculty must continue to be supported in their professional development efforts. Faculty need time to devote to professional development. Provisions for released time in the form of course reduction are particularly helpful in this regard. Administrators such as deans and department chairs can be supportive by building environments that stimulate these efforts. Inviting faculty to periodic teaching retreats, seminar groups, or personal consultations on teaching for examining and reflecting on their practice, with colleagues or a faculty development specialist can create a climate that reinforces the value of excellence in teaching. The research also affirms the need for faculty professional development programs to be broad enough in scope to support the full range of faculty needs, concerns, and interests. What can we glean from the history of faculty development, the teaching development of the future professoriate, and how faculty develop as teachers? How do these issues relate to the changing context of higher education?
THE CHANGING CONTEXT OF HIGHER EDUCATION One needs to not only look at the Chronicle of Higher Education and other publication and periodical venues in higher education to read about and understand the changing context of higher education. In fact, our colleagues and universities reflect these changes. Faculties and administrations across 458
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the country are revisiting the mission of higher education. Research funding is limited and the ability of technology and interactive multimedia are forcing institutions to think about ways to enhance learning among students and reward effective teaching among faculty (Gaff and Simpson, 1994). There is a renewed attention being paid to undergraduate education. Ernest Boyer remarked in 1990 that this renewal in emphasis has focused on the core curriculum and the quality of campus life. In fact, the 1990s might well be remembered as the decade of the undergraduate in American higher education. In his report of the professoriate in 1990, Boyer stated that teaching is not well rewarded in many campuses in higher education. One could easily say that this sentiment still rings true today. Faculty are advised that spending a lot of time on teaching and advising will diminish one’s prospects for promotion and tenure. Faculty have been socialized to believe that research and publication are the primary means to academic status. However, many would argue that the reasons why they enter academic are chiefly because of their love for teaching and service. Yet, these professional obligations are not afforded their weight in personnel decisions. Boyer argues, “for American higher education to remain vital we urgently need a more creative view of the work of the professoriate” (Boyer, 1990, p. xii). The concept of scholarship is broadening and many in the academy are insisting on increased rewards for public service and teaching (Boyer, 1990). Accreditation bodies and government agencies are stressing the importance of the institution’s role in assessing learning outcomes. Assessment of learning outcomes is forcing institutions to be more accountable in order to demonstrate their commitment to and impact on student learning. Considerable resources are being used to collect and report qualitative and quantitative assessment data to external reviewers and audiences for accountability. However, assessment also involves efforts to improve the performance of faculty, academic units, administrative and student service units, and faculty development centers and programs. One cannot address the emphasis on assessment and accountability without ignoring their impact on the college curriculum. The curriculum of colleges and universities represents programs of study that are selected to meet the educational needs of a population, the profession, and a global, and diverse society. A recurring debate in higher education is the responsiveness of graduate and undergraduate curricula to the need for perceived changes. Some of the curriculum-related challenges that will no doubt influence faculty professional development in the future include: (1) the importance of providing students with a general and liberal education in 459
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the face of increased pressure toward a technical or vocational education; (2) the need to prepare students to live and work in an increasingly multicultural and global society as the knowledge base in the disciplines increases; (3) the need to move from the commonly held posture of the “additive approach” to curriculum review to a “transformative approach”; (4) and the development of lifelong learning skills in and experiences for our students. The social and cultural composition of students in higher education are also changing. Current demographic predictors indicate that the majority of population will become the minority in the near future (Gaither, 1999; Murdock and Hogue, 1999; Kan-Rice, 2000). Demographic shifts in the college student population include changes in age, gender, race, ethnicity, religion, socioeconomic status, physical and learning ability, and sexual identity. At the same time these shifts have sparked social changes in terms of employer expectations, university curriculum reviews, learning outcomes from accreditation agencies, and the like. In particular, differences occur across racial and ethnic groups when examining the academic preparation for college statistics as well as retention and graduation data published by the National Center for Education Statistics (NCES, 2000). Despite the gains made in the recruitment of faculty and students of color, in comparison to the majority population, the numbers of students and faculty of color remain disproportionately low (Bronstein, Rothblum, and Solomon, 1993; Nakanishi, 1993; Johnsrud and Des Jarlais, 1994; Cross, 1996; NCES, 2000). Demographic and social challenges that will influence faculty professional development in the future include: (1) creating classroom and university environments that are welcoming to all students; (2) improving the recruitment and retention of students and faculty of color to reflect the demographics of the national population; (3) infusing a deeper meaning of diversity that goes beyond race and gender, including the value of social and cultural diversity to the university and to higher education; (4) and creating a pipeline for the professoriate that is reflective of society as a whole. Many institutions in higher education are experiencing decreased funding from a variety of sources. While it is difficult to predict what the future holds for economic recovery, some fiscal retrenchments have eliminated programs and services, including those that provide for the professional development of faculty and graduate teaching associates. One such example occurred in 2002 when the Center for Teaching and Learning at the University of Nebraska, Lincoln, the second oldest teaching and learning center in the United States, was eliminated. The primary reason given was 460
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that there is no longer a need for a centralized unit to support faculty in their teaching efforts. Colleges and departments can now do this work. Is this a sentiment of the future? What does this say about faculty professional development? In order to sustain faculty professional development during these troubled times, the challenges that will influence these efforts include: (1) convincing state legislatures and other agencies that colleges and universities are vital to the economy and should receive priority funding; (2) generating new sources of revenue; (3) finding ways of working with private and public providers of postsecondary education; and (4) doing more with less resources to fulfill the university’s mission for excellence in undergraduate education. New technologies are also creating new avenues for delivery of teaching and learning. In particular, the use of new instructional technologies among students and faculty has increased dramatically during the last decade. Colleges and universities have welcomed these new technologies by investing a significant amount of human and physical resources in infrastructures, equipment, and staff training. In my opinion, we are still not at a place where we are thinking deeply enough about technology and learning. Stephen Ehrmann, Director of the Flashlight Program and Vice President of the TLT Group, the Teaching, Learning, and Technology Affiliate of the American Association of Higher Education (AAHE) makes this point more succinctly. He argues that we are not “asking the hard questions about technology use and education” (Ehrmann, 1999). These questions might include, “Is technology magic? Is our investment helping the people who most need help? How does our use of technology affect costs? Is technology improving practice?” (Ehrmann, 1999, pp. 25–29). He makes yet another point, “Technologies such as computers (or pencils) don’t have predetermined impacts; it’s their uses that influence outcomes” (Ehrmann, 1999, p. 27). According to Sell (2002), at the same time we are embracing new technologies, institutional resources used for technology acquisition, maintenance, and updating are not available for “human capital,” the primary assets of any institution. One particular challenge at this campus lies in courses offered through distance learning. While there is clearly a need for providing students at a distance in the state with an opportunity to take classes without travelling 10 hours, there is the frustration experienced on the part of colleagues who feel inadequate in their own training and development in the use of distance education technologies. A similar frustration is encountered by students at remote sites who feel that they 461
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are “disconnected” and not a part of the “learning community” which exists on the main campus. The challenges and opportunities for faculty professional development for instructional technology in the future include: (1) using technology to enhance student learning; (2) creating more opportunities for the use of active learning strategies through the use of technology; (3) creating partnerships among instructional technology and professional development units to make the best use of technology in teaching and learning; and (4) creating opportunities for faculty professional development in the effective use of distance learning programs. The publication of Scholarship Reconsidered: Priorities of the Professoriate by Ernest Boyer (1990) has focused on the redefinition of traditional views of scholarship with regard to academic work. While the Carnegie Foundation and the AAHE have led the national discussion in this area, many institutions are still holding on to the dominant view of scholarship that gives preference to disciplinary research and peer-reviewed publications in refereed journals. Teaching and the scholarship of teaching tend to be devalued and not held in the same regard as research and publications in recognized disciplines. In fact, a colleague, at a research intensive university in the Midwest stated that she was told by her department chair that her scholarship of teaching efforts would not be counted for promotion and tenure. The improvement of teaching and learning, however, may very well depend on the expertise of faculty and faculty development professionals to conduct, report, critique, and apply research that broadens and deepens the knowledge base for instructional practice. The challenges and opportunities for faculty professional development in the future include: (1) overcoming the perception held by many faculty that excellent teaching is expected but not rewarded; (2) strengthening the emphasis on using formative evaluation for diagnosing where and how teaching can be improved in order to enhance student learning; and (3) applying knowledge about effective teaching and learning to faculty and student practices as well as faculty development practices. How do we face these challenges and opportunities so that faculty work remain vital for the 21st century?
KEEPING FACULTY WORK VITAL FOR THE 21ST CENTURY In the 15 years since I have been involved in faculty development, there is little doubt in my mind that the professoriate is changing. Keeping 462
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faculty work vital for the 21st century requires attention to the demographic pipeline of new individuals who will be entering the professoriate in the next decade. One such area is the racial and ethnic makeup of the faculty in higher education. As Boyer stated in 1990, “Clearly, the vitality of scholarship is threatened if the pool of recruits dwindles . . . Further, concerns about tomorrow’s professoriate cannot be seriously raised without focusing, with special urgency, on minority faculty, since the next generation of scholars will be challenged, as never before, by diversity in the classroom. The intolerably small pool of qualified minority applicants represents a shocking weakness, if not an indictment, of American education at all levels” (Boyer, 1990, p. 66). The diversity of the professoriate remains a challenge for colleges and universities. With the recent attacks on affirmative action many colleges and universities are faced with a recruiting pool that is not diverse. While women have been making strides in the faculty ranks, we still lack significant numbers of African Americans, Hispanic Americans, Asian Americans, and Native Americans. Faculty of color (African American, Hispanic, Asian or Pacific Islander, and American Indian/Alaskan Native) represent 13.4 percent of the total full-time instructional faculty in degreegranting institutions (National Center for Education Statistics, 2000). Furthermore, only 5 percent of the full professors in the United States are African American, Hispanic, or Native American, and the proportion of African American faculty at predominantly White colleges and universities today is 2.3 percent (Trower and Chait, 2002). African Americans, Asian Americans, Latinos, and Native Americans in particular constitute between 20 and 25 percent of the U.S. population. We need to do a better job preparing, recruiting, and helping new faculty succeed. We also need to help majority faculty do a better job of not only educating a diverse student body but also mentoring a diverse faculty. As a majority faculty member said, in defense of a faculty colleague of color at a departmental faculty retreat that addressed diversity issues among the faculty, “I have to tell you guys that I believe that there’s differential treatment in the reactions from students. Students treat her differently than they treat me” (Stanley, Porter, Simpson and Ouelett, in press). The recruitment, support, and renewal of faculty experiences like “Eric French,” “Geneva Westgate,” “Dean Elinor Jackson,” and “George Miller” shared at the beginning of this chapter are essential organizational tasks for any college or university. With the renewed emphasis on undergraduate teaching and teaching competence, faculty like “Geneva 463
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Westgate” should be supported in their professional development as well as student development pursuits. These efforts should have a place in the reward system if colleges and universities are to be a place for excellence in undergraduate education. For professors like “Eric French” who have fallen into a rut with their teaching, professional development must bring renewal. For administrators like “Dean Elinor Jackson,” professional development must help in efforts to make academic committees work so that administrative responsibilities are less burdensome. For colleagues like “George Miller” who subscribe to the traditional ways of knowing and thinking about students and learning, professional development must challenge this thinking in ways that lead to change. By focusing on and reemphasizing the strengths, expertise, and experiences we bring as faculty to academia, and more specifically to teaching and learning, we allow ourselves the opportunity to share and reflect on our limitations, assumptions, and concerns about teaching and learning. Beyond the faculty professional development activities afforded to faculty, institutions also have a responsibility to provide opportunities, resources, and evaluation systems that enable faculty to perform to their potential. As many colleges and universities experience an aging population of faculty, and as “early retirement incentives” have enabled productive faculty to leave their institutions, the renewal and replacement of faculty become serious issues. In 1930, G.J. Laing, Dean of the graduate school at the University of Chicago asked: “What are we doing in the way of equipping [graduate students] for their future work?” Have the departments of the various graduate schools kept the teaching career sufficiently in mind in the organization of their program[s] of studies? “Or have they arranged their courses with an eye to the production of research workers only, thinking of the teacher’s duties merely as a means of livelihood . . . while he carries on his research? And finally comes the question: What sort of college teachers do our Doctors of Philosophy make?” (Boyer, 1990, p. 70). Challenges that will face the professional development of the changing professoriate in the future include: (1) preparing graduate students as future faculty; (2) recruiting minority graduate students for the college faculty; (3) linking the professional development of faculty to excellence in teaching, research, and service; and (4) improving the reward systems used for hiring, tenure, promotion, and merit salary increases. At the 2002, annual conference of the POD Network in Higher Education in Atlanta, Georgia, Dr. Beverly Daniel Tatum, newly selected President of Spelman College gave a plenary address, titled, “The ABC 464
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Approach to Creating a Climate of Achievement” on college and university campuses. Her premise to the “ABC” approach from which I have extrapolated in the context of faculty professional development, is that colleges and universities should be doing more to A-ffirm the identity of our students and faculty so that institutions of higher education can be a place where they can grow and thrive, B-uild community for our faculty and students so that we are truly a learning community where all forms of scholarship are valued and rewarded, and C-ultivate leadership so that the next generation of students and faculty on our colleges and universities reflect the diversity of society and the nation as a whole. As we look toward the future, it is clear that changing student demographics will have a direct impact on the teaching and learning climate as well as recruitment efforts in higher education (Brazziel, 1993; Gaither, 1999; Murdock and Hogue, 1999). Not only will the racial and ethnic composition of college classrooms change, but also we will have to look critically at how these demographic changes affect higher education and the professional development of our students and faculty. There are clear implications for faculty professional development for not only whom we teach (students), but also whom we hire (faculty), how we teach (teaching strategies) and what we teach (courses and curricula). Lynn Weber Cannon articulates this point in her teaching philosophy. “My broadest goals as a teacher is to assist students in developing a framework to evaluate the social system, to question it, to understand how their own perspectives, life chances, options, and opportunities as well as those of others are shaped by it. I want them to be the smartest social analysts they can be, because these skills will serve them well for the rest of their lives in a way that knowing the latest research findings will not” (Cannon, 1994, p. 301). Professional development of faculty in enhancing learning so that students are better able to live and work in a diverse and global society should include defining diversity and multiculturalism broadly; working on changes in the reward structure to recognize these efforts; creating multiple points of entry into multicultural faculty development initiatives; holding faculty and administrators accountable through assessment of diversity efforts; and modeling diversity in higher education by communicating the university’s values and mission in word and practice. The growing number of post-tenure review policies on campuses around the country will influence the vitality of faculty work in the 21st century. As Marilla Svinicki, Director of the Center for Teaching 465
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Effectiveness and Associate Professor of Educational Psychology at The University of Texas, Austin, states very poignantly, “The imposition of post-tenure review has put two powerful constituencies of the university in difficult positions. The deans and department chairs are in a difficult position because they are responsible for seeing to it that post-tenure reviews get carried out in a reasonable manner. The faculty are in a difficult position, especially the senior faculty, because the rules have changed in mid-game, and they must respond to this change” (Svinicki, 1998, p. 6). Tenured faculty in the past who have never participated in faculty development activities now face a potentially difficult task of preparing for posttenure review. While many academicians have taken different positions on the legitimacy of post-tenure review, many challenges remain for faculty professional development. The first of the challenges will be to rekindle faculty interest in the scholarly, problem-solving side of teaching and research. Faculty should be encouraged and supported to build upon the knowledge base of research on learning and teaching to investigate questions related to student learning. These questions should be related to how learning occurs, what does learning look like, and how to nurture deep learning in and beyond the classroom. This is, in fact, similar to the current movement for “a science of learning — the application of scientific principles to the study of learning” (Halpern and Hakel, 2002, p. 1). The second challenge is to design a reasonable peer review system so that we have a broader view of the teaching methodologies and learning processes that occur in the classroom. A reasonable peer view system should include faculty ownership and include formative and summative approaches. We need to move beyond discussions that are waterlogged in issues related to reliability and validity, who is a peer, vulnerability of the peer reviewer, demands on time, and the like, to a system where faculty and administrators work together to create a climate that fosters and rewards teaching. A reasonable peer review system goes beyond classroom observations of teaching to a more complete design, implementation, and assessment of teaching that provide documentation related to “the what,” “the who,” “the how,” and “the why” of teaching and learning. Peer reviewers should be experienced and open to alternative teaching strategies and conceptions of student learning. A third challenge is to support faculty as lifelong learners over the course of their academic careers. Faculty should be able to see the benefits of continued engagement in professional development activities. Perhaps 466
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the concept of “holistic faculty development” is far more appropriate to consider for the 21st century. Holistic faculty development is based on the premise that the effect of teaching and learning centers working together with institutional agencies create a stronger effort at effecting change in scholarship than the individual efforts of a faculty development program (Zahorski, 2002). One of the keys to success for faculty professional development for the 21st century is the potential role of academic leaders and faculty development professionals as partners or agents for change. “Faculty developers have long recognized the key role to be played by department chairs, deans, and senior academic administrators in the success of instructional development programs” (Sorcinelli and Aitken, 1995, p. 311). Researchers in the field of faculty development in mid-1970s argued that support and recognition for good teaching would be greater if administrators played a key role in valuing teaching initiatives in colleges and universities (Berquist and Phillips, 1975; Gaff, 1975; Centra, 1976; Lindquist, 1978). However, this is a double-edged sword on many levels. For example, many deans and department chairs would like a more supportive environment for teaching, but feel that their efforts would not be supported by central administration or by individual faculty in their colleges and departments (Gray et al., 1992). “Central administration is frequently told by external constituencies — parents, alumni, trustees, legislators — that there is a need to improve teaching on campus. But just as frequently, administrators may be reluctant to take a strong stand on the issue within the campus for fear that they will be perceived by faculty as not supporting the research mission of the institution” (Sorcinelli and Aitken, 1995, p. 314). As a faculty colleague stated rather cynically in a research study I conducted on the teaching experiences of African American faculty at two predominantly White research universities in the south, “I served for several years on our departmental review committee for promotion and tenure. I get to hear that dialogue on teaching. They talked about teaching a lot, but not in a larger, everyday context . . . research is the thing. As much as the committee would like to say, ‘We care about teaching,’ some people have terrible teaching evaluations and excellent research and they get tenure. So, it’s like, ‘Could we just be for real here?’ ” (Stanley, Porter, and Simpson, under review). An evaluation study of the Lilly Teaching Fellows programs at 34 research universities found that department chairs and deans, through informal encouragement and positive recognition, provide invaluable support to 467
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faculty in their teaching efforts (Rice and Austin, 1990). There is a growing body of literature on the role of the department chair in enhancing teaching effectiveness (Lucas, 1989, 1990, 2002; Tucker, 1992; Cresswell, Wheeler, Seagren, Egly, and Beyer, 1990). These researchers offer concrete ideas for programs and professional development plans, such as in-service seminars or workshops, teaching awards, and graduate student training. Some of these ideas include transforming the department into a team to foster trust, and increase morale and productivity. Lucas (2002) argues that “affirming the value of the faculty must begin in the department” (p. 50). A first step in encouraging and supporting faculty scholarship is a careful review of mission statements, departmental policies and procedures. A key area is a department’s mission statement. “When there is no alignment between what individual faculty members do and whether they move forward the goals of the department, scholarly engagement will not be valued by those in the hierarchy who must make recommendations or decisions about whether a particular type of scholarship will be valued” (Lucas, 2002, p. 51). Departmental policy statements, built in accountability plans for release time and “stop the clock” tenure policies for extraneous circumstances, for example, can serve to engender trust in the faculty and create a climate of excellence. A department or college Dean can create a climate that values the scholarship of teaching by devoting time on a faculty meeting agenda or scheduling a retreat to discuss teaching and the changing views of scholarship. I find it interesting that departments often operate from the assumption that faculty need development in research, but rarely in teaching. This is often reflected in the disproportionate numbers of workshops or seminars, calls for research proposals, and the announcements of college seed grant research opportunities that often surface in the daily life of a faculty member. While it is commonplace to have workshops or colloquia on research, departments that have similar efforts aimed at the scholarship of teaching are rare. Professional development plans on teaching should include aspects of scholarly work on teaching such as classroom teaching, advising, classroom research, mentoring, and the like. College expectations for promotion and tenure should include summative and formative assessments of teaching. Professional development of faculty should enlist administrative support at multiple levels — central administration, deans, and department chairs. Providing recognition and rewards for faculty in their teaching efforts also sends a clear message for the value of teaching. Hardly anyone 468
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would argue that the motivation for good teaching is primarily intrinsic; however, providing recognition through salary or resources are also strong incentives for successful faculty development (Sorcinelli, 1985; Rice and Austin, 1990). The professional development of academic administrators is an overlooked area in faculty professional development. Changes in the professoriate also influence changes in administrative leadership. Academic administrators are also being held accountable for how well they accomplish their jobs. The administrative portfolio concept proposed by Seldin and Higgerson (2002), offers a hands-on approach to document the scope and quality of an administrator’s activities and accomplishments. The administrative portfolio can be used in the formative sense to assess an administrator’s growth and development, as well as identify areas for improvement. Encouraging self-reflection on one’s roles and responsibilities is important for administrators as the process and product sensitizes them to the work and scope of the scholarship of teaching.
SCHOLARSHIP RECONSIDERED AND ONCE AGAIN REVISITED: SOME FINAL THOUGHTS The new millennium has already sparked profound changes in the nation and the world. Higher education will not go untouched. In 1990, Ernest Boyer asked, “How can the role of the scholar be defined in ways that not only affirm the past but also reflect the present and adequately anticipate the future?” (Boyer, 1990, p. 75). A great deal of progress has been made, but more needs to be done to firmly instill the need for continuous learning and professional development in the lives of faculty. Faculty work extends beyond the ideas and methods of the disciplines. The work of the faculty is difficult to describe and classify (Bowen and Schuster, 1986; Boyer, 1990; Rhodes, 1990; Rice, 1991; Diamond, 2002). This work is not uniform across all institutions or disciplines. According to Clark (1987), the work of the professoriate is one of extreme differentiation. Relationships vary with colleagues and patterns of authority across institutions. Faculty work includes teaching, research and creative activity, practice and professional service, and citizenship (Braskamp and Ory, 1994). “All of these roles require knowledge and skills beyond that of a researcher, and all are proper foci for development” (Gaff and Simpson, 1994, p. 176). 469
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There is growing evidence that professors want, and need, better ways for the full range of their aspirations and commitments to be acknowledged. Faculty are expressing serious reservations about academia to which they have committed their professional lives. When I asked the 15 African American faculty at the two predominantly White research universities I used for my case study to share their teaching experiences, all had contemplated leaving academia. The primary reasons for remaining in higher education are their commitment to the students and service to the community. Faculty professional development for the 21st century should recognize that teaching is crucial, that the “scholarship of integration” is increasingly important, and that, in addition to research, the work of the academy must relate to the world beyond campus. Everyone will no doubt relate to the experiences of “Eric French,” “Geneva Westgate,” “Dean Elinor Jackson,” and “George Miller.” These experiences present rich possibilities for faculty professional development. These possibilities include challenges, support, and rewards. Professional development opportunities should not be seen as punitive, threatening, and unimportant. Professional development opportunities include all the work of the professoriate, not only the scholarship of discovery. Institutions of higher education are recognizing that their students need some preparation in teaching if they are to be marketable in the future. Opportunities to teach, guest lecture, advise students, serve on curriculum committees, and engage in inquiry about teaching and learning provide graduate students with points of entry into the realities and complexities of faculty life and work. We are getting more support for preparing graduate students to teach. Graduate deans and graduate faculty advisors who support the professional development of graduate students enable the future professoriate to be better prepared for what it takes to teach. They will, in turn, because they found these opportunities beneficial, will be more likely to continue that drive to learn about teaching. Kenneth Eble, in his book, Professors as Teachers, states, “The narrowness of vision, the disdain for education, the reluctance to function as a teacher are ills attributable in large part to graduate training. Upgrading the preparation of college teachers in graduate schools is therefore fundamentally important not only to improving teaching but to refashioning higher education” (Eble, 1972, p. 180). Higher education leaders acknowledge that diversity is important to the mission of the institution. Mission statements, strategic planning documents, visioning exercises, goal statements, and the like express these ideas in compelling and admirable ways. The student population on many 470
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campuses are diverse in a multitude of social and cultural identities — race, gender, culture, sexual identity, age, physical and learning ability, socioeconomic status, nationality, religion, and the like. The faculty is no different. Despite the richness and complexities associated with this diversity, colleges and universities are still grappling with how to mirror the demographics of the state and nation. Too often faculty, students, and administrators engage in behaviors and attitudes that detract from the meaning and value of diversity. Sensitivity seminars and workshops on diversity are important, but we must probe deeper. Professional development activities should include curriculum transformation, recruitment and retention training, using climate assessment data to effect changes in policy, workshops and seminars for administrators, exploring avenues of access to power and privilege and how these affect recruitment and retention. Teaching and learning centers have played a key role in the professional development of faculty for over thirty years. Teaching and learning centers provide vital resources for the professional development of faculty. Professional development staff provide faculty, students, and administrators with a theory and database for the research on teaching and learning in higher education. They also provide a place where faculty and administrators can go to further educate themselves about curriculum, student development, adult learning, assessment, multicultural teaching, and leadership. For many faculty, the teaching and learning center on a university campus is a “safe haven,” a place where they can go and have conversations about successes and challenges on teaching without fear of labeling or reprisal. Many centers facilitate study on faculty, instructional, and organizational development for their colleges and universities. A close look at job postings for leaders of teaching and learning centers reveal that many universities seek a Director who possesses knowledge of and experience in college teaching and learning as well as credibility with faculty and administrators. With the renewed emphasis on undergraduate teaching and teaching competence, the cycle of individuals entering the professoriate, diversity and globalization of the curriculum, new pressures for accountability, and the need to have faculty remain vital and productive over the entire life cycle, and the growing number of post-tenure policies around the country, faculty professional development for the 21st century will require institutions relying on teaching and learning centers more than ever before. Professional development takes time, expertise, and resources. If it is not built into the workload of the faculty, it will not be seen as important. 471
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“A college or university need not go broke trying to help its staff become more effective” (Lindquist, 1981, p. 746). Faculty professional development can be achieved through the centralized established efforts of a teaching and learning center or through decentralized efforts of faculty development committees and college faculty development plans and activities. With a threat to the vitality of institutions as a result of funding reductions in higher education, retrenchment has eliminated programs and services, including those for professional development. However, too often we use financial constraints as an excuse to do little or nothing for the continued professional growth and development of faculty. If we are committed to their continuous growth and development, money can be found to support faculty in their teaching efforts. According to Shea (1997), faculty come to consultations on teaching for a variety of reasons. Many come after having received disappointing ratings on student evaluations; for long-term help on their teaching; for assistance with a specific teaching issue; some are at a transition period in their professional lives; some request a thorough analysis of their teaching; some are in a search of a better formula for their teaching; some are confident teachers and seek affirmation for their performance; and still others seek counsel from someone who is far removed from their own department for fear of repercussion. Perhaps the ultimate message of this chapter is that faculty professional development for the 21st century will require systematic investment in the work of faculty. Professors, in order to be fully effective, cannot work in isolation. Why not imagine a vital network of colleges and universities in higher education where the range of human talent, with a richness in social and cultural diversity, is valued and supported? As a faculty participant in a research study that I conducted on factors that contribute to the teaching development of faculty development center clientele stated, “I have this opportunity to take these young people through a period of their life, whether it’s ten weeks or four years, and help them develop. In my teaching philosophy, everyone can learn, if they want to. And my desire is to be an assistant to that learning process. So whatever the student outcomes are, I’ve been there to facilitate those outcomes. To me that is important and that is why I am where I am” (Stanley, 2000, p. 166). Professors in the new millennium are looking for balance in their daily life and work, collegiality, community, understanding, and acceptance. Colleges and universities need to find ways to meet the professional and personal development needs of future scholars. My teaching philosophy looks very different from that of my colleagues. However, it is my hope 472
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that when a colleague reads or inquires about my philosophy of teaching, they will understand who I am as a scholar, what and how I teach, and my values and beliefs about teaching and learning. I look for support and challenge to think about issues or ideas on teaching that I have not thought about before. More importantly, it is my hope that this will stimulate thought and discussion among my peers about teaching. When colleges and universities relate to scholars like “Eric French,” “Geneva Westgate,” “Dean Elinor Jackson,” and “George Miller” as individuals, and consider their career stages, we create a community of scholars that are better prepared to meet the challenges of the 21st century.
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REFERENCES Abedor, A.J., and Sachs, S.G. (1978). The relationship between faculty development (FD), organizational development (OD) and instructional development (ID): Readiness for instructional innovation in higher education. In R.K. Bass and D.B. Lumsden (eds.), Instructional Development: The State of the Art (pp. 2–19). Columbus, OH: Collegiate Publishing, Inc. Association of American Colleges and Universities (1985). Integrity in the College Curriculum: A Report to the Academic Community. Washington, D.C.: Association of American Colleges and Universities. Bennett, W.J. (1984). To Reclaim a Legacy. Washington, D.C.: National Endowment for the Humanities. Berquist, W., and Phillips, S. (eds.). (1975). A Handbook for Faculty Development. Washington, D.C.: Council for the Advancement of Small Colleges. Boice, R. (1989). Results of the 1989 survey of faculty development practices among POD membership. Paper distributed at the annual conference of the Professional and Organizational Development (POD) Network in Higher Education, October Jekyll Island, GA. Boice, R. (1991). Quick Starters: New Faculty Who Succeed. New Directions for Teaching and Learning (Vol. 48, pp. 111–121). San Francisco: Jossey-Bass. Boyer, E.T. (1986). College: The Undergraduate Experience in America. Princeton, NJ: Carnegie Foundation for the Advancement of Teaching. Boyer, E.L. (1990). Scholarship Reconsidered. Priorities of the Professoriate. Princeton, NY: The Carnegie Foundation for the Advancement of Teaching. Bowen, H.R., and Schuster, J.H. (1986). American Professors: A National Resource Imperiled. New York: Oxford University Press. Bowen, W.G., and Sosa, J.A. (1989). Prospects for Faculty in the Arts and Sciences. Princeton, NJ: Princeton University Press. Braskamp, L.A., and Ory, J.C. (1994). Assessing Faculty Work: Enhancing Individual and Institutional Performance. San Francisco, CA: Jossey-Bass. Brazziel, W.F. (1993, June). Shaping graduate education’s future: Implications of demographic shifts for the 21st century. Connecticut: (ERIC Document Reproduction No: ED358783) Brinko, K.T. (1993). The practice of giving feedback to improve teaching: What is effective? Journal of Higher Education 64(5): 574–593. Bronstein, P., Rothblum, E.D., and Solomon, S.E. (1993). Ivy Halls and Glass Walls: Barriers to Academic Careers for Women and Ethnic Minorities. New Directions for Teaching and Learning. No. 53. San Francisco-Jossey-Bass. Cannon, L.W. (1994). Fostering positive race, class, and gender dynamics in the classroom. In K.A. Feldman and M.P. Paulsen (eds.), Teaching and Learning in the Classroom. Needham Heights, MA: Ginn Press. Centra, J. (1976). Faculty Development Practices in U.S. Colleges and Universities (Project Report 76–30). Princeton, NJ: Educational Testing Service. Chism, N.V.N. (1988). The process of development in college teachers: Toward a model. A paper presented at the American Educational Research Association, New Orleans, Louisiana. Chism, N.V.N. (1999). Peer Review of Teaching: A Sourcebook. Bolton, MA: Anker.
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Stanley: Faculty Professional Development for the 21st Century Chism, N.V.N., and Szabo, B.L. (1996). Who uses faculty development services? To Improve the Academy: Resources for Faculty, Instructional, and Organizational Development (Vol. 15, pp. 115–128). Clark, B.R. (1987). The Academic Life: Small Worlds, Different Worlds. Princeton, NJ: Carnegie Foundation for the Advancement of Teaching and Princeton University Press. Clark, S.M., and Lewis, D.R. (eds.). (1985). Faculty Vitality and Institutional Productivity: Critical Perspectives for Higher Education. New York: Teachers College Press. Cresswell, J.W., Wheeler, D.W., Seagren, A.T., Egly, N.J., and Beyer, K.D. (1990). The Academic Chairperson’s Handbook. Lincoln, NE: The University of Nebraska Press. Cross, W.T. (1996). Pathway to the professoriate: The American Indian pipeline. In C. Turner, M. Garcia, A. Nora, and L. Rendon (eds.), Racial and Ethnic Diversity in Higher Education, (pp. 327–336). ASHE Reader Series. Needham Heights, MA: Simon & Schuster. Crow, M.L., Milton, O., Moomaw, W.E., and O’Connell, W.R. (eds.). (1976). Faculty Development Centers in Southern Universities. Atlanta: Southern Regional Education Board. Cytrynbaum, S., Lee, S., and Wadner D. (1982). Faculty development through the life course. Journal of Instructional Development 5: 11–22. Davis, W.E. (1987a). TA training: Professional development for future faculty. In N.V.N. Chism (ed.), Institutional Responsibilities and Responses in the Employment and Education of Teaching Assistants (pp. 129–131). Columbus, OH: The Ohio State University. Davis, W.E. (1987b). Teaching assistant training and preparation for Future Faculty Roles. Unpublished manuscript, University of California, Teaching Resources Center, Davis, CA. Diamond, R.M. (2002a). Faculty, instructional development, and organizational development: Options and choices. In K. Gillespie (ed.), A Guide to Faculty Development (pp. 2–8). Bolton, MA: Anker. Diamond, R.M. (2002b). Defining scholarship for the twenty-first century. In K. Zahorski (ed.), Scholarship in the Postmodern era: New Venues, New Values, New Visions, New Directions for Teaching and Learning, No. 90 (pp. 73–79). San Francisco: Jossey-Bass. Diamond, R.M., and Gray, P. (1987). National Study of Teaching Assistants. Syracuse, NY: Syracuse University, Center for Instructional Development. Eble, K.E. (1972). Professors as Teachers. San Francisco: Jossey-Bass. Eble, K.E., and McKeachie, W.J. (1985). Improving Undergraduate Education Through Faculty Development. San Francisco: Jossey-Bass. Ehrmann, S.C. (1999). Asking the hard questions about technology use and education. Change (March/April): 25–29. Erickson, G. (1986). A survey of faculty development practices. To Improve the Academy: Resources for Student, Faculty, & Institutional Development 5: 182–196. Erickson, G.R., and Erickson, B.L. (1979). Improving college teaching: An evaluation of a teaching consultation procedure. Journal of Higher Education 50: 670–683. Ervin, G., and Muyskens, J.A. (1982). On training TAs: Do we know what they want and need. Foreign Language Annals 15(5): 335–344. Evertson, C.M., and Holley, F.M. (1981). Classroom observation. In J. Millman (ed.), Handbook of Teacher Evaluation (pp. 90–109). Beverly Hills, CA: Sage Publications. Froh, R.C., Gray, P.J., and Lambert, L.M. (1993). Representing faculty work: The professional portfolio: In R.M. Diamond and B.E. Adam (eds.), New Directions for Higher Education: No. 81. Recognizing Faculty Work: Reward Systems for the Year 2000 (pp. 97–118). San Francisco, CA: Jossey-Bass.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Gaff, J.G. (1975). Toward Faculty Renewal. San Francisco: Jossey-Bass. Gaff, J.G. and Simpson, R.D. (1994, Spring). Faculty development in the United States. Innovative Higher Education 18(3): 167–176. Gaither, G.H. (1999). What the future holds. New Directions for Higher Education 27(4): 115–118. Gillespie, K. (2002). A Guide to Faculty Development. Bolton, MA: Anker. Graf, D.L., and Wheeler, D. (1996). Defining the Field: The POD Membership Survey. The POD Network in Higher Education. Gray, P.J., Froh, R.C., and Diamond, R.M. (1992). A National Study of Research Universities on the Balance Between Research and Undergraduate Teaching. Syracuse, NY: Syracuse University, Center for Instructional Development. Halpern, D.F., and Hakel, M.D. (eds.). (2002, Spring). Applying the science of learning to university teaching and beyond. New Directions for Teaching and Learning, No. 89. San Francisco: Jossey-Bass. Hodgkinson, H.L. (1974). Adult development: Implications for faculty and administrators. Educational Record 55: 263–274. Hutchings, P. (1996). Making teaching community property: A menu for peer collaboration and peer review. Washington, D.C.: American Association for Higher Education. Johnsrud, L.K., and Des Jarlais, C.D. (1994). Barriers to tenure for women and minorities. The Review of Higher Education 17(4): 335–353. Kan-Rice, P. (ed.). (2000, Jan–Feb). California’s Changing Face: The Challenges Ahead. Future in Focus, 2000–2025: Population. Oakland, CA (ERIC Document Reproduction Service No. ED 443 611) Laing, G.J. (1930). The newer educational programs and the training of teachers. In W.S. Gray (ed.), The Training of College Teachers (p. 51). Chicago: The University of Chicago Press. Levinson-Rose, J., and Menges, R.F. (1981). Improving college teaching: A critical review of research. Review of Educational Research 51(3): 403–434. Lewis, K.G. (1997). Collecting information using class observation. In K.T. Brinko and R.J. Menges (eds.), Practically Speaking: A Sourcebook for Instructional Consultants in Higher Education (pp. 29–52). Stillwater, OK: New Forums Press. Lindquist, J. (ed.). (1978). Designing Teaching Improvement Programs. Washington, DC: Council for the Advancement of Small Colleges. Lindquist, J. (Ed.) (1978a). Designing Teaching Improvement Programs. Washington, DC: Council for the Advancement of Small Colleges. Lindquist, J. (1981). Professional development. In A.W. Chickering and Associates (eds.), The Modern American College: Responding to the New Realities of Diverse Students and a Changing Society (pp. 730–747). San Francisco: Jossey-Bass. Lucas, A.F. (ed.). (1989). The department chairperson’s role in enhancing college teaching. In New Directions for Teaching and Learning, No. 37. San Francisco: Jossey-Bass. Lucas, A.F. (1990). The department chair as change agent. In P. Seldin and Associates (eds.), How Administrations can Improve Teaching (pp. 63–88). San Francisco: Jossey-Bass. Lucas, A.F. (2002, Summer). Engendering trust through institutional policies practices. In Z. Zahorski (ed.), Scholarship in the Postmodern Era: New Venues, New Values, New Visions. New Directions for Teaching and Learning, No. 90. (p. 49–57). San Francisco: Jossey-Bass. Lunde, J.P., and Healy, M. (1991). Doing Faculty Development by Committee. Stillwater, OK: New Forums Press.
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Stanley: Faculty Professional Development for the 21st Century Mathis, B.C. (1982). Faculty development. In H.E. Mitzel (ed.), Encyclopedia of Educational Research (3rd edn., pp. 646–655). New York: Free Press. McKeachie, W.J. (1951). Teaching Tips: A Guidebook for the Beginning College Teacher. Lexington, MA: D.C. Heath. McKeachie, W.J. (1969). Teaching Tips: A Guidebook for the Beginning College Teacher (7th edn.). Lexington, MA: D.C. Heath. McKeachie, W.J. (1978). Teaching Tips: A Guidebook for the Beginning College Teacher (8th edn.). Lexington, MA: D.C. Heath. McKeachie, W.J. (1990). Research on college teaching: The historical background. Journal of Educational Psychology 82: 189–200. McKeachie, W.J. (1993). Lessons I have learned in training college teachers. In M. Weimer (ed.), Faculty as Teachers: Taking Stock of What we Know (pp. 79–80). University Park, PA: National Center on Postsecondary Teaching, Learning, and Assessment. Menges, R.J., and Mathis, B.C. (1988). Key Resources on Teaching, Learning, Curriculum, and Faculty Development. San Francisco, CA: Jossey-Bass. Menges, R.J., and Brinko, K.T. (1990). A three-dimensional model for planning and assessing faculty development efforts. Journal of Staff, Program, & Organizational Development 8(3): 133–141. Murdock, S.H., and Hogue, N. (1999). Demographic factors affecting higher education in the United States in the twenty-first century. New Directions for Higher Education 27(4): 5–13. Murray, H.G. (1984). The impact of formative and summative evaluation of Teaching in North American universities. Assessment and Evaluation in Higher Education 9(2): 117–132. Myers, R. (1980). Developmental theories of learning. In J.L. Bess (ed.), Academic Work: Doing it Well, Doing it Better. Papers from a Conference held at Teachers College, Columbia University, April 14–15, 1978. Nakanishi, D.T. (1993, Spring). Asian pacific Americans in higher education: Faculty and administrative representation and tenure. In New Directions For Teaching and Learning (Vol. 53). San Francisco: Jossey-Bass. National Center for Education Statistics. (2000). Digest of Education Statistics, 2000. Washington, D.C.: U.S. Department of Education, Office of Educational Research and Improvement. National Education Association. (1996). The Politics of Remedy: State Legislative Views on Higher Education. Washington, D.C.: National Education Association. Nyquist, J.D., Abbott, R.D., Wulff, D.H., and Sprague, J. (eds.). (1991). Preparing the Professoriate of Tomorrow to Teach: Selected Readings in TA Training. Dubuque, IA: Kendall Hunt Publishing. Perry, W. (1970). Intellectual and Ethical Development in the College Years. New York: Holt, Rhinehart, and Winston. Piccinin, S., Farquharson, A., and Mihu, E. (1993). Teaching assistants in Canadian universities: An unknown resource. The Canadian Journal of Higher Education 23(2): 104–117. Quehl, G.H., and Berquist, W.H. (1977). Final report to the W.K. Kellogg Foundation on the Advanced In-Service Faculty Development Program of the Council for the Advancement of Small Colleges. Washington, D.C.: Council for the Advancement of Small Colleges [Council of Independent Colleges]. Quinlan, K. (1996). Involving peers in the evaluation and improvement of teaching: A menu of strategies. Innovative Higher Education 20: 299–307. Rhodes, F.H.T. (1990). The New American University. David Dodds Henry Series. University of Illinois.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Rice, R.E. (1991). Toward a broader conception of scholarship: The American Context. In I.T.G. Whitson and R.C. Geiger (eds.), Research and Higher Education: The United Kingdom and the United States. Bristol, PA: Society for Research into Higher Education and Open University Press. Rice, R.E., and Austin, A.E. (1990). Organizational impacts on faculty morale and motivation to teach. In P. Seldin and Associates (eds.), How Administrators can Improve Teaching (pp. 23–42). San Francisco: Jossey-Bass. Richlin, L. (1991). Preparing future faculty: Meeting the need for teacher-scholars by enlarging the view of scholarship in PhD programs. Unpublished doctoral dissertation, Claremont Graduate School. Richlin, L. (1995). Preparing the faculty of the future to teach. In W.A. Wright and Associates (eds.), Teaching Improvement Practices: Successful Strategies for Higher Education (pp. 255–282). Bolton, MA: Anker. Ronkowski, S.A. (1993). Scholarly teaching: Developmental stages of pedagogical Scholarship. In L. Richlin (ed.), New Directions for Teaching and Learning: No. 54. Preparing Faculty for the New Definitions of Scholarship (pp. 15–26). San Francisco, CA: Jossey-Bass. Sanders, D., and McCutcheon, G. (1986). The development of practical theories of teaching. Journal of Curriculum and Supervision 2(1): 50–67. Sanders, D. (1978). A theory of educational program development. Unpublished manuscript, The Ohio State University. Sanford, N. (1967). Where Colleges Fail. San Francisco: Jossey-Bass. Schuster, J.H., and Wheeler, D.W., and Associates. (1990). Enhancing Faculty Careers: Strategies for Development and Renewal. San Francisco: Jossey-Bass. Seldin, P., and Higgerson, M. (2002). The Administrative Portfolio: A Practical Guide to Improved Administrative Performance and Personnel Decisions. Bolton, MA: Anker Publishing. Sell, G.R. (2002). A preliminary summary of responses to questions regarding the POD Futures Strategy. Unpublished document of the Professional and Organizational Development Network in Higher Education. Shea, M. (1997). Variability among faculty. In K.T. Brinko and R.J. Menges (eds.), Practically Speaking: A Sourcebook for Instructional Consultants in Higher Education (pp. 181–185). Stillwater, OK: New Forums Press. Sorcinelli, M.D. (1985, April). Faculty careers: Personal, institutional, and societal dimension. Paper presented at the meeting of the American Educational Research Association, Chicago, IL. Sorcinelli, M.D. (1997). The teaching improvement process. In K. T. Brinko and R.J. Menges (eds.), Practically Speaking: A Sourcebook for Instructional Consultants in Higher Education (p. 157). Stillwater, OK: New Forums Press. Sorcinelli, M.D., and Cunningham, H. (1991). Developing teaching skills through individual consultation. Nurse Educator 16(3): 7–11. Sorcinelli, M.D., and Aitken, N.D. (1995). Improving teaching: Academic leaders and faculty developers as partners. In W.A. Wright and Associates (eds.), Teaching Improvement Practices: Successful Strategies for Higher Education (p. 311). Bolton, MA: Anker Publishers. Stanley, C.A., Porter, M.E., and Simpson, N.J., and Ouelett, M.L. (in press). A case study of the teaching experiences of African American faculty at two predominantly White research universities. Journal on Excellence in College Teaching. Stanley, C.A. (2001). A review of the pipeline: The value of diversity in staffing teaching and learning centers in the new millennium. The Journal of Faculty Development 18(2): 75–86.
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11. DOCTORAL STUDENT ATTRITION AND PERSISTENCE: A META-SYNTHESIS OF RESEARCH Carolyn Richert Bair University of Northern Iowa Jennifer Grant Haworth Loyola University of Chicago
Forty to sixty percent of students who begin their doctoral studies in selective colleges and universities in the United States do not persist to graduation (Berelson, 1960; Bowen and Rudenstine, 1992; Nerad and Cerny, 1991; Tinto, 1987/1993). Despite careful selection processes employed at colleges and universities and the high achievement level of those pursuing the doctorate, attrition from doctoral programs has remained at this striking level for at least half a century (Bowen and Rudenstine, 1992; Reiff, 1992). This high dropout rate seems incongruous, especially given the tremendous importance of doctoral study to research, education, leadership, policy and professional practice. Recipients of doctoral degrees have traditionally occupied prestigious positions in research and education, where they have been called upon and funded to produce new knowledge. Doctoral education provides the labor force not only for top positions within the professoriate, but also in educational administration, scientific laboratories and research facilities, and business and industry (Haworth, 1996). Because of the prestigious position occupied by doctoral education, it would seem to follow that students who do not complete their studies would be carefully and systematically tracked and understood and that an attrition rate of ostensibly 50 percent overall would be of deep concern to J.C. Smart (ed.), Higher Education: Handbook of Theory and Research, Vol. XIX, 481–534. ©2004 Kluwer Academic Publishers. Printed in The Netherlands.
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college and university administrators, faculty, and policy-makers. But this has not been the case (Malaney, 1988). While many studies have been done that seek to understand aspects of attrition or reasons for persistence of students from one or more doctoral programs, very little research has been comprehensive in terms of the number of institutions included and the number of programs studied. Further, conclusions about doctoral student attrition and persistence have been difficult to draw because of the differences across studies. There are many reasons why comprehensive research on doctoral-level attrition is lacking. One of the foremost reasons is that nationwide databases on attrition are not kept, as they are with doctoral completion (National Research Council, 1997). Likewise, colleges and universities often have no systematic, routine data collection processes established within programs, graduate schools, or records offices. Records on doctoral students are often housed at the program level or department level rather than centrally within universities. Accessing these records is seldom a smooth process and researchers have relied on the good will of deans, department chairs, program chairs, and staff in order to complete archival work and follow-up with students who have chosen to leave their institutions. In some instances researchers have met with reluctance, not least because deans or chairpersons may not be well staffed to readily assist with the location of attrition and retention information or may have uncertainty concerning the results that will be produced. Moreover, students who have dropped out are often difficult to locate, and the information they provide comes from recollections, which often change over time. No less telling, variance exists among students and programs of study, which has hampered research on doctoral student attrition and persistence. Due to these complexities, most attrition/retention researchers have restricted their studies to single institutions and sometimes to single programs, although a few comprehensive studies have been done with foundation or university support (Berelson, 1960; Bowen and Rudenstine, 1992; Nerad and Cerny, 1993). Tinto (1987/1993) suggested that an important reason why there is less research on doctoral attrition than on undergraduate attrition is because “research on graduate attrition has not been guided either by a comprehensive model or theory of graduate persistence or by the methodological strategies that have been successfully employed in the study of undergraduate persistence” (p. 231). Tinto maintained that such a model or theory would give shape to doctoral student persistence studies, as has been the case with research on undergraduate student persistence. 482
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Why should researchers be concerned about our nation’s high doctoral attrition rate? Put simply, there are both economic and humanitarian reasons for concern, and the low rate of completion by doctoral students is a problem for post-secondary educators. On the economic side, there has long been an ebb and flow with regard to doctorates awarded in the United States (Fechter and Gaddy, 1998). In recent years there have been predictions of shortages of specialists holding doctoral degrees in most fields (Abel, 1985; Bowen and Rudenstine, 1992; Bowen and Schuster, 1986; Bowen and Sosa, 1984; Cartter, 1976; Fiske, 1989; Ziolkowski, 1990). Were these shortages to occur, they would affect not only education, but also business, industry, and government. Ironically, in recent years there have also been predictions of an oversupply of new doctorates (Holden, 1995; Worthington, 1996), and indeed there has been an actual oversupply of doctoral specialists in many fields (Holden, 1995; Worthington, 1996). These potential and actual developments have fueled questions about the employability of new doctoral degree recipients (Ehrenberg, 1992). Finally, and not least, graduate education is costly to colleges and universities in terms of student selection, student funding, cost of instruction, and faculty, administrative, and staff time. It is also costly to students, who invest considerable money and time pursuing their degrees.
PURPOSE AND SIGNIFICANCE OF THIS STUDY The decision to persist or to drop out of a program of study is highly complex and often involves the interplay of institutional and student factors (Tinto, 1987/1993). Yet, while a number of scholars have sought to identify and isolate those factors that contribute to doctoral student attrition and retention, no one has yet sought to systematically examine and integrate the results of these studies, scrutinizing the evidence to determine which factors “really make a difference.” This study seeks to fill that void. Accordingly, the purpose of this research was to synthesize findings from the aforementioned literature in an effort to develop a comprehensive understanding of doctoral student attrition and persistence. Toward this end, a qualitative method — meta-synthesis — was advanced to sort and integrate findings from the large body of research on doctoral student persistence. Through this method, several major themes emerged from the literature on doctoral student attrition and persistence. 483
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Findings from multiple studies can be combined to serve many purposes. Research synthesis can format and summarize scientific information so that it reaches larger audiences (Cooper and Rosenthal, 1980), aid in the development of theory, and give direction to future research (Cooper, 1979). Additionally, research synthesis can offer policy-makers broad understandings of the research evidence on a particular topic, thereby providing them with the necessary information to inform and guide the policy-making process (Guba, 1978).
METHOD APPROACH TO INQUIRY For this study, a qualitative method, meta-synthesis, was developed in order to systematically analyze data contained in the large body of research on doctoral student attrition and persistence. This approach is described in this section. It is difficult to extract accurate, meaningful, and comprehensive information from a large number of studies on a selected topic without the application of rigorous research procedures. Over the past 30 years researchers have developed research syntheses as credible methodologies for the combination of multiple research studies on a similar topic. Two distinct types of formal research syntheses have been available prior to this study: meta-analysis and meta-ethnography. Researchers who conduct syntheses of research studies using quantitative approaches and data from quantitative research studies have used meta-analysis as their methodology of choice. In meta-analysis, which Glass formally introduced to the behavioral and social sciences in the mid-1970s (Glass, 1976, 1977), the results of quantitative studies are statistically combined. The process involves the selection of multiple studies on a similar topic and the synthesis of individual data points (usually effect sizes, or standardized mean differences) from across those studies. An average of the effect sizes is calculated. In this way, findings of each study are represented through a common metric, usually standard deviation. This measure of central tendency is on a continuum; accordingly, the researcher can calculate the extent to which items in the studies vary in magnitude of effect. Meta-analysis is a reductionistic research approach in the positivist tradition (Glass, 1976, 1977). 484
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Researchers who are interested in synthesizing findings of multiple qualitative studies through the use of qualitative methods have used an approach called meta-ethnography. Introduced by Noblit and Hare (1988), meta-ethnography involves “a rigorous procedure for deriving substantive interpretations about any set of ethnographic or interpretive studies” (p. 9). Meta-ethnography goes beyond a single case study, discourse analysis, narrative, or other ethnographic study in order to examine multiple accounts critically. Because ethnography is focused on understanding how individuals make sense of certain realities within a given context, researchers concentrate on identifying key metaphors or themes. As a method, meta-ethnography emphasizes a critical review of texts of studies, relying on notes, matrices, and descriptions in constructing interpretations and in synthesizing understandings from multiple studies (Noblit and Hare, 1988). The data management techniques of Miles and Huberman (1984/1994) are often used in the process of analyzing materials in metaethnography in order to increase the reliability and validity of conclusions (Huberman and Miles, 1994). Whereas meta-analysis is a quantitative methodology applied to quantitative studies, and meta-ethnography is a qualitative methodology applied to qualitative studies, a new qualitative research design was needed for this study. This approach was termed “meta-synthesis” and was used to synthesize findings from a combination of both qualitative and quantitative studies. Meta-synthesis is designed to be qualitative, in that it is not technically possible to synthesize data from both quantitative and qualitative studies using a quantitative approach, due to the absence of a common metric. Like other forms of qualitative research, meta-synthesis seeks to “describe and understand phenomena as wholes, or at least in ways that reflect their complexity” (Guba, 1978, p. 14). As a qualitative synthesis it is integrative and expansionistic, rather than reductionistic, in that it compares and analyzes many studies together in a constructivist way, allowing interpretive themes or key metaphors to emerge from the synthesis. As Ward (1983) put it: “synthesis can be used to refer to all efforts to relate knowledge, including previously unrelated or contradictory knowledge, and to show it is relevant to a specific situation or topic” (p. 26). Interpretation and induction are essential tasks of qualitative research synthesis (Noblit and Hare, 1988) and are incorporated in meta-synthesis. The methodology of meta-synthesis has many similarities with metaethnography, since both are integrative approaches in the phenomenological tradition. Meta-synthesis stands in contrast to meta-analysis, however, 485
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in that little emphasis is placed on the reduction of data from multiple studies. In much the same way as “meta-ethnography synthesizes the substance of qualitative research” and “meta-analysis synthesizes the data” [of quantitative research] (Noblit and Hare, 1988, p. 81), meta-synthesis integrates the substance of both qualitative and quantitative research studies. The research approach of meta-synthesis springs from the phenomenological, or interpretive, paradigm of naturalistic inquiry (Guba, 1978; Noblit and Hare, 1988) and is aimed at scientifically describing, understanding, and integrating findings that, in this particular study, have been published on the topic of doctoral student attrition or persistence. This research approach is interpretive, because it explains social/cultural phenomena and uses data that have been gathered from individuals in myriad ways and are contained within the texts produced by the authors of those studies. This study was designed to “make sense of an object of study . . . to bring to light an underlying coherence,” thereby creating a picture of doctoral student persistence or non-persistence to the degree (Taylor, 1982, p. 153). In qualitative synthesis, multiple studies are translated into one another’s terms (Noblit and Hare, 1988). Consonant with phenomenological/interpretivist inquiry, an emergent research design was used, because to attempt to specify the design in full detail could have constrained the complexity of the information-building process (Guba, 1978). As studies were reviewed, ongoing decisions were made regarding data recording and management (Miles and Huberman, 1984/1994). Specifically, ongoing decisions were made as to data selection, condensation, display, observation of patterns, and the drawing of conclusions. This emergent design was particularly useful in a synthesis of studies on doctoral student attrition/persistence, where texts needed to be analyzed and integrated and, in the process, new interpretations created (Noblit and Hare, 1988). Research questions were stated in broad, general terms so as to allow patterns and understandings to build (Lincoln and Guba, 1985). Studies selected for use in this meta-synthesis were subject to selection criteria; however, the total number remained open to allow for the addition of studies as the research progressed. SAMPLE SELECTION AND DATA COLLECTION The sample used for this study consisted of research completed on doctoral student attrition and persistence between 1970 and 1998. Research studies were drawn from various sources, including published articles, books, dissertations, papers presented at national conferences, reports, 486
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theses, and unpublished studies. In keeping with Mullen and Rosenthal’s (1985) recommendation of using the full range of sources in order to have a more complete and accurate study, various electronic databases and abstracting services were used to identify as many studies as could be located between 1970 and the present. Additionally, other approaches were employed to identify studies, including the “descendency approach” of using direct indexing sources such as Books in Print and university on-line indices; the “ancestry approach” of following bibliographies back to earlier studies; and the “invisible college approach” of corresponding with researchers directly (Mullen and Rosenthal, 1985, p. 17). Once studies were identified and read, final determinations were made regarding whether they fit the criteria for the study. Studies that were identified but not included in the sample were eliminated for one or more of five specific reasons: (a) the study was conducted prior to 1970; (b) the study did not produce clear and understandable findings; (c) the study did not separate “doctoral” students from “graduate” students; (d) the study attempted to understand persistence or attrition from the perspective of currently enrolled doctoral students; and (e) a full copy of the study could not be obtained. The year 1970 was selected with three objectives in mind. First, studies prior to 1970 are more difficult to locate, especially those contained in conference proceedings and those obtained through contact with the researcher. Second, changes in research methodology that resulted from the development of microcomputers and statistical packages began at approximately that time, and the studies following 1970 began to reflect the influence of those developments. Third, this parameter provided a realistic and neutral means for limiting the number of studies included in the meta-synthesis. In light of these criteria, 430 research studies were identified for possible inclusion in the meta-synthesis; 118 of these were used in the final sample. The vast majority of studies excluded were those written prior to 1970. Approximately one-tenth of the studies was excluded for reasons (b), (c), (d), and (e) mentioned above. PROCEDURES Both inductive and integrative approaches were used in the analysis of data. A four-step process was followed. First, studies were gathered, read and summarized, and specific categories of information were noted on a summary form designed for that purpose. The summary form was 487
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detailed to include the following categories of information: (a) Author(s), (b) Title of Study, (c) Source/Citation, (d) Date of Study, (e) Descriptions of the Study’s Participants, (f) Institution(s) Represented, (g) Type of Study (design, methodology, analysis), (h) Instrument(s) Used (survey, interview protocol, institutional data), (i) Findings Regarding Rates of Attrition/Persistence, ( j) What the Study Examined; Variables and Questions Studied, (k) Findings/Results Related to Persistence/Attrition, (l) Limitations of the Study, (m) Future Research Recommended, and (n) Also.1 Because studies were systematically read and recorded in this way, pertinent information was available in summary form for use in the integration and synthesis of studies. For example, when undergraduate grade-point-average and its relationship to doctoral student attrition/ persistence was examined, studies could then be compared that looked at this particular item. Were the studies similar in terms of methodology employed? Who were the participants? What characterized the institutions represented in the subsample for this particular object of study? Additionally, during this first step, quotations were recorded on the reverse side of the summary form so that they were readily available and could be used later to illuminate, explain, or interpret the findings. After all of the studies were read and summarized, the step of “determining how the studies are related” (Noblit and Hare, 1988) was completed. Studies were examined to identify and determine those relationships that existed among them. Toward this end, information was recorded category by category using a second summary sheet, a matrix of information. The matrix was developed based on guidelines provided by Miles and Huberman (1984/1994). Information that related to each specific category of findings (such as financial assistance and its relationship to attrition/persistence) from each of the aforementioned summary forms was recorded on the matrix. This process produced numerous matrices that, in effect, functioned as written summaries of key findings across studies, topic by topic, and contained the weight of evidence for each item of study. The categories of information recorded from each study generally included: (a) author, (b) date, (c) institutions studied, (d) fields of study, (e) type of research study, (f) methodology used, and (g) findings. Each matrix contained information from all studies on the particular set of
1 The category “also” was used to make notes regarding interesting or important information that did not fit nicely into one of the column headings.
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findings covered on that matrix. Because the matrices were used to summarize by category of finding, they displayed the collective of studies in the sample that contained information on that category of findings. The next step was to “translate” the categories of information from one study into another using the matrices, a procedure that allowed for comparisons of each category of information across studies. Noblit and Hare (1988) recommended thinking in terms of analogies for this process (i.e., €1 is analogous to €2 in the following ways, and differs in the following ways, and so on). Study results were juxtaposed, cross compared, and integrated, so that key concepts and themes of one study could be seen in terms of the key concepts and themes of other studies in the sample. The matrices were particularly helpful in this process, visually depicting common and contradictory findings for each category of information on sample, fields of study, methodology and findings. Colorcoding was used to highlight the different categories of entries on each matrix of information. The following types of questions were asked: Were there similarities, commonalties, or contradictions across studies with regard to each category of information? What could be seen about each category of findings in one study and how did that relate to the same category of findings in other studies in the sample? Were findings for each category similar for similar types of institutions and different for different types of institutions? Were patterns revealed when field of study and program size were taken into account? Were there any patterns that related to other factors, such as the methodology used in conducting the study? Finally, the translations noted above were synthesized, and the categories of findings were compared in order to see the many categories of information in relationship to each other. Cross comparisons focused on multiple programs, fields of study, and colleges/universities. In this last analytical step, the focus was on the whole, or on all of the themes of the study, and on understanding them in relationship to each other. VALIDITY Trustworthiness within this study was established through confirmability, credibility, and transferability (Lincoln and Guba, 1985). To enhance confirmability, a large number of methodologically diverse studies was included. All available studies that met the criteria for inclusion in the meta-synthesis were used, and the research findings were carefully read and recorded on summary sheets and matrices. To ensure credibility of the 489
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findings, an external review process was used, in which an external auditor examined three studies from the research sample and the corresponding summary forms and matrices. There was essential agreement between the external auditor and researcher on the information being recorded from the research studies to the summary forms and matrices. Transferability was present in the structure of the meta-synthesis in as much as multiple accounts over time were examined. LIMITATIONS The most obvious limitation of a meta-synthesis of existing research is that the data are limited to those research studies selected for inclusion. Because of this, other factors associated with a doctoral student’s decision to persist or drop out may exist that have not yet been identified by researchers. In short, meta-synthesis can potentially transcend simple interpretation through the integration of multiple studies but it is nonetheless limited to the findings of the studies at hand. A second limitation concerns the research quality of the studies included in the final sample. In this meta-synthesis, studies were not excluded based on quality, with the exception of those that did not produce clear and understandable findings. Owing to the broad range of studies included in this investigation, it is possible that some could be questioned with regard to quality. Mullen and Rosenthal (1985) have described a further limitation, which they call the “file drawer” problem (p. 17). Rosenthal (1984) has estimated that only 5 percent of quantitative studies (those with significant results) are published; the rest are relegated to storage, ostensibly because they have yielded insignificant results. If accurate, this skews the body of research available to the meta-researcher. This phenomenon seems less likely to occur in research studies that are qualitative in that statistical significance is not a defining characteristic of qualitative research and qualitative researchers report their findings without having comparison as a requisite feature. Before turning to findings, it is important to note that the scope and sample of the research studies examined in this meta-synthesis varied considerably. Approximately two-thirds of the institutions at which the studies were conducted are classified as Research I universities; the remaining one-third are state universities, private colleges and universities, and professional schools. Most of the studies reviewed were conducted at single 490
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institutions and very few studies involved two or more institutions. Some of the studies concentrated on all doctoral programs within a graduate school, while others focused on several programs in a single school or department or even a single program.
FINDINGS AND DISCUSSION Ten key findings emerged from the 118 research studies on doctoral student attrition and persistence included in the meta-synthesis used in this study (see Table 11.1). Each is reviewed in this section. Table 11.1: Key Findings 1. Attrition and Persistence Rates Vary by Field of Study and Program of Study 2. Departmental Culture Affects Doctoral Student Persistence: ● The degree and quality of the relationship between doctoral student and advisor or faculty has a strong, positive relationship to successful completion of the doctorate ● Student involvement in various programmatic, departmental, institutional, and professional activities and opportunities contributes favorably to doctoral student retention and completion ● Students’ satisfaction with their academic programs — including the perceived fulfillment of their doctoral expectations — contributes favorably to doctoral degree completion ● Peer interaction is related to persistence, insofar as degree completers are more likely to be involved with their academic peers than non-persisters ● The financial support offered to doctoral students is related to attrition and persistence; students who hold research assistantships, teaching assistantships, fellowships, or graduate assistantships are more likely to complete their degrees than students who rely on other types of funding ● Difficulty with various aspects of the dissertation relates to attrition 3. Academic Achievement Indicators are Generally not Effective Predictors of Doctoral Degree Completion, with the Exception of GRE Advanced Scores 4. Findings are Mixed With Respect to Employment and Financial Factors 5. Personal and Psychological Variables Represent a Relatively New Direction in the Study of Doctoral Student Attrition and Persistence; A Number of these Variables has been Shown to Relate to Persistence 6. Demographic Variables do not Conclusively Distinguish Persisters from Those Who Drop Out 7. Retention and Attrition Rates Vary Widely Among Institutions 8. ABD is Not the Stage Where the Greatest Proportion of Doctoral Students Necessarily Departs 9. Time-to-Degree is Related to Attrition 10. Doctoral Programs that Have Smaller Entering Cohorts Have Consistently Lower TTD and Consistently Higher Completion Rates Than Programs with Larger Entering Cohorts
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ATTRITION AND PERSISTENCE RATES VARY BY FIELD OF STUDY AND PROGRAM OF STUDY Doctoral student attrition and persistence rates vary widely depending on the field of study and even more widely depending on program of study. Across all the studies reviewed, the lowest attrition rates were found in the laboratory sciences, and the highest rates occurred in the social sciences and humanities. According to Benkin (1984, pp. 155, 165), “When academic and demographic factors were controlled, the factor that was repeatedly significant in predicting degree completion was a student’s field of study . . . each field of study acts as a separate environment within the institution and has a differential impact on rates of degree completion.” The weight of the research evidence suggests strongly that doctoral student attrition and persistence rates differ by field of study and even more by program of study (Bauer, 1997; Benkin, 1984; Berg and Ferber, 1983; Bowen and Rudenstine, 1992; Decker, 1972, 1973; Ferrer de Valero, 1996; Golde, 1995, 1996; Jacks, Chubin, Porter, and Connolly, 1983; Matchett, 1988; Nerad and Cerny, 1991; O’Connell, 1991; Ott, Markewich and Ochsner, 1984; Reamer, 1990; Sauer, 1986; Swoboda, 1978; Valentine, 1986, 1987; Zwick, 1991). The lowest rates of attrition have been found in the laboratory sciences and the highest rates in the social sciences and humanities. Golde (1996), for example, documented the following attrition rates in a large Research I university: 17 percent for life sciences, 21 percent for physical sciences, 27 percent for humanities, and 27 percent for social sciences. When she disaggregated the data at the departmental level, she found further variations: 18 percent attrition for biology, 27 percent for geology, 30 percent for English, and 37 percent for history (1984–89 cohorts). Without disaggregating the data at all, Golde would have simply found an overall attrition rate of 23 percent, with 14 percent still enrolled and 62 percent graduated. Her analysis of the data by field of study revealed that attrition rates vary depending on field and program of study. Similarly, Nerad and Cerny (1991) found completion rates ranging from 72 percent for biology to 37 percent for languages and literature at the University of California, Berkeley, for 1978 and 1979 cohort groups (see Table 11.2). Numerous researchers have offered explanations for these differences by field of study. For example, Sauer (1986) suggested that lower attrition rates in the sciences might be related to the “exacting structure imposed on [science] students by the laboratory sciences and by financial support of their students,” whereas higher attrition rates in the social sciences may be “due 492
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in part to less structure, more ambiguous expectations, and less financial support” (p. 3). Bauer (1997) offered that differences in the way various disciplines “do research” also contribute to varying degrees of completion rates by field of study. “In many of the physical and life science disciplines,” wrote Sauer, “research is conducted in a laboratory by groups of Ph.D. candidates and fellows under the direct supervision of their advisor” (p. 167). There is a greater involvement between the advisor and the advisee as the dissertation topic is chosen and also a “greater likelihood that the advisee’s dissertation research was a part of the advisor’s research project in the physical and life sciences than in the humanities or social sciences” (p. 167). Because of the team atmosphere present in the lab, characterized by constant contact between student and advisor, there is “day-to-day awareness of expectations for progress and observation of whatever progress is being made” (p. 167). Sauer contrasted this with those typically found in the humanities and social sciences, where “research . . . is done in solitude, and often in the field. Ph.D. candidates are less in contact with their advisors and Ph.D. counterparts, less supervised, and there is less day-to-day awareness of the passage of time and attainment of project timelines or milestones” (p. 167). Variations in the financial assistance made available to doctoral students by field of study also appear to play a role in persistence of doctoral Table 11.2: Completion Rates by Field of Study Author
Completion Rates
Time Frame
University
Bowen and Rudenstine (1992)
65% Natural Sciences 55% Economics, Political Science 50% English, History, Other Humanities
1967–76, studied in 1992
10 Research I Universities
Ferrer de Valero (1996)
3% Adult and Continuing Ed. 80% Accounting
1986–90, studied in 1996
Research I
Nerad and Cerny (1991)
72% Biology 69% Physical Science 65% Natural Resources 49% Social Science 48% Professional 39% Arts 37% Language/Literature
1978–79, studied in 1989
Research I
O’Connell (1991)
63.11% Medical Sciences 23.81% Humanities
1976–81, studied in 1989
Doctoral I
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students (Berg and Ferber, 1983; Bowen and Rudenstine, 1992; Ferrer de Valero, 1996; Sauer, 1986). For example, Berg and Ferber (1983) found that 9 out of 10 doctoral students in the physical and biological sciences received assistantships or fellowships, compared to only 30 percent of women and 56 percent of men in education. For the same grouping from 32 departments at a Research I university, 68 percent of men and 46 percent of women earned Ph.Ds in the sciences, compared to 22 percent of men and 28 percent of women in education. In their study of doctoral programs in six fields of study at 10 elite universities, Bowen and Rudenstine (1992) likewise found that physics students who were supported primarily by fellowships completed their doctorates at substantially higher rates than students who had to rely on their own resources. O’Connell (1991) attributed differences in completion rates by field of study to individual characteristics of doctoral students varying by field. In a study of psychological type at a Doctoral I university, O’Connell concluded that: In disciplines where the primary academic activity is research, and where the disciplinary paradigms are better defined, such as graduatelevel scientific research in the medical sciences, the [psychological] type patterns of dropouts and Ph.D. completers are more distinct and fall into predictable patterns. On the other hand, in doctoral programs with multiple academic and career foci and less developed disciplinary paradigms (such as the humanities), the type pattern of Ph.D. completion is more heterogeneous and pattern recognition is more complex. (p. 304)
Researchers using qualitative methodologies have likewise contributed to the exploration of differences in attrition and completion rates by field of study (Ferrer de Valero, 1996; Golde, 1995, 1996; Jacks, Chubin, Porter, and Connolly, 1983). In a narrative study of doctoral ABDs (all-butdissertations) across 18 departments at 15 universities, Jacks, Chubin, Porter, and Connolly (1983) found that different factors contributed to persistence for students in various fields of study. Psychology ABDs experienced problems with doctoral committees or advisors, while sociology ABDs struggled with the selection of a research topic, and bio-science ABDs had financial difficulties. For each field of study, these factors served as the major reason for doctoral student attrition. Likewise, Ferrer de Valero (1996) found that certain departmental factors (such as financial support, orientation/advising, and faculty attitudes toward students) positively affected outcomes in certain fields of study but not in others. Golde (1995) found that the stages at which attrition took place differed 494
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across areas of study (life sciences, physical sciences, humanities and arts, social sciences) and across fields of study (biology, geology, English, history). As more qualitative studies are completed in the future, additional descriptions will be available to explain more fully how students in various fields experience doctoral education differently. DEPARTMENTAL CULTURE AFFECTS DOCTORAL STUDENT PERSISTENCE In various studies of doctoral education, degree completion has been linked to the interactions students have in their own and other departments on campus. In this section, student/faculty relationships are highlighted, along with student involvement in academic life, student satisfaction with program, student-to-student interactions, institutional financial assistance, and dissertation factors. The Degree and Quality of the Relationship Between Doctoral Student and Advisor or Faculty has a Strong, Positive Relationship to Successful Completion of the Doctorate The single most frequently occurring finding in this meta-synthesis was that successful degree completion is related to the degree and quality of contact between a doctoral student and her or his advisor(s) or other faculty in the student’s doctoral program. Simply put, where positive relationships between students and their advisors or other faculty members were present, students were significantly more likely to complete their doctoral degrees. This finding held across various types of quantitative studies. In all of the qualitative studies included, the students or former students who were interviewed offered descriptions of the importance of the student–faculty or student–advisor relationship as it related to doctoral student completion. Further, in all mixed-methodology studies in which a qualitative component was incorporated, student-to-advisor and student-to-faculty relationships emerged as a key finding. Finally, of all the studies reviewed here, not a single one countered the importance of the relationship between student and advisor or student and faculty toward the completion of the doctoral degree. In the vast majority of studies, degree recipients were distinguished from those who had either withdrawn or were ABD, and the value of a positive student/advisor or student/faculty relationship was one of the cited variables (Benkin, 1984; Berg and Ferber, 1883; Butler, 1996; Campbell, 1992; Carlson, 1995; Clewell, 1987; Cooper, 1996; Daniels-Nelson, 1983; Delaney, 1981; Dickinson, 1983; Dolph, 1983; Ducette, 1990; Ferrer de Valero, 1996; Flores, 495
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1984; Foote, 1988; Gell, 1995; Girves and Wemmerus, 1988; Golde, 1994, 1996; Grissom, 1985; Hagedorn, 1993; Hassan-Shahriari, 1983; Howard, 1981; Huang, 1995; Huguley, 1988; Jacks, Chubin, Porter, and Connolly, 1983; Jones, 1987; Karolyi, 1993; Lawson, 1985; Leadabrand, 1985; Lees, 1996; Lenz, 1994; Long, 1987; Lovitts, 1996; Macht, 1978; Mah, 1986; McCabe-Martinez, 1996; Muszynski, 1988; Nagi, 1974, 1975; Nerad and Cerney, 1991; O’Bara, 1993; O’Connell, 1991; Patterson-Stewart, 1996; Presley, 1996; Reamer, 1990; Reiff, 1992; Sauer, 1986; Schultz, 1983; Skudlarek, 1992; Swoboda, 1978; Tierce, 1984; Valentine, 1986, 1987; Wagner, 1986). In other studies, degree recipients specified that advisors were more readily approachable and accessible than did ABDs or withdrawn students (Benkin, 1984; Ducette, 1990; Flores, 1984; Macht, 1978; Swoboda, 1978). In studies of attrition, the student’s departure was found to be due in part to inadequate or inaccurate advising, lack of interest or attention on the part of the advisor, unavailability of the advisor/faculty to students, or a negative relationship or even conflict between the student and advisor/faculty (Campbell, 1992; Delaney, 1981; Dickinson, 1983; Dolph, 1983; Golde, 1994; Heiss, 1970; Huguley, 1988; Jacks, Chubin, Porter, and Connolly, 1983; Karolyi, 1993; Lovitts, 1996; Mah, 1986; Muszynski, 1988; Nerad and Cerney, 1991; Porozny, 1970; Reiff, 1992; Swoboda, 1978). The “relationship” between student and advisor or other faculty member(s) is difficult to define and study, except in very general terms, such as through items on surveys and questions on interview protocols. While some researchers have attempted to quantify the relationship (Berg and Ferber, 1983; Dolph, 1983; Sauer, 1986; Tierce, 1984), descriptors of the faculty/student relationship have been advanced by the majority of researchers, both as they relate to successful degree completion and to attrition. Table 11.3 contains representative descriptors excerpted from the studies of successful degree completion, clustered into three general categories. Table 11.4 contains those items seen as contributing to non-persistence. Many researchers have identified the student/advisor relationship as an important, if not the most important, variable in both doctoral student attrition and persistence (Dickinson, 1983; Ferrer de Valero, 1996; Girves and Wemmerus, 1988; Nagi, 1974, 1975; Presley, 1996). Dickinson (1983), for example, found that “the single most important factor associated with student attrition is a feeling of lack of cooperation and understanding on the part of the student’s advisor” (p. 79). In a study on doctoral student completion, Ferrer de Valero (1996) described the student–advisor relationship as the most important factor promoting timeto-degree (TTD) and completion rates and as a “critical factor in graduate student success”(cited by 88 percent of study participants) (p. 129). 496
Bair and Haworth: Doctoral Student Attrition and Persistence Table 11.3: Descriptors of Student/Advisor and Student/Faculty Relationships that are Positively Related to Successful Degree Completion Quality of the relationship Positive relationships in quality and time Ability to talk about problems encountered Close, personal relationship Satisfactory interaction Good student/advisor relationship Value of student/faculty interaction Student is satisfied with relationship Student is treated as junior colleague Student knows one or more faculty quite well Frequent contacts Ease of interaction Opportunities to meet informally Characterized by trust High level of faculty/advisor expertise High quality of advising Quality as a teacher and scholar Usefulness in providing needed information Caring as an advisor National reputation as faculty Helpfulness on questions related to research Academic coaching Career sponsorship Provides valuable advice
Characteristics of the advisor Easy to approach Accessible (faculty and chairperson) Personally supportive of students Cooperative Concerned for students as persons Supportive (major professor) Supportive (committee members) Supportive (general faculty) Encourages students Encourages student/faculty interaction Personally supportive of students Caring, patient, kind High amount of help Concern for student development Supportive (mentor) Voice of care and power Concern for teaching Acceptance of students Confirmation of students Personal counseling of students Friendship with students
Student Involvement in Various Programmatic, Departmental, Institutional, and Professional Activities and Opportunities Contributes Favorably to Doctoral Student Retention and Completion Research evidence suggests that student involvement is also related to doctoral student retention and completion (Benkin, 1984; Boozer, 1972; Brien, 1992; Ducette, 1990; Ferrer de Valero, 1996; Girves and Wemmerus, 1988; Golde, 1995, 1996; Lawson, 1985; Nerad and Cerny, 1991; Reamer, 1990; Reiff, 1992; Skudlarek, 1992; Valentine, 1986, 1987). Involvement includes attendance at and participation in graduate association meetings, academic activities, social activities, informal and formal meetings, and activities of the profession. 497
Concerns regarding faculty Problems in faculty/student relationships Student not well acquainted with faculty Need faculty to serve as supportive mentors Insufficient active intervention by faculty Need to interact informally with faculty Ambiguity regarding faculty expectations Lack of encouragement from faculty Need more faculty concern for teaching Hesitant to approach faculty Need faculty concern for student development Need faculty voices of care and power
Concerns with program/department/school Community not nurturing Need to understand department structure Need to know who is in authority Need clarity on where to go with problems Need for useful information Insufficient guidelines/suggestions Lack of clarity on criteria for evaluation Extremely informal rules in the department Need career sponsorship
Concerns with dissertation advisor/advisement Problems with dissertation advisor Problems with dissertation committee Lack of advisor cooperation Lack of advisor understanding Advisor not caring Dissertation advisor not helpful Dissertation advisor not encouraging Mismatched expectations and working styles Number of advisor’s current committees Insufficient support by major professor Inadequate advising during dissertation Difficulty finding a director Major faculty changes during dissertation Advisor left the institution or died More attention needed from director Need guidance from major professor Need better advice from chairperson Infrequency of contacts Student’s standing with advisor unknown Support for stress during dissertation Inaccessibility of advisor
Table 11.4: Characteristics of Student/Advisor and Student/Faculty Relationships that are Related to Attrition in Research Studies HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX
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The need for universities to have intentional structures that support the academic and social integration of doctoral students is grounded largely on an outcome of Golde’s (1995, 1996) studies. Based on her mixedmethod examination of departmental contextual factors at a major research university, Golde (1996) concluded that “departmental context is a central contributor to attrition” (pp. 356–357) and identified numerous areas for examination of departmental practices and other potential contributors to attrition, including “office locations, student directories, orientation programs, student participation in departmental decision making, [and] doctoral studies requirements” (p. 358). Golde’s study suggests that departments with higher structure have lower attrition rates. The timing and communication of departmental rules, regulations, structures, and processes were also found to be important (Golde, 1996; Lawson, 1985). The benefits of participation in professional activities for successful degree completion have also been established (Clewell, 1987; Destigter, 1983; Ducette, 1990; Harris, 1976). Nearly three-fourths of the students who participated in professional activities, such as presenting papers and publishing articles, persisted in Clewell’s study (1987). In a path analytic test of Tinto’s model within a single institution, Ducette (1990) concluded “it is the individual’s level of integration into both the academic and social systems that most directly affects graduation” (p. 121). Conversely, Ducette found that those doctoral students who did not attend departmental, state, national or other events or lectures were less likely to graduate. Girves and Wemmerus (1988) also found that “involvement or socialization in one’s program” was “directly related to doctoral degree progress” in their multiple regression analysis with 42 departments at 12 universities. Students’ Satisfaction with their Academic Programs — Including the Perceived Fulfillment of their Doctoral Expectations— Contributes Favorably to Doctoral Degree Completion The research evidence underscores that students’ satisfaction with their academic programs — including their realization of their doctoral expectations — contributes favorably to doctoral degree completion (Boozer, 1972; Cooke, Sims, and Peyrefitte, 1995; Foote, 1988; Girves and Wemmerus, 1988; Golde, 1995, 1996; Lovitts, 1996; Murrell, 1987; Nagi, 1974, 1975; Sauer, 1986; Skudlarek, 1992; Valentine, 1986, 1987). The converse also holds sway: when students are disappointed in or dissatisfied with their 499
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doctoral programs, they are far more likely to abandon doctoral study (Boozer, 1972; Lovitts, 1996). What contributes to student satisfaction? Based on the research studies reviewed, the following items were most consistently mentioned: quality of the doctoral program, frequent and ongoing communication with students, fairness in requirements, consistency among faculty in the evaluation of students, faculty concern for students as professionals, and adequate guidance. Those doctoral students who were most likely to complete were those who were satisfied with their programs, courses, and instruction (Ducette, 1990; Foote, 1988); those who perceived the coursework to be of high quality and value (Valentine, 1986, 1987); those who had higher levels of satisfaction and whose expectations had been met (Cooke, Sims, and Peyrefitte, 1995); and those who were not only satisfied with their programs of study, but also with the work that they had completed in those programs (Skudlarek, 1992). Peer Interaction is Related to Persistence, Insofar as Degree Completers are more Likely to be Involved with their Academic Peers than Non-persisters. Student-to-student relationships and social integration figure into student attrition or persistence as well, although not as prominently as student/faculty relationships and student involvement in academic life (Lovitts, 1996). The interest in and support of doctoral students for each other was found to be an important factor in all but two of the research studies in which it was examined (Dolph, 1983; Frasier, 1993). In the quantitative studies reviewed, degree completers were more likely to be involved with their academic peers than non-persisters (Benkin, 1984; Boozer, 1972; Brien, 1992; Dolph, 1983; Ferrer de Valero, 1996; Grissom, 1985; Hagedorn, 1993; Leadabrand, 1985; Tierce, 1984). This finding also held sway in qualitative and mixed-design studies (Brien, 1992; Ferrer de Valero, 1996). The Financial Support Offered to Doctoral Students is Related to Attrition and Persistence; Students who Hold Research Assistantships, Teaching Assistantships, Fellowships, or Graduate Assistantships are more Likely to Complete their Degrees than Students who Rely on Other Types of funding One of the “structures” that institutions, graduate schools, departments, and programs have in place to attract and support doctoral 500
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students is financial assistance. But does financial support relate to doctoral student persistence? The weight of the evidence suggests that it does, and that different types of financial support relate correspondingly to different levels of persistence (Benkin, 1984; Boozer, 1972; Bowen and Rudenstine, 1992; Cook and Swanson, 1978; Dolph, 1983; Ducette, 1990; Franklin, 1970; Girves and Wemmerus, 1988; Macht, 1978; Sauer, 1986). This finding cannot be considered without reference to field of study, insofar as the funding types differ and are much higher in certain fields of study (Bowen and Rudenstine, 1992; Sauer, 1986). For example, it is normative for students in the sciences to be fully supported, whereas humanities and social sciences students may receive only partial support and may work away from campus (Benkin, 1984). That said, there are a number of general findings regarding the relationship between financial support and persistence that are evident in the research literature: ●
●
●
●
Students who hold teaching assistantships have higher rates of completion than many other categories of doctoral students (Bowen and Rudenstine, 1992; Boozer, 1982; Dolph, 1983; Franklin, 1970; Huang, 1995; Macht, 1978). Students who hold research assistantships have higher rates of degree completion than many other categories of doctoral students (Benkin, 1984; Boozer, 1972; Bowen and Rudenstine, 1992; Dolph, 1983; Huang, 1995; Sauer, 1986). Fellowship students have high completion rates (Benkin, 1984; Boozer, 1972; Dolph, 1983; Franklin, 1970; Huang, 1995; Macht, 1978). Having a graduate assistantship is a strong, positive indicator of graduation (Cook and Swanson, 1978; Dolph, 1983; Ducette, 1990; Franklin, 1970) for students in educational administration.
In her study of attrition across all doctoral fields at a major research university, Benkin (1984) concluded the following: It seems clear that students who have the types of support that either require no work (fellowships and grants) or that reward students for doing the type of research that leads to a degree (research assistantship) will be more likely to progress rapidly toward a degree. In contrast, students who have to work at positions not directly related to their research, whether on or off campus, will be more likely to progress more slowly or not at all. (p. 159)
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Since institution-provided assistantships involve students in the academic environment through research, teaching, or administrative assignments, it follows that they would also serve a socializing function and help to integrate students into their academic environments. This effect was demonstrated in a single-institution study of 12 colleges and 42 departments by Girves and Wemmerus (1988). Through the use of multiple regression analysis, Girves and Wemmerus found that type of financial support (TA, RA) was directly related to “involvement or socialization in one’s program” (p. 175) which, in turn, was directly related to doctoral degree completion. Bowen and Rudenstine (1992) studied minimum completion rates to determine whether financial support for students came from “institutional” or from “own support” sources (p. 179). They found that minimum completion rates for one of the institutions were as low as 14.2 percent for those students relying on their own support to 41.8 percent for students receiving institutional support (p. 179). In another institution in the same study, students relying on their own support had a 37.9 percent completion rate, compared to a 63.0 percent completion rate for those receiving institutional funding. All five of the examples of institutional versus own support provided by Bowen and Rudenstine (1992) show the same directionality, leading to the conclusion that “students forced to rely primarily on their own resources have had markedly higher attrition rates and longer TTD than comparable students who received financial aid” (p. 178).2 Difficulty with Various Aspects of the Dissertation Relates to Attrition The dissertation phase of doctoral study has been the direct focus of some research studies; in others, it has been included as an important aspect (Bauer, 1997; Cooper, 1996; Daniels-Nelson, 1983; Delaney, 1981; Franek, 1982; Gell, 1995; Grissom, 1985; Hassan-Shahriari, 1983; Hobish, 1978; Howard, 1981; Huguley, 1988; Jacks, Chubin, Porter, and Connolly, 1983; Jones, 1987; Karolyi, 1993; Lees, 1996; Lenz, 1994; Mah, 1986; Mariano, 1993; McCabe-Martinez, 1996; Muszynski, 1988; Peacock, 1996; Tierce, 1984; Valentine, 1986, 1987; Wagner, 1986). Not surprisingly, less difficulty with
2
Bowen and Rudenstine (1992) indicated that stage of attrition may be an important factor to consider when examining funding patterns and student retention. Citing an example at The University of Chicago, they noted that “attrition rates for own support students were high in the pre-ABD years, but relatively low for those who cleared that hurdle” (p. 182).
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many aspects of the dissertation has been found to relate to doctoral degree completion (Valentine, 1986, 1987). Muszynski (1988, p. 81) listed seven factors that aided in dissertation completion based on her multiple regression analysis study of psychology doctoral students and graduates at a major university: (a) good advisor (supportive, interested, competent, secure), (b) good topic choice (quickly manageable, interesting), (c) internal strength (independence, high motivation, ability to endure frustration), (d) self-imposed deadline or goal, (e) avoiding or limiting employment, (f) delaying internship (until completion of dissertation), and (g) externally imposed incentives (such as future employment). Conversely, Muszynski (1988) found that personality factors such as perfectionism and depression, as well as stressful life events, might hinder dissertation completion. Three particular aspects of the dissertation phase of doctoral work were studied by more than one researcher. These were selection of topic, time devoted to the dissertation, and the change that occurs in academic format. A number of researchers have found that early selection of the dissertation topic was important for successful degree completion (Delaney, 1981; Grissom, 1985; Mah, 1986; McCabe-Martinez, 1996). Some factors related to attrition in the dissertation phase of study are the number of times the dissertation topic changed (Delaney, 1981), difficulty reducing the topic and making it manageable in scope (Hugeley, 1988), lack of an appropriate, strong dissertation topic (Lenz, 1994), and poor topic choice or inaccessible subject (Muszynski, 1988). Conversely, variables related to successful degree completion included little difficulty with the selection of a topic (Howard, 1981), selection of a stimulating, strong, and exciting dissertation topic (Lenz, 1994), and selection of an interesting and manageable topic (Muszynski, 1988). Maximizing the time devoted to the development of the dissertation aids in completion (Delaney, 1981; Wagner, 1986). Not surprisingly, spending time with the demands of one’s job rather than on the dissertation was found to stand in the way of dissertation completion (Huguley, 1988). Mah (1986) described the changes that take place as a doctoral student moves from coursework and exams into the dissertation phase as a “cut-off from the previous structure of scheduled classes, from deadlines, and from opportunities for interaction with students and faculty” (p. 132). These changes, Mah found, hindered degree completion. The lack of structure in the dissertation stage was reported to be an obstacle to completion by 50 percent of ABDs in Huguley’s (1988) study. 503
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ACADEMIC ACHIEVEMENT INDICATORS ARE GENERALLY NOT EFFECTIVE PREDICTORS OF DOCTORAL DEGREE COMPLETION, WITH THE EXCEPTION OF GRE ADVANCED SCORES Many research studies have been done in an effort to understand what types of individuals make the most “successful” doctoral students. The predictive studies of the 1970s, followed by a smaller number of studies in the 1980s and 1990s, were often institutional research studies in which the focus was on differences between those who persisted and those who did not, largely through analysis of institutional records. Numerous independent variables have been examined, including Graduate Record Examination (GRE) scores, Miller Analogies Test (MAT) scores, grade point averages (GPA), and academic majors. Studies that have examined the relationship between GRE scores and doctoral student degree completion contradict each other, with the exception of GRE Advanced scores. GRE verbal scores were found to predict doctoral degree completion in only 3 out of 20 studies (Harris, 1976; Howard, 1981; Porozny, 1970); in the remaining 17 studies statistically significant relationships were not found. Along these same lines, only 11 studies out of 26 revealed GRE Quantitative scores to be predictors of completion (Burnham and Hewitt, 1972; Hackman, Wiggins, and Bass, 1970; Harris, 1976; Howard, 1981; Lemp, 1980; Mann, 1977; Nagi, 1974, 1975; Porozny, 1970; Traw, 1973; Williams, Harlow, and Gab, 1970; Willingham, 1974). In contrast, GRE Advanced test scores were shown to relate to successful degree completion in four out of six studies (Hirschberg and Itkin, 1978; Porozny, 1970; Traw, 1973; Williams, Harlow and Gab, 1970). MAT scores have not been found to be consistent predictors of successful degree completion. In 12 studies that examined the MAT as a correlate of persistence, statistical significance was found in only four (Harris, 1976; Hochberg, 1972; Krauskopf, 1973; Porozny, 1970). Undergraduate GPA was found to be related to doctoral student persistence in only 5 out of 23 studies (Bybee, 1972; Franklin, 1970; Harris, 1976; Hochberg, 1972; Porozny, 1970). Five of fifteen researchers found master’s GPA to relate positively to doctoral degree completion (Harris, 1976; Huang, 1995; Porozny, 1970; Williams, Harlow, and Gab, 1970). Doctoral GPA has been studied as well; of the 12 studies reviewed, only three identified doctoral GPA as a significant predictor of completion (Cook and Swanson, 1978; Pristo, 1977; Traw, 1973). 504
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In addition to the aforementioned variables, several other academic indicators have been studied by a few scholars. The results of these studies suggest that none of the following variables adequately predicts doctoral completion: baccalaureate origins (i.e., type of undergraduate institution, quality of undergraduate institution) (Boozer, 1972; Decker, 1972, 1973; Franklin, 1970; Pristo, 1977); holding the master’s prior to admission to the Ph.D. (Decker, 1972, 1973; Grissom, 1985; Pristo, 1977); length of time between bachelor’s degree and master’s degree (Destigter, 1983; Muhic, 1971), time elapsed between master’s degree and doctorate (Franklin, 1970; Pristo, 1977); length of time between bachelor’s degree and doctorate (Dolph, 1983; Pristo, 1977); master’s degree major (Franklin, 1970; Schultz, 1983); prior undergraduate major (Schultz, 1983); number of years taken to complete the master’s degree (Muhic, 1971); and junior/senior undergraduate GPA (Lunneborg and Lunneborg, 1973). On balance, the weight of the research evidence suggests convincingly that traditional academic indicators are not reliable predictors of persistence to the doctoral degree. This finding supports Dolph’s (1983) conclusion that “future studies on attrition should concentrate on more intrinsic and substantive matters and move away from investigations of demographic variables” (Dolph, 1983, p. 97). FINDINGS ARE MIXED WITH RESPECT TO EMPLOYMENT AND FINANCIAL FACTORS While a considerable number of doctoral students are funded by their universities or other sources, many continue to work full- or part-time during their doctoral programs. Across several studies, those who did not complete the doctoral degree cited responsibilities of full-time employment as an obstacle, impediment, or reason for dropping out (Grissom, 1985; Lenz, 1994; McCabe-Martinez, 1996; O’Bara, 1993; Reamer, 1990; Reeble, 1975; Sauer, 1986; Schultz, 1983; Swoboda, 1978; Whitacre, 1987). Job responsibilities emerged as the most significant factor affecting degree progress and completion in the interview portion of a mixed-design study by McCabe-Martinez (1996) of Hispanic public school personnel. The students who did not complete doctoral degrees in McCabe-Martinez’s study reported that their employment impeded their progress, while those who did complete reported that their employment was an enhancement to their progress. While this may seem contradictory, the major implication of the McCabe-Martinez study is that the responsibilities of employment can work either way: they can either enhance or impede progress toward the 505
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degree. This stands in contrast to Bowen and Rudenstine’s (1992) finding that students who must provide their own support had markedly higher attrition and TTD than those who received institutional funding in all five situations included in their study. Financial problems and pressures and insufficient finances were cited as situational barriers to completion in several studies ( Jones, 1987; Leadabrand, 1985; Lemley, 1976; Lenz, 1994; Lovitts, 1996; Murrell, 1987; Reeble, 1975; Whitacre, 1987). Although financial difficulties were present, they were not always found to be significant as actual impediments to persistence (Boozer, 1972; Campbell, 1992; Dolph, 1983; Girves and Wemmerus, 1988). PERSONAL AND PSYCHOLOGICAL VARIABLES REPRESENT A RELATIVELY NEW DIRECTION IN THE STUDY OF DOCTORAL STUDENT ATTRITION AND PERSISTENCE; A NUMBER OF THESE VARIABLES HAS BEEN SHOWN TO RELATE TO PERSISTENCE Particularly over the past decade, researchers have had a growing interest in looking within the individual to study psychological factors and characteristics of doctoral students and how these affect attrition and persistence (Weiss, 1987; Wentzel, 1987; Germeroth, 1991). Four personal or psychological characteristics — student motivation, goal directedness, self-concept, and well-being — have been the focus of recent inquiry, although several other less-studied characteristics have also been investigated. Doctoral student motivation was examined in almost one-fourth of the studies included in this meta-synthesis (Bauer, 1997; Butler, 1995; Clewell, 1987; Decker, 1972, 1973; Ferrer de Valero, 1996; Frasier, 1993; Grissom, 1985; Hassan-Shahriari, 1983; Hirschberg and Itkin, 1978; Hugeley, 1988; Lees, 1996; Lovitts, 1996; Macht, 1978; Mah, 1986; McCabe-Martinez, 1996; Nagi, 1974, 1975; Porozny, 1970; Schultz, 1983; Skudlarek, 1992; Swoboda, 1978). By and large, researchers found motivation to be strongly related to doctoral degree completion. For instance, lack of motivation was cited as being the single most important factor connected to attrition in Nagi’s study (1974), where both completers and non-completers indicated that “motivation or the lack of motivation was the dominant personal reason for either completion or non-completion of the doctoral program” (p. 61). Frasier’s study (1993) was the only one in which personal motivation was not found to be a significant factor. Her study was distinct, however, in that it involved only those graduates and non-graduates who had achieved ABD status. 506
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In Decker’s (1972) study, “motivation and commitment” were treated as one variable and found to be a major, if not dominant, element in persistence. Other researchers have found commitment to relate to persistence as well (Cooke, Sims, and Peyrefitte, 1995; Dorn, 1995; Dorn, Papalewis, and Brown, 1995; Lawson, 1985; Leadabrand, 1985; Reamer, 1990). Students who have a “never give up” attitude are more likely to complete the doctorate than others (Brien, 1992; Clewell, 1987; Mah, 1986; Reamer, 1990). As Reamer (1990) found: Although most persisters confessed to having wanted to leave their programs, they also overwhelmingly stated that it was their unwillingness to experience failure that kept them in school. This suggests a determination to succeed against all odds, which may be a personal quality that helps students to persist. One persister said he stayed in the program because “I really wanted that degree. I really like to face up to a challenge.” (p. 23)
The importance that students place on the doctoral degree for attainment of their career goals was among the most important predictors of persistence identified by Lemp (1980). Similarly, Brien (1992) found that the “belief in what the doctorate could do for one’s career aspirations” was important and that “if one believes the degree will in fact ‘open new doors’ or ‘give . . . credibility,’ then it was more likely that students would diligently continue in the doctoral program” (p. 104). Other studies in which career goals were found to be significantly related to doctoral persistence included those by Boozer (1972), Delaney (1981), Hassan-Shahriari (1983), Lovitts (1996), Mah (1986), Nerad and Cerny (1991), Swoboda (1978), and White (1986). The significance of student self-image or self-concept to doctoral student completion remains uncertain (Benkin, 1984; Bishop, 1981; HassanShariari, 1983; McCabe-Martinez, 1996; Presley, 1996; Reiff, 1992; Swoboda, 1978). Bishop (1981) and Presley (1996) found that students who have positive views of themselves may be more likely to successfully complete the doctorate, while students’ negative views of themselves may relate to withdrawal. Further, they found no significant differences between completers and noncompleters with respect to self-concept (Bishop, 1981; Presley, 1996). Studies reviewed differ considerably regarding issues of health and wellbeing. For instance, health problems and illness were given as reasons for student withdrawal by Lovitts (1996), while they were not found to be a significant variable in Grissom’s study (1985). Dolph (1983) did not find a significant difference between successful degree completers and non-completers with regard to emotional problems among educational 507
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administration majors, but Campbell (1992) did in his study of educational leadership majors. Surprisingly few studies dealt with stress, although in a survey research study employing logistic regression analysis, Frasier (1993) found “emotional stress due to fear of failure, stress or role conflict” to be one of five significant reasons for dropping out. Likewise, Wood (1978) found that doctoral recipients experienced fewer critical, stressful periods than did dropouts. Findings of the preceding studies indicate that there are potentially meaningful relationships between certain individual, personal characteristics, and doctoral student persistence. These and other personal variables are endogenous to individuals and, therefore, rest largely outside of the realm of influence of colleges and universities. Nonetheless, they represent an emerging area of research focused on doctoral students with relevance to learning, teaching, advising, and administration that is worthy of further study. DEMOGRAPHIC VARIABLES DO NOT CONCLUSIVELY DISTINGUISH PERSISTERS FROM THOSE WHO DROP OUT Demographic variables have been studied widely over the years, in that they have been fairly standard items included on surveys as demographic data. Because they occur so frequently in the research, the following are discussed here: age, children and family, full- or part-time enrollment status, gender, and race/ethnicity. A substantial body of evidence indicates that age is not a statistically significant variable in discriminating between those who earn the doctorate and those who do not (Bishop, 1981; Campbell, 1992; Delaney, 1981; Dolph, 1983; Ducette, 1990; Dunnerstick, 1990; Flores, 1984; Franklin, 1970; Frasier, 1993; Girves and Wemmerus, 1988; Mah, 1986; Muhic, 1971; Ott, Markewich, and Ochsner, 1984; Quinn, 1991; Vacc and Picot, 1984; Valentine, 1986, 1987). In several studies younger students were more likely to graduate (Cook and Swanson, 1978; Skudlarek, 1992; Wagner, 1986), while in a few others higher levels of degree completion were found among older students (Artiga, 1983; Destigter, 1983). The weight of the evidence in this study indicates that the number of children or dependents of doctoral students is not a significant predictor of persistence or attrition (Dolph, 1983; Flores, 1984; Franklin, 1970; Frasier, 1993; Macht, 1978; Muhic, 1971; Valentine, 1986, 1987). Similarly, in the majority of studies, marital status was not related significantly to either persistence or attrition (Dolph, 1983; Franklin, 1970; Frasier, 1993; Girves and 508
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Wemmerus, 1988; Valentine, 1986, 1987; Wagner, 1986). There were studies in which marriage was shown to be positively related to persistence (Harris, 1976; Lemp, 1980; Lunneborg and Lunneborg, 1973), but these were counterbalanced by other studies indicating that single individuals were more likely to complete the doctorate (Flores, 1984; Hagedorn, 1993; Schmersahl, 1974). Several studies in this sample examined full- versus part-time status and its relationship to doctoral attrition or persistence (Cook and Swanson, 1978; Dolph, 1983; Franklin, 1970; Presley, 1996; Quinn, 1991; Valentine, 1986, 1987). The findings of these studies were split; that is, roughly half of the studies indicated that full-time enrollment is positively related to doctoral student degree completion, while the other half revealed no significant difference between degree completion and full-time status. The majority of studies indicated that gender is not significantly related to doctoral degree completion (Bishop, 1981; Bowen and Rudenstine, 1992; Campbell, 1992; Cooper, 1996; Delaney, 1981; Destigter, 1983; Dolph, 1983; Ducette, 1990; Dunnerstick, 1990; Franklin, 1970; Frasier, 1993; Girves and Wemmerus, 1988; Grissom, 1985; Gunn and Sanford, 1988; Mah, 1986; Muhic, 1971; Ott, Markewich, and Ochsner, 1984; Quinn, 1991; Vacc and Picot, 1984; Wagner, 1986). Males were found to be more likely to graduate than females in some studies (Abedi and Benkin, 1987; Artiga, 1983; Boozer, 1972; California Postsecondary Education Commission, 1990; Cook and Swanson, 1978; Decker, 1973; Gillingham, Seneca, and Taussig, 1991; Hirshberg and Itkin, 1978; Lemley, 1976; Lemp, 1980; Lunneborg and Lunneborg, 1973; Naylor and Sanford, 1982; Schmersdahl, 1974; Zwick, 1991), while females were more likely to graduate than males in a small number of studies (Sauer, 1986; Williams, Harlow, and Gab, 1970). Completion rates also do not vary consistently based on race or ethnicity (Anderson and Hrabowski, 1977; Cooke, Sims, and Peyrefitte, 1995; Davis, 1981; Delaney, 1981; Dolph, 1983; Frasier, 1993; Girves and Wemmerus, 1988; Mah, 1986; Ott, Markewich, and Ochsner, 1984; Presley, 1996; Quinn, 1991; Vacc and Picot, 1984). In the studies examined here, only a few revealed a significant difference in completion rates among racial groups (Clewell, 1987; Matchett, 1988; Zwick, 1991).
RETENTION RATES VARY WIDELY AMONG INSTITUTIONS Just how serious of a problem is doctoral student attrition? In this sample, less than one-third of the studies reported some type of information 509
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about retention or attrition rates. In some instances, the information was a single, general retention or attrition rate (see Tables 11.5 and 11.6). In others, various ways of describing attrition and persistence were used; for example, a retention rate was given for only those students who had passed the qualifying exam (Quinn, 1991) or reached ABD status (Campbell, 1992; Cook and Swanson, 1978; Frasier, 1993; Grissom, 1985; Hobish, 1978, 1979). Retention rates were reported for stages of departure (Ferrer de Valero, 1996; Table 11.5: Doctoral Level Retention Statistics
Author
Program(s)
University(ies) Cohort Years
Abraham (1979)
All Programs
Research I
Benkin (1984)
58 Majors
Research I
Bowen and Rudenstine (1992) Cook and Swanson (1978) Decker (1973)
6 Fields
10 Research I
Ferrer de Valero (1996) Golde (1995)
57 programs
Research I
4 disciplines
Research I
Educational Research I Administration Economics Research I
Gunn and Sanford (1988)
North Carolina Research I Higher Ed. Data Base
Lunneborg and Lunneborg (1973) McCabeMartinez (1996) Murrell (1987)
Psychology
Research I
Education
Research I
6 Education Programs All doctorate
Research I
All doctorate
Research I
Naylor and Sanford (1982) Nerad and Cerny (1991)
Research I
510
1963–69, studied in 1979 1969–71, studied in 1984 1960s–80s, studied in 1990 1964–78, studied in 1978 1956–66, studied in 1971 1986–90, studied in 1995 1984–89, studied in 1995 1974, studied after 8 and 11 years, respectively 1963–67, studied after 4 years 1985, studied in 1995 1975–80, studied in 1986 1974, studied in 1980 1978–79, studied in 1989
Retention Rate % 61 68 58.8
57 32 45 62.27 53.8 68.0
29
68.6
59 59.4 58
Bair and Haworth: Doctoral Student Attrition and Persistence Table 11.6: Doctoral Level Attrition Statistics
Author
Programs Studied
Universities
Cohort Years
Benkin (1984)
58 majors
Research I
Dolph (1984)
Educational Administration Educational Administration Counseling Psychology
Doctoral I
1969–71 studied in 1984 1970–80
Ducette (1990) Jones (1987)
Doctoral I Doctoral I
1972–83 studied in 1990 1970–80 studied in 1986
Attrition Rate 32% 45% 61% 18%
Huang, 1995; McCabe-Martinez, 1996; Reamer, 1990), for males and females separately (Dolph, 1984; Golde and Petrides, 1996), and for races separately (Davis, 1981). As reflected in Table 11.5, a number of researchers have disaggregated data by field of study. In some studies, retention refers to actual doctoral student degree completion; in others, retention is defined to include not only those who completed their degrees, but also those still enrolled. In others, the retention rate is given, accompanied by a notation as to what percent of students are still enrolled. Yet other studies analyze retention rates after an elapsed period of time, permitting the classification of doctoral students into two groups — those who completed and those who did not. Retention statistics from studies in this sample are contained in Table 11.5. The collection points and inclusive cohort years differ widely, as do programs and universities included. Accordingly, this table presents the range of retention rates. The range of reported retention rates extends from a low of 29 percent to a high of 68.8 percent. In the study reporting the lowest retention rate (Lunneborg and Lunneborg, 1973), where the study was conducted at a single, Research I university, the cohort group members were psychology doctoral students who were given 4 years to complete the degree. The study reporting the highest completion rate (McCabe-Martinez, 1996) was of Hispanic public school personnel handpicked by their superintendents to study at a Research I university, analyzed 10 years after admission to the program. It is interesting to note that 21.6 percent were still in the program, 5.9 percent were at the dissertation stage, and only 3.9 percent had actually dropped out. These examples illustrate how widely the cohort samples and approaches for reporting retention statistics vary in the literature. Several researchers have used attrition 511
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rates rather than retention rates to report student persistence outcomes (see Table 11.6). ABD IS NOT THE STAGE WHERE THE GREATEST PROPORTION OF DOCTORAL STUDENTS NECESSARILY DEPARTS Doctoral students who are ABD are, perhaps, at the most visible stage from which to withdraw from doctoral study. However, ABD is not the stage at which the greatest proportion of doctoral students necessarily departs. Indeed, according to some researchers, as much as two-thirds of doctoral attrition occurs prior to the achievement of ABD status (Benkin, 1984; Bowen and Rudenstine, 1992; Cook and Swanson, 1978; Golde, 1995; Nerad and Cerny, 1993). Bowen and Rudenstine (1992) identified three stages of attrition: presecond year, after second year but pre-ABD, and ABD. In their research on 6 fields of study at 10 Research I universities, they found that 87.0 percent of doctoral students returned to start their second year, 69.9 percent achieved ABD status, and 56.6 percent completed the degree. Similarly, in their study of doctoral programs at a Research I university, Nerad and Cerny (1991) concluded, “Contrary to popular belief, the majority of the graduate students who failed to earn their doctorates left the program before advancement to the candidacy for the Ph.D., not after” (p. 2). In their study, 24 percent of students were found to have left doctoral study during the first 3 years,3 while another 10 percent left after advancement to candidacy, and 8 percent were still pending. While few researchers whose studies were included in this metasynthesis looked at stages of attrition, those that did found consistent results. It appears to be important to continue to examine the stages at which doctoral students withdraw, based on these research studies, in order to gain a complete perspective on doctoral student attrition and persistence. TIME-TO-DEGREE IS RELATED TO ATTRITION Recent studies have shown that the longer the time spent in graduate school, the greater the chance that students will not persist to the degree
3
Nerad and Cerny reported that of the 24 percent who left during the first 3 years, 83 percent had earned master’s degrees.
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(Bowen and Rudenstine, 1992; Ferrer de Valero, 1996; Frasier, 1993; Hirschberg and Itkin, 1978; Nerad and Cerny, 1991; Tuckman, Coyle, and Bae, 1989, 1990). This finding went uncontested in this research, despite the small number of studies that examined this particular variable. That said, this appears to be a strong finding because of the scope of the studies that support this conclusion. For example, Bowen and Rudenstine’s (1992) study examined 10 major universities and 6 fields of study, Ferrer de Valero’s (1996) is of 57 disciplines at a major university. There also appears to be a solid connection between completion rates when analyzed by field of study and the length of time that it takes to earn the degree (Bowen and Rudenstine, 1992; Ferrer de Valero, 1996; Nerad and Cerny, 1991; Sauer, 1986). In Bowen and Rudenstine’s (1992) study, completion rates and TTD varied “more systematically with field of study than any other variable” (p. 123). Bowen and Rudenstine further found that “natural science always has the highest completion rate, followed by social science, and then humanities, across data sets, across gender, across time, across funding” (1992, p. 124). While there is a very large body of research that exists on the subject of doctoral TTD, this meta-synthesis only looked at TTD as it related to attrition and persistence. DOCTORAL PROGRAMS THAT HAVE SMALLER ENTERING COHORTS HAVE CONSISTENTLY LOWER TTD AND CONSISTENTLY HIGHER COMPLETION RATES THAN PROGRAMS WITH LARGER ENTERING COHORTS Entering cohort size and its relationship to attrition and persistence is the last key finding of this meta-synthesis. This finding is included not because of its occurrence in multiple studies, but because of the endorsement it was given as an important consideration in Bowen and Rudenstine’s (1992) comprehensive study and because it is not a variable likely to occur in research where only small programs or only large programs are studied. In the 10 institutions and 6 programs they studied, Bowen and Rudenstine found that “graduate programs with relatively small entering cohorts” had “consistently higher completion rates and lower TTD than those with larger entering cohorts” (p. 11). This finding held across stages of attrition. According to Bowen and Rudenstine, this was “one of the most important findings” (p. 149) of their study. To be sure, although only one study has identified program size as a potentially important factor in doctoral student persistence, the scope of Bowen and Rudenstine’s research suggests that this may be a finding deserving of more study in the future. 513
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The 10 central findings that have emerged from this meta-synthesis highlight those factors that appear to “make a difference” in the retention of doctoral students as well as underscore the complexity that characterizes doctoral student attrition and persistence. An overarching finding of this meta-synthesis is that no single variable explains doctoral student attrition or persistence; rather, several variables are at play. Seeking to understand the interplay of these variables (and which ones may be more “central” to retention than others) is a challenging task. As Jacks, Chubin, Porter, and Connolly (1983) observed in their narrative study of doctoral attrition in 18 departments at 15 universities: In no case did an interviewee give only one reason for his or her failure to complete . . . often people began the interview by giving a single “stock” explanation, but as the interview progressed several issues emerged, and the first one mentioned was not necessarily the most significant. (p. 176)
Lovitts (1996, p. 142) has likewise underscored this point: “When students leave, it is usually not for a single reason, but often for a constellation of reasons.” The complexity inherent in understanding doctoral student persistence, therefore, raises several implications for policy, practice, and future research.
IMPLICATIONS FOR POLICY AND PRACTICE On the grounds that the findings of this meta-synthesis merit the attention of faculty, administrators, and policy-makers who work in and set policy for doctoral programs — as well as scholars who study doctoral education — we advance eight specific implications for policy and practice below. In addition, three broad recommendations for future research are offered. VARIATIONS IN PERSISTENCE RELATED TO FIELD OF STUDY The finding that persistence among doctoral students varies considerably across fields of study has important implications for educators, pointing to the need to understand how doctoral education may be viewed and enacted differently across various fields of study. For example, since the lowest rates of attrition are found in the laboratory sciences, what practices 514
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might faculty in other disciplines adapt or adopt from those in the laboratory sciences that could potentially enhance the retention of their doctoral students? Faculty and administrators in non-laboratory based-fields might wish to examine the supervision they provide to students, the nature of peer relationships present in their programs, the congruence and “fit” between their own and students’ research interests, and the extent and types of financial support students receive — practices, some have speculated (Berg and Ferber, 1983; Sauer, 1986), that contribute to higher retention rates among doctoral students in the laboratory sciences. Interestingly, the findings of this meta-synthesis suggest that the aforementioned practices are important cultural “variables” that promote student retention across fields. In turn, in-depth, qualitative case studies of doctoral programs are needed to understand more fully how various cultural practices within them, potentially unique to fields of study, affect doctoral student retention (this point is addressed later under “multi-institutional research”).
PROGRAM AND DEPARTMENT CULTURE When program or departmental faculty examine practices and policies that may have an impact on attrition and persistence, they are frequently studying aspects of program/department culture. Since this is an area over which faculty and administrators can exercise substantial control, it is likely that changes made within it will have a salutory influence on persistence. The findings of this meta-synthesis suggest that relationships between faculty and students, one key aspect of program/department culture, should be examined and strengthened as needed. The descriptors contained in Table 11.3 provide a template that faculty can use to examine and reflect on their relationships with doctoral students and dissertation advisees. In like manner, they can examine faculty–student relationships in their program, department, and school in light of these research findings. The importance of frequent, collegial, and supportive faculty–student interaction also has important implications for the advising and mentoring of doctoral students, as well as for socializing them to the profession (Baird, 1990). The research evidence suggests rather strongly that students are more likely to persist to graduation if they develop a meaningful relationship with a faculty member with whom they can discuss expectations and receive adequate guidance on a regular basis. As such, the importance 515
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of establishing formal advising structures that stress regular interaction between faculty and students becomes paramount. Findings from this meta-synthesis likewise underscore the importance of orientation sessions for new students, particularly if they involve panel presentations/discussions by faculty on their research and professional interests. Another clear implication of the research in this area is the need to provide students with clear information about evaluation criteria, various structures (e.g., academic and social involvement opportunities) that are in place to assist them, faculty views on advising and mentoring of students, and faculty expectations for student involvement and success. Given the key role that frequent faculty–student interaction plays in doctoral student retention, it is quite likely that merit and tenure review policies may need to be established or revised to reward faculty for their involvement in advising and mentoring students. Faculty workload policies may also need to be adjusted to ensure that students’ interests are protected (e.g., creating policy that limits the number of dissertations a faculty member may direct at any given point in time). For their part, the research suggests that students would do well to become active participants in their own education. When students understand the benefits that are likely to accrue to them as a result of their involvement in programmatic, departmental, institutional, and professional activities, they may begin to design their own structures to provide for such involvement as well as participate in those available to them. Doctoral student organizations and student-formed, ad hoc dissertation support groups can be helpful in promoting student interaction and in supporting students as scholars. Professional development programs sponsored by the program, department, or graduate school (such as speakers and seminars) can further bolster student involvement and interaction, as can opportunities for students to become involved with faculty in shared research projects. Financial support for student organizations and for student participation in and presentations at professional conferences are also likely to go a long way toward promoting student involvement in these activities. Student satisfaction is a key aspect of departmental culture as well, and the results of this study offer several implications for policy and practice. Perhaps the most important is the need to engage in ongoing program assessment, inviting student feedback on various aspects of the doctoral experience. Classroom assessment techniques (Angelo and Cross, 1994), exit interviews with graduating students, and alumni and current student surveys could be useful strategies for collecting student satisfaction data. 516
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Findings from this meta-synthesis suggest that student input should be sought on the quality of their courses and the doctoral program, adequacy of communication to students, fairness in departmental and program requirements, consistency in student evaluation, concern for students as professionals, and adequacy of academic guidance. Assessment in these areas would not only provide faculty and administrators with empirical understandings of students’ satisfaction with their programs, but it would also inform students about what faculty and administrators value and seek to improve or sustain. Peer interaction is another aspect of program/department culture over which programs may exercise considerable control, insofar as faculty and administrators can emphasize student-to-student interaction through classroom and out-of-classroom activities. Simply informing students that peer interaction has been found to enhance doctoral student retention may encourage them to seek its benefits, particularly when preparing for exams or coping with the ambiguity and stresses associated with completing the dissertation. Efforts to change policies and practices related to doctoral student funding are likely to be more difficult to implement. That said, findings from this meta-synthesis suggest rather strongly that faculty and administrators should examine this feature of their programs closely. Funding does appear to “make a difference” in the studies analyzed. Funded students were more likely to complete their doctoral degrees — and in a more timely fashion — than those who relied on their own financial resources. Moreover, certain forms of support (such as research assistantships in certain fields of study and teaching assistantships in others) appeared to yield the best results, perhaps suggesting the need to prioritize certain forms of funding in institutional financial aid policies. The dissertation phase presents additional opportunities for faculty and administrators to have a positive impact on persistence. The research indicates that faculty would do well to provide students with opportunities to explore and test potential dissertation topics early in their programs (perhaps through dissertation seminars or peer discussion groups). Several research studies have also emphasized the need for faculty to clarify and clearly communicate to students their expectations about “what constitutes a dissertation” and how they view their roles and responsibilities as dissertation advisors. Finally, findings from this study indicate that efforts to minimize isolation during the dissertation writing stage (such as through dissertation support groups) are likely to aid in doctoral student persistence. 517
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ACADEMIC ACHIEVEMENT INDICATORS Faculty frequently emphasize standard academic achievement indicators such as GPAs and standardized test scores as important criteria in doctoral student admission. However, the results of this research suggest rather convincingly that these indicators are seldom reliable predictors of persistence in doctoral education, with the exception of the GRE Advanced Scores. In addition, standardized test scores have been criticized for being biased against women and minorities (Hagedorn and Nora, 1996). Given this, administrators and faculty concerned about predicting doctoral student persistence might do well to examine in greater depth other variables and design alternative admissions criteria in light of them. Hagedorn and Nora (1996), for example, have suggested using “alternative predictors of cognitive and noncognitive skills” when evaluating prospective doctoral applicants. Such alternative predictors include “previous participation in activities, events and work” (p. 36) related to the discipline, evaluated through “writing samples, critique of a report or articles, interviews, presentations, completion of a report, plan for research, and peer-group discussion” (p. 38). Whether various admissions criteria act independently or interact with other variables to impact doctoral student persistence is another question warranting assessment by faculty and administrators. The use of alternative criteria for admitting doctoral students, including those that involve personal/psychological variables (such as planning skills, professional goals, motivation, and creativity) require further study to determine their effectiveness in predicting doctoral student completion. Given the results of this meta-synthesis, it would appear that new avenues also need to be explored in an effort to identify variables and approaches that meet with greater success than the indicators so widely in place at the current time. EMPLOYMENT AND FINANCIAL FACTORS Findings from this meta-synthesis indicate that financial factors, including part- or full-time employment outside of the university, may either impede or enhance the progress of doctoral students, depending upon each individual student’s situation. Accordingly, institutions would be well served to monitor this aspect of their programs. In doctoral programs in several professional fields of study, for instance, it is not uncommon for doctoral students to be employed full time while completing their 518
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doctorates, and their full-time employment status often enhances their academic experience, creating connections between theory and practice that are frequently robust (Haworth and Bair, 2000; McCabe-Martinez, 1996). To be sure, the converse may also hold sway, particularly in situations where financial or logistical problems become barriers to progress. A formal advising system that tracks students’ TTD and academic progress — and reviews these with students on a regular basis — is likely to provide faculty with several important insights, including the impact of full-time employment on academic progress and degree attainment. Faculty and administrators can also develop formal structures within their programs, such as alternative course delivery formats, that may be especially supportive of professionals who are pursuing their doctoral degrees on a part-time basis. DEMOGRAPHIC VARIABLES Although demographic variables have been studied widely, few have been found to have a significant effect on doctoral student persistence. The implication of this finding may simply be that practitioners and policy-makers should direct their attention to crafting practices and policies that emphasize other factors that the research evidence has shown enhance persistence. RETENTION RATES ACROSS INSTITUTIONS Findings from this study indicate that rates of attrition and persistence vary widely from institution to institution, and cohort samples and the approaches used to research and report retention and attrition statistics vary widely in the literature, as well. If practitioners and policymakers are serious about understanding and doing something about doctoral student persistence, an effort must be made to establish institutional and national databases that track attrition and degree completion. With national guidelines for data collection, institutions across the country could, for the first time, use similar approaches to gather information in standardized categories, promoting the development of retention “benchmarks” specific, perhaps, to different types of institutions and fields of study. (This recommendation for a nationwide database is further discussed later under “national research”.) 519
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STAGES OF ATTRITION AND PERSISTENCE Even though it may be the most visible, ABD is not the stage where the greatest proportion of doctoral students necessarily departs. The finding that as much as two-thirds of doctoral attrition occurs before this stage has clear implications for policy and practice. Programs, departments, schools/colleges, and institutions would be well advised to continue to examine and understand the first and second stages of attrition (pre-second year and after second year but pre-ABD) as well as the attrition that occurs during the ABD stage. Significant attention should be given to strengthening retention efforts during these early stages, as well as to those structures that support students early in their doctoral studies, since many are well within the realm of institutional influence. If faculty and administrators carefully attend to and monitor admissions criteria, orientation practices, their own and students’ expectations for doctoral study, the clarity and fairness of student evaluation criteria, and the nature and frequency of faculty–student and student–student interactions, it is likely that early student departure can be reduced. Each of these items revisits the topic of program culture and further points to the importance of creating cultures of success from the beginning of the doctoral program. To be sure, faculty and administrators must also pay close attention to student attrition at the dissertation stage, since approximately onethird of doctoral students discontinue their studies at that point. Faculty and administrators who develop mechanisms that assist students in topic selection, emphasize the importance of sequential planning, address motivation and how it may be sustained, and provide frequent faculty guidance and encourage peer support (such as dissertation support groups) are likely to minimize student departure at the ABD stage.
TIME-TO-DEGREE The longer a student spends in graduate school, the greater the chance that the student will drop out prior to completion. This finding has important implications for faculty and administrators, who may wish to design and implement policies and practices to shorten TTD. It also underscores the need for institutions to standardize the measurement of doctoral completion time in an attempt to understand its patterns and its impact and to bring about changes designed to stabilize or even decrease 520
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TTD (Tuckman, 1991). Among other things, research suggests that frequent student–faculty contact, adequate financial support, consistent scheduling of courses, clear expectations about the nature and goals of the doctoral dissertation, and regular peer interaction provide students with the structural and social support mechanisms necessary to complete their doctoral studies in a timely fashion.
IMPLICATIONS FOR FURTHER RESEARCH Despite the rather large number of research studies that have been conducted, the complexity inherent in doctoral student attrition and persistence offers several avenues for further study. Three broad categories of research are needed: institutional, multi-institutional, and national. INSTITUTIONAL RESEARCH A major implication that follows from this research is the need for institutions to monitor doctoral student persistence at the program, department, and institutional levels. Faculty, administrators, and institutional researchers need to take seriously the task of collecting doctoral attrition and retention information in order to acquire a longitudinal understanding of the patterns surrounding their own students. While some institutions, of course, have mechanisms for the routine collection and analysis of doctoral student attrition and retention information already in place, it is clear from this meta-synthesis that many do not. Institutional and programmatic self-assessment can best serve institutions in understanding and improving attrition and persistence when it is fashioned to involve mixed methodologies. By using quantitative and qualitative approaches, numerical data can be analyzed and tracked and the voices and viewpoints of students and other stakeholders can be heard and considered. The system in place at the University of California at Berkeley (Nerad and Cerny, 1991) serves as an excellent model for other institutions in this respect. Through a combination of statistical analyses of demographic student data, comparisons with at least one other Research I university engaged in similar institutional research on doctoral student attrition, interviews with current and former students, and surveys of doctoral graduates, administrators have been able to 521
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create a model for understanding and enhancing doctoral student retention at Berkeley4. Although mentioned previously, several promising areas for institutional and programmatic assessment merit additional attention here. Clearly, assessments focused on understanding and documenting dimensions of program/departmental culture are critical. Regular assessments of the effectiveness and impact of professional development opportunities for students, orientation programs, mentoring/advising systems, and departmental communication practices with students should be conducted. Faculty (as individuals and collectively) would do well to regularly examine their portion of the faculty/student relationship, from teaching through dissertation advisement. Financial aid policies and practices should also be examined, as should other departmental and institutional policies and practices that may relate to improved doctoral student retention. MULTI-INSTITUTIONAL RESEARCH Many of the studies reviewed for this meta-synthesis examined only one program or one department at a single institution. While useful, these studies do not provide an understanding of doctoral student persistence and attrition across fields of study at various types of institutions. In this respect, multi-institutional studies offer a promising direction for future research; those that employ qualitative and longitudinal designs are especially needed. Of the few multi-institutional studies that exist, most have relied upon survey research methods to study doctoral student attrition and persistence. As with any method, these broad-scale surveys have answered some questions and left others unanswered. For instance, while these studies have documented differences in retention rates and TTD across fields of study in different institutions, they have left unanswered the question of how various program, departmental, and institutional practices, policies, and conditions affect persistence. From this vantage point, qualitative investigations offer a promising avenue for future research. 4
In their comparative analysis, Nerad and Cerny (1991) examined and collected data on the mode in which doctoral student research takes place (apprenticeship, laboratory, no structure, etc.), whether a Master’s degree is required in the doctoral program, the structure of the program, the definition of dissertation, the level of advising and mentoring that takes place, factors related to department climate, availability of research money, types of financial support, campus facilities, and the job market (p. 4).
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Through in-depth, multi-site case studies, researchers are likely to uncover context-rich explanations regarding the importance of previously identified variables as well as surface new factors or combinations of factors that play a central role in attrition and retention. Indeed, studies of this sort have the potential to produce important understandings of how various “cultural” features of doctoral programs — and, potentially, fields of study — may shape and define students’ doctoral experiences in ways that contribute to or work against their eventual degree completion. Longitudinal studies are also needed that take into account stages of degree progress. Studies of this kind could be designed to determine the points at which attrition occurs for doctoral students across area and field of study. A benefit of longitudinal studies is that they operate apart from the ex post facto realm, which has heretofore been the predominant way in which doctoral student attrition and persistence have been studied. Ex post facto research has the major limitation of asking students to reflect back on their experiences after the passage of a period of time. It relies on memory, which may or may not be accurate at the time of the data collection. In contrast, longitudinal studies could examine students’ experiences along the path toward the doctoral degree, examining how those experiences relate to and influence degree completion, leaves of absence, or withdrawal from doctoral studies. Ideally, longitudinal studies should be conducted across institutions as well as programs of study in an effort to produce robust and generalizable findings. Studies conducted across institutions are needed in order to address certain gaps in the research. For example, most of the multi-institutional studies that have been done to date have examined doctoral education only at large, prestigious research universities. In terms of research across institutions, we know very little about programs in smaller institutions and programs at universities that are not classified as research universities. Another example has to do with entering doctoral student cohort size, which Bowen and Rudenstine (1993) highlighted as a key finding of their multi-institutional investigation of doctoral programs. Future multi-institutional studies should include this variable in their investigations in order to test further its impact on doctoral student retention. Multi-institutional quantitative studies are also needed that examine systematically the interactions among variables that contribute to attrition or to persistence. Research designed to understand not only which variables are most crucial, but also how these variables interact to either reduce or contribute to retention, is particularly important. Given the relative ease 523
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of contemporary data analysis, studies of this sort are a necessary and particularly desirable aspect of future research on attrition and persistence. NATIONAL RESEARCH While the aforementioned suggestions for future research are likely to go a long way toward addressing current gaps that exist in the literature, probably the most important recommendation that grows out of this metasynthesis is the need to establish a national database on doctoral student attrition and persistence. Ideally, this database would track and monitor all students who enter doctoral study, much like the database that the National Research Council (1997) currently maintains on those who graduate. While the creation and maintenance of such a database would be a major undertaking, it would likely generate an empirically robust understanding of the gravity and complexity of doctoral student attrition and persistence. The database would likewise produce consistent information across institutions, making comparisons possible. The possibilities for research would be limited only by the questions asked on the survey. The above recommendations for research are made in the spirit of linking research, theory, practice, and policy. As Tinto (1987/1993) observed, retention “must focus on the institution as well as on the student, and on the actions of the faculty and staff who are the representatives of the institution; . . . [retention] arises from and is demonstrated in the everyday interaction among students, faculty, and staff in the formal and informal domains of institutional life” (p. 201). This study supports that statement in large measure, but it also points to the need to understand further the complexity of factors that accompany the enduring question: “Why do so many doctoral students depart without completing the degree?”
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Bybee, J.R. (1972). Prediction in the College of Education Doctoral Program at the Ohio State University. Doctoral dissertation, The Ohio State University, 1972. Dissertation Abstracts International 33(08A). California Postsecondary Education Commission. (1990). Shortening time to the doctoral degree: A report to the legislature and the University of California in response to Senate Concurrent Resolution 66 (California Report No. 90–29). Sacramento, CA: California Postsecondary Education Commission. ERIC Document Reproduction Service No. ED 338198. Campbell, R.B. (1992). A study of the completion and non-completion of the Doctor of Education degree in Educational Leadership at the University of Delaware. Doctoral dissertation, University of Delaware, 1992. Dissertation Abstracts International 53(06A). Carlson, S.L. (1995). An examination of the external factors that influence midlife women’s behavior to persist in obtaining a graduate degree. Doctoral dissertation, The Ohio State University, 1995. Dissertation Abstracts International 56(09). Cartter, A.M. (1976). Ph.Ds and the Academic Labor Market. New York: McGraw-Hill. Clewell, B.C. (1987). Retention of Black and Hispanic doctoral students. GRE Board Research Report No. 83–4R. Princeton, NJ: Educational Testing Service. ERIC Document Reproduction Service No. ED 285466. Cook, M., and Swanson, A. (1978). The interaction of student and program variables for the purpose of developing a model for predicting graduation from graduate programs over a 10-year period. Research in Higher Education 8(1): 83–91. Cooke, D.K., Sims, R.L., and Peyrefitte, J. (1995). The relationship between graduate student attitudes and attrition. Journal of Psychology 129(6): 677–689. Cooper, B.C. (1996). Faculty characteristics associated with retention of doctoral students. Doctoral dissertation, Louisiana State University and Agricultural and Mechanical College, 1996. Dissertation Abstracts International 57(09A). Cooper, H.M. (1979). Statistically combining independent studies: A meta-analysis of sex differences in conformity research. Journal of Personality and Social Psychology 37: 131–146. Cooper, H.M., and Rosenthal, R. (1980). Statistical versus traditional procedures for summarizing research findings. Psychological Bulletin 87: 442–449. Daniels-Nelson, M.D. (1983). Doctoral candidates’ and graduates’ perceptions of advisoradvisee relationships in selected areas of education at The Ohio State University. Doctoral dissertation, The Ohio State University, 1983. Dissertation Abstracts International 44(09A). Davis, R.J. (1981). Selected factors influencing the selection, academic achievement, and career development of Black doctoral students and doctoral-degree recipients in industrial education. Doctoral dissertation, The Ohio State University, 1981. Dissertation Abstracts International 42(03A). Decker, R.L. (1972, March). Determinants of success in economic education. Western Economic Journal, Agora 10: 110. Decker, R.L. (1973). Success and attrition characteristics in graduate studies. Journal of Economic Education 4: 130–137. Delaney, F.H. (1981). Factors affecting attrition or successful degree completion among doctoral candidates at Boston College, 1972–1978. Doctoral dissertation, Boston College, 1981. Dissertation Abstracts International 42(11A). Destigter, L.L. (1983). A comparison of Ph.D. completers and non-completers in adult and continuing education at Michigan State University. Doctoral dissertation, Michigan State University, 1983. Dissertation Abstracts International 44(07A).
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Bair and Haworth: Doctoral Student Attrition and Persistence Dickinson, W.C. (1983). Factors relating to attrition from and completion of the doctoral program in educational administration from the University of Pittsburgh (Pennsylvania) (Ph.D. Dissertation, University of Pittsburgh, 1983). Dissertation Abstracts International 45(02A). Dolph, R.F. (1983). Factors relating to success or failure in obtaining the doctorate. Doctoral dissertation, Georgia State University, 1983. Dissertation Abstracts International 44(11A). Dorn, S.M. (1995). Doctoral student perceptions of cohesiveness and its effect on persistence. Doctoral dissertation, University of California, Davis, 1995. Dissertation Abstracts International 56(06A). Dorn, S.M., Papalewis, R., and Brown, R. (1995). Educators earning their doctorates: Perceptions. Education 116(2): 305–315. Ducette, M.O. (1990). Variables influencing doctoral student graduation: A path analytic test of Tinto’s process model. Doctoral dissertation, State University of New York at Buffalo, 1990. Dissertation Abstracts International 52(06A). Dunnerstick, R. (1990). Do admission criteria to the doctor of education in educational administration program predict completion? Doctoral dissertation, University of Akron, 1990. Dissertation Abstracts International 51(01A). Ehrenberg, R.G. (1992, June). The flow of new doctorates. Journal of Economic Literature 30: 830–875. Fechter, A.E., and Gaddy, C.D. (1998). Trends in doctoral education and employment. In J.C. Smart (ed.), Higher Education: Handbook of Theory and Research (Vol. XIII, pp. 353–377). New York: Agathon Press. Ferrer de Valero, Y.J. (1996). Departmental factors affecting time to degree and completion rates of doctoral students at one land-grant, research institution. Doctoral dissertation, Virginia Polytechnic Institute and State University, 1996. Dissertation Abstracts International 57(09A). Fiske, E. (1989, September 13). Shortages seen for faculties for the 1990s. New York Times, A–1. Flores, L.J. (1984). A study of successful completion and attrition among Chicana Title VII bilingual education doctoral fellows at selected southwestern universities. Doctoral dissertation, New Mexico State University, 1985. Dissertation Abstracts International 45(12A). Foote, M.L.S. (1988). Persisters’ and non-persisters’ perceptions of institutional integration at the doctoral level. Doctoral dissertation, University of Connecticut, 1988. Dissertation Abstracts International 49(08A). Franek, S.A. (1982). ABD to Ph.D.: Counseling interventions to facilitate dissertation completion. Doctoral dissertation, University of Nebraska, 1982. Dissertation Abstracts International 43(06B). Franklin, J.B. (1970). Attrition and success of doctoral students in the educational administration department of Arizona State University. Doctoral dissertation, Arizona State University, Tempe, 1970. Dissertation Abstracts International 31(08A). Frasier, E.R.M. (1993). Persistence of doctoral candidates in the college of education, University of Missouri-Columbia (Missouri). Doctoral dissertation, University of Missouri, Columbia, 1993. Dissertation Abstracts International 54(11A). Gell, S.K. (1995). Factors associated with completion or non-completion of doctoral dissertations: Self-direction and advisor/advisee congruity. Doctoral dissertation, University of Maryland, College Park, 1995. Dissertation Abstracts International 56(11A). Germeroth, D. (1991). Lonely days and lonely nights: Completing the doctoral dissertation. ACA Bulletin 76: 60–89.
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Gillingham, L., Seneca, J.J., and Taussig, M.K. (1991). The determinants of progress to the doctoral degree. Research in Higher Education 32(4): 449–467. Girves, J.E., and Wemmerus, V. (1988). Developing models of graduate student degree progress. Journal of Higher Education 59(2): 163–189. Glass, G.V. (1977). Integrating findings: The meta-analysis of research. Review of Research in Education 5: 351–379. Glass, G.V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher 5: 3–8. Golde, C.M. (1994, November). Student descriptions of the doctoral student attrition process. Paper presented at the annual meeting of the Association for the Study of Higher Education (ASHE). Tucson, AZ, ERIC Document Reproduction Service No. ED 375733. Golde, C.M. (1995, November). Early and late doctoral student attrition: Descriptions of the graduate education process. Paper presented at the annual meeting of the Association for the Study of Higher Education (ASHE). Orlando, FL. Golde, C.M. (1996). How departmental contextual factors shape doctoral student attrition. Doctoral dissertation, Stanford University, 1996. Dissertation Abstracts International. Golde, C.M., and Petrides, L.A. (1996). Thinking about quitting. Paper presented at the annual meeting of the Association for Higher Education (ASHE), Memphis, TN. Grissom, M.A. (1985). Attrition after successful completion of doctoral qualifying examinations: An analysis of characteristics and attitudes of doctoral graduates and nongraduates. Doctoral dissertation, University of North Texas, 1985. Dissertation Abstracts International 46(09A). Guba, E.G. (1978). Toward a Methodology of Naturalistic Inquiry in Educational Evaluation. University of California, Los Angeles: Center for the Study of Evaluation. Gunn, C.S., and Sanford, T.R. (1988, Summer). Doctoral student retention. College and University 63(4): 374–382. Hackman, J.R., Wiggins, N., and Bass, A. (1970). Prediction of long-term success in doctoral work in psychology. Educational and Psychological Measurement 30: 365–374. Hagedorn, L.S. (1993, November). Graduate retention: An investigation of factors relating to older female graduate students. Paper presented at the annual meeting of the Association for the Study of Higher Education (ASHE). ERIC Document Reproduction Service No. ED 365181. Hagedorn, L.S., and Nora, A. (1996, Winter). Rethinking admissions criteria in graduate and professional programs. In J.G. Haworth (ed.), Assessing Graduate and Professional Education: Current Realities, Future Prospects. New Directions for Institutional Research, No. 92. San Francisco: Jossey-Bass. Harris, C. (1976). Selection criteria and procedures for predicting the success of industrial education doctoral applicants. Doctoral dissertation, Michigan State University, 1976. Dissertation Abstracts International 37(06A). Hassan-Shahriari, F.Z. (1983). An analysis of factors relating to the attrition rate of doctoral students at the dissertation level at the school of education and human development of the George Washington University. Doctoral dissertation, George Washington University, 1983. Dissertation Abstracts International 44(04A). Haworth, J.G. (1996). Doctoral programs in American higher education. In J.C. Smart (ed.), Higher Education: Handbook of Theory and Research (Vol. XI, pp. 372–422). New York: Agathon Press. Heiss, A.M. (1970). Challenges to Graduate Schools: The Ph.D. Program in Ten Universities. San Francisco: Jossey-Bass.
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Bair and Haworth: Doctoral Student Attrition and Persistence Hirschberg, N., and Itkin, S. (1978). Graduate student success in psychology. American Psychologist 33: 1083–1093. Hobish, T.T. (1978). A study of selected psychological factors related to the completion or non-completion of the doctoral dissertation among male and female doctoral degree candidates. Doctoral dissertation, New York University, 1978. Dissertation Abstracts International 39(04B). Hobish, T.T. (1979). An abstract of a study of selected psychological factors related to completion or non-completion of the doctoral dissertation among male and female doctoral degree candidates. ERIC Document Reproduction Service No. ED 188552. Hochberg, C.K. (1972). Predictive effectiveness of the Miller Analogies Test and other variables for doctoral degree students in the School of Education at Fordham University. Doctoral dissertation, Fordham University, 1972. Dissertation Abstracts International 33(01A). Holden, C. (1995). Is it time to begin Ph.D. population control? Science 270: 123–128. Howard, R.K. (1981). A follow-up study of doctoral attrition in the College of Education. Doctoral dissertation, Florida State University, 1981. Dissertation Abstracts International 42(08A). Huang, L. (1995). Minority graduate educational persistence: A study of CIC Fellows. Doctoral dissertation, Purdue University, 1995. Dissertation Abstracts International 56(07A). Huberman, A.M., and Miles, M.B. (1994). Data management and analysis methods. In N.K. Denzin, and Y.S. Lincoln (eds.), Handbook of Qualitative Research (pp. 428–444). Thousand Oaks, CA: Sage. Huguley, S. (1988). An investigation of obstacles to completion of the dissertation and of doctoral student attitudes toward the dissertation experience. Doctoral dissertation, Pepperdine University, 1988. Dissertation Abstracts International 50(02A). Jacks, P., Chubin, D.E., Porter, A.L., and Connolly, T. (1983). The ABCs of ABDs: A study of incomplete doctorates. Improving College and University Teaching 31(2): 74–81. Jones, G.B., Jr. (1987). Eleven years of admissions to the Temple University Program in Counseling Psychology, 1970–1980: A study in degree completion. Doctoral dissertation, Temple University, 1987. Dissertation Abstracts International 48(02B). Karolyi, M.S. (1993). All but the dissertation: Perceptions of ABD level attrition among faculty, alumni, and ABDs in a graduate school of education at a large, public, Midwestern university. Doctoral dissertation, Kent State University, 1993. Dissertation Abstracts International 54(09A). Krauskopf, C. (1973). The shape of the MAT/PhD relation. Measurement and Evaluation in Guidance 5: 502. Lawson, L.G. (1985). Doctoral student attrition: A role theory approach. Doctoral dissertation, University of California, Santa Barbara, 1985. Dissertation Abstracts International 46(06): 1532A. Leadabrand, J.A. (1985). Doctoral candidate persistence in community and human resources: A replica of Pascarella and Terenzini’s studies based on Tinto’s concept. Doctoral dissertation, University of Nebraska, 1985. Dissertation Abstracts International 46(08A). Lees, K.A. (1996). Understanding how female doctoral student interactions with their chairpersons during the dissertation process affect doctoral persistence. Doctoral dissertation, University of Northern Colorado, 1996. Dissertation Abstracts International 58(02A). Lemley, N.C. (1976). A follow-up study of the inactive doctoral students in the Department of Educational Administration and Supervision at the University of Southern Mississippi. Dissertation Abstracts International 37(04A).
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Lemp, P.H. (1980). Determinants of persistence in graduate education: The doctoral student. Doctoral dissertation, Stanford University, 1980. Dissertation Abstracts International 41(05A). Lenz, K.S. (1994). A multiple case study examining factors affecting the completion of the doctoral dissertation by academically able women. Doctoral dissertation, University of Denver, 1994. Dissertation Abstracts International 55(12A). Lincoln, Y.S., and Guba, E.G. (1985). Naturalistic Inquiry. Beverly Hills, CA: Sage. Long, J.B. (1987). Factors related to attrition and success in degree and non-degree doctoral students in education. Doctoral dissertation, Northern Arizona University, 1987. Dissertation Abstracts International 48(10A). Lovitts, B.E. (1996). Leaving the ivory tower: A sociological analysis of the causes of departure from doctoral study. Doctoral dissertation, University of Maryland, College Park, 1996. Dissertation Abstracts International 57(12A). Lunneborg, C.E., and Lunneborg, P.W. (1973). Doctoral student attrition in psychology. Research in Higher Education 1: 379–387. Macht, M.W. (1978). Determinants of completion in doctoral education: An evaluation of a social work program. Doctoral dissertation, University of Wisconsin, 1978. Dissertation Abstracts International 39(06A). Mah, D.M. (1986). The process of doctoral candidate attrition: A study of the ABD phenomenon. Doctoral dissertation, University of Washington, 1986. Dissertation Abstracts International 47(12A). Malaney, G.D. (1988). Graduate education as an area of research in the field of higher education. In J.C. Smart (ed.), Higher Education: Handbook of Theory and Research (Vol. IV, pp. 397–454). New York: Agathon Press. Mann, C.M. (1977). Quantitative evaluation of applicants for graduate school. Journal of Geological Education 25: 118–119. Manzo, K.K. (1994). Flaws in fellowships: Institutional support essential to boosting number of African American doctoral students. Black Issues in Higher Education 11(10): 46–52. Mariano, C.M. (1993). A study of Ed.Ds, Ph.Ds, and ABDs in Educational Administration. Doctoral dissertation, Boston College, 1993. Dissertation Abstracts International 54(06A). Matchett, W. (1988). A study of attrition among graduate students at New Mexico State University. Las Cruces, NM. ERIC Document Reproduction Service No. ED 298811. McCabe-Martinez, M.C. (1996). A study of perceptions of factors that enhanced and impeded progress toward the completion of the doctoral degree in education for Hispanic students employed in the public school systems. Doctoral dissertation, Boston College, 1993. Dissertation Abstracts International 57(07A). Miles, M.B., and Huberman, A.M. (1984/1994). Qualitative Data Analysis: An Expanded Sourcebook (2nd edn.). Newbury Park, CA: Sage. Muhic, J.J. (1971). Prediction of success for doctoral degree in physical education. Doctoral dissertation, University of Utah, 1971. Dissertation Abstracts International 32(06A). Mullen, B., and Rosenthal, R. (1985). Basic Meta-Analysis: Procedures and Programs. Hillside, NJ: Lawrence Erlbaum. Murrell, J.P. (1987). A study of barriers perceived as having impact on degree attainment by doctoral students. Doctoral Dissertation, Texas A and M University, 1987. Dissertation Abstracts International 48(04A).
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Bair and Haworth: Doctoral Student Attrition and Persistence Muszynski, S.Y. (1988). The relationship between demographic/situational factors, cognitive/affective variables, and needs and time to completion of the doctoral program in psychology. Doctoral dissertation, Kent State University, 1988. Dissertation Abstracts International 50(03B). Nagi, J.L. (1974). Attrition factors in the Ed. D. program in Educational Administration at State University of New York at Albany. Doctoral dissertation, State University of New York at Albany, 1974. Dissertation Abstracts International 35(1465A). Nagi, J.L. (1975). Predictive validity of the GRE and MAT. Educational and Psychological Measurements 35: 471–472. National Research Council (1997). Summary Report 1996: Doctorate Recipients from United States Universities. Washington, D.C.: National Academy Press. Naylor, P.D., and Sanford, T.R. (1982). Intrainstitutional analysis of student retention across student levels. College and University 57(2): 143–159. Nerad, M., and Cerny, J. (1993). From facts to action: Expanding the graduate division’s educational role. In L. Baird (ed.), Increasing Graduate Student Retention and Degree Attainment. New Directions for Institutional Research (No. 80, pp. 27–40). San Francisco: JosseyBass. Nerad, M., and Cerny, J. (1991, May). From facts to action: Expanding the role of the graduate division. CGS Communicator. Noblit, G.W., and Hare, R.D. (1988). Meta-Ethnography: Synthesizing Qualitative Studies. Newbury Park, CA: Sage. O’Bara, C.C. (1993). Why some finish and why some don’t: Factors affecting Ph. D. degree completion. Doctoral dissertation, Claremont Graduate School, 1993. Dissertation Abstracts International 54(06A). O’Connell, E.C. (1991). An investigation of the relationship of psychological type to the completion of the Doctor of Philosophy Degree. Doctoral dissertation, Loyola University Chicago, 1991. Dissertation Abstracts International 52(02A). Ott, M.D., Markewich, T.S., and Ochsner, N.L. (1984). Logit analysis of graduate student retention. Research in Higher Education 21(4): 439–460. Patterson-Stewart, K.E. (1995). African American persistence through doctoral programs at predominantly white universities. Doctoral dissertation, University of Toledo, 1995. Dissertation Abstracts International 56(09A). Peacock, S.Y. (1996). The timely completion of the dissertation among graduates of five Ph.D. programs at Saint Louis University: The relationships among psychological type, life experiences, support group participation, and perceptions of advisor/advisee relationships. Dissertation Abstracts International 56(09A). Porozny, G.H.J. (1970). Relationship of selected intellectual and personal factors to completion of business education doctoral program. Doctoral dissertation, University of North Dakota, 1970. Dissertation Abstracts International 13(12A). Presley, C.L. (1996). Individual and institutional factors that affect the success of AfricanAmerican graduate and professional school students. Doctoral dissertation, University of Michigan, 1995. Dissertation Abstracts International 56(08A). Pristo, L.J. (1977). The prediction of doctoral program success for the adult education department at Arizona State University. Doctoral dissertation, Arizona State University, 1977. Dissertation Abstracts International 38(2006A).
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CONTENTS OF PREVIOUS VOLUMES
VOLUME I College Environmental Influences on Learning and Cognitive Development Ernest T. Pascarella, University of Chicago Learning Theory and Research Cameron Fincher, University of Georgia Methods and Theories of Instruction Michael T. McCord, University of Georgia The Concept of Strategy: From Business to Higher Education Ellen E. Chaffee, National Center for Higher Education Management Systems Administrative Computing in Higher Education Andrew T. Masland, Digital Equipment Corp. Legal Parameters of the Faculty Employment Relationship Barbara A. Lee, Rutgers University and Steven G. Olswang, University of Washington Publication, Performance, and Reward in Science and Scholarship Mary Frank Fox, University of Michigan Program Quality in Higher Education Clifton F. Conrad, University of Arizona, and Robert T. Blackburn, University of Michigan The Quest for Excellence: Underlying Policy Issues Anthony W. Morgan, University of Utah, and Brad L. Mitchell, Ohio State University Historical Research on Admissions and Access in Higher Education John R. Thelin, College of William and Mary Applications of Causal Models in Higher Education Lee M. Wolfle, Virginia Polytechnic Institute and State University Toward a New Partnership for Financing a College Education Michael L. Tierney, University of Pennsylvania International Students in Comparative Perspective Y.G.-M. Lulat and Philip G. Altbach, SUNY at Buffalo Author and Subject Indexes 1985: 528 pages ISBN 0-87586-065-6
VOLUME II Transformational Leadership in Colleges and Universities Kim S. Cameron and David O. Ulrich, University of Michigan
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Managing Decline in American Higher Education Raymond F. Zammuto, University of Colorado at Denver The Importance of Being General: Philosophy, Politics, and Institutional Mission Statements Gordon K. Davies, State Council of Higher Education for Virginia Postscript to “The Importance of Being General”: Rethinking Organizational Behavior and Public Policy John R. Thelin, College of William and Mary Affirmative-Action Employment Discrimination Monique W. Clague, University of Maryland Evaluation Research and Educational Decision-Making Jonathan Z. Shapiro, Louisiana State University Rates of Return to Higher Education: An Intensive Examination Larry L. Leslie, University of Arizona, and Paul T. Brinkman, National Center for Higher Education Management Systems Research on Academic Programs: An Inquiry into an Emerging Field Clifton F. Conrad, University of Arizona, and Anne M. Pratt, College of William and Mary Trends and Issues in Curricular Development Cameron Fincher, University of Georgia Social Control in the Academic Profession John M. Braxton, Loyola University of Chicago Theories of Student Departure Revisited Vincent Tinto, Syracuse University Emerging Perspectives on Continuing Professional Education Wayne D. Smutz, Mary Beth Crowe, and Carl A. Lindsay, Pennsylvania State University Author and Subject Indexes 1986: 462 pages ISBN: 0-87586-078-8
VOLUME III Qualitative Research Methods in Higher Education Robert L. Crowson, University of Illinois at Chicago Bricks and Mortar: Architecture and the Study of Higher Education John R. Thelin and James Yankovich, College of William and Mary Enrollment Demands and Their Policy Uses in Institutional Decision Making William C. Weiler, University of Minnesota State Regulation and Campus Autonomy J. Fredericks Volkvein, SUNY at Albany Administrative Leadership in Higher Education Cameron Fincher, University of Georgia Department Reviews for Product Improvement in Higher Education Everett K. Wilson, University of North Carolina at Chapel Hill Diversity in University Governance: Attitudes, Structure, and Satisfaction David A. Whetten and Kenneth Bettenhausen, University of Illinois The Influence of College on Moral Development Larry Nucci and Ernest T. Pascarella, University of Illinois at Chicago An Analysis of Student Academic Rights D. Parker Young and Martha C. Braswell, University of Georgia The Expansion of Higher Education Enrollments in Agrarian and Developing Areas of the Third World William Edgar Maxwell, University of Southern California The Organization and Provision of Continuing Professional Education: A Critical Review and Synthesis Ronald M. Cevero and William H. Young, Northern Illinois University Author and Subject Indexes 1987: 462 pages ISBN 0-87586-080-X
VOLUME IV The College Environment Revisited: A Review of Research and Theory Leonard L. Baird, University of Kentucky
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Contents of Previous Volumes Outcomes, Assessment, and Academic Improvement: In Search of Usable Knowledge Peter T. Ewell, National Center for Higher Education Management Systems Higher Education and Work in Europe Ulrich Teichler, Gesamthochschule Kassel, FRG, and Northwestern University Fiction to Fact: College Novels and the Study of Higher Education John R. Thelin, College of William and Mary, and Barbara K. Townsend, Loyola University of Chicago Economic Issues in Strategic Planning and Management in Higher Education James C. Hearn, University of Minnesota Faculty Vitality: Contexts, Concerns and Prospects Shirley M. Clark and Darrell R. Lewis, University of Minnesota Faculty Participation in Strategic Policy Making David D. Dill, University of North Carolina at Chapel Hill, and Karen Peterson Helm, North Carolina State University The Conceptual Foundations of Organizational Culture Kim S. Cameron and Deborah R. Ettington, University of Michigan Graduate Education as an Area of Research Gary D. Malaney, University of Massachusetts at Amherst Author and Subject Indexes 1988: 482 pages ISBN: 0-87586-086-9
VOLUME V Strategy and Effectiveness in Systems of Higher Education Ellen Earl Chaffee, North Dakota State Board of Higher Education Responsibility Without Authority: The Impossible Job of the College President Robert Birnbaum, National Center for Postsecondary Governance and Finance The Paradigm Revolution in the Academic Disciplines Yvonna S. Lincoln, Vanderbilt University Effects of Academic Labor Markets on Academic Careers Ted I. K. Youn, Boston College Faculty Evaluation and Faculty Development in Higher Education John A. Centra, Syracuse University Higher Education’s Odd Couple: Campus Archives and the Office of Institutional Research John R. Thelin, College of William and Mary and Marsha V. Krotseng, University of Hartford Student Financial Aid and Institutional Behavior Michael McPherson, Williams College, Alan P. Wagner, OECD (Paris), and Nancy Willie-Schiff, New York State Department of Education Understanding Student College Choice Don Hossler, Indiana University, and Jon Braxton and Georgia Coopersmith, Syracuse University Undergraduate Socialization John C. Weidman, University of Pittsburgh Log-Linear Applications in Higher Education Research Dennis Hinkle and Gerald McLaughlin, Virginia Polytechnic Institute and State University, and James T. Austin, University of Illinois (Champaign-Urbana) Environmental Analysis/Forecasting in Academic Planning James L. Morrison, UNC at Chapel Hill, and Thomas V. Mecca, Piedmont Technical College Author and Subject Indexes 1989: 421 pages ISBN 0-87586-093-1
VOLUME VI A Paradigm for Research on Higher Education William F. Massy, Stanford University Minority Student Access to, and Persistence and Performance in, College: A Review of the Trends and Research Literature Shirley Mow, Educational Testing Service and Michael Nettles, University of Tennessee
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Master’s Degree Programs in American Higher Education Clifton F. Conrad and David J. Eagan, University of Wisconsin-Madison Doctoral Study in the Field of Higher Education Barbara K. Townsend, Loyola University of Chicago The American College History: A Survey of its Historiographic Schools and Analytic Approaches from the Mid-Nineteenth Century to the Present Lester F. Goodchild, University of Denver, and Irene Pancner Huk, University of Chicago A Survey of Academic Advising as an Area of Inquiry Richard A. Voorhees, Black Hills State University Thanks for the Memories: The Fusion of Quantitative and Qualitative Research in the Study of the College Student and the College Experience Roger G. Baldwin and John R. Thelin, The College of William and Mary The Melancholy of Anatomy: The Personal and Professional Development of Graduate and Professional School Students Leonard L. Baird, University of Kentucky Putting Power into University Governance Cynthia Hardy, McGill University LISREL: An Introduction and Applications in Higher Education Research Frances K. Stage, Indiana University An Analysis of State Formula Budgeting in Higher Education Martin M. Ahumada, University of Arizona Author and Subject Indexes 1990: 536 pages ISBN: 0-87586-094-X
VOLUME VII Perceived Control in College Students: Implications for Instruction in Higher Education Raymond P. Perry, University of Manitoba The Changing Locus of Control Over Faculty Research: From Self-Regulation to Dispersed Influence Melissa S. Anderson and Karen Seashore Louis, University of Minnesota The Federal Role in American Graduate Education Patricia J. Gumport, Stanford Institute for Higher Education Research Effective Teaching Behaviors in the College Classroom Harry G. Murray, University of Western Ontario Differential Progress of Women Faculty: Status 1980–1990 Mary M. Dwyer, Arlene A. Flynn, and Patricia S. Inman, University of Illinois at Chicago Measuring, Understanding, and Doing Something About the Rise in Doctorate Completion Time Howard P. Tuckman, Memphis State University Faculty Mobility in an Organizational Context Dolores L. Burke, Duke University Instructional Interventions: A Review of the Literature on Efforts to Improve Instruction Maryellen Weimer and Lisa Firing Lenze, Penn State University Professional Education: Stratifying Curricula and Perpetuating Privilege in Higher Education Gary Rhoades, University of Arizona Leadership in Community Colleges: Looking Toward the Second Century Susan B. Twombly and Marilyn J. Amey, University of Kansas Religious Higher Education in America: An Historiographic Survey F. Michael Perko, Loyola University of Chicago Author and Subject Indexes 1991: 492 pages ISBN 0-87586-097-4
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VOLUME VIII Collegiality: Toward a Clarification of Meaning and Function James L. Bess, New York University Quality by Design: Toward a Framework for Quality Management in Higher Education David D. Dill, University of North Carolina at Chapel Hill Beyond “the State”: Interorganizational Relations and State Apparatuses in Post-Secondary Education Gary Rhoades, University of Arizona Students’ Evaluations of University Teaching: A Multidimensional Perspective Herbert W. Marsh, University of Western Sydney, Macarthur, and Michael J. Dunkin, University of Sydney, Australia Reputational Rankings of Colleges, Universities, and Individual Disciplines and Fields of Study, from Their Beginnings to the Present David S. Webster, Oklahoma State University Using Alternative Paradigms: Four Case Studies John H. Milam, Jr., West Virginia University Bibliometrics: A Method for the Study of the Literature of Higher Education John M. Budd, Louisiana State University A Critique of Intensive Courses and an Agenda for Research Patricia A. Scott and Clifton F. Conrad, University of Wisconsin at Madison Remediation in Higher Education Darrel A. Clowes, Virginia Polytechnic Institute and State University Author and Subject Indexes 1992: 532 pages ISBN 0-87586-099-0
VOLUME IX An Analysis of the Paradigmatic Evolution of U.S. Higher Education and Implications for the Year 2000 Hasan Simsek and Richard B. Heydinger, University of Minnesota A Motivational Analysis of Academic Life in College Martin V. Covington, University of California, Berkeley The Paradox of Growth in Federal Aid for College Students, 1965–1990 James C. Hearn, University of Georgia Scientist and Engineer Supply and Demand Larry R. Leslie and Ronald L. Oaxaca, University of Arizona Two-Year Colleges and Minority Students’ Aspirations: Help or Hindrance? Amaury Nora, University of Illinois at Chicago The Influence of College Residence Halls on Students Gregory S. Blimling, Appalachian State University Postmodernism and Critical Theory in Higher Education: Implications for Research and Practice William G. Tierney and Robert A. Rhoads, The Pennsylvania State University Qualitative and Quantitative Approaches to Academic Culture: Do They Tell Us the Same Thing? Marvin W. Peterson and Melinda G. Spencer, University of Michigan Higher Education in China: Challenges of Making Foreign Knowledge Serve China Wenhui Zhong and Ruth Hayhoe, Ontario Institute for Studies in Education College and University Budgeting: What Do We Know? What Do We Need to Know? William F. Lasher and Deborah L. Greene, University of Texas at Austin Author and Subject Indexes 1993: 508 pages ISBN: 0-87586-109-1
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX
VOLUME X Student Learning at Metropolitan Universities George D. Kuh, Nick Vesper, and Lee E. Krehbiel, Indiana University—Bloomington Applications of Generalizability Theory in Higher Education Assessment Research Gary R. Pike, University of Missouri—Columbia Policy Models and Policy Instruments in Higher Education: The Effects of Governmental PolicyMaking on the Innovative Behavior of Higher Education Institutions Frans A. van Vught, University of Twente, The Netherlands Reframing Policy Research: A Critical Examination of Research on Federal Student Aid Programs Edward P. St. John and Richard J. Elliott, University of New Orleans Educational Paradigms in the Professional Literature of the Community College John H. Frye, Triton College Logistic Regression Analysis in Higher Education: An Applied Perspective Alberto F. Cabrera, SUNY—Albany Integrating General Education, Wellness, and Athletics: A Conceptual, Historical, and Reform Agenda Lester F. Goodchild, Sheila M. Arredondo, and Robin B. Glaser, University of Denver The Matrix Representation System: Orientation, Research, Theory and Application Kenneth A. Kiewra, University of Nebraska—Lincoln New Faculty Socialization in the Academic Workplace Dana Dunn and Linda Rouse, The University of Texas, and Monica A. Seff, Bowling Green State University Author and Subject Indexes 1994: 454 pages ISBN 0-87586-111-3
VOLUME XI Variation Among Academic Disciplines: Analytical Frameworks and Research John M. Braxton, Vanderbilt University, and Lowell L. Hargens, The Ohio State University Public Policy and Public Trust: The Use and Misuse of Performance Indicators in Higher Education Brian P. Nedwek, St. Louis University Integrated Qualitative and Quantitative Research: Epistemology, History, and Designs John W. Creswell, University of Nebraska-Lincoln, Lester F. Goodchild, University of Denver, and Paul P. Turner, University of Nebraska-Lincoln Developments in State Funding for Higher Education Daniel T. Layzell, The University of Wisconsin System Gender and Academic Publishing Kathryn B. Ward, Southern Illinois University, and Linda Grant, University of Georgia The Dimensionality of Student Ratings of Instruction: What We Know and What We Do Not Philip C. Abrami, Sylvia d’Apollonia, and Steven Rosenfield, Concordia University Organizational Effectiveness and Quality: The Second Generation Kim S. Cameron and David Whetten, Brigham Young University Theory and Research in Administrative Leadership Cameron Fincher, University of Georgia Governments, Governance, and Canadian Universities Glen A. Jones, Ontario Institute for Studies in Education Doctoral Programs in American Higher Education Jennifer Grant Haworth, Loyola University Chicago Author and Subject Indexes 1996: 464 pages ISBN 0-87586-115-6
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VOLUME XII Technology Transfer from Universities Irwin Feller, Graduate School of Public Policy & Administration, The Pennsylvania State University State Policy and Private Higher Education William Zumeta, Graduate School of Public Affairs, University of Washington Appraising Tinto’s Theory of College Student Departure John M. Braxton and Anna V.S. Sullivan, Vanderbilt University, and Robert M. Johnson, Jr., Belmont College A Hierarchical Linear Modeling Approach to Studying College Effects Corinna A. Ethington, The University of Memphis The Cost Effectiveness of American Higher Education Jeffery E. Olson, College of Education, St. John’s University A Secondary Analysis of Claims Regarding the Reflective Judgment Interview Philip K. Wood, University of Missouri Student Learning and Cognitive Development in the Community College Richard A. Voorhees, Colorado Community College and Occupational Education System What Discourages Research-Practitioners in Faculty Development Bob Boice, State University of New York at Stony Brook McCarthyism and the Professoriate: A Historiographic Nightmare? Philo A. Hutcheson, Georgia State University Author and Subject Indexes 1997: 498 pages Paper: ISBN 0-87586-118-0 Cloth: ISBN 0-87586-119-9
VOLUME XIII Recollections and Reflections C. Robert Pace, UCLA Emeritus Reflections on the Study of Effective College Teaching and Student Ratings: One Continuing Quest and Two Unresolved Issues Kenneth Feldman, State University of New York at Stony Brook Differentiation and Diversity in Higher Education Studies Jeroen Huisman, University of Twente Reviewing and Rethinking Administrative Costs Gary Rhoades, University of Arizona State Efforts to Keep Public Colleges Affordable in the Face of Fiscal Stress Michael Mumper, Ohio University Discriminant Analysis in Higher Education Research Carl J. Huberty and Laureen L. Lowman, University of Georgia Faculty Demography: Exploring the Effects of Seniority Distributions in Universities James C. Hearn, University of Georgia, and Melissa S. Anderson, University of Minnesota Feminist Teaching in Higher Education Becky Ropers-Huilman, Louisiana State University Women and Minorities in Higher Education Larry R. Leslie and Ronald Oaxaca, University of Arizona Trends in Doctoral Education and Employment Alan E. Fechter and Catherine D. Gaddy, Commission on Professionals in Science and Technology Author and Subject Indexes 1998: 414 pages Paper: ISBN 0-87586-121-0 Cloth: ISBN 0-87586-122-9
VOLUME XIV Teaching, Learning, and Thinking About Teaching and Learning W. J. McKeachie, University of Michigan Costs and Productivity in Higher Education: Theory, Evidence and Policy Implications Darrell R. Lewis and Halil Dunbar, University of Minnesota
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX Institutional Adaptation: Demands for Management Reform and University Administration Patricia J. Gumport, Stanford University, and Barbara Sporn, Vienna University of Economics and Business Administration University Restructuring: The Role of Economic and Political Contexts Patricia J. Gumport and Brian Pusser, Stanford University Understanding Strategy: An Assessment of Theory and Practice Jennifer B. Presley, WestEd and David W. Leslie, College of William and Mary New Colleges for a New Century: Organizational Change and Development in Community Colleges Richard L. Alfred and Patricia Carter, University of Michigan Rasch Measurement in Higher Education Rita K. Bode, Rehabilitation Institute of Chicago and Benjamin Wright, University of Chicago Greek-letter Social Organizations in Higher Education: A Review of Research David H. Wilder and Hugh F. McKeegan, Bucknell University Cultural Capital as an Interpretive Framework for Faculty Life Jeffery P. Bieber, University of Kentucky Cruel Environments: Sexual Abuse and Harassment in the Academy Linda Serra Hagedorn, University of Southern California The Global Emergence of a Field: Content, Form, and Promise in Women’s Studies Nelly P. Stromquist, University of Southern California Author and Subject Indexes 1999: 510 pages Paper: ISBN 0-87586-125-3 Cloth: ISBN 0-87586-126-1
VOLUME XV Developing a Career in the Study of Higher Education Burton R. Clark, University of California, Los Angeles Economic Perspectives on Rising College Tuition: A Theoretical and Empirical Exploration Michael B. Paulsen, University of New Orleans The Governance of Higher Education Edward R. Hines, Illinois State University Approaches to Studying and Levels of Understanding: The Influences of Teaching and Assessment Noel Entwistle, University of Edinburgh Analytic Framework of Institutional Support for Student Assessment Marvin W. Peterson and Marne K. Einarson, University of Michigan Organizational Behavior in Higher Education and Student Outcomes Joseph B. Berger, University of Massachusetts Amherst, and Jeffrey E. Milem, University of Maryland Value Congruence and Organizational Climates for Undergraduate Persistence Marguerite Bonous-Hammarth, University of California, Los Angeles Field of Dreams: Organization Field Approaches to Understanding the Transformation of College Access, 1965–1995 Patricia M. McDonough, University of California, Los Angeles, Marc J. Ventresca, Northwestern University, and Charles Outcalt, University of California, Los Angeles Contesting Values in American Higher Education: The Playing Field of Intercollegiate Athletics J. Douglas Toma, University of Missouri-Kansas City, and Michael E. Cross, Princeton University Strategic Planning in a Transitory Higher Education Environment: Building on Historical Foundations and Industrial Parallels Anoush M. Pisani, University of Southern Mississippi, and Joseph W. Filkins, DePaul University Globalization Impacts on the Third World University Gustavo Fischman, Arizona State University, and Nelly P. Stromquist, University of Southern California Author and Subject Indexes 2000: 568 pages Paper: ISBN: 0-87586-127-x Cloth: ISBN: 0-87586-128-8
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VOLUME XVI Apologia Pro Vita Mia Robert Berdahl, University of Maryland, College Park Varieties of Validity: Quality in Qualitative Research Yvonna S. Lincoln, Texas A&M University Academic Freedom and Federal Courts in the 1990s: The Legitimation of the Conservative Entrepreneurial State Benjamin Baez, Georgia State University, and Sheila Slaughter, University of Arizona Quality Management, Power, and Values in European Higher Education John Brennan, Centre for Higher Education Research and Information, The Open University Bringing Political Theory to University Governance: A Comparative Analysis of Governing Boards at the Universidad Nacional Autónoma de México and the University of California Brian Pusser, University of Virginia, and Imanol Ordorika, Universidad Nacional Autónoma de México Understanding Equity and Access in Higher Education: The Potential Contribution of Pierre Bourdieu Erin McNamara Horvat, Temple University Low-inference Teaching Behaviors and College Teaching Effectiveness: Recent Developments and Controversies Harry G. Murray, University of Western Ontario Disincentives to Commitment to Teaching in Japan: Toward a Theory of Normative Discontinuity James L. Bess, Amherst, Massachusetts Intimate Partnerships and Publication Productivity Elizabeth G. Creamer, Virginia Tech Federal Financial Aid: How Well Does It Work? Sarah E. Turner, University of Virginia
VOLUME XVII An Unplanned Journey into Higher Education Joan S. Start, University of Michigan Student Motivation and Self-Regulated Learning in the College Classroom Paul R. Pintrich and Akane Zusho, University of Michigan College Students’ Degree Aspirations: A Theoretical Model and Literature Review with a Focus on African American and Latino Students Deborah Faye Carte, Indiana University Understanding and Using Efficiency and Equity Criteria in the Study of Higher Education Policy Stephen L. DesJardins, University of Iowa The Policy Shift in State Financial Aid Programs Donald E. Heller, Pennsylvania State University Back to the Basics: Regression as it Should be Corinna A. Ethington, University of Memphis, Scott L. Thomas, University of Georgia, Gary R. Pike, University of Missouri-Columbia The Evolving Role of the Community College: Policy Issues and Research Questions Kevin J. Dougherty, Columbia University Reexamining Doctoral Student Socialization and Professional Development: Moving Beyond the Congruence and Assimilation Orientation James Soto Antony, University of Washington Implementation Analysis in Higher Education Åse Gornitzka, Svein Kyvik, and Bjørn Stensaker, Norwegian Institute for Studies in Research and Higher Education (NIFU) Academic Careers for the 21st Century: More Options for New Faculty Judith M. Gappa, Purdue University Author and Subject Indexes 2002: 511 pages Paper: ISBN 0-87586-137-7 Cloth: ISBN 0-87586-136-9
VOLUME XVIII From Number Crunching to Spirituality Alexander W. Astin, University of California, Los Angeles State Governance Reform of Higher Education: Patterns, Trends, and Theories of the Public Policy Process Michael K. McLendon, Vanderbilt University
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HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH, VOL. XIX College Environments, Diversity, and Student Learning Sylvia Hurtado, Eric L. Dey, Patricia Y. Gurin, and Gerald Gurin, University of Michigan Identity Research in Higher Education: Commonalities, Differences, and Complementaries Kristen A. Renn, Patrick Dilley, and Matthew Prentice, Michigan State University and Southern Illinois University What can Labor Economics Tell us About the Earnings and Employment Prospects for Faculty? Robert K. Toutkoushian, University System of New Hampshire Studying Faculty Salary Equity: A Review of Theoretical and Methodological Approaches Laura W. Perna, University of Maryland Using Multilevel SEM to Study Leadership Effectiveness in Higher Education Vicki J. Rosser, University of Missouri-Columbia Event History Methods: Conceptual Issues and an application to Student Departure from College Stephen L. DesJardins, University of Michigan Globalization and Universities Jan Currie, Murdoch University Evaluating College and University Teaching: Reflections of a Practitioner William E. Cashin, Kansas State University Confronting the Burden of the Past: The Historical Antecedents of the Present Predicament of African Universities Y.G-M. Lulat, State University of New York at Buffalo An Institutional Perspective on Higher Education Policy: The Case of Academic Quality Assurance David D. Dill, University of North Carolina at Chapel Hill Author and Subject Indexes 2003: 742 pages Paper: 1-4020-1232-2 Cloth: 1-4020-1231-4
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INDEX
academic leaders 467 access 43–47, 54–56, 58, 60, 62, 67, 68, 70, 72, 74–78, 242, 244, 250, 263, 271, 273–276, 279, 280, 282–284, 287, 291, 292, 297, 298, 301, 302 accountability 135, 146, 156, 158, 159, 197, 207, 208, 211, 222, 223, 227, 230 African-American students 18 articulation 136, 144, 156, 159, 160, 169 assessing teaching 35 attrition 481–488, 491, 492, 494, 496, 498–503, 505, 506, 508–515, 517, 520–524 Australia 241, 243, 247, 251, 255, 262, 265, 266, 270, 273, 279–283, 291–293, 296, 299, 301 Balance Wheel 209, 210 Board of trustees 101, 116 budget cuts 201, 203, 223 budget process 196, 198, 227, 234 budgeting 197–202, 205, 211, 213, 215–232, 234, 235 and planning 199, 230 career influences 1 centralization/decentralization 144, 149–152, 165, 166, 168 China 311–369 clinical significance 176, 178, 189, 190 college environments 2, 7–9, 14–16, 20 college impact studies 22 college student 3, 8, 10, 14, 15, 27 withdrawal studies 5 community college governance systems 133, 134, 137, 140, 141, 143, 158, 159, 163, 165 completion 482, 483, 491–498, 499, 501–509, 511, 513, 518–520, 523 constituents 117 cost center budgeting 216, 223, 224, 230 costs vs. prices 204, 207 culture 85, 87, 114–118, 120, 121, 124 curriculum 442, 446, 448, 451, 459, 460, 470, 471
debt aversion 277, 301 decision-making 88, 91, 96, 98, 103, 106, 109, 114, 116, 117, 121, 122 defining issues test 376 degree 481, 483, 486, 491–493, 495–497, 499–509, 511–513, 517, 519, 520, 522–524 demographics 198, 211, 235 departure 496, 510, 520 determining faculty effectiveness 12, 29 discounting 205, 206 diversity 457, 460, 463, 465, 470–472 doctoral 481–484, 486–488, 490, 497, 499–524 doctorate 481, 483, 491, 494, 495, 505, 507–510, 512, 519 dropout 481, 494, 508 economics 48, 198 education funding 273, 278, 300 effect size 175, 176, 179–191 efficiency 253, 265, 273, 276, 300, 301, 319, 349, 352, 354, 358 equity 245, 260, 265, 267, 269, 271–173, 282, 300, 301 Europe 241, 243, 245, 248, 249, 257, 264, 300, 301 experimental studies 9 faculty development 11, 17, 36, 441–448, 450–455, 457–459, 462, 465–467, 469, 472 faculty renewal 454 faculty senate 86, 93, 95, 96, 98–100, 102 faculty vitality 443 faculty work 443, 444, 462, 463, 465, 469, 470 fee deregulation 242, 288, 294, 298 finance 54–56, 68, 75, 198, 209, 229 financial aid 45, 46, 53, 55, 56, 61–66, 68, 72, 75, 76, 78, 135, 136, 157, 158, 204, 205, 208, 211, 232, 234 flexibility 198 formula budgeting 216, 218, 226 fund raising 205, 213 future professoriate 443, 455, 458
545
INDEX GASB-35 200, 201 Germany 246, 249, 251, 255, 262, 265, 266, 273, 283, 284, 286, 287, 296 globalization 358 governance board composition 144, 147, 149 governance models 142 governance structure 85, 86, 91, 92, 96, 98, 104, 112, 114–116, 118, 124 governance taxonomies 135, 136, 165 graduate 482, 487, 496, 508 graduation 481, 499, 501, 515
New Zealand 241, 243, 251, 277, 280, 294–296, 299, 301, 302 null hypothesis 175–179, 191 opportunity 43–46, 65–56, 59, 62, 63, 68, 71–74, 77, 78 organizational culture 115 organizational development 445, 446, 449, 450, 471 organizational structure 89, 99, 111, 125
p values 176, 177, 179, 180 performance budgeting 216, 221–223, 226–230 performance funding 156, 158, 159 persistence 482–488, 491–495, 497, 500, 501, 504–510, 512–515, 517–524 policy 46, 54–56, 58, 61, 74, 75, 77 postsecondary public policy issues 159 practical significance 178, 189 price elasticity 267, 275, 278, 296 privatization 94 program budgeting 216, 219–221, 227
higher education 241–246, 248–254, 256–261, 263–268, 270–291, 293, 295–297, 300–303 as a discretionary budget item 208, 209 expansion 312, 322, 340 human capital 252, 253, 258–261, 263, 266–268, 270, 279, 300–302 theory 252, 260, 265, 275, 300 hypothesis testing 191 incentive budgeting 216, 222, 223, 227 incremental budgeting 216, 217, 219, 221, 225, 234, 235 inequality 358 innovation 95, 113, 114, 118, 123 institutional characteristics 198, 231 instructional development 444, 446, 448–450, 466
rate of return analysis 253, 255, 256 responsibility center budgeting 197, 216, 223–225, 230, 234 retention 482, 483, 491, 497, 502, 509–512, 514–517, 519–524
K-16 69, 70, 77 K-16 systems 156, 160 knowledge economy 313, 340 mass higher education 311–313, 330, 333, 334, 338–340, 344–347, 350, 351, 355, 356, 361, 368, 369 massification 311, 312, 314, 335, 339, 345, 346, 348, 350, 352, 356, 367, 368 mentors 5, 7 meta-synthesis 481, 483–487, 489–491, 495, 506, 509, 512–518, 521, 522 mid-year recisions 199 modes of governance 349 moral reasoning 375–379, 382–384, 386, 414, 416–429 Netherlands 241, 244, 246, 248–251, 255, 256, 262, 264–266, 273, 278, 286, 288–290, 296, 298
SAT research 22 scholarship of teaching 35–37, 443, 456, 462, 468, 469 shared governance 85–92, 94, 97, 100, 102, 104, 106–109, 112–120, 122, 125 frameworks 99 history 92 signaling 243, 252, 253, 263 state boards of education 137, 138, 145 state funding 151, 152, 156, 165 statewide governance systems 133, 135, 141, 156, 165, 169 statistical significance 175–180, 189 strategic planning 89, 102, 119 stratification 45, 46, 48, 56, 71–73, 77, 78 student contributions 279, 294, 296, 300 student evaluations 6, 12, 30, 33, 38 student learning 446, 448, 455, 467, 471 student support 242, 249, 254–257, 265, 267–269, 271, 274, 276, 278, 279, 284–287, 289–201, 298, 299, 301, 302
546
Index students 481–488, 490–524 success 482, 496, 516, 518, 520 taxonomy of educational objectives 38 teaching centers 451–453, 456–458, 472 teaching development 443, 455–458, 472 technology 109–112 tuition 202–207, 210, 224, 232 and fees 202–207, 210, 224, 232 fees 241–245, 248–251, 254, 255, 257, 264, 267, 270–276, 278–280, 283–291, 293, 297, 300–302 undergraduate education 456, 459, 461 undergraduate students 376, 388, 389, 392, 402–404, 408, 412–414, 417–419, 421, 425
United Kingdom 243, 248, 250, 251, 256, 261, 264, 266, 273, 278, 290, 291, 293, 296, 299, 302 universities 314–322, 324, 325, 327, 328, 330, 331, 333, 334, 337, 340–344, 346–354, 356–363, 365–368, 481, 482, 487, 492–494, 499–503, 510–513, 518, 521 vocationalism
340, 346
women PhDs 18 workforce preparation
163, 164
zero-base budgeting 216, 221, 227
547
AUTHOR INDEX
Pagenumbers in between […] means complete chapter by author Aaron B., 187, 192 Abbott R.D., 455, 477 Abdolmohammadi M.J., 392, 399, 400, 402, 428 Abedi J., 509, 525 Abedor A.J., 449, 474 Abel E., 483, 525 Abelson R.P., 175, 192 Abraham K.A., 510, 525 Acemoglu D., 272, 304 Adams M., 398, 428 Addleman J.A., 392, 407, 412, 434 Advisory Committee on Student Financial Assistance, 55, 79, 204, 236 Aitken N.D., 467, 478 Albrecht T., 284, 285, 304 Alexander K., 48, 79 Alfred R.L., 102, 127, 542 Algina J., 187, 194 Allmendinger D.F., 73, 79 Alsalam N., 49, 81, 548 Altbach P.G., ii, 171, 337, 360, 364, 365, 368, 370, 535 Amacher R., 96, 127 American Association of Higher Education, 6, 40, 127, 236, 461, 476, American Association of University Professors, 86, 127, 130 American College Testing Program, 407, 428 American Psychological Association, 180, 192 Anderson D, 388, 436 Anderson E.F., 509, 525 Anderson L.W., 38, 40 Andrews L., 282, 304 Angelo T.A., 516, 525 Antonio A.L., 69, 77, 84 Armstrong L., 111, 112, 127 Armstrong M.B., 391, 392, 398, 428 Arrow K.J., 252, 263, 304 Artiga A., 508, 509, 525 Ashworth J., 256, 304
Association of American Colleges and Universities, 375, 428, 445, 474 Association of Governing Boards of Universities and Colleges, 86, 88, 127, 152 Astin A.W., 2, 19, 20, 40, 389, 404, 427, 428, 543 Austin A.E., 443, 468, 469, 478 Bae Y., 513, 532 Baez B., 27, 543 Bagozzi R.P., 183, 192 Bailey J.J., 401, 435 Bailey S., 401, 436 Bair C.R., vi, [481–534], 519 Baird L.L., 9, 515, 525, 536, 538 Baldridge J.V., 86, 102, 103, 104, 105, 127 Ball S.J., 349, 370 Barnett R., 388, 393, 394, 395, 428 Barr N., 248, 260, 261, 269, 270, 271, 274, 291, 293, 298, 300, 304 Bartel A.P., 258, 304 Bass A., 504, 528 Bastid M., 316, 370 Bateman J.M., 217, 218, 220, 222, 225, 237 Batts V., 418, 433 Bauer W.C., 492, 493, 502, 506, 525 Baugh F., 176, 186, 188, 192 Baumstark K.E., 388, 391, 393, 395, 403, 430 Baxter Magolda M.B., 409, 428 Beach J.A., 93, 127 Bebeau M., 376, 378, 379, 382, 385, 386, 387, 428, 436 Beck H.P., 98, 127 Becker G.S., 47, 48, 50, 79, 252, 304 Behling R., 396, 437 Bell D., 313, 370 Benbow C.P., 393, 437 Bendixen L.D., 392, 406, 428 Benkin E., 492, 495, 496, 497, 500, 501, 507, 509, 510, 511, 512, 525
549
AUTHOR INDEX Bennett M.J., 417, 431 Bennett W.J., 55, 79, 445, 474 Berdahl R.O., 134, 171, 223, 236, 237, 543 Berelson B., 481, 482, 525 Berg H.M., 492, 494, 495, 496, 515, 525 Berger M., 49, 79 Bernard J.L., 392, 433 Berns S.B., 190, 193 Bernstein J., 49, 82 Berquist W.H., 17, 40, 443, 445, 454, 467, 474, 477 Bettenhausen K., 536 Beyer K.D., 468, 475 Biffl G., 256, 304 Biggs D., 388, 393, 395, 428 Biklen S., 28, 40 Billingslea R., 412, 429 Birnbaum R., 86, 102, 105, 106, 127, 537 Bishop A.E., 507, 508, 509, 525 Blackwell E.A., 101, 127 Blasi A., 418, 419, 428 Blöndal S., 255, 256, 261, 262, 264, 304 Bloom B.S., 25, 38, 40 Blumenstyk G., 239 Blundell R., 256, 263, 304 Bock T., 403, 404, 417, 420, 430 Bogdan R., 28, 40 Boice R., 454, 458, 474, 541 Bok D., 368, 370 Bok D.C., 405, 428 Boldt R.F., 24, 40 Bonawitz M.F., 388, 391, 392, 398, 428 Boozer J.S., 497, 499, 500, 501, 505, 506, 507, 509, 525 Borduin C.M., 388, 391, 393, 395, 403, 430 Borevskaya N., 356, 359, 370 Boring E.G., 175, 192 Borland J., 262, 304 Boss J.A., 392, 398, 401, 402, 428 Boswell K., 159, 161, 171 Bouhmama D., 388, 428 Bound J., 49, 79 Bowen H.R., 53, 79, 207, 236, 469, 474, 483, 525 Bowen W.G., 97, 127, 455, 474, 481, 482, 483, 492, 493, 494, 501, 502, 506, 509, 510, 512, 513, 523, 525 Bowman J.T., 417, 435 Boyer E., 405, 416, 428 Boyer E.L., 35, 40, 443, 456, 459, 462, 463, 464, 469, 474 Boyer E.T., 445, 474
Boyes M.C., 412, 438 Brabeck M., 392, 419, 428, 429 Bracco K.R., 130, 133, 135, 173 Bragg D.D., 160, 161, 164, 171, 173 Braskamp L.A., 12, 469, 474 Braun D., 349, 370 Brawer F., 133, 162, 171 Braxton J.M., 26, 70, 81, 536, 537, 540, 541 Bray M., 351, 356, 359, 365, 370 Brazziel W.F., 465, 474 Bredemeier B.J., 419, 429 Breneman D.W., 55, 58, 79, 202, 205, 206, 234, 236, 276, 304 Brewer D.J., 49, 51, 79, 80 Brien S.J., 497, 500, 507, 525 Brinkman P.T., 49, 50, 53, 77, 82, 218, 236, 275, 276, 277, 307, 536 Brinko K.T., 444, 447, 474, 477 Brint S., 73, 74, 79, 133, 171 Bronneman-Helmers H.M., 278, 304 Bronstein P., 460, 474 Brown C.M., 392, 433 Brown R., 507, 527 Brown W.C., 368, 370 Buier R.M., 388, 429 Bunting C.J., 400, 437 Burd S., 207, 236 Burgan M., 104, 127 Burke J.C., 227, 228, 229, 236 Burnham P., 504, 525 Burwell R.M., 388, 396, 410, 414, 429 Butler J.N. Jr., 495, 506, 525 Butman R.E., 388, 396, 410, 414, 429 Bybee J.R., 504, 526 Bylaws: James E. Beasley School of Law, 107, 127 California Postsecondary Education Commission, 509, 526 Callan P.M., 58, 75, 79, 130, 133, 135, 173, 204, 209, 210, 236 Callender C., 278, 304 Campaigne D.A., 276, 304 Campbell R.B., 495, 496, 506, 508, 509, 510, 526 Candee D., 379, 429 Cannon C., 388, 391, 394, 429 Cannon L.W., 465, 474 Canton E., 256, 262, 271, 272, 274, 275, 278, 279, 283, 305, 308, 394, 430 Carey J.K., 399, 429 Carkhuff R.R., 417, 429
550
AUTHOR INDEX Carlson S.L., 495, 526 Carroll C.D., 204, 236 Carroll J., 25 Cartter A.M., 483, 526 Cartwright C.C., 396, 419, 429, 431 Caruthers J.K., 218, 220, 224, 236 Carver R., 179, 192 Cashwell C.S., 408, 414, 439 Center for Community College Policy, 146, 148, 149, 151, 157, 159, 160, 164, 171 Center for Public Higher Education Trusteeship and Governance, 145, 146, 147, 148, 171 Centra J.A., v, vii, [1–42], 40, 454, 467, 474, 537 Cerny J., 481, 482, 492, 493, 497, 507, 510, 512, 513, 521, 522, 531 Cerny P.G., 349, 370 Chait R.P., 97, 99, 128, 130, 463, 479 Chapman B., 252, 255, 257, 258, 273, 280, 282, 283, 298, 305 Chen X.-X., 315, 370 Cheng X., 335, 372 Chevalier A., 302, 305 Chickering A., 409, 429 China Education Daily (2000), 333, 343, 344, 354, 370, 371 China Education Daily (2001), 312, 313, 356, 357, 359, 361, 370 China Education Daily (2002), 359, 371 Chism N.V.N., 443, 448, 457, 458, 474, 475 Christensen C.M., 106, 109, 128 Christiansen F., 361, 371 Chubin D.E., 492, 494, 496, 502, 514, 529 Cistone P.J., 101, 127 Clark B.R., 9, 114, 118, 128, 469, 475, 542 Clark S.M., 444, 475, 537 Clewell B.C., 495, 499, 506, 507, 509, 526 Clinedinst M.E., 204, 236 Clouse B., 388, 392, 394, 407, 414, 429 Coder R., 388, 436 Cohen A., 133, 162, 171 Cohen E.R., 388, 392, 402, 429 Cohen J., 177, 178, 179, 181, 183, 186, 187, 188, 189, 190, 192 Cohen P.A., 11, 12, 41 Cohen R., 392, 433 Colby A., 378, 379, 429 Coleman J.S., 71, 79 Collis D., 112, 128 Conaty J., 49, 81 Conklin K.D., 212, 236
Conlon G., 302, 305 Connolly T., 492, 494, 496, 502, 514, 529 Connor H., 277, 278, 305 Cook M., 501, 504, 508, 509, 510, 512, 526 Cook P.J., 106, 128 Cooke D.K., 499, 500, 507, 509, 526 Cooley S.L., 417, 435 Cooper B.C., 495, 502, 509, 526 Cooper D., 388, 436 Cooper H.M., 484, 526 Cooper M., 392, 439 Coopersmith G., 70, 81, 537 Corson J., 94, 128 Cortina J.M., 175, 192 Costa P.T. Jr., 394, 429 Courant P.N., 231, 232, 236 Courtney R.G., 24, 40 Coyle S., 513, 532 CPB and CHEPS, 267, 279, 303, 305 Cresswell J.W., 468, 475 Crocker J., 411, 433 Cross K.P., 9, 31, 41, 516, 525 Cross W.T., 460, 475 Crouse J., 59, 84 Crow M.L., 445, 475 Crumbaugh J.C., 415, 429 Cumming G., 190, 191, 192 Cummings R., 388, 391, 392, 396, 419, 429 Cunningham A.F., 204, 236 Cunningham H., 447, 478 Curry J., 224, 225, 239 Curtis J., 412, 429 Cytrynbaum S., 445, 475 Dale R., 362, 373 Daniels-Nelson M.D., 495, 502, 526 Davis G., 145, 146, 147, 148, 163, 165, 171 Davis K., 47, 79 Davis R.J., 509, 511, 526 Davis W.E., 455, 475 Davison M.L., 386, 388, 391, 406, 410, 432, 436, 438 Day V.E., 399, 400, 434 de Jong F., 278, 279, 305 de los Santos G., 141, 142, 143, 144, 145, 159, 173 Dearden L., 304 Decker R.L., 492, 505, 506, 507, 509, 510, 526 Deemer D., 399, 436 Dejoie R.M., 388, 391, 396, 434 Delaney F.H., 495, 496, 502, 503, 507, 508, 509, 526
551
AUTHOR INDEX Deng X.-P., 319, 330, 371 Denison E.F., 48, 80 Department for Education and Skills, 290, 305 Derry S.J., 409, 430 Derryberry W.P., 387, 403, 421, 430 Des Jarlais C.D., 460, 476 Destigter L.L., 499, 505, 508, 509, 526 DeWolfe T.E., 400, 430 Dewson S., 277, 278, 305 Dey E.L., ii, 425, 431, 544 Diamond R.M., 26, 28, 41, 443, 445, 446, 448, 449, 450, 451, 455, 469, 475, 476 Dickinson W.C., 495, 496, 527 Diener T., 143, 171 Dill D.D., ii, 86, 95, 96, 128, 537, 539, 544 Dimmock C.A.J., 362, 372 Dixon J.W., 410, 430 Dollinger S.J., 394, 407, 430 Dolph R.F., 495, 496, 500, 501, 505, 506, 507, 508, 509, 511, 527 Donlon T.R., 23, 41 Dorn S.M., 507, 527 Dosser D.A., 180, 194 Doti J.L., 205, 236 Dougherty K.J., 49, 80, 169, 171, 543 Draper R.D., 406, 438 Drummond M.E., 101, 128 Du Z.-R., 312, 371 Ducette M.O., 495, 496, 497, 499, 500, 501, 508, 509, 511, 527 Duckett L., 419, 430 Duderstadt J.J., 102, 109, 128 Duffy E.A., 276, 305 Duffy J., 399, 431 Duiker W., 346, 371 Dunkle M.E., 391, 392, 406, 428 Dunlap W.P., 175, 192 Dunn J., 215, 236 Dunnerstick R., 508, 509, 527 Duryea E.D., 98, 128 Dyas L., 388, 429 Dykes A.R., 102, 128 Ebbers L., 133, 173 Eberhart N., 161, 173 Eble K.E., 444, 470, 475 Eckel P.D., 102, 121, 128, 129 Education Commission of the States, viii, 69, 80, 134, 135, 136, 139, 151, 159, 160, 164, 171 Education Trust, The (2001), 69, 80
Educational Testing Service College and University Programs, 407, 430 Egly N.J., 468, 475 Ehrenberg R.G., 49, 51, 79, 80, 483, 527 Ehrmann S.C., 461, 475 Eide E., 49, 80 Eisemon T., 347, 371 El-Khawas E., 312, 345, 355, 371 Ellwood D., 44, 80 Elmer N.P., 392, 394, 430, 435 Elmore P., 181, 192 Endicott L., 403, 404, 417, 420, 430 Erickson B.L., 447, 448, 475 Erickson G., 454, 475 Erickson G.R., 447, 448, 475 Erikson E.H., 409, 410, 430 Ervin G., 455, 475 Erwin T.D., 402, 404, 432 Ethington C.A., ii, 541, 543 Evans J., 394, 428 Evens J., 386, 430 Evertson C.M., 446, 475 Ewell P.T., 86, 128, 537 Eyler J., 398, 418, 420, 430 Ezekiel M., 184, 192 Fairbank, J.K., 316, 373 Fane G., 258, 306 Faucett J.M., 394, 430 Fechter A.E., 483, 527, 541 Feldman K., 12, 19, 41, 474, 541 Felsö F., 278, 306 Felton G.M., 388, 394, 412, 430 Ferber M.A., 492, 494, 495, 496, 515, 525 Ferrer de Valero Y.J., 492, 494, 495, 496, 497, 500, 506, 510, 513, 527 Ferron J.M., 187, 192 Fidler F., 182, 188, 191, 192 Field S., 255, 262, 304 Finch S., 190, 191, 192 Finger W.W., 388, 391, 393, 395, 403, 430 Finn C.E., 54, 80 Finney J.E., 55, 58, 79, 130, 133, 135, 173, 210 Fisher D.G., 394, 430 Fleishman A.I., 190, 192 Flores L.J., 495, 496, 508, 509, 527 Folger, J., 223, 237 Foote M.L.S., 496, 499, 500, 527 Fornell C., 183, 192 Foster J.D., 388, 394, 410, 431 Fouladi R.T., 190, 194 Fountain B.E., 143, 173
552
AUTHOR INDEX Fox M.A., 39, 41, 49, 80 Franek S.A., 502, 527 Frank R.H., 106, 112, 128 Frankiewicz R., 394, 435 Franklin J.B., 12, 501, 504, 505, 508, 509, 527 Frasier E.R.M., 500, 506, 508, 509, 510, 513, 527 Freeman R.B., 48, 49, 80 Fretwell E.K., 86, 102, 129 Friedan B., 6, 41 Friedman H., 187, 193 Froelich D.R., 413, 431 Froh P., 28, 41 Froh R.C., 457, 475, 476 Frost L.W., 413, 431 Fry R., 212, 237 Frye J.H., 540 Gaa J., 394, 435 Gab D., 504, 509, 533 Gabbin A.L., 392, 396, 437 Gabhart D.R.L., 392, 396, 428, 435 Gaddy C.D., 483, 527, 541 Gade M., 134, 172 Gaff J.G., 444, 445, 450, 451, 452, 459, 467, 469, 476 Gaither G.H., 460, 465, 476 Gaito J., 175, 194 Galotti K.M., 388, 392, 414, 431 Gao Q., 316, 371 Garmon L.C., 419, 432 Garrett R.L., 140, 149, 150, 151, 156, 168, 171 Gell S.K., 496, 502, 527 Gemmell N., 261, 306 Gerald D.E., 212, 237 Germeroth D., 506, 527 Getz I., 394, 434 Gewirtz J.L., 377, 381, 433 Gfellner B.M., 388, 391, 392, 393, 410, 431 Gibbons M., 313, 334, 345, 346, 371 Gibbs J., 379, 429 Giddens A., 50, 80 Gielen U., 379, 431 Gigerenzer G., 191, 194 Giles D.E., 398, 430 Gillespie K., 443, 444, 476 Gilligan C., 392, 431 Gillingham L., 509, 528 Gilmour J.E., 98, 101, 128 Girouard, N., 255, 262, 304 Girves J.E., 496, 497, 499, 501, 502, 506, 508, 509, 528
Gladieux L.E., 72, 80, 275, 306 Glantz S.A., 191, 193 Glaser E., 408, 438 Glass G.V., 183, 189, 193, 484, 528 Glazer A., 388, 435 Glennerster H., 261, 306 Glover R.J., 388, 392, 394, 418, 420, 431 Goldberg I., 276, 305 Golde C.M., 492, 494, 496, 497, 499, 510, 511, 512, 528 Goldin C., 272, 306 Gongre W.M., 388, 391, 392, 393, 394, 395, 431 Good J.L., 396, 431 Goodchild L.F., 133, 172, 538, 540 Gordon L.D., 73, 80 Gorman M., 399, 402, 431 Gough, J., 373 Graf D.L., 451, 476 Grant G., 123, 128 Gray L., 28, 41 Gray P., 455, 475 Gray P.J., 457, 467, 475, 476 Gray W.M., 408, 431 Green L., 393, 411, 431 Greene D.L., 197, 216, 225, 237, 539 Gregg M., 177, 193 Griffith R., 102, 128 Grissom M.A., 496, 500, 502, 503, 505, 506, 507, 509, 510, 528 Grogger J., 49, 80 Groot W., 253, 306 Grossman A., 113, 129 Grubb W.N., 49, 80 Guangming Daily, 342, 371 Guarino A.J., 413, 431 Guba E.G., 484, 485, 486, 489, 528, 530 Guliani B., 6, 41 Gunn C.S., 509, 510, 528 Gurin G., 544 Gurin P., 425, 431, 544 Guthrie K.H., 392, 412, 431 Hackerman, 39, 41 Hackman J.R., 504, 528 Hagedorn L.S., 56, 83, 84, 496, 500, 509, 518, 528, 542 Hakel M.D., 466, 476 Halpern, D.F., 466, 476 Hamilton N., 85, 89, 90, 104, 128, 129 Hammer M.R., 417, 431 Hanney S., 349, 371
553
AUTHOR INDEX Hansen W.L., 55, 76, 80 Hanushek E.A., 259, 306 Hardee B.B., 418, 433 Hardy C., 90, 92, 103, 105, 106, 114, 129, 538 Hare R.D., 485, 486, 488, 489, 531 Harlow S., 504, 509, 533 Harris C., 499, 504, 509, 528 Harris M.J., 175, 193 Hartnett R.T., 9, 16, 21, 22, 41, 42 Hartog J., 253, 256, 306 Hass R.G., 418, 432 Hassan-Shahriari F.Z., 496, 502, 506, 507, 528 Hauptman A.M., 58, 64, 80, 275, 306 Hauser R.M., 47, 49, 50, 83 Haveman R.H., 253, 254, 260, 306, 309 Havemann E., 47, 80 Haworth J.G., vi, [481–534], 481, 519, 528, 540 Hay J., 388, 392, 394, 419, 431 Hayhoe R., 314, 315, 317, 319, 371, 539 Haymes M., 411, 431 He D.-C., 323, 325, 326, 353, 371 Healy M., 445, 454, 455, 476 Healy, 103 Hearn J.C., 45, 63, 71, 74, 80, 81, 537, 539, 541 Heaton C., 76, 81 Heffernan M., 399, 431 Heiss A.M., 496, 528 Heller D.E., 55, 57, 58, 60, 62, 65, 66, 81, 275, 276, 306, 543 Helm K.P., 86, 95, 96, 128, 537 Hendel D.D., 393, 407, 431 Henkel M., 349, 371 Henson R.K., 186, 194 Herzberg P.A., 186, 193 Hess B., 187, 193 Hewer A., 379, 429 Hewitt B., 504, 525 Hewlett M.G., 392, 412, 437 Higgerson M., 469, 478 Higher Education Act, 45, 54, 63, 64, 207, 375, 432 Hill C.R., v, [175–196] Hines C.V., 184, 193 Hines E.R., 147, 148, 172, 542 Hirsch W.Z., 125, 129 Hirschberg N., 504, 506, 513, 529 Hobish T.T., 502, 510, 529 Hochberg C.K., 504, 529 Hodgins H.S., 175, 195 Hodgkinson H.L., 445, 476
Hofer B.K., 405, 432 Hogue N., 460, 465, 477 Holden C., 483, 529 Holland B., 223, 236, 237 Holland T.P., 97, 128, 130 Holley F.M., 446, 475 Holley R.T., 394, 432 Hollinger D.A., 99, 102, 129 Holmes S.E., 187, 193 Holm-Nielsen L., 347, 371 Honey J.C., 26, 41 Hood A., 388, 432 Hope D.J., 392, 435 Hossler D., 63, 70, 76, 81, 217, 218, 220, 222, 225, 236, 237, 276, 304, 537 Hovey H.A., 57, 58, 59, 81, 209, 210, 237 Howard K.I., 190, 194 Howard R.K., 496, 502, 503, 504, 529 Hoxby C.M., 301, 306 Hrabowski F.A., 509, 525 Huang L., 496, 501, 504, 511, 529 Hubbell L.L., 205, 237 Hubbs-Tait L., 419, 432 Huberman A.M., 485, 486, 488, 529, 530 Huberty C.J., 175, 179, 186, 187, 193, 541 Hudec S.M., 417, 419, 421, 432 Hudson L.M., 408, 410, 430, 437 Huffman W.E., 258, 306 Huguley S., 496, 502, 503, 529 Huijsman R., 278, 306 Hunter J.E., 176, 193 Hurtado S., 425, 431, 544 Husser W.J., 212, 237 Hutchings P., 448, 476 IBO (Interdepartmental Policy Research Committee), 288, 289, 290, 306 Icerman R., 388, 391, 396, 432 Ignash J.M., 160, 172 Immerwahr J., 43, 59, 62, 81 Insley R., 392, 393, 407, 432 International Institute for Management Development, 336, 371 Irish S., 63, 76, 81 Isaac J.E., 256, 304 Itkin S., 504, 506, 509, 513, 529 Jacks P., 492, 494, 496, 502, 514, 529 Jackson D., 417, 432 Jackson E., 442, 443, 463, 464, 470, 473 Jackson J., 49, 81 Jackson L.A., 400, 430
554
AUTHOR INDEX Jacobs B., 279, 306 Jacobson N.S., 190, 193 James E., 49, 81 Jeffrey C., 388, 396, 432 Jennings J., 70, 81 Jiang L., 357, 371 Johnes G., 251, 306 Johnson G., 49, 79 Johnson J., 394, 430 Johnson J.L., 392, 393, 407, 432 Johnsrud L.K., 460, 476 Johnstone B., 35, 351, 371 Johnstone D.B., 242, 250, 306 Johnstone S.M., 214, 237 Jones D., 59, 81 Jones E., 49, 81 Jones G.B. Jr., 496, 502, 506, 511, 529 Jongbloed B, v, ix, [241–310], 254, 279, 288, 306, 307 June A.W., 200, 201, 237 Kane T.J., 44, 45, 53, 62, 66, 67, 71, 73, 76, 80, 81, 276, 277, 307 Kan-Rice P., 460, 476 Kaplan G., 101, 129 Karabel J., 71, 73, 74, 79, 82, 133, 171 Karcher J., 388, 391, 396, 432 Karolyi M.S., 496, 502, 529 Katz A.D., 392, 398, 411, 432 Katz I., 418, 432 Katz L., 49, 82 Kazdin A.E., 190, 193 Keller G., 85, 102, 129 Kemp M., 277, 304 Kendall P.C., 190, 193 Kengkau A., 418, 437 Kennelley M., 388, 391, 396, 432 Kerr C., 134, 172 Kezar A., 121, 129 Kieffer K.M., 190, 193, 195 Kilgannon S.M., 392, 402, 404, 432 Kimko D.D., 259, 306 King P.M., vi, ix, 375–440, 384, 388, 391, 392, 393, 406, 410, 419, 421, 432 Kingston P.W., 50, 72, 82 Kirk R.E., 179, 181, 182, 189, 193 Kirst M.W., 68, 77, 84 Kitchener K.S., ix, 388, 391, 393, 406, 410, 432 Klinger D., 206, 237 Knapp T.R., 183, 193 Knepp M., 231, 232, 236
Knowles A.S., 330, 371 Kochman A., 388, 429 Kodde D.A., 278, 306, 307 Koelman J., 279, 288, 306, 307 Kogan M., 349, 371 Kohlberg K., 378, 379, 433 Kohlberg L., 377, 378, 379, 382, 383, 384, 392, 395, 410, 415, 429, 432, 433 Kottke J.L., 413, 431 Krathwohl D.R., 38, 40 Krauskopf C., 504, 529 Kromrey J.D., 184, 187, 192, 193 Krop R.A., 77, 84 Kuh G.D., 217, 218, 220, 222, 225, 237, 401, 425, 433, 540 Kuhry B., 278, 304 Kupersmid J., 178, 193 Kurtines W.M., 377, 381, 433 Laanan F.S., 49, 83, 158, 159, 172 Ladewig B.H., 388, 403, 438 LaForce B., 388, 394, 410, 431 Laing G.J., 464, 476 LaMartina A.K., 407, 430 Lambert L., 28, 41, 457, 475 Lance T.S., 181, 195 Lang D.W., 230, 237 Lapovsky L., 205, 236, 237 Larcker D.F., 183, 192 Lardy N., 335, 372 LaRue, A., 392, 408, 433, 434 Lasher W.F., v, [197–240], viii, 197, 216, 225, 237, 539 Lawson A., 408, 433 Lawson L.G., 496, 497, 499, 507, 529 Lawson S., 179, 186, 194 Layzell D.T., 75, 76, 84, 226, 238, 540 Leadabrand J.A., 496, 500, 506, 507, 529 Leatherman C., 86, 129 Lee B.A., 91, 92, 98, 114, 129, 535 Lee S., 445, 475 Lees K.A., 496, 502, 506, 529 Leinhardt G., 177, 193 Lemley N.C., 506, 509, 529 Lemp P.H., 504, 507, 509, 530 Lenz K.S., 496, 502, 503, 505, 506, 530 Lenze L.F., 447, 479, 538 Leslie D.W., 85, 86, 102, 118, 119, 129, 542 Leslie L., 224, 225, 237 Leslie L.L., 48, 50, 53, 77, 82, 275, 276, 277, 307, 349, 373, 536, 539, 541 Letts C.W., 113, 129
555
AUTHOR INDEX Levinson-Rose J., 447, 476 Levy F., 49, 82 Lewis D.R., 444, 475, 537, 541 Lewis K.G., 447, 476 Lewis L.S., 50, 72, 82, 102, 129 Li P., 313, 372 Lichtenberg F.R., 304 Light P., 114, 129 Lincoln Y.S., ii, 85, 486, 489, 530, 537, 543 Lindblom C., 217, 238 Lindquist J., 441, 442, 443, 467, 472, 476 Linn R.L., 9, 15, 16, 20, 21, 41, 42 Lipton M., 78, 83 Liu H.-F., 313, 316, 372 Liu S.-C., 335, 372 Locke D.C., 392, 433 Loevinger J., 409, 410, 415, 433 Loftus G.R., 175, 193 Longin T.C., 102, 129 Longsdon J.M., 418, 433 Lord F.M., 9, 186, 194 Lostoski C., 131 Lovell C.D., v, viii, 133–173, 133, 157, 158, 163, 172 Lovett C.M., 233, 238 Loviscky G.E., 388, 392, 433 Lovitts B.E., 496, 499, 500, 506, 507, 514, 530 Lowman L.L., 187, 193, 541 Lubinski D., 393, 402, 437 Lucas A.F., 468, 476 Lucas R., 258, 307 Lucas S.R., 78, 82 Luhtanen R., 411, 433 Lumina Foundation for Education, 55, 82 Lund J.P., 63, 81 Lunde, J.P., 445, 454, 455, 476 Lunneborg C.E., 505, 509, 510, 511, 530 Lunneborg P.W., 505, 509, 510, 511, 530 Lupfer M.B., 392, 419, 433 Lutwak N., 410, 433 Lyons J., 433 Ma J., 301, 307 Macht M.W., 496, 501, 506, 508, 530 Maddux C.D., 388, 429 Mah D.M., 496, 502, 503, 506, 507, 508, 509, 530 Malaney G.D., 482, 530, 537 Malinowski, C.I., 433 Malone B., 394, 340 Mann C.M., 504, 530 Manno B.V., 54, 80 Manski C.F., 275, 307
Manzo K.K., 530 Mao Z.-D., 317, 318, 328, 372 Marcia J.E., 409, 410, 415, 433 Margo R.A., 272, 306 Margulies J., 211, 238 Mariano C.M., 502, 530 Markewich T.S., 492, 508, 509, 531 Marsh H.W., 12, 539 Maryland State Department of Education, 58, 82 Masanz J., 388, 436 Mason E.S., 391, 413, 415, 433 Matchett W., 492, 509, 530 Mathis B.C., 444, 445, 477 Mayhew M.J., vi, ix, [375–440], 384, 392, 419, 421, 432 McCabe-Martinez M.C., 496, 502, 503, 505, 506, 507, 510, 511, 519, 530 McCaulley M.H., 394, 434 McConahay J.B., 418, 433 McConnell T.R., 106, 129, 134, 171 McCormack T., 101, 129 McCrae R.R., 394, 429 McCutcheon G., 457, 458, 478 McDonough P.M., 70, 71, 72, 77, 82, 542 McGlinchey J.B., 190, 193 McGrath E.J., 98, 129 McGuinness A.C., 86, 129, 135, 172 McKeachie W.J., 2, 12, 443, 444, 446, 452, 453, 475, 477, 541 McKeown M.P., 226, 238 McMillan L., 401, 436 McNally S., 305 McNeel S., 388, 396, 397, 434 McPherson M.S., 275, 276, 277, 307, 537 McPherson R., 394, 435 Measuring Up 2000, 159, 172 Megargee E.I., 412, 434 Meiners R., 96, 127 Meisinger R.J. Jr., 199, 217, 218, 220, 221, 222, 224, 225, 238 Menges R.F., 447, 476 Menges R.J., 12, 443, 444, 445, 477 Mentkowski M., 388, 391, 393, 394, 395, 397, 406, 410, 424, 434 Merisotis J.P., 204, 236 Merriam Webster’s Collegiate Dictionary, 198, 238 Merrien F., 349, 370 Metzger W.P., 94, 129 Michael W.B., 413, 431 Mihu E., 477 Miles M.B., 485, 486, 488, 529, 530
556
AUTHOR INDEX Miller G., 27, 442, 443, 463, 464, 470, 473 Miller M., 101, 129 Milton O., 445, 475 Min W.-F., 313, 372 Minassians H., 228, 229, 236 Mingle J.R., 164, 165, 172 Ministry of Education, 313, 320, 321, 322, 323, 324, 326, 327, 330, 331, 338, 343, 351, 353, 355, 362, 372 Minor J., 85, 101, 130 Mishel L., 49, 82 Mittag K.C., 175, 194 Mok K.-H., 320, 333, 349, 372 Monk-Turner E., 49, 82 Moomaw W.E., 445, 475 Moore R., 275, 307 Moore W.E., 47, 79 Morgan A., 218, 220, 221, 222, 224, 238 Morgan E.R., 394, 430 Morgan R., 145, 172 Morrell E., 78, 83 Morris J.D., 186, 193 Mortenson T., 43, 61, 69, 82 Mortimer K.P., 106, 129 Motwani J., 392, 393, 407, 432 Moylan S., 392, 439 Mudrack P.E., 391, 413, 433 Mueller R., 49, 82 Muhic J.J., 505, 508, 509, 530 Muhlberger P., 407, 419, 421, 434 Mullane S.P., 392, 413, 434 Mullen B., 487, 490, 530 Mumper M., 54, 82, 541 Murdock S.H., 460, 465, 477 Murk D.A., 392, 394, 407, 412, 434 Murnane R., 49, 82 Murphy K., 49, 82 Murray H.G., 12, 447, 477, 538, 543 Murray L.W., 180, 194 Murrell J.P., 499, 506, 510, 530 Mustapha S.L., 388, 400, 434 Muszynski S.Y., 496, 502, 503, 531 Muyskens J.A., 455, 475 Myers I.B., 394, 434 Myers R., 457, 477 Nagi J.L., 496, 499, 504, 506, 531 Nahuis R., 272, 307 Nakanishi D.T., 460, 477 Narvaez D., 378, 379, 382, 385, 386, 387, 394, 403, 404, 417, 420, 428, 430, 434, 436 National Association of College and University Business Officers, 206, 238
National Association of State Budget Officers, 57, 82, 203, 238 National Association of State Universities and Land-Grant Colleges, 375, 434 National Center for Education Development Research, 331, 332, 345, 372 National Center for Education Statistics (1993), 350, 372 National Center for Education Statistics (2000), 460, 463, 477 National Center for Education Statistics (2001), 162, 172 National Center for Education Statistics (2002), 82 National Center for Education Statistics (2003), 82 National Center for Public Policy and Higher Education, 55, 57, 60, 61, 66, 82, 159, 203, 229, 238 National Commission on the Cost of Higher Education, 207, 238 National Commission on the High School Senior Year, 69, 82 National Committee of Inquiry into Higher Education, 256, 261, 290, 307 National Conference of State Legislatures, 203, 238 National Council of State Legislatures, 152, 172 National Education Association, 163, 445, 477 National Education Research Institute, 326, 328, 330, 372 Naylor P.D., 509, 510, 531 Nelson B., 293, 307 Nelson C., 103, 104, 129 Nelson E.S., 392, 396, 437 Nelson N., 175, 194 Nelson R.R., 258, 307 Nerad M., 481, 482, 492, 493, 496, 497, 507, 510, 512, 513, 521, 522, 531 Nevin K.J., 397, 434 Newcomb T., 19, 41 Newman F.L., 190, 194 Newman J., 346, 434 Newman R., 101, 129 Nichols D.P., 413, 434 Nichols M.L., 399, 400, 434 Nilsson J.E., 181, 195 Noblit G.W., 485, 486, 488, 489, 531 Nora A., 518, 528, 539 Northwest Education Research Center, 146, 172
557
AUTHOR INDEX Nucci L., 376, 434, 536 Nyquist J.D., 455, 477 O’Bara C.C., 496, 505, 531 O’Connell E.C., 492, 493, 494, 496, 531 O’Connell W.R., 445, 475 O’Donoghue T.A., 362, 372 O’Grady K.E., 180, 194 Oakes J., 78, 83 Oakes M., 175, 194 Ochsner N.L., 492, 508, 509, 531 Odink J., 306 OECD, 245, 246, 256, 257, 261, 262, 263, 264, 265, 266, 307 Olejnik A.B., 392, 408, 433, 434 Olejnik S., 187, 193, 194 Oosterbeek H., 253, 269, 270, 271, 274, 278, 306, 307, 308 Orr M.T., 160, 161, 173 Orwig M., 218, 220, 224, 236 Ory J.C., 12, 469, 474 Ott M.D., 492, 508, 509, 531 Ouelett M.L., 463, 478 Pace C.R., 2, 7, 14, 15, 26, 41, 541 Palmer P.J., 409, 434 Palmer-Canton E., 394, 340 Pan M.-Y., 316, 372 Papalewis R., 507, 527 Paradice D.B., 388, 391, 396, 434 Pargament K.I., 414, 434 Parker C.A., 388, 391, 432 Parry M.E., 21, 41 Parsons M.D., 54, 74, 83 Pascarella E.T., 22, 41, 376, 396, 401, 425, 434, 435, 529, 535, 536 Patrinos H.A., 264, 308 Patterson-Stewart K.E., 496, 531 Paulsen M.B., ii, viii, 53, 54, 83, 197, 203, 210, 238, 542 Peacock, S.Y., 502, 531 Pendergrass M.L., 406, 438 People’s Daily, 318, 323, 336, 363, 372 Pepper S., 319, 372 Perna L.W., v, vii, [43–84], 51, 56, 62, 65, 68, 77, 83, 544 Perry R.P., ii, 12, 538 Perry W., 457, 477 Peterson M.W., 539, 542 Peterson P.M., 365, 370 Peterson R.E., 9, 16, 42 Petrides L.A., 511, 528
Petrocelli J.V., 181, 195 Peyrefitte J., 499, 500, 507, 509, 526 Pfnister A.O., 102, 108, 109, 129 Phelps E.S., 258, 307 Phillips S.R., 17, 40, 445, 467, 474 Phinney J.S., 411, 435 Piaget J., 408, 435 Piccinin S., 455, 477 Picot R., 508, 509, 532 Pintrich P.R., 405, 432, 543 Pittman K., 70, 84 Plueddemann J., 392, 435 Poling T.H., 394, 430 Ponemon L., 388, 435 Ponemon L.A., 396, 398, 419, 435 Population Census Office, 336, 339, 351, 373 Porozny G.H.J., 496, 504, 506, 531 Porter A.L., 492, 494, 496, 502, 514, 529 Porter, M.E., 447, 463, 467, 478, 479 Poulin R., 214, 237 Power C., 379, 429 Power M., 349, 373 Pratt S.B., 392, 401, 435 Presley C.L., 496, 507, 509, 531 Pressley M., 392, 435 Price D.V., 51, 72, 83 Price R.F., 311, 359, 373 Pristo L.J., 504, 505, 531 Psacharopoulos G., 252, 264, 308 Pusser B., 98, 130, 542, 543 Quarry E.B., 388, 391, 392, 393, 394, 395, 407, 435 Quehl G.H., 454, 477 Quinlan K., 448, 477 Quinn E.L.C., 508, 509, 510, 532 Ramin, J., 63, 76, 81 Ramo K.J., 91, 104, 108, 109, 130 Rao Y., 364, 373 Ratcliff J.L., 133, 173 Rauch J., 258, 308 Reall, M.J., 401, 435 Reamer S.B., 492, 496, 497, 505, 507, 511, 532 Redford J., 394, 435 Reeble B.E., 505, 506, 532 Reed L.A., 319, 373 Reese R.J., 190, 193 Reese S.J., 206, 239 Reetz D.R., 181, 195 Reeves M.F., 392, 428 Reeves T.G., 417, 435
558
AUTHOR INDEX Reid R.A., 418, 433 Reiff M., 481, 496, 497, 507, 532 Reiser L., 429 Reitsch A., 101, 128 Renwick S., 392, 394, 430, 435 Research Associates of Washington, 239 Rest J.R., 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 391, 393, 394, 399, 405, 406, 416, 417, 418, 419, 420, 423, 428, 434, 435, 436, 438 Reuben J., 375, 436 Rhodes F.H.T., 469, 477 Rhodes R.A.W., 333, 373 Rholes W.S., 401, 436 Rice R.E., 468, 469, 478 Richards P.S., 394, 436 Richardson J.T., 103, 130 Richardson R.C. Jr., 86, 97, 104, 130 Richardson R., 141, 142, 143, 144, 145, 159, 173 Richardson R.C., 133, 135, 141, 142, 143, 173 Richlin L., 455, 456, 457, 478 Riesman D., 123, 128 Rifkin T., 160, 173 Rinne H., 418, 437 Ritchie G.D., 394, 413, 436 Ritzen J.M.M., 278, 306, 307 Roberts J.K., 186, 194 Roberts L.J., 190, 193 Robertson R., 362, 373 Robinson D.H., 175, 194 Rock D.A., 20, 41, 42 Rogers G., 378, 397, 436 Rogers J., 78, 83 Roherty B.M., 209, 239 Rokeach M., 413, 436 Romer P., 258, 259, 308 Ronkowski S.A., 455, 478 Rosenbaum D.E., 239 Rosenthal R., 175, 188, 194, 195, 484, 487, 490, 526, 530, 532 Rosnow R.L., 175, 188, 194 Rosovsky H., 90, 91, 125, 130 Rotenburg K.J., 392, 412, 437 Roth A.P., 67, 83 Rothblum E.D., 460, 474 Rotou O., 181, 192 Rotter J.B., 412, 437 Rowland G.L., 388, 392, 406, 412, 438 Rudenstine N.L., 481, 482, 483, 492, 493, 494, 501, 502, 506, 509, 510, 512, 513, 523, 525 Rumberger R.W., 49, 51, 83
Ruppert S.S., 164, 165, 172 Ryan C., 282, 283, 305 Ryan W.P., 113, 129 Rydell C.P., 77, 84 Ryden M., 419, 430 Sachs S.G., 449, 474 Sacks P., 71, 83 Salvage T., 282, 305 Sanchez, J.R., 49, 83 Sanders C.E., 393, 402, 437 Sanders D., 457, 458, 478 Sanford N., 1, 5, 42, 409, 437, 457, 478 Sanford T.R., 509, 510, 528, 531 Santilli N.R., 408, 437 Sauer J.L., 492, 493, 494, 496, 499, 501, 505, 509, 513, 515, 532 Saunders S.M., 190, 194 Sausman C., 256, 261, 308 Sbragia A., 349, 373 Schafer L.E., 396, 439 Schapiro M.O., 275, 276, 277, 307 Schmersahl K.W., 509, 532 Schmidt F., 191, 194 Schmidt P., 213, 229, 239 Schmidtlein F., 199, 239 Schmierer D., 392, 435 Schmitt J., 49, 82 Schram S., 318, 373 Schraw G., 391, 392, 406, 428 Schuh J.H., 401, 425, 433 Schultz M.C., 496, 505, 506, 532 Schultz T.W., 47, 83, 252, 258, 308 Schuster J.H., 86, 102, 130, 452, 469, 474, 478, 483, 525 Schwarz S., 133, 173 Scott J.V., 85, 86, 130 Scott P.A., 312, 334, 343, 345, 373, 539 Seagren A.T., 468, 475 Sedlmeier P., 191, 194 Seldin P., 469, 478 Selingo J., 211, 239 Sell G.R., 461, 478 Seneca J.J., 509, 528 Sewell W.H., 47, 49, 50, 83 Seybert J.A., 388, 400, 434 Shanghai Higher Education Research Institute, 328, 373 Shanghai Institute of Intellectual Development, 334, 373 Shapiro N., 70, 83 Shaub M.K., 388, 392, 437
559
AUTHOR INDEX Shaver D.G., 388, 392, 396, 437 Shaver J., 178, 179, 194 Shea J., 269, 308 Shea M., 472, 478 Shields D.L., 419, 429 Shils E., 367, 373 Shoichet C.E., 239 Shu X.-C., 316, 373 Shulman L.S., 35, 391, 437 Siegwart C.M., 392, 412, 437 Simmons D.D., 411, 413, 415, 437 Simpson N.J., 463, 467, 478 Simpson R.D., 444, 445, 450, 451, 452, 459, 469, 476 Simpson T.L., 419, 429 Sims R.L., 499, 500, 507, 509, 526 Sinclair U., 105, 130 Skudlarek L.J., 496, 497, 499, 500, 506, 508, 532 Slaughter A., 349, 373 Slaughter S., 98, 130, 543 Slobko T., 307 Smart J.C., iii, viii, 2, 49, 83, 197, 210, 238 Smith C.A., 400, 437 Smith C.J., 162, 173 Smith C.P., 419, 433 Smith D.G., 130 Smithson M., 190, 194 Smits J., 306 Smolicz J.J., 365, 373 Smulders S., 272, 307 Snodgrass J., 396, 437 Snyder M., 412, 437 Snyder P., 179, 181, 186, 194 Solmon L.C., 49, 83 Solomon S.E., 460, 474 Sorcinelli M.D., 443, 447, 456, 467, 469, 478 Sosa J.A., 455, 474, 483 South China Morning Post, 360, 366, 373 Speicher B., 379, 429 Spence M., 47, 48, 83, 252, 308 Sprague J., 455, 477 St. James A., 394, 430 St. John E.P., 54, 74, 83, 540 St. Pierre K.E., 392, 396, 437 Stampen J.O., 75, 76, 84 Stanley C.A., vi, ix, [441–480], 447, 451, 458, 463, 467, 472, 478, 479 Steel J., 256, 261, 308 Steiger J.H., 190, 194 Stepp J.O., 391, 392, 393, 394, 395, 408, 437 Stevens J., 186, 194
Stiglitz J.E., 260, 263, 308 Stoll S.K., 401, 435 Strait M.J., 388, 391, 393, 394, 395, 397, 434 Strange, C., 433 Strauss J., 224, 225, 239 Stroud S., 388, 392, 393, 437 Studenmundt A., 307 Stults D.M., 413, 434 Sullivan C.A., v, vii, [197–240] Surbeck E., 407, 408, 411, 438 Svinicki M., 443, 465, 466, 479 Swail W.S., 72, 80 Swanson A., 501, 504, 508, 509, 510, 512, 526 Sweeney J.T., 394, 430 Swinyard W., 418, 437 Swoboda M.J., 492, 496, 505, 506, 507, 532 Szabo B.L., 447, 457, 475, 479 Tafel J., 161, 173 Taubman P., 48, 84 Taussig M.K., 509, 528 Taylor B.E., 97, 128, 130 Taylor C., 486, 532 Taylor J.B., 407, 408, 411, 419, 438 Taylor T., 365, 373 Temple J., 253, 263, 308 Teng S., 316, 373 Tennant S., 392, 398, 400, 438 Terenzini P.T., 22, 41, 396, 401, 425, 435 Terman L.M., 393, 438 Tertiary Education Advisory Commission, 308 Teulings C.N., 272, 306, 308 Texas Higher Education Coordinating Board, viii, 212, 223, 239 The College Board, 14, 23, 45, 60, 61, 63, 64, 65, 66, 67, 79, 212, 239 The Institute for Higher Education Policy, 53, 81 Thelin J.R., 535 Thoma S.J., 378, 379, 382, 385, 386, 387, 388, 389, 391, 392, 394, 403, 417, 419, 421, 426, 430, 436, 438 Thomas S.L., v, vii, [43–84], 49, 51, 72, 83, 84, 98, 130 Thomason N., 190, 192 Thompson B., v, viii, [175–196], 194, 195 Thompson J.K., 418, 433 Thulstrup E.W., 337, 373 Tiberius R., 443, 452, 453, 479 Tierce G.L., 496, 500, 502, 532
560
AUTHOR INDEX Tierney W.G., ii, v, vii, 56, 84, [85–132], 97, 101, 106, 114, 115, 118, 121, 130, 358, 373, 539 Tinto V., 27, 34, 481, 482, 483, 499, 524, 532, 536 Titus M., 62, 65, 83 To D., 49, 81 Tollefson T.A., 133, 137, 140, 143, 144, 150, 165, 168, 173 Toombs W., 444, 479 Townsend B.K., 141, 160, 172, 537, 538 Townsend P., 357, 373 Traw L.S., 504, 532 Trouth C., v, viii, [133–173], 133, 172 Trow M., 90, 91, 98, 115, 119, 125, 130, 311, 334, 345, 350, 374 Trower C.A., 463, 479 Trusheim D., 59, 84 Trusty J., 181, 195 Tryon W.W., 177, 195 Tucker A., 468, 479 Tucker D.O., 392, 433 Tuckman H.P., 521, 532, 538 Tuckman, S., 513, 532 U.S. Bureau of Labor Statistics, 43, 84 U.S. Department of Education, National Commission on Excellence in Education, 239 UNDP (United Nations Development Program), 358, 374 UNESCO Statistical Yearbook (1998), 313, 374 Unger R.K., 406, 438 Vacc N.N., 508, 509, 532 Vacha-Haase T., 181, 186, 195 Valentine N.L., 492, 496, 497, 499, 500, 502, 503, 508, 509, 533 Van Der Werf M., 206, 239 van Leeuwen M., 306 Van Wicklin J., 388, 396, 410, 414, 429 Vandement W., 217, 218, 219, 220, 239 Veblen T., 95, 131 Venezia A., 68, 77, 84 Venniker R., 259, 263, 308 Vernez G., 77, 84 Vogel E., 336, 374 Volkvein J.F., 536 Vorhees R., 158, 173 Vossensteyn H., 254, 274, 275, 283, 286, 307, 308
Wadner D., 445, 475 Wagner D.V., 496, 502, 503, 508, 509, 533 Wahrman J., 394, 413, 438 Wainer H., 175, 194 Wainwright A., 201, 239 Wales T., 48, 84 Walfish D., 355, 374 Walker H.A., 388, 392, 406, 412, 438 Walker L.J., 392, 438 Wang L.-N., 335, 372 Wanshaffe K.R., 408, 411, 438 Ward S., 485, 533 Waters B., 407, 408, 411, 438 Watson G., 408, 438 Webbink H.D., 269, 278, 306, 308 Weber L.E., 103, 125, 129, 130, 465 Wechsler H., 133, 172 Wei G.-K., 353, 374 Weimer M., 447, 479, 538 Weisbrod B.A., 76, 80, 260, 308 Weiss A., 48, 84, 253, 308 Weiss L., 506, 533 Welch F., 49, 82 Wellman J.V., 148, 149, 152, 157, 173, 204, 236 Welzenbach L., 217, 218, 220, 240 Wemmerus V., 496, 497, 499, 501, 502, 506, 508, 509, 528 Wenhui Daily, 356, 374 Wentzel M.L., 506, 533 Wessler R., 410, 433 West P.S., 47, 80 Western Interstate Commission for Higher Education and The College Board, viii, 212, 239 Westfall S., 63, 76, 81 Whalen E., 224, 225, 239, 240 Wheat L.W., 415, 438 Wheeler D., 451, 476 Wheeler D.W., 452, 468, 475, 478 Whitacre M.D., 505, 506, 533 Whiteley J.M., 388, 392, 410, 412, 438 Whitt E.J., 401, 425, 433 Wiggins N., 504, 528 Wildavsky A., 198, 240 Williams D., 98, 101, 128, 131 Williams G.C., 243, 309 Williams J., 504, 509, 533 Williams R., 304, 392, 438 Willingham W.W., 504, 533 Wilson J.P., 412, 429 Wilson R., 447, 479 Winter R., 373
561
AUTHOR INDEX Wise D., 49, 84 Wise D.A., 275, 307 Wolfe B., 53, 84, 253, 254, 260, 306, 309 Wolpin K., 48, 84 Wolvin A.D., 102, 131 Wood D.J., 508, 533 Wood P.K., 388, 391, 393, 406, 410, 432, 541 Woolington V.J., 408, 414, 439 World Bank, 254, 264, 271, 309, 337, 347, 349, 351, 358, 374 Worthington R., 483, 533 Wright R.L., 392, 401, 438 Wulff D.H., 455, 477 Wygant S., 392, 438 Xie Z.-X., 327, 328, 334, 340, 351, 352, 354, 355, 374 Xiong Q.-N., 312, 371 Yamada M.M., 130 Yang R., vi, ix, [311–374], 311, 355, 363, 364, 365, 374
Yohalem N., 70, 84 Young J.S., 408, 414, 439 Yu L., 323, 325, 326, 327, 374 Zahorski K.J., 467, 479 Zarinpoush F., 392, 439 Zbib I., 392, 393, 407, 432 Zeidler D.L., 396, 439 Zhang L., 51, 84, 358, 359, 374 Zheng D.-Y., 315, 374 Zhong W.-H., 363, 374, 539 Zhongguo Jiaoyu Nianjian Editorial Committee, 324, 325, 374 Zhou Y.-T., 316, 374 Zhou-McGovern Y., 398, 428 Ziegele F., 284, 285, 309 Zijl M., 306 Ziolkowski T., 483, 533 Zuckerman A., 175, 195 Zuckerman M., 175, 195, 412, 439 Zumeta W., 76, 84, 541 Zuvekas S., 53, 84 Zwick R., 492, 509, 533
562
