Progressing Science Education: Constructing the Scientific Research Programme into the Contingent Nature of Learning Science (Science & Technology Education Library)

Progressing Science Education

Science & Technology Education Library VOLUME 37 SERIES EDITOR Dana Zeidler, University of South Florida, Tampa, USA

FOUNDING EDITOR Ken Tobin, City University of New York, USA

EDITORIAL BOARD Fouad Abd El Khalick, University of Illinois at Urbana-Champaign, USA Marrisa Rollnick, University of the Witwatersrand, Johannesburg, South Africa Svein Sjøberg, University of Oslo, Norway David Treagust, Curtin University of Technology, Perth, Australia Larry Yore, University of Victoria, British Columbia, Canada HsingChi von Bergmann, University of Calgary, Canada

SCOPE The book series Science & Technology Education Library provides a publication forum for scholarship in science and technology education. It aims to publish innovative books which are at the forefront of the field. Monographs as well as collections of papers will be published.

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Keith S. Taber

Progressing Science Education Constructing the Scientific Research Programme into the Contingent Nature of Learning Science

Keith S. Taber Faculty of Education University of Cambridge UK

ISSN 1572-5987 ISBN: 978-90-481-2430-5 e-ISBN: 978-90-481-2431-2 DOI: 10.1007/978-90-481-2431-2 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2009928772 © Springer Science+Business Media, LLC 2009 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Acknowledgments

Although none of the chapters included here have been published before, I obviously draw upon ideas discussed in earlier work. In particular, I owe a debt of thanks to Eric Scerri who suggested I might write something defending constructivism in Science Education for the interdisciplinary journal Foundations of Chemistry, where he was editor. My response to that request coincided with a shift in the publisher’s policy that meant that my submission was accepted on the proviso that I cut it down to about a third of its original length. The published version (Taber, 2006b) focused on responding to key criticisms of constructivism, which is the basis of Chapter 5 of this work. I am also thankful to the editors of the review journal, Studies in Science Education (Jim Donnelly and Phil Scott), for responding positively to my suggestion that I might be able to rework the material that had to be excluded from the Foundations of Chemistry paper for a submission to Studies. This led to a review that focused more on the achievements of the research programme (Taber, 2006a). However, it also became clear that even the generous word count allowed in a review paper could do little more than offer a brief outline of the research programme. Writing the present volume allowed me to expand and develop the arguments in the Foundation of Chemistry and Studies in Science Education papers. However, I am aware that in offering an account of research into an area such as learning in science even a substantial book involves considerable selection of material. This work has no doubt been improved considerably through the process of peer review. The book proposal was considered by four referees; and a full draft of the manuscript was read by three reviewers. The comments of these anonymous reviewers (in one particularly generous case, amounting to a small volume in itself) have no doubt influenced the present work for the better. Discussion with members of the informal Learning Science Research Group (graduate students and visiting scholars) at Cambridge was also very helpful in clarifying aspects of how to present my argument. Members of the group while I was preparing the book included Fatin Aliah Phang binti Abdullah, Oktay Betkas (Middle East Technical University, Turkey), Pamela Black, Richard Brock, Professor Qiyong Cai (Chongqing Education College, P.R. China), Valeska Grau Cárdenas, Calvin Dorion, Teresa Quail and Fran Riga. As always in such matters, the flaws that remain are the responsibility of the author. v

vi

Acknowledgments

Dialogue with a wide range of academics and teaching colleagues, and other students, has no doubt developed my thinking in many subtle ways without my always explicitly recognising it. In particular, I should mention Mike Watts who supervised my doctoral research at Roehampton, John Gilbert, editor-in-chief of the International Journal of Science Education, who offered encouragement in revising my first ever submission to the journal, and colleagues who have worked with me on empirical studies: Daniel Tan (National Institute of Education, Singapore), Alejandra García-Franco (National Autonomous University of Mexico) and Karina Adbo (Kalmar University, Sweden). The support of the Science and Technology Education Series Editor, Sherry Southerland, and in particular my editor at SpringerKluwer, Harmen van Paradijs, has facilitated the development of the book. Given that a key message of the research discussed here is the highly contingent nature of learning, I would like to thank my parents, Roy and Phyllis Taber, for providing the supportive early learning environment – a great deal of love, care and attention – that facilitated the construction of the foundations for all my later learning. Finally, I should acknowledge the importance of the University of Cambridge’s policy on study-leave for providing the time for serious writing, and above all my wife Philippa for understanding (and accepting) that I wanted to spend so much of my sabbatical year at my iMac surrounded by piles of books and papers.

Contents

Introduction: The Scientific Research Programme into Learning Science .... 1

Science Education As a Research Field Within a Domain of Enquiry ................................................................................. 1.1 1.2

1.3

1.4 1.5

1.6

1.7

1.8

A Research Topic: Learning Science .................................................. 1.1.1 The Construction Metaphor for Learning ............................... Sharing Meanings for Key Terms ....................................................... 1.2.1 Learning as a Potential for New Behaviour ............................ 1.2.2 Knowledge as a Label for What Is Currently Considered to Be So ............................................................... 1.2.3 Beliefs, Ideas and Conceptions ............................................... 1.2.4 Thinking and the Mind ........................................................... Locating the Research Topic in a ‘Field of Study’ ............................. 1.3.1 The Wider Domain of Enquiry ............................................... 1.3.2 The Relationship of Topic and Field....................................... 1.3.3 Progressing Science Education? ............................................. The Domain of Enquiry – Background to the Field ........................... 1.4.1 Public and Personal Knowledge ............................................. Philosophical Views on Learning ....................................................... 1.5.1 Dewey’s Pragmatic View of Knowledge ................................ 1.5.2 Glasersfeld’s Radical Constructivism ..................................... Influences from Psychological Studies of Development .................... 1.6.1 Piaget’s Construction of the Child’s World ............................ 1.6.2 Vygotsky and Scaffolded Construction of Our Worlds .......... 1.6.3 Kelly’s Personal Constructs of the World ............................... 1.6.4 Perry’s Model of Intellectual Development ............................ Studies of Cognition ........................................................................... 1.7.1 Introspection and Behaviourism ............................................. 1.7.2 Gestalt Theorists ..................................................................... 1.7.3 Learning Through Metaphor................................................... 1.7.4 Information Processing Models .............................................. Structure of Mind ................................................................................ 1.8.1 General Processing Models ....................................................

1 7 7 8 9 10 11 12 15 16 17 17 19 19 20 21 22 23 24 25 28 31 33 34 34 35 36 37 39 39 vii

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Contents

1.8.2 1.8.3

Modular Minds ................................................................... Representational Redescription in Cognitive Development ....................................................................... 1.8.4 Mental Models and Representation .................................... 1.8.5 Metacognition ..................................................................... Approaches to Instruction and Pedagogy ......................................... 1.9.1 Gagné and the Conditions of Learning ............................... 1.9.2 Ausubel ............................................................................... 1.9.3 Bruner ................................................................................. The Field: Research in Science Education........................................ 1.10.1 Curriculum Development.................................................... 1.10.2 The Piagetian Research Programme in Science Education........................................................... 1.10.3 Dissatisfaction with the Piagetian Perspective ................... 1.10.4 Constructivism in Science Education .................................

40

‘Scientific’ Research in Education ..........................................................

51

2.1

51 52 53 53 55 56 59 59 61 62 63 65 65 67 68 68

1.9

1.10

2

2.2

2.3

2.4 2.5

2.6

2.7

The Notion of Educational Science .................................................. 2.1.1 Why Do We Need to Put a Boundary Around Science?..... A Post-Positivist View of Science..................................................... 2.2.1 Positivism and Objective Knowledge ................................. 2.2.2 Popper’s Three Worlds Model ............................................ 2.2.3 Science, Realism and Objectivity ....................................... Scientific Method .............................................................................. 2.3.1 The Problem of Induction ................................................... 2.3.2 The Problem with Deduction .............................................. 2.3.3 Another Problem with Refutations ..................................... 2.3.4 The Complication of Instrumentation ................................. The Role of Theory in Scientific Research ....................................... 2.4.1 Kuhn and Adherence to Theory .......................................... Experimental and Naturalistic Research in Science ......................... 2.5.1 Reductionism in Science and ‘Relational’ Perspectives ..... 2.5.2 Traditional Ecological Knowledge ..................................... 2.5.3 A Post-Positivist Notion of ‘Science’ That Can Include Education ............................................... Research Paradigms in Education ..................................................... 2.6.1 The Significance of Judgements About Choice of Research Paradigm ............................................................. 2.6.2 Positivist or Interpretivist.................................................... 2.6.3 Nomothetic or Idiographic .................................................. 2.6.4 Confirmatory or Discovery ................................................. 2.6.5 Questioning the Dichotomy of Research Approaches in Education ........................................................................ Scientific Research in Education ...................................................... 2.7.1 A Post-Positivist Paradigm for Educational Research? ......

40 41 42 43 43 44 44 46 46 46 48 49

69 70 71 72 74 75 76 77 78

Contents

3

A Model of Science: Lakatos and Scientific Research Programmes ............................................................................. 3.1 3.2

79

Lakatos: An Alternative to Popper and Kuhn ................................. Paradigms As a Unit of Analysis in Science .................................. 3.2.1 Revolutionary Science and Normal Science ..................... 3.2.2 The Notion of a Paradigm ................................................. 3.2.3 Normal Science ................................................................. 3.2.4 The Disciplinary Matrix .................................................... 3.2.5 Scientific Revolutions ....................................................... 3.2.6 Gestalt-Shifts and Paradigm-Shifts ................................... 3.2.7 Incommensurability of Paradigms .................................... Criticisms of Kuhn’s Model ............................................................ 3.3.1 Relativism and Subjectivity .............................................. 3.3.2 The Myth of the Framework ............................................. 3.3.3 Qualified Relativism.......................................................... 3.3.4 Progress and Non-Revolutions .......................................... Parallels Between Science and Science Education? ....................... Lakatos and RP As Units of Analysis ............................................. The Key Features of a SRP ............................................................. 3.6.1 The Hard Core and the Negative Heuristic ....................... 3.6.2 The Protective Belt ............................................................ 3.6.3 The Positive Heuristic of a RP .......................................... 3.6.4 Models As Part of the Protective Belt ............................... Refutation in RP.............................................................................. 3.7.1 Quarantine of Anomalies .................................................. Evaluating RP ................................................................................. 3.8.1 Progressive RP .................................................................. 3.8.2 Degenerate RP ................................................................... 3.8.3 Competition Between RP .................................................. Relating Paradigms, Programmes and Frameworks ....................... Scientific RP and the Social Sciences ............................................. 3.10.1 The Significance of Demarcation ...................................... 3.10.2 Normative Knowledge and RP .......................................... 3.10.3 Progressive and Scientific RP ........................................... 3.10.4 RP in Science and Psuedoscience ..................................... The Origins of a RP ........................................................................ 3.11.1 Nursing RP ........................................................................ Summary .........................................................................................

79 81 81 82 82 83 84 84 85 86 87 88 89 91 91 92 93 94 95 96 97 98 99 100 100 101 101 102 103 104 106 106 108 108 109 110

A Scientific Research Programme Within Science Education .............

111

3.3

3.4 3.5 3.6

3.7 3.8

3.9 3.10

3.11 3.12 4

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4.1

Constructivism As a Research Orthodoxy in Science Education ... 4.1.1 Pupils, Paradigms and Alternative Frameworks? .............. 4.1.2 The Notion of Children’s Science ..................................... 4.1.3 Considering Pupils As Scientists ...................................... 4.1.4 Students’ Conceptual Frameworks in Science ..................

111 113 114 114 115

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Contents

4.2

4.3

4.4

4.5

4.6

4.7 4.8

4.9

4.10

4.11

4.12

4.1.5 Concepts, Misconceptions and Alternative Conceptions .. 4.1.6 Personal Constructivism.................................................... 4.1.7 Learning Science As a Generative Process ....................... 4.1.8 Early Evidence of the Significance of Learners’ Ideas ..... The ‘Alternative Conceptions Movement’ ...................................... 4.2.1 Major Projects: LiSP, CLiSP and SPACE ......................... 4.2.2 Constructivism Becomes Widely Taken-for-Granted ....... Conceptualisations of the Research Programme............................. 4.3.1 Driver and Erickson Set Out Premises for a RP................ 4.3.2 Gilbert and Swift Suggest a Lakatosian Analysis ............. 4.3.3 A Descriptive and Pre-Theoretical Movement? ................ 4.3.4 A Recent Suggestion for the Hard Core of the RP............ Characterising the Research Programme ........................................ 4.4.1 A Model of the Hard Core ................................................ 4.4.2 A Positive Heuristic for the RP ......................................... 4.4.3 Building the Protective Belt of the RP .............................. Knowledge Construction................................................................. 4.5.1 Learning Science Is an Active Process of Constructing Personal Knowledge .................................... The ‘Transfer’ Model of Learning .................................................. 4.6.1 The Status of the Transfer Model ...................................... 4.6.2 Objections to a Transfer Model of Coming to Knowledge .................................................................... 4.6.3 Personal Knowledge and Personal Construction .............. How Does Knowledge Construction (i.e. Learning) Take Place?... Learners’ Scientific Ideas ................................................................ 4.8.1 Learners Come to Science Learning with Existing Ideas About Many Natural Phenomena ............................ 4.8.2 What Ideas Do Learners Bring to Science Classes? ......... 4.8.3 What Is the Nature of These Ideas? .................................. Implications for Learning ............................................................... 4.9.1 The Learners’ Existing Ideas Have Consequences for the Learning of Science ............................................... 4.9.2 How Do Learners’ Ideas Interact with Teaching? ............. Implications for Teaching ............................................................... 4.10.1 It is Possible to Teach Science More Effectively if Account Is Taken of the Learner’s Existing Ideas ......... 4.10.2 How Should Teachers Teach Science? .............................. Learners’ Knowledge Structures..................................................... 4.11.1 Knowledge Is Represented in the Brain As a Conceptual Structure ......................................................... 4.11.2 How Is Knowledge Represented in the Brain? ................. Individual Differences..................................................................... 4.12.1 Learners’ Conceptual Structures Exhibit Both Commonalities and Idiosyncratic Features ..............

115 116 116 117 117 118 118 119 120 120 121 122 122 122 123 123 125 125 126 126 128 128 130 131 131 132 133 133 134 135 136 137 137 138 139 140 142 143

Contents

xi

4.12.2

How Much Commonality Is There Between Learners’ Ideas in Science?............................................... 4.13 Researchers’ Representations ......................................................... 4.13.1 It Is Possible to Meaningfully Model Learners’ Conceptual Structures ....................................................... 4.13.2 What Are the Most Appropriate Models and Representations?......................................................... 4.14 Applying the Model of the RP ........................................................ 5

The Negative Heuristic and Criticisms of Constructivism in Science Education ................................................................................ Constructivism As Culturally Imperialist Movement That Is damaging to Many Traditional Cultures ............................. 5.1.1 Bowers’s Version of Constructivism ................................. 5.1.2 Levels of Cognitive Development and Ways of Knowing ....................................................... 5.1.3 An ‘Absurd’ Assumption .................................................. 5.1.4 Constructivism and ‘Content’ in the Curriculum .............. 5.1.5 Science Education Undermining Traditional Knowledge Systems .......................................................... 5.1.6 Constructivism and TEK ................................................... 5.2 The Philosophical Stance of the Constructivist Programme........... 5.2.1 Philosophical Commitments Informing Research ............ 5.2.2 Constructivism As a Label for a Research Paradigm ........ 5.2.3 Philosophical Critiques ..................................................... 5.2.4 Relativist Leanings in Constructivist Writing in Science Education ............................................................. 5.2.5 Flavours of Constructivism ............................................... 5.2.6 Glasersfeld’s ‘Radical’ Constructivism As an Instrumentalist Perspective ............................................... 5.2.7 Matthew’s Criticisms of Radical Constructivism.............. 5.2.8 Scerri’s ‘Philosophical Confusion’ ................................... 5.2.9 Equating Constructivism with Ignorance .......................... 5.2.10 Teaching Science As a Consensual Body of Knowledge .................................................................... 5.3 The Status of Theory in the RP ....................................................... 5.3.1 Natural History and Science in the RP.............................. 5.3.2 Validity of Theoretical Constructs .................................... 5.3.3 Needless Constructivist Jargon ......................................... 5.3.4 Confused Terminology ...................................................... 5.3.5 Empirical Support for Theoretical Constructs .................. 5.4 The Social Constructivist Perspective ............................................. 5.4.1 Criticisms of the RP .......................................................... 5.4.2 Different Flavours of Social Constructivism .....................

143 144 144 145 145

147

5.1

148 149 150 152 154 155 158 160 161 163 163 164 167 169 174 176 177 178 183 183 184 184 185 190 191 192 193

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Contents

5.4.3 Acknowledgement of the Social Dimension ......................... 5.4.4 Including Social Constructivism Within the RP ................... 5.5 The Research–Practice Interface....................................................... 5.5.1 The Criticisms ....................................................................... 5.5.2 The Research–Practice Debate.............................................. 5.5.3 Matthews’ Criticisms of Constructivist Learning As Unguided Discovery ........................................................ 5.5.4 Constructivist Approaches to Curriculum Development and Instruction ................................................ 5.5.5 The Adoption of the Constructivist Agenda in Classrooms ........................................................................ 5.6 Constructivism in Science Education As a Degenerate RP .............. 5.6.1 Constructivism As the Basis of a Progressive RP in Science Education ............................................................. 6

Building the Protective Belt of the Progressive Research Programme .............................................................................. 6.1

Students Understanding Science ....................................................... 6.1.1 Challenges of Exploring Student Thinking ........................... 6.1.2 A Rational Reconstruction of the Literature on Learners’ Ideas in Science ............................................... 6.1.3 What Ideas Do Learners’ Bring to Science Classes? ............ 6.1.4 What Is the Nature of the Ideas That Learners Bring to Science Classes? ..................................................... 6.1.5 Explaining Diverging Views of the Nature of Learners’ Ideas.................................................................. 6.1.6 How Much Commonality Is There Between Learners’ Ideas in Science?................................................... 6.2 Students Learning Science ................................................................ 6.2.1 Levels of Analysis of Learning ............................................. 6.2.2 How Does Knowledge Construction Take Place in Learning Science? ............................................................. 6.3 Teachers Teaching Science ............................................................... 6.3.1 Teaching Within the Domain Boundary................................ 6.3.2 Finding Out Where the Learners Are .................................... 6.3.3 Using Knowledge of Students’ Conceptual Resources to Inform the Teacher ............................................................ 6.3.4 Making Existing Thinking Explicit to Allow Exploration and Challenge .................................................... 6.3.5 Making the Unfamiliar Familiar ........................................... 6.3.6 Learning by Analogy............................................................. 6.3.7 Scaffolding the Building of Shared Knowledge.................... 6.3.8 Teaching As Developing a Community of Practice in the Classroom....................................................................

197 198 199 199 200 201 202 206 216 217

219 221 221 222 222 226 256 257 263 263 268 298 299 300 303 305 308 309 309 311

Contents

7

xiii

6.3.9 Consolidating New Learning .............................................. 6.3.10 Claims for Constructivist Teaching ..................................... 6.3.11 Constructivist Teacher Education? ...................................... 6.4 To What Extent Has the RP Addressed the Issues Set Out in the Positive Heuristic? .................................................................. 6.4.1 What Ideas Do Learners’ Bring to Science Classes? .......... 6.4.2 What Is the Nature of These Ideas? .................................... 6.4.3 How Much Commonality Is There Between Learners’ Ideas in Science?................................................. 6.4.4 How Is Knowledge Represented in the Brain? ................... 6.4.5 What Are the Most Appropriate Models and Representations?........................................................... 6.4.6 How Does Knowledge Construction (i.e. Learning) Take Place? .......................................................................... 6.4.7 How Do Learners’ Ideas Interact with Teaching? ............... 6.4.8 How Should ‘Constructivist’ Teachers Teach Science? ...... 6.4.9 A Progressive Research Programme ...................................

311 312 313

The Positive Heuristic: Directions for Progressing the Field ...............

325

7.1 7.2

327 328

7.3

7.4

7.5

7.6

What We Know Now ........................................................................ The Continuing Challenge for the RP............................................... 7.2.1 Post-positivist Approaches to Research: Fitness for Purpose .............................................................. Complexity: The Need to Study Individual Learners in Depth ........ 7.3.1 Exploring Cognitive Structure ............................................ 7.3.2 Techniques for Exploring Student Thinking and Cognitive Structure ............................................................. 7.3.3 The Development of Interview Methodology ..................... 7.3.4 Analytical Approaches ........................................................ Generalisability: The Value of the Methodological Pendulum ......... 7.4.1 Individual Differences – And Facilitating Expert Thinking .................................................................. Learning As a Process: The Need to Study Change ......................... 7.5.1 The Timescale of Learning ................................................. 7.5.2 Two Approaches to Studying Change in Learners’ Ideas .................................................................... 7.5.3 The Nature of Cross-sectional Studies ................................ 7.5.4 The Nature of Longitudinal Studies .................................... 7.5.5 Complementarity ................................................................. 7.5.6 The Conceptual Ecology: The Need to Study Learning in Its Mental Context ........................................................... Teaching As Facilitation of Learning: The Need to Study Learning in Classroom Contexts ...................................................... 7.6.1 Communities of Practice: The Need to Study Learning in Its Social Context.............................................

314 314 315 317 317 318 318 319 320 323

328 330 330 332 335 337 337 339 339 340 341 341 342 344 345 345 346

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Contents

7.7

7.8

7.9

Natural Experiments: The Need to Compare Across Educational Contexts ........................................................................ 7.7.1 Surveying Populations in Diverse Educational Contexts ..... 7.7.2 Sampling a Population .......................................................... Bringing It All Together: A Progressive Methodological Pendulum?.............................................................. 7.8.1 Testing Out Pedagogic Approaches ...................................... 7.8.2 Interdisciplinary Research: Drawing upon Insights from Cognate Areas .............................................................. Constructivism, Contingency and the Progressive Research Programme........................................................................

347 349 351 351 352 354 355

Final Thoughts: Is There Really a RP, and Does It Matter? .....................

357

References .......................................................................................................

361

Name Index .....................................................................................................

385

Subject Index ..................................................................................................

391

List of Figures

Fig. 3.1 Fig. 3.2 Fig. 4.1

The Necker cube ............................................................................ The main components of a Lakatosian RP .................................... Developing representations of students’ conceptual structures ..................................................................... Fig. 5.1 Possible meanings for ‘alternative frameworks’ ........................... Fig. 6.1 Representing knowledge in two domains ...................................... Fig. 6.2 A generalised alternative conceptual framework for chemical bonding (From Taber, 2000c) ................................... Fig. 6.3 Caricature of understanding ‘hot’ in terms of two distinct domains, for which knowledge is represented separately and with different characteristics ................................................... Fig. 6.4 Comparing two conceptual frameworks (From Taber, 1997) ........ Fig. 6.5 The role of p-prims as intermediate level knowledge elements in cognitive structure ...................................................... Fig. 6.6 A model of learning involving diverse conceptual resources. (From Taber, 2008e: 1038) ............................................................ Fig. 6.7 Conceptual resources contributing to different conceptual frameworks (Modified from Taber, 1999) ................... Fig. 6.8 An example of a shifting conceptual profile during learning (From Taber, 1999) .......................................................... Fig. 6.9 Categories of learning impediment in the typology of learning blocks .......................................................................... Fig. 6.10 Applying the typology of learning blocks ..................................... Fig. 7.1 Learning takes place in a multi-layered environment.................... Fig. 7.2 Dimensions of research studies: Degree of intervention; scale ......................................................... Fig. 7.3 Different strands of research contributing to an overall research programme ..........................................................

85 94 146 187 247 249

250 261 274 284 285 295 302 305 331 353 354

xv

List of Tables

Table 4.1 Table 4.2 Table 5.1 Table 5.2 Table 5.3 Table 7.1

The hard core of the RP can be identified in the seminal studies that initiated the programme ........................................... A characterisation of the positive heuristic of the RP (Based on Taber, 2006a) .............................................................. Two types of error in matching research to underpinning commitments ......................................................... Radical constructivism as intermediate to realist and relativist positions ................................................................. Foci of two main forms of constructivism .................................... Conditions for expecting different frequencies of common conceptions among students in distinct populations .....

124 124 162 173 182 349

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Introduction: The Scientific Research Programme into Learning Science

This book is about a ‘research programme’ (RP) within education – the RP that explores learning in science to inform science teaching. As education is more than anything else about teaching and learning, this RP is central to the field of Science Education. So this book is about themes that are of interest to anyone working in Science Education – whether as a researcher or teacher. The book is an account of the current status of our understanding, and of the RP that is seeking to move that understanding forward. The term RP is used here in a technical sense, as suggested by the philosopher of science, Imre Lakatos, and in particular suggests a particular way of thinking about research undertaken within a field that has a continuity and coherence, and which provides a basis for deciding whether a research tradition is scientific or not. Put simply (and this is explained in more detail later in the book) a RP that is developing and successfully testing new ideas according to a recognised plan, is considered as ‘progressive’. And ‘scientists’ – that is the kind of researchers who expect theoretical ideas to tend to fit, explain and predict empirical data – would be expected to make a rational choice to work in that kind of tradition (rather than, say, a tradition generating few new ideas, or one where each new data set requires ad hoc adjustments to theory to fit the evidence). I am writing this book as a natural science (chemistry) graduate, and an experienced school and college science teacher, who has made the transition to academic work in education. So I am now a social scientist. Part of my motivation in writing this book is a desire to set out how (following the model of Lakatos in particular) research in Science Education can be considered to be science. To make such a case I need to show that within Science Education there can in principle be RP that are scientific (and so progressive) just as in the natural sciences. However, that in itself is only part of my justification for writing this volume: for the power of the model of scientific RP (SRP) is that it offers heuristic guidance to researchers – to support researchers in different parts of the world in working within such a coherent tradition. Moreover it also offers a means of demarcation, a way of distinguishing the issues and questions that are on and off limits within the RP. I think that is especially important in Science Education at this time. For some decades ‘constructivism’ has been a ‘buzz word’ in Science Education, and in some countries where governments see a need to modernise their science education to support economic K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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Introduction: The Scientific Research Programme into Learning Science

development, it is seen as basis of reform. Yet some critics now consider constructivism has done its work, and has become just an empty mantra; whilst others see it as a potentially dangerous threat to the education of young people and to the well-being of their communities, or even to the economic future of their national economies. That range of opinions deserves some attention considering what is at stake. As will become clear in the book, although there is a discernible clear core to constructivist work in Science Education, the term is used in such different ways that it is not surprising it can be seen as revelation, revolutionary, passé, irrelevant and despicable by different commentators. By being clear about what the RP in learning science is actually about, it becomes possible to disentangle the research tradition from the myriad uses of the label ‘constructivism’. I consider myself to be a constructivist, but given that this can mean so many different things (some of which would not apply to my views), it may be that the term itself is no longer a useful label for the RP. This book will offer in some detail my view on what the core of that RP is, but it is useful to offer readers a preview of some central points: 1. The RP described here is commonly related to formal science education. 2. The RP is not about what should be taught, but how it can be better taught. 3. The RP assumes that it is meaningful to talk about the learning of individual science students.

A Focus on Formal Science Education Much learning about science is informal and occurs outside of classrooms and without contact with any officially nominated teachers. The RP is certainly interested in that learning, but a significant rationale for the programme (which is often supported from public funds) is to inform professional science teaching. Throughout this book the reader will meet the assumption that there is a normative version of what science students should know or understand. Governments often see science education as extremely important, and set out a formal curriculum. In most educational contexts, then, there is what I refer to as ‘target knowledge’, the way of understanding science topics that the teacher is charged with presenting and against which students are usually tested and graded. The teacher’s job is to do what is possible to shift students towards that understanding, and the role of science education research is to inform the teacher in her/his work. It should be noted, however, that understanding the target knowledge and being able to apply it need not be equated with ‘believing’ it, or with abandoning other ways of thinking.

It Does Not Matter What Is Taught in Science Lessons! I do not assume that governments or their agencies always get the target knowledge right. The curriculum is the outcome of political processes, which usually means some kind of compromise between the views of different interest groups. One may

The Structure of the Book

3

disagree with the priorities for what should be taught and learnt, or, if accepting them, still consider that the actual formulation of target knowledge is misjudged (in either pedagogical or scientific terms). Science is important to national economies, but probably science education today is most important because of the ecological problems people have caused, and the need for informed citizens who can exercise their democratic rights to influence governments around the world to respond in responsible ways. Young people in schools today will face important decisions not just as voters, but also as consumers and indeed as individual moral agents: decisions that can be informed by scientific knowledge and understanding. Getting the curriculum right is a highly important priority. However, despite passionately believing this, I consider it a rather orthogonal concern to the topic of this book. Arguments about which scientific ideas should be taught and learnt are vital, but cannot be determined within a RP into how students learn. Nonetheless, once those immensely important decisions are made, it is this RP that will help facilitate the teaching of whatever it is that is considered so important for young people to learn.

Individual Learners Are an Important Focus It is possible to develop notions of knowledge and learning which consider that knowledge and learning exist only in an interpersonal social plane, and some of these ideas will appear in this book. However, the RP discussed here has been framed since its start in terms of the construction of knowledge by individual learners, based on the assumption that learning processes lead to knowledge being represented in individual minds. There is, as the reader will find, plenty of scope in the RP to consider the social and cultural aspects of learning and knowledge development, but perspectives that exclude notions of the individual as unhelpful or irrelevant cannot fit within the RP, as they are inconsistent with the tenets around which it has been built. As will become clear in the book, the structure of a RP offers guidance on what we do not have to consider, as well as what we should be focusing on in our research. Ultimately such commitments, although they can be warranted and contested, have to be rejected or accepted. Readers who do not see any value in the notion of the individual as a learner (within a social and cultural context, of course) will not wish to work in the RP discussed here. That is not to say, that they may not find much of interest in the volume, and indeed I would welcome a parallel account of an alternative RP in Science Education built upon such ‘constructionist’ views. According to Lakatos, parallel RP are not only possible, but they can be healthy, offering an alternative for the scientists working in one tradition if it eventually ceases to be progressive.

The Structure of the Book The book is organised into seven chapters. (See Fig.1) The first three chapters set out the background to the argument that there is a SRP in Science Education. The fourth chapter offers a model of the ‘constructivist’ RP that explores the various

4

Introduction: The Scientific Research Programme into Learning Science

background

Chapter 1 The programme of research into learning in science builds upon work in the wider domain of enquiry that has identified key contingencies that channel the direction of students’ learning.

Chapter 2 Post-positivist perspectives on science accept that knowledge can have no absolute foundations, but seek to explain how science can still offer reliable knowledge. Within such perspectives, research in education can potentially be scientific.

Chapter 3 Research traditions can be modelled as Lakatosian Research Programmes (RP). RP can be evaluated in terms of whether they are empirically and theoretically progressive, and so truly scientific.

to the model of

application

A significant body of research from within Science Education can be understood as a RP into Learning in Science, with an explicit hard core of basic assumptions, and a positive heuristic that identifies key research questions and issues, and so sets out how the programme may be progressive.

Chapter 4

The negative heuristic of the RP provides the basis for determining which criticisms of constructivism in science education are rightly part of valid debate within the RP, and which fail to engage with the concerns of the RP. Chapter 5

A review of the current state of the RP’s protective belt demonstrates that the programme has been progressive, offering a rich set of refutable variants to make interpretations and predictions of an increasing complex database. Chapter 6

A review of progress in the RP supports an account of how the positive heuristic indicates priorities for future research, to ensure that the RP remains scientific, and continues to progress Science Education. Chapter 7

Fig. 1 The structure of the book

ways student learning in science is contingent upon features of the learning context (the individual’s own conceptual ecology located within a wider learning environment), and this is used in the final three chapters to consider criticisms of the research; to evaluate progress; and to suggest research priorities. Chapter 1 provides an overview of the field in which this RP is active, Science Education. Using the idea that the research field is located in a wider domain of enquiry, the chapter sets out the key areas of scholarship that have fed into the RP into learning science. Education as a formal discipline is quite recent, and the chapter demonstrates that discussions about the nature of learning have a long pedigree. These different strands of work had already highlighted some of the ways that what is learnt is contingent – for example, on existing knowledge – before the field of Science Education came into being. Chapter 2 looks at the nature of different approaches to research, and the debates about under what circumstances enquiry in a social Science, such as Education, can be considered to be ‘scientific’. Chapter 3 presents an account of Lakatos’s ‘methodology of scientific research programmes’, which offers a way of understanding the structure of RP, and evaluating whether they remain scientific or ‘progressive’. The chapter explains the terms used to describe RP: the hard core and protective belt, and the positive and negative heuristics. Chapter 4 builds upon the background in the earlier chapters to offer a description of a SRP in Science Education. The chapter presents a sketch of the development

The Structure of the Book

5

of a major international movement in science education, usually referred to as ‘constructivism’ or ‘the alternative conceptions movement’. This chapter includes the central premise of the book: that around the years 1978–1983, the basis of a RP was set out by a set of highly influential papers. An account of the key tenets of that programme (the ‘hard core’), and the key research questions to be explored are set out. This model of the RP is drawn upon in the remaining chapters of the book. At its heart the RP is an exploration of the nature of the contingencies that need to be considered to understand science learning, and a consideration for how teaching ought to be planned accordingly. Chapter 5 explores a range of criticisms that have been directed at ‘constructivism’ in Science Education. The term ‘constructivism’ is given such varied meanings and implications that it is quite easy for scholars to argue across each other. However, the Lakatosian model in Chapter 4 provides the basis for determining which criticisms are actually relevant to the RP. The ‘negative heuristic’ of the programme allows us to show that some of the criticisms aimed at constructivism do not apply (to the RP in Science Education), and so do not need to be considered within the RP. Chapter 6 explores progress in the RP to date. The ‘positive heuristic’ of a RP sets out the central problems to be considered and the directions that research should take. The result is the development of a ‘protective belt’ of theory around the programme’s central premises: the set of conjectures and tentative models which offer ‘refutable variants’ of the RP (i.e. theoretical ideas consistent with the hard core, but open to modification and replacement in the light of further research). The chapter shows that despite criticisms that ‘constructivist’ research has achieved little beyond cataloguing a good many quaint ideas children bring to science lessons, there has been a wealth of useful studies offering various models of aspects of science learning and teaching. The chapter discusses some of the studies that I consider to have been most significant in promoting exploration of central notions. I also draw upon examples from my own work to illustrate key ideas. It concludes that the RP can be considered to have been progressive, but that progress has been patchy, and much more work is needed before the programme’s potential for informing more effective science teaching can be fully realised. Chapter 7 builds upon the findings of Chapter 6, by considering the nature of the research needed to move forward to the next level of understanding. The characterisation of the achievements of the RP show that at the present time (a) the RP has offered a good many useful models (refutable variants) of science learning and teaching, but collectively these different models are often inconsistent; (b) the RP has collected empirical evidence that suggests that most of the models seem to be supported by some findings, but contradicted by others – and so demonstrated that the phenomena studied are too complex to be described by simple models which can be applied across the full range of science learning (of grade levels, topics, etc.). This chapter considers how research needs to be directed so that, collectively, future studies are able to unpack some of this complexity to begin to understand why and when certain teaching and learning contexts are best understood in terms of particular models. Ultimately, of course, one would hope for an overarching theory into which useful variants of the RP can be subsumed.

6

Introduction: The Scientific Research Programme into Learning Science

It was suggested above that ‘constructivism’ may no longer be a useful label for the RP. It may also be in the nature of a progressive RP that whilst it stays true to its most basic commitments, its own success in developing understanding around its central concerns may cause it to outgrow its initial characterisation. The RP is certainly based on a (psychological) constructivist tenet that learning is a process of building up knowledge, rather than somehow absorbing knowledge wholesale from teachers or other authorities. It is a moot point to what extent this is now taken for granted by science teachers, but it is hardly a matter of contention among scholars, even those who are highly critical of what they perceive as ‘constructivism’ in Science Education (and who refer to this undisputed basic principle as ‘trivial’ constructivism). If I were asked what is the key idea that the RP (and the wider domain of inquiry) has demonstrated, I think it would simply be that ‘what we learn is highly contingent upon a range of influences’ and it is this that makes the job of the teacher (and perhaps the science teacher in particular) so challenging. Of course, a key factor is what we already know and understand (but that begs the questions of how we learnt what we already know), and the extent to which it can be used to make sense of new information. Learning is contingent on properties of our cognitive systems; of our views about the nature and status of what we are being taught (Do we understand that theoretical knowledge is tentative, and models have limitations? Do we think that evolution contradicts core beliefs?); of the way our language dissects and reflects the world; of how we understand metaphors and analogies – and so much more. The RP into learning science has the job of making sense of how students come to have the science knowledge they do, in the light of all these contingencies, and how – given this highly contingent nature of learning – teaching can be designed to best shift student thinking towards target knowledge. When considered in this way, it seems unsurprising that three decades of work directed by the RP has left plenty of scope for researchers to make further progress in what is a highly complex, but fascinating, field of enquiry. Keith S. Taber Cambridge, 2008

Chapter 1

Science Education As a Research Field Within a Domain of Enquiry

Education is a relatively recent discipline that is centrally concerned with teaching and learning. Science Education as an identifiable field with a formal disciplinary structure (journals, conferences, chairs in universities, degree courses) is just a few decades old. Yet very quickly Science Education has become established, and has produced a vast literature related to teaching and learning in science – and indeed has produced specific traditions that can be considered as research programmes (such as a Piagetian programme focused on cognitive development, and a ‘constructivist’ programme focused on conceptual understanding). This has been possible because the field of learning in science is located within a wider domain of enquiry that encompasses philosophical investigation of key notions such as knowledge; psychological studies of learning and cognition; studies into the historical development of science and scientists’ individual thinking; and broader cognitive science scholarship looking at a wide range of issues such as the nature of mind, artificial intelligence and the role and nature of languages. These various areas of scholarship provide the field of Science Education with a broad source of ideas and findings. This chapter offers an account of this background, and in particular demonstrates that by the time Science Education became established as a research field, there was already a good deal of information available on the way learning is constrained and channelled, suggesting that what a student in a science lesson will learn will be highly contingent on a range of considerations.

1.1

A Research Topic: Learning Science

This book describes an area of educational research that has been the basis of considerable activity in Science Education over several decades. This is research into learning science, a topic area that has been the subject of thousands of studies, undertaken in many countries over many years (Duit, 2007). ‘Learning science’ does not here mean the science of learning – although that will certainly be part of the concern of the book – but learning in the science disciplines; learning about science; learning some science.

K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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Science Education As a Research Field Within a Domain of Enquiry

Many of these studies have focused on exploring aspects of student thinking about science topics, before, during or after, formal instruction. It could be argued that describing such studies as being about ‘learning’ is generous, as they are really studies of learners’ thinking patterns, their ideas. Learning is a process concerned with changes in knowledge and understanding, so strictly a study that merely investigates what students think or believe (or at least can suggest in response to a researcher’s questions) at one point in time should not be considered to be a study of learning. This is ‘fair comment’ when addressed to many of the individual research studies. However, one of the main assumptions underlying this book is that individual research studies are only valuable as part of a coherent programme of research. To appreciate the value of a particular study we have to see its contribution in terms of this wider context: the way it is conceptualised in terms of previous research; the way it raises questions or testable hypotheses for later studies; rater than as an isolated piece of work (Taber, 2007a, cf. NRC, 2002). Indeed, even when we may not explicitly acknowledge this, it is impossible to meaningfully evaluate any research without reference to some such context. From this perspective, studies that ‘simply’ seek to identify learners’ ideas about light and vision, or global warming, or the reality of atoms, etc., must be judged against their wider motivations. When we do this, it becomes clear that these studies are generally located by their authors within a context that clearly relates to learning science. It is also important to recognise that such explorations of student thinking are often (implicitly if not explicitly) evaluating students’ ideas against a normative standard – the curricular models that are set out as ‘targets’ for student learning (Taber, 2008d). These curricular representations of scientific models and theories define the subject matter of school or college science (Kind & Taber, 2005).

1.1.1

The Construction Metaphor for Learning

Even when the studies make no pretence at illuminating learning processes, they are often, nonetheless, undertaken in order to inform teaching. Such studies generally adopt (again explicitly or tacitly) an assumption that one determinant of learning is what the learner already knows or believes, and therefore evidence of the ‘current’ state of understanding can inform teaching. This might be called the constructivist doctrine – that new learning is contingent upon what is already known – and ‘constructivism’ is a commonly used label for the body of work being considered here. This term takes construction, i.e. building, as its root metaphor (Hacking, 1999), and as will be demonstrated through the book, the same label of ‘constructivism’ is used to refer to a range of viewpoints by different commentators who have diverse views on the nature of the building materials available for constructing knowledge. This is unfortunate, as there are many critiques of constructivism(s), and some of these are more pertinent to the research programme into learning science

1.2

Sharing Meanings for Key Terms

9

than others. Addressing major criticisms of ‘constructivist’ research (the work of Chapter 5) will involve some disentangling of this confusion to distinguish criticism actually engaging with what is essential to the research programme discussed here, from that which targets other meanings of the term. The constructivist programme in Science Education that forms the core focus of this book can be considered to be concerned with the contingencies that channel learning, and how these can be better understood to help teachers guide student learning. Arguing that knowledge of current understanding can inform teaching does not in itself make that knowledge ‘about learning’. However, the argument is that such studies can be part of what is needed to explore learning processes – if learning involves changes in knowledge and belief, then studies that describe students’ ideas can (in principle) contribute to that programme. Later in the book (Chapter 4) it will be shown that a great deal of this work can be understood as forming a ‘Scientific Research Programme’ (SRP). The notion of a SRP is a way of making sense of research traditions developed by the philosopher of science and mathematics, Imre Lakatos (1970). This particular way of thinking about research traditions will be explored in Chapter 3, but for present purposes, the reader is asked to accept the general argument in principle, that studies of students’ ideas about science topics can contribute to our understanding of how science is learnt.

1.2

Sharing Meanings for Key Terms

Before proceeding, it is important to acknowledge that a number of the terms already met do not necessarily have consensual and unproblematic meanings. Terms such as ‘learning’, ‘thinking’, ‘ideas’, ‘beliefs’ and ‘knowledge’ tend to be widely used in everyday talk with sufficiently shared meanings to facilitate effective communication. As in everyday conversation most English-speaking people have meanings for such terms that allow satisfactory communication, this would suggest that most people’s meanings are sufficiently aligned (or overlapping) for the terms to be unproblematic in such contexts. Even in professional contexts – teachers talking to each other, or reporting to parents, for example – statements such as ‘his subject knowledge is poor’; ‘she has a lot of interesting ideas’; and ‘the class has learnt very little since the start of the term’ are usually well enough understood to negate the need for tightly defining key terms. However, when considering what different scholars have to say about learning in science, we are concerned with claims that are sometimes contentious and apparently contradictory, and in this context it is important to set out what is meant by the words used. In a volume that presents an argument concerned with ‘learning’, ‘ideas’, ‘knowledge’, etc., these words take on more technical meanings, and need to be defined more tightly. It is worth exploring some of these terms at this early point, then, as the particular ways these words may be used will be significant for the various arguments considered in this book.

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1.2.1

1

Science Education As a Research Field Within a Domain of Enquiry

Learning as a Potential for New Behaviour

In this book, then, learning is considered to be a process through which a change in the potential for behaviour is brought about. This behaviour could be of different kinds, but the main focus of the book is conceptual learning, so an example from that realm might be useful. Consider an individual who might be asked to explain what a polymer is. It is possible to consider an experience (such as listening to a teacher’s classroom presentation, for example) that leads to some (for the moment, unspecified) changes in the person such that after the experience they have the potential to respond to a question such as ‘what is a polymer?’ differently than before. The process of change is here considered learning. Clearly the individual may never have reason to respond to the question ‘what is a polymer?’ in which case the potential may not be fulfilled. However, some change has taken place that could lead to different behaviour (e.g. different verbal responses to questions), and so learning has occurred. Although this way of defining learning refers to behaviour, this need not imply the ‘behaviourist’ approach that studies how stimuli lead to responses without conjecturing mechanisms in terms of mental states or events. The mental aspect of learning is very much a focus of the research considered in this book. This simple example illustrates a number of key points about the complexity of studying this topic. As learning produces a potential for changed behaviour, then in principle learning can occur without evidence of a change. Moreover, producing evidence of learning is not straightforward. Failure to induce changed behaviour cannot be considered to show no new potential (just not the specific potential to produce new behaviour in the precise conditions under which we seek it). Similarly, apparently new behaviour may not result from learning, but from the failure to establish the necessary conditions for eliciting the behaviour previously. It is also clear that another student in the same class could listen to the same teacher-presentation without undergoing any (or at least the same) change in potential for new behaviour. Moreover, our student who has learnt may not necessarily have learnt what the teacher intended or what the curriculum sets out as desirable. Although I have defined learning in terms of changes in potential for behaviour, it will be simpler to usually discuss learning in a more shorthand way. So, for example, consider a hypothetical youngster, Linnaeus, who had developed the potential to, under appropriate circumstances (such as being asked ‘is this alive?’ or ‘can you point to anything here that is alive?’), indicate that he considered animals but nothing else to be living. Consider next that this youngster underwent some sort of experience that brought about learning – perhaps spending time with his grandmother as she worked in her garden, perhaps a formal lesson at school – such that he was now (again, under appropriate circumstances) able to indicate that he considered there were two main groups of living things, animals and plants. It will be much more concise to say that Linnaeus learnt about a second class of living things (and to imply by this that the potential for different behaviour had developed).

1.2

Sharing Meanings for Key Terms

11

As suggested above, in the context of formal science education there is normally a set curriculum that specifies some form of ‘target’ for the learning that teachers are expected to facilitate. This might often be called the ‘target knowledge’.

1.2.2

Knowledge as a Label for What Is Currently Considered to Be So

Knowledge is a term used in different ways. The word ‘knowledge’ is sometimes reserved by philosophers for ‘true, justified, beliefs’ (Thayer-Bacon, 2003, Matthews, 2002). In this usage, a person must believe something to be true, and have good grounds to believe it to be true, and must be right that it is true, for his or her belief to be judged as knowledge. Whilst such a definition may be useful in abstract, it is clearly only possible to consider something to be knowledge using these criteria if we are in a position to recognise what is true ourselves. As some philosophers would argue that we can never be absolutely sure of what is true (as we will see later in the book), then we would have never been able to confirm anyone had any knowledge in this sense. Clearly, this is not how the word ‘knowledge’ is more commonly used. Such a definition would also be unhelpful when we consider the nuances of the “knowledge” we are concerned with in science education. Consider again our hypothetical example of young Linnaeus who considers (i.e. has ‘learnt’) that living things fall into two main groups, animals and plants. According to canonical science this is not a true belief, as there are considered to be five kingdoms of living things, so this youngster’s notions are deficient. We cannot therefore, by these standards, consider what has been learnt to be knowledge. It would be possible to argue about whether we could consider that Linnaeus does have knowledge that animals and plants form two groups of living things, even though his belief that animals and plants form the two groups of living things is false, but such a discussion may not be especially enlightening. This is particularly so considering that in education we often do not judge what children tell us in terms of some absolute standard of truth but rather in terms of what has been set out in a curriculum document. If Linnaeus was following a primary school science curriculum that set out knowledge of the living world in terms of two groups of organisms, animals and plants, it seems harsh to deny his learning as leading to a form of knowledge. The notion of knowledge as true, justified belief is linked to an assumption that in principle there can be some arbiter of what actually is true. Such an assumption may have seemed very reasonable with the apparent progress of the postEnlightenment project of the scientific revolution. For example, Newton’s laws of motion and ‘universal’ gravitation seemed to offer a model of what science would achieve – insights into a world that was knowable, and describable in simple relationships. Indeed, adopting a metaphor from available technology, the universe

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was considered to be clockwork. By the turn of the twentieth century there was a common view that science would soon enter a phase of tidying up details. Developments in areas such as relativity, complexity and – especially – quantum mechanics showed this was far from the case. So, for example, the acceptance of Einstein’s ideas on relativity showed that Newton’s great achievements were fundamentally flawed, and – by any reasonable judgement of what is true, justified, belief – simply could no longer be considered to represent knowledge of the world. Despite this, Newtonian mechanics continues to be taught in schools as an approved part of the curriculum, and to be tested in formal school examinations. Students are expected to know, understand and apply the ‘equations of motion’ based on Newtonian physics. Moreover, Newtonian mechanics is not taught as a historical model of what scientists used to think, but is rather presented as knowledge worth learning for its own sake. This is of course quite justified, for although we now believe that as descriptions of motion the Newtonian equations are not strictly ‘true’, they actually ‘work’ pretty well in most circumstances. In practice Newton’s mechanics is not usually considered wrong but rather to provide perfectly good approximations or models for many purposes. These may be inapplicable in particle accelerators and near black holes, but they do the job when predicting the motion of people and cars, and ships and planes on or near the earth. So ‘knowledge of’ Newtonian mechanics is certainly still valued. This suggests that the traditional philosopher’s notion of ‘true, justified, beliefs’ may not be the most helpful one when considering learning in science. Another way of describing this situation is to say that Newtonian mechanics may no longer be considered a perfect description of the universe, but it remains a highly useful tool providing its range of application is well understood. Indeed many models and theories in science may be best understood this way, as useful instruments when thinking about the world, rather than as true accounts of how the world actually is. Given that, as suggested above, ‘true’ knowledge may be at best an ideal, this may offer a more useful way to think about knowledge. In general, in this volume, references to the knowledge of individuals will be intended to imply something like Dewey’s (see §1.5.1) notion of the storehouse of interpretations and models of the world which can inform intelligent action – action based on past experiences. Those experiences will include direct empirical experience of the physical world (playing with toy bricks, gardening, building sandcastles, etc.), but will also include observing and engaging in conversations with peers, parents, teachers, etc., both directly and through interaction with media such as books, television, the Internet, computer games and so forth.

1.2.3

Beliefs, Ideas and Conceptions

It might be suggested that given the contended meaning of ‘knowledge’, it would be better to avoid the term and instead to use an alternative. Indeed, terms such as

1.2

Sharing Meanings for Key Terms

13

‘beliefs’, ‘ideas’ and ‘conceptions’ are commonly used – although in the research discussed in this book it is often the case that these terms may be used with an assumption of common agreed meanings that may sometimes be unwarranted. Where knowledge has been used for true, justified, beliefs, the term ‘belief’ can be used to refer to what an individual takes to be so, regardless of whether it is judged true or justified by a commentator. This might be quite appropriate in some areas of scholarship, but is problematic as an alternative in the present volume. In learning science, students demonstrate a wide range of ideas (more on that term, next) and commit to them at very different levels. These include both the ‘alternative’ ideas that originate from outside science and science education, and the so-called misconceptions where science teaching is misinterpreted; and also ideas presented in school instruction. Belief is often about a matter of degree, not a simple dichotomy. Indeed, in science, this is as it should be. Science teachers should not be asking students to believe that the earth is 4.6 billion years old, or that the universe was created in a ‘big bang’, or that the speed of light in vaccuo is invariant. Rather, that there is considerable evidence that the earth formed about 4.6 billion years ago; that a ‘big bang’ model of the universe is one cosmological model that has a good deal of explanatory power; that adopting the counter-intuitive idea that the speed of light is always observed as the same explains a good many phenomena, and has led to some interesting predictions that have been since confirmed. It might be argued that there is much taught in school science that can be safely believed: that mammals have a spinal cord; that sodium is an element; that copper conducts electricity. However, it is obvious even in these cases that such ‘facts’ are based upon either tautologies (how we choose to define mammals; chordates, etc.) or extended frameworks of ideas (what we understand by electrical conduction). Even a basic scientific term such as ‘element’ has not only shifted historically, but may not have a simple universal meaning today (Scerri, 2007). For example, whether the elements sodium and chlorine are considered to be present in the compound sodium chloride can depend upon how the compound (no pun intended) meanings of element as an essence, a pure substance or an abstract notion are emphasised in different languages. So, in England a student suggesting sodium was present in common salt would normally be considered ‘wrong’, whereas a counterpart a few kilometres away in France making the same suggestion in French would be likely considered correct (Cokelez, Dumon & Taber, 2008). If science teaching should be seen as more about teaching young people to appreciate the explanatory power of (rather than to ‘believe’) the products of science – laws, theories, models, etc. – then it is not their ‘beliefs’ that are central to our theme. One alternative term that has been used instead is simply children’s ideas (e.g. Black & Lucas, 1993). This term is seen as fairly neutral compared with knowledge or beliefs, and someone can have an idea without committing to it as something that is ‘true’. However, this degree of inclusion is something of a ‘mixed blessing’ – Hacking (1999: 10) refers to the word ‘idea’ as “a very unsatisfactory shorthand”. Science requires creativity, and the ability to generate a wide range of ideas can be important for this. However, just as we are not only interested in

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what students fervently believe when concerned with their learning in science, we are usually not interested either in the full range of ideas they might generate in relation to a topic. Rather, we are more commonly concerned with the subset of ideas that, whilst not taken as articles of faith, are considerably more than fanciful notions immediately dismissed. Here I am going to suggest the adoption of another term commonly used (but seldom tightly defined) in the Science Education literature in relation to students’ ideas, that of conceptions. For present purposes a conception will be considered a way of thinking about a subject that is considered to have some merit to the holder. So a student may sometimes strongly believe such a conception, but other conceptions may be more tentatively held or they may just be notions that are under active consideration as possibly useful ways of making sense of things. Conceptions, as I use the term, are of the form of propositional knowledge (sic, in the less formal sense adopted above) such that they can be verbalised: • • • • • • •

The earth is round Einstein was a genius There are two types of living things Mushrooms are neither plants nor animals Every moving thing comes to a stop eventually Sodium chloride contains the elements sodium and chlorine Chemicals react so that atoms can complete their electron shells

Conceptions, so understood, may or may not align with widely accepted scientific thinking and/or what is set out in a school or college curriculum. As conceptions are considered potentially viable ways of understanding the world, that are not necessarily strongly committed to, it is quite possible, indeed likely, that an individual might hold conceptions that are mutually inconsistent (i.e. judged from the individual’s own perspective). This would only be ‘irrational’ where the individual was strongly committed to (believed) several inconsistent conceptions: for where conceptions are tentative, work-in-progress, conjectures to be tested, or having uncertain ranges of application, it is perfectly rational to hold ‘inconsistent’ conceptions. Students may conjure up or be exposed to all kinds of notions: that electricity is a kind of fluid; that humans were produced on earth by an act of special creation independent of the origins of other species; that whales are large fish; that aliens from other planets are living among us and have infiltrated governments; that dogs and cats are the males and females of the same species; that plants do not respire during the day because they are busy photosynthesising, etc. However, where students acknowledge such ideas as fanciful and so not being useful in making sense of the world, they are unlikely to be significant to their learning about science. Whatever the originality or origins of such ideas, it is those that are adopted (not necessarily consciously) as being potentially useful for interpreting experience that are significant for learning of formal science. It is these I will refer to as an individual’s conceptions, and I will consider a students’ knowledge to be the set of such conceptions at any particular time.

1.2

Sharing Meanings for Key Terms

1.2.4

15

Thinking and the Mind

The discussion here of ideas and beliefs and conceptions needs to be tempered by acknowledging that there is a rather major difficulty in talking about a person’s ideas or knowledge or conceptions in this collective way, which suggests that such entities have an ontological status of some permanence. Such permanent objects would need to be located somewhere, and commonly the mind is considered to be the ‘place’ where these cognitive objects are kept and used. Yet we only know what a person knows or believes by asking them, and in practice this can only be done one question at a time. This is true even in the most direct case of introspection into one’s own ideas (so whilst we are thinking about our own position on the likelihood of alien abductions, we are not aware of our stand on whether it is useful to think of the earth’s biota as a kind of supra-organism). At any one moment in time it is only possible to be thinking about one thing. If knowledge was a static collection of disconnected conceptions then it might be possible – in principle at least – to catalogue a person’s ‘store of knowledge’ in a serial process, something like doing a stocktake in a shop. However, even in a shop it is difficult to do an accurate stocktake without closing the shop so that goods deliveries and sales are stopped whilst the inventory is made. Closing down the activities of the mind to do the stocktake is not an option – when the mind is inactive we have no access to its resources. The assumption above that experiences lead to learning, suggests that in principle the experience of undertaking any (mental) stocktake can actually change the stock. Given the time it would take to catalogue a mind, there could be considerable learning and so significant changes in that mind during the process. The mind itself is a useful concept, and like others considered here – learning, knowledge, etc. – is widely used without being well defined in everyday talk. As beings with consciousness, we each have a notion of what our mind is, and make assumptions that others have similar minds. Indeed acquiring a ‘theory of mind’ is seen as a key stage in normal human development (Goswami, 2008). There are a number of implicit characteristics that seem to be generally assumed in the way we tend to talk – what we might think of as a ‘folk’ model of mind. The mind is usually associated with the individual as a central part of identification as a ‘self’; it is considered to have some permanence, i.e. although people ‘change their minds’ on specifics there is an underlying continuity in that mind despite such changes; the mind is considered to either contain or at least have access to ‘contents’ such as memories and knowledge (in the sense discussed above); the mind allows interaction with the world (we perceive, we communicate, we deliberately act in the world); the mind is itself active: it allows us to plan, remember, reflect, judge, etc. One tradition in philosophy is to consider mind as something other than matter – something separate but able to know the material world. That is, mind has commonly been associated with the immaterial – with spirit or soul. This tradition has, since the advent of cognitive science as a field and advances in

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neuroscience, been increasingly complemented by a widespread assumption that the ‘mind’ phenomenon arises from aspects of brain function. Despite this, the long-standing influence of Cartesian dualism (seeing mind and matter as distinct) undoubtedly has an insidious influence shown in the common tendency to contrast mind with body. A detailed examination of the nature of mind falls outside the scope of a book such as this, but it is nonetheless important to set out how terms are understood here. The assumption made in this book is that thinking is a process that is somehow facilitated by some aspect(s) of brain structure, and is a form of information processing, some of which is open to conscious awareness. Further: that processing, i.e. thinking, although itself a transient experience, accesses and is facilitated by aspects of human brain structure that are robust (open to some modification, but not substantially changing in the short term). Some of these aspects of structure are largely common to all people, but there are also specific features reflecting previous experiences that are somehow represented in brains. Our topic here then concerns learning in science, understood in terms of changes in brains that facilitate new potential behaviors, specifically in terms of the relevant knowledge, i.e. available ways of making sense of the world, that support thinking about scientific topics.

1.3

Locating the Research Topic in a ‘Field of Study’

The research topic, learning in science, is a major concern of researchers in what is now widely acknowledged as a substantive field. There is little doubt that Science Education has established itself as a recognised field in recent decades, albeit a relatively young field (Jenkins, 2000b), within the academic discipline of Education. There are international journals, conferences, higher degree courses, etc., carrying the label ‘Science Education’. Activity in the field supports four major research journals (International Journal of Science Education; Science Education; Research in Science Education; Journal of Research in Science Teaching), as well as an influential reviews journal (Studies in Science Education). There are other international Science Education journals (as well as regional and national ones), and a good deal of research and scholarship in the field is also published in ‘general’ educational, cognitive science and interdisciplinary journals (including Science & Education). Within Science Education, there are the more specialised sub-fields of Chemistry Education, Physics Education, Biological Education, etc., which also have their own journals. For example, Chemistry Educators are supported by the Journal of Chemical Education published by the American Chemical Society, and the freeaccess Internet journal Chemistry Education: Research and Practice, published by the UK Royal Society of Chemistry and hosted on the Society’s website. There is also a specialist journal solely concerned with teacher education and development in science (Journal of Science Teacher Education).

1.3

Locating the Research Topic in a ‘Field of Study’

1.3.1

17

The Wider Domain of Enquiry

According to Duschl and Hamilton (1992: 1–2), connected fields (those ‘that explore a common ground of enquiry, that seek solutions to the same problem, that ask related questions, that draw from a related literature, and that share knowledge classes’) may be considered to make up a ‘domain of inquiry’. Duschl and Hamilton claim that Science Education is part of such a domain, as ‘since the 1950s advances in philosophy of science, cognitive psychology, and science education have led to the development of a domain that, for lack of any specific label, seeks to understand the dynamics of the growth of scientific knowledge’ (p. 7). As will be seen later in the book (see particularly Chapters 6 and 7), work in Science Education draws upon both of these other related areas. The cognitive sciences offer models of learning, and science studies (such as the history, philosophy and sociology of science) offer interesting parallels between the public growth of scientific knowledge and the development of scientific understanding in individual learners. Science Education is also increasingly being influenced by arguments about what is, or should, count as science and scientific knowledge. For example, increasing concern with environmental issues has led some to ask how the deep knowledge of specific local ecologies often possessed by indigenous populations can be taken into consideration. Such traditional ecological knowledge (TEK) or indigenous science (Aikenhead, 2006) does not take the form of formal scientific theories, often being inseparable from other aspects of culture – spirituality, mythology and everyday living (Thayer-Bacon, 2003). TEK offers valuable insights into management of food-stocks (for example) that complement formal scientific theories. When such formal science is related to highly complex systems it may not be directly applicable in the field without the local TEK (van Eijck & Roth, 2007).

1.3.2

The Relationship of Topic and Field

At one level we can understand the field of Science Education to be about the teaching and learning of science, for teaching and learning are the primary concerns of education, The distinctive focus of educational research must be upon the quality of learning and thereby of teaching. With few exceptions, the classroom, the transaction between teacher and learner in all its complexity, are what research should shed light upon. (Pring, 2000: 27)

So any research carried out in Science Education should ultimately relate to teaching and learning of the subject. However, as we have seen above when

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considering studies of student thinking, the immediate focus of a study may not directly link to processes of teaching and learning. So research within Science Education may focus on assessment techniques, student attitudes to science subjects, student perceptions of science-related careers, teacher beliefs about the nature of science or how learning occurs, what children attend to on visits to museums, or many other topics. All of these, and many other areas, can contribute to building up a knowledge base in Science Education that can inform science teaching. The logic of the argument made above is that for studies in any of these areas to be influential, they should be conceived, executed and reported within the context of an ongoing body of work that sets the agenda for research, what might be called a ‘programme of research’. Usually when a paper is submitted for publication in a research journal this is one of the issues that reviewers are asked to consider: whether the research is conceptualised sufficiently in terms of a research tradition already represented in the literature. Whilst a paper is expected to show some novelty for it to be published, a manuscript that explores totally original research questions that do not derive from previous research; and which does so in terms of concepts not previously used in the field, and through previously untested methodology, would be unlikely to be accepted in a peerreviewed journal. So although (i) all research in Education, and so in Science Education, should be related to the core concerns of teaching and learning; (ii) this book is about an area of research relating to learning in science; and (iii) it is considered here that teaching cannot be separated from learning, and so research on teaching inevitably links to learning issues; it does not follow that the area of research considered in this book includes all research undertaken within Science Education. Rather, different traditions of research are possible within a field and these can explore different perspectives, and can offer complementary insights. For example, when reviewing work on children’s ideas in science, Joan Solomon (1993a) offered four distinct perspectives that have informed studies. As an illustration, research into assessment techniques in science is important as assessment has a number of major roles in formal education (not least, offering summative judgements on students that may facilitate or restrict choice of further study and career). Some work on assessment (e.g. on developing diagnostic instruments informed by the literature of learners’ ideas in science) links directly with the key concerns of this book. However, a study into whether multiple choice items in physics with three distractors (i.e. offering a question with four possible answers, only one being considered correct) can be as effective as items with four distractors, whilst potentially offering useful findings to inform one aspect of science teaching, is not considered to fall within the topic area being explored here. This book then discusses an area of work in the field of Science Education that is central to the concerns of Education (teaching and learning), but does not encompass all research published within that field.

1.4

The Domain of Enquiry – Background to the Field

1.3.3

19

Progressing Science Education?

The key argument in this book is that a substantial body of research relating to learning in science may be understood to be part of a Research Programme in the sense used by Lakatos (1970). For Lakatos, a Research Programme (RP) is ‘scientific’ when it meets his criteria for being ‘progressive’. This book argues that the Lakatosian model allows us to see (a) that this area of research has been progressive over several decades, and to consider (b) how this programme of research can continue to be progressive. Although my focus here is with a subset of the published studies in Science Education, I believe this area of work is of central importance to all those working in the field. I would offer four arguments for this: 1. This particular area of research is central to the key concerns of the field, i.e. teaching and learning in science. 2. Although only one strand of research in Science Education, this body of work actually makes up a considerable proportion of work in the wider field. 3. This area of work has commonly been discussed as an identifiable sub-field in a way that is unique within the field, and indeed is sometimes discussed as if identical to the wider field. 4. If research in Science Education is itself to be considered ‘scientific’ then it should be organised and presented as having recognisable structures of a scientific field. The conceptualisation of research into learning science as a scientific RP therefore can stand as a model of how other areas of work in the field could (and arguably should) be understood. I would strongly argue, therefore, that this book is substantially about how to progress Science Education as a field of research, exemplified through a substantive body of research into learning in science.

1.4

The Domain of Enquiry – Background to the Field

Science Education is a field with a fairly short history. Peter Fensham (2004) has offered a very readable personal account of the development of the field. Internationally there are now many professors of Science Education, and many places to undertake higher degrees or research training in Science Education. However, this is a relatively recent development. It is difficult to offer any kind of precise date for the formation of Science Education as a field. Organisations representing science teachers have published journals since early in the twentieth century, and curriculum development in science has been an active area since at least the 1960s. It is clear that research into learning science that might be readily identified as part of ‘Science Education’ as a field did not arise from a scholarly vacuum. Rather, there are a number of traditions

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of thought and research which have influenced and been drawn upon in Science Education. This chapter offers a brief tour of some of the main areas of work that informed our field. Although this summary account offers some useful historical background, its role here is of more significance. The diverse areas of study touched upon here have all contributed to the way learning in science is conceptualised and so to approaches taken to enquiring into science learning. In particular it will be shown that a range of different perspectives from within the wider domain of enquiry have illuminated the different contingencies that impede or channel learning, and these perspectives have informed ‘constructivist’ thinking and research in Science Education. Influences originating in parallel strands of enquiry in cognate areas, have offered constructs and theoretical notions that can guide specific research approaches. This book argues strongly for seeing research into learning within Science Education that is commonly identified as ‘constructivist’ as making up a RP, and – more than this – a programme which still has much to offer. This argument is best appreciated by understanding how this RP is located within the wider ‘domain of enquiry’ where studies “ask related questions … draw from a related literature, and … share knowledge classes” (Duschl & Hamilton, 1992: 1–2). This broader perspective will inform the arguments met later in the book.

1.4.1

Public and Personal Knowledge

A theme that will infuse through much of the discussion presented in this book is the acknowledged difficult ‘relationship between “knowledge” as the possession of individuals and “knowledge” as the collective property of communities of “knowers”, e.g. professional scientists’ (Toulim, 1999: 54). Paralleling this distinction is that between how such forms of knowledge are acquired, i.e. how individuals come to knowledge and how scientific knowledge develops. Although, the acceptance of new material as canonical scientific knowledge has a strong institutional aspect (Ziman, 1968) this can only happen after individual scientists propose an argument for the new ideas or facts. The parallels between the ideas developed by children and those that have historically been considered candidates for scientific knowledge have been acknowledged (Piaget & Garcia, 1989). Subsequent chapters will discuss some key theories about the nature of science, that focus on the ‘public’ aspect of developing knowledge, so these theories are not discussed here. The brief accounts in this chapter focus on areas of work within the domain of enquiry that are primarily concerned with learning and the learner as an individual. These will be considered under headings relating to philosophical perspectives on learning; psychological studies of development; studies of aspects of cognition; the structure of ‘mind’; and work focused primarily on instruction and pedagogy. The argument that our focal topic is embedded within a wider domain concerned with ‘related questions … related literature … shared knowledge’ might lead the reader to expect that there will inevitably be considerable linkage

1.5

Philosophical Views on Learning

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and overlap between the material considered under my different headings. This is indeed so, and the structure of the following sections is primarily intended to aid readability, rather than set out a formal typology of studies within the domain.

1.5

Philosophical Views on Learning

Constructivist perspectives on learning have been influenced by work from both philosophical and psychological sources. Mathematics Education and Science Education as fields have been widely influenced by constructivist thinkers such as Ernst von Glasersfeld, although he has mischievously suggested that this was not always the case, To introduce epistemological considerations into a discussion of education has always been dynamite. Socrates did it, and he was promptly given hemlock. Giambattista Vico did it in the 18th century, and the philosophical establishment could not bury him fast enough. In our own time there was Jean Piaget. He really wanted to stay out of education but allowed himself to be drawn in – and we know what has happened to his epistemology at the hands of interpreters and translators. It seems that to discuss education from an epistemological point of view was a sure way of committing intellectual suicide. Recently, however, the world of education may have begun to change. (Glasersfeld, 1983: 41)

Philosophers have long discussed the source of human knowledge, and this has become a key theme for philosophy of science (see Chapter 2). In the Meno, Plato reports Socrates’s demonstration that even an untutored slave could understand theorems of geometry, without teaching – but simply by being asked a succession of questions. Socrates suggests that if the slave boy was able to tell of things he had never been taught then he must be in a sense remembering knowledge that was available to him prior to his present life, i.e. knowledge that his eternal soul had available, But if he always possessed this knowledge he would always have known; or if he has acquired the knowledge he could not have acquired it in this life, unless he has been taught geometry; … But if he did not acquire the knowledge in this life, then he must have had and learned it at some other time? … And if there have been always true thoughts in him, both at the time when he was and was not a man, which only need to be awakened into knowledge by putting questions to him, his soul must have always possessed this knowledge, for he always either was or was not a man? (Plato, 380 BCE)

Socrates is reported as arguing that ‘without anyone teaching him he will recover his knowledge for himself, if he is only asked questions’, and concluding that the slave boy’s knowledge of geometry was innate. Readers will not necessarily agree that ‘only asking questions’ implies ‘without teaching’, for Socrates and Plato use dialogue in a way that might well be described as ‘scaffolding’ these days (see the references to the work of Vygotsky and Bruner below, §1.6.2 and §1.9.3), and is certainly part of the approach used everyday by teachers (Edwards & Mercer, 1987) in many Education systems (see §6.3.7). Socrates’s demonstration is at the heart of the limitations of deductive logic, a theme that links to questions of scientific methodology, i.e. how one can ever move

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beyond what can be logically deduced from what one already knows (see §2.3.1). The debate about the extent to which knowledge is innate continues to this day (Elman et al., 1998). Kant’s philosophy, for example, assumes some basic categories (such as space and time) innate to the human mind (Jeans, 1943/1981). Such issues may seem of remote relevance to classroom science teaching but are actually pertinent to the nature of human knowledge, and the means by which we can come to knowledge (and the necessary constraints and biases acting when we learn). Socrates explained innate knowledge in terms of a human soul, where today we are more likely to look for evolutionary explanations, i.e. to explain the nature of the any innate aspects of human knowledge in terms of natural selection acting upon ancestor humans (and their non-human precursors). On this view, evolution has equipped us with apparatus for surviving and thriving in the environment. Such apparatus may unfold in individual development to support increasing sophisticated problem-solving capacity (e.g. as in Piaget’s model, see §1.6.1 below); and may bias us to perceive the environment in certain ways (see the sections on the gestalt theorists, §1.7.2, and the structure of mind, §1.8, below). From an evolutionary perspective, such innate knowledge does not have to be ‘true’ in any absolute sense, but simply has to have survival value in the context of the particular environments where it was selected, which are not such environments as modern technologically sophisticated societies or formal school classrooms which have only existed for a few generations (Geary, 2007). This view suggests that humans may commonly be biased to come to certain forms of knowledge that may or may not be considered ‘correct’ from a scientific perspective. This clearly has significant consequences for school science learning, leading to ‘intuitive physics’ and to perceptual biases towards recognising certain ‘natural kinds’ (Keil, 1992; Karmiloff-Smith, 1996) which may be at odds with curriculum knowledge.

1.5.1

Dewey’s Pragmatic View of Knowledge

One influential thinker who adopted such an approach was John Dewey. Dewey questioned the mind–matter dualism that was commonly assumed in epistemology, the branch of philosophy concerned with how we can develop true knowledge. Since Descartes, a common starting point for thinking about knowledge was an assumption that mind and matter were fundamentally different, and that the task of epistemology was to explain how minds can have true knowledge of an external material world. Dewey found it more helpful to think about the individual as an integral part of the world, acting in it, and being acted upon in a ‘transactional’ model. That is, the individual was part of a developing system, acting in the environment and so inevitably changing the environment and also being changed (Biesta & Burbules, 2003). From Dewey’s ‘pragmatic’ perspective the individual built up knowledge of the world (that he or she was a part of) as a result of this experience of acting in the world, and so the individual’s knowledge was the product of experiencing the outcomes of previous actions, and acted as the basis for making decisions to guide

1.5

Philosophical Views on Learning

23

future actions. The term action here is an inclusive one – it could be a grasping for a toy, attracting the attention of the mother, responding to a school test question, submitting a scholarly paper to a journal, giving consent to a surgical operation, etc. As the world is changing all the time, the current context is never entirely identical to previous situations, and so such knowledge can never be final (i.e. offer totally assured direction for present and future actions). From such a perspective, knowledge is not seen as a true representation of an external world, but as a set of tools for guiding action. Dewey thought his ‘transactional’ approach reflected that of science – an empirical activity where scientists transacted with nature, informed by the knowledge developed in previous encounters but always prepared to revise their understanding of the world. Scientific knowledge, like personal knowledge, was a set of tools acquired from previous experience that can guide our next action in the world. Taking such a meaning for ‘knowledge’ means accepting that different individuals will develop different knowledge depending upon their past experience, and so Dewey’s approach has been considered be relativist, i.e. seeing knowledge as relative to particular standpoints. In a sense this is clearly so, but this is only problematic if knowledge is expected to comprise ‘true’ accounts of an objective external world, when what is counted as knowledge must be the same for everyone. Dewey’s pragmatic approach does not argue that different (and potentially inconsistent) accounts of the world should be seen as equally valid descriptions of an objective universe: just rather that what may be sensibly taken as the basis for informing action by any individual will be contingent upon their previous experiences, which will be a unique set of experiences and an infinitesimal subset of the possible experiences human beings may have. Sometimes perspectives such as Dewey’s may be called a ‘qualified relativism’ (see §3.3.3). A key point to appreciate about such contingently acquired knowledge is that it not only depends upon unique personal experience, but also has an iterative nature. Acting in the world provides experiences that are understood in certain ways and that provide guidance for future action – the individual starts to build up mental models of how their world is – and which therefore act as the starting point for interpreting future experiences. The individual’s knowledge is certainly fallible – open to be changed in the light of further experience – but, in general, our experiences are capable of being interpreted in many possible ways, so what an individual develops is knowledge that offers workable (rather than ‘true’) models of the world.

1.5.2

Glasersfeld’s Radical Constructivism

Ernst von Glasersfeld is known for his advocacy of a perspective labelled ‘radical constructivism’. Glasersfeld is building upon a tradition of thinkers who can be considered to offer support to a ‘constructivist’ perspective on learning. One of these is Dewey himself (Evetts, 1973: 33; Hyland, 1993: 94), for whom ‘education was the construction and reorganisation of experiences that add meaning and that increase

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one’s ability to direct the course of subsequent experiences’ (Apple & Teitelbaum, 2001: 180, present author’s emphasis). However, the origins of the constructivist perspective are ancient (Russell, 1961: 775; Clark, 1968: 181, 187–8; Evetts, 1973: 33; Egan, 1984: 28), and can be traced back to at least as far as Plato and Socrates, and other significant figures would include Jesus who taught with parables to contextualise abstract ideas; and Rousseau who had a model of education based on a view that ‘knowledge comes from the senses, and that children should engage actively with a well organised environment, and learn by interacting with it’ (O’Hagan, 2001: 56). Glasersfeld himself has highlighted the work of Vico, ‘who considered human knowledge a human construction that was to be evaluated according to its coherence and its fit with the world of human experience’ (Glasersfeld, 1992). Glasersfeld describes his own position of radical constructivism – ‘a theory of active knowing, not a conventional epistemology that treats knowledge as an embodiment of Truth that reflects the world “in itself”, independent of the knower’ – as based around two key principles (Glasersfeld, 1988: 1), • Knowledge is not passively received either through the senses or by way of communication, but it is actively built up by the cognizing subject. • The function of cognition is adaptive and serves the subject’s organization of the experiential world, not the discovery of an objective ontological reality. This reflects Dewey’s philosophy as referring to ‘personal knowledge’ that has practical utility to the knowing subject. So Glasersfeld considers knowledge as relative to the active knower, rather than in terms of something that can be known to be ‘true’ by some objective means. This leads to a view of the teacher’s role not as a source of transferred knowledge, but rather in terms of supporting the process of building up knowledge: ‘to help and guide the student in the conceptual organization of certain areas of experience’ (Glasersfeld, 1983: 67). Glasersfeld highlights the importance of diagnostic skills in identifying a student’s current thinking, a process involving the teacher forming mental models of the student’s existing knowledge. For Glasersfeld, the teacher needs to have both an awareness of the student’s current understanding and good subject knowledge – ‘an adequate idea of where the student is and … an adequate idea of the destination’ – as both are needed to guide the student towards target knowledge.

1.6

Influences from Psychological Studies of Development

As well as being influenced by philosophical scholarship about the nature of knowledge and learning, Science Education as a field has drawn upon psychological studies of learning. Studies of learning are traditionally located in Psychology, and to some extent Education is seen as more of an “applied” discipline, that might look to apply psychological findings to schooling and other learning contexts. This certainly occurs, although the extent to which educational studies of learning link with psychological research is variable.

1.6

Influences from Psychological Studies of Development

25

Within Science Education, there are studies of science learning that make strong explicit links to psychological concepts and findings, whereas others have no explicit linkage. Similarly, there are studies of learning from within psychology that have used scientific contexts, and these do not necessarily link to work in Science Education. One explanation for this stage of affairs would be to point to institutional factors, so that academics in Education and Psychology departments work in largely different professional worlds, leading to what might be referred to as distinct ‘paradigms’ or ‘disciplinary matrices’ (to draw upon Kuhnian terminology – see §2.4.1), with different priorities and aims, methodological preferences and so forth. Whilst there is much merit in such an explanation, it need not be seen as being a cynical viewpoint where primarily social factors have dominated intellectual concerns (although undoubtedly social factors have some influence). Rather, we can explain this as a perfectly rational state of affairs. The concerns of psychologists researching learning would necessarily be in general terms, as befits the nature of the science. Early work in this discipline, therefore, often had the character of exploring artificial learning tasks (e.g. remembering nonsense syllables) in ‘laboratory’ conditions. Much of this work was not immediately of use to inform teaching, and did not offer useful starting points for educational researchers interested in learning in classroom contexts. The psychologists were simplifying and controlling the phenomena they were studying, as a perfectly sensible approach to start to develop models of very complex phenomena. This does not apply to all avenues of psychological research, but certainly reflects much work in the field (e.g. the behaviourist school, see §1.7.1). However, some psychological approaches were more in tune with the values of educational studies, and had much greater influences on educational research (and practice). Some of the most influential are discussed below.

1.6.1

Piaget’s Construction of the Child’s World

Jean Piaget was one of the most influential researchers from outside Science Education to study aspects of thinking and learning in scientific topics. Piaget is seen as a psychologist (although this was not how he chose to characterise his work), and his primary interest is better considered to be development rather than learning. That is, Piaget was not particularly interested in processes of teaching, but rather in the ‘natural’ development of human cognition. Piaget considered himself a ‘genetic epistemologist’, and was concerned with the ‘typical’ course of cognitive development that people passed through, and which was to a significant extent determined by our biology (Piaget, 1972b), The theory … Jean Piaget called Genetic Epistemology. The name was not chosen at random. He wanted to make clear that he intended to analyze knowledge as it developed in the growing human mind, and not, as philosophers usually have done, as something that exists in its own right, independent of the human knower. (Glasersfeld, 1990: 1–2)

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Piaget (1972b: 17) described his theory as ‘an account of an epistemology that is naturalist without being positivist … and that above all sees knowledge as a continuous construction’. For Piaget, there was a universal pattern of cognitive development that was part of our genetic inheritance as human beings. Piaget is best known for proposing a ‘stage-theory’ of development (Beard, 1969; Crain, 1992) that has been summarised as ‘children of a given age are more likely to demonstrate similarity of [mental] structures than children of different ages’ (Brown, 1977). Piaget developed his model, over many studies reported in a large number of publications, in terms of identifiable stages in human cognitive development. A ‘hard core’ commitment of Piaget’s programme of work was that all normal people passed through the same major stages in an invariant sequence. This ordering was fixed because each stage of development gave rise to structures that enabled more sophisticated actions on the environment, the world; that in turn provided the basis upon which the next stage could develop. Piaget’s work has been widely reported and reviewed (Beard, 1969; Kitchener, 1992; Bliss, 1993, 1995), and the details of his scheme have been widely criticized (Donaldson, 1978; Pope & Gilbert, 1983; Sugarman, 1987; Sutherland, 1992). Nonetheless, he undoubtedly had a very significant influence, and his work is still used today, e.g. providing a key foundation for the ‘cognitive acceleration’ movement in Science Education (§1.10.2). One of the most significant findings of Piaget’s programme of genetic epistemology was that the type of thinking most characteristic of science, abstract logical thought that Piaget termed ‘formal operations’, was not usually fully attained until well into the secondary school years (if at all). To the extent that Piaget’s model was accepted as valid, it clearly had important implications for the teaching of science. According to Piaget, the forms of thinking possible are determined by the learner’s stage of cognitive development. As Bodner (1986: 873) explains ‘Piaget argued that knowledge is constructed as the learner strives to organize his or her experiences in terms of preexisting mental structures or schemes’. For Piaget, learning is contingent upon the presence of necessary cognitive structures that develop during intellectual maturation. Just as interesting as his overall findings were Piaget’s search for methodology that would give him insight into children’s minds, including the clinical interview that has since been adopted and modified in Science Education research (Gilbert, et al., 1985, see §7.3.3) and some of the specific data he collected in his studies. The nature of Piaget’s focus on developing thinking meant that a good deal of his work explored how children of different ages responded to tasks that fell within science and mathematics – although his work was wide ranging, looking for example at moral development. For Piaget a newborn can only ‘think’ through his or her actions on the world – sucking, crying, pushing, etc. and has no formal concepts with which to understand the world. Yet the adult is able to use symbolic language to refer to abstract notions such as time and space, force and energy, and to appreciate physical principles such as conservation (that in some sense there is the same amount of orange juice when it is poured from the jug into a number of glasses – despite the somewhat different appearance after the operation).

1.6

Influences from Psychological Studies of Development

27

Pope and Gilbert (1983: 196) have described the ‘essence’ of Piaget’s epistemology as being ‘constructivist’. Somehow the infant has to ‘construct’ mental models of the world, starting from perceived regularities in the sensory impressions that came to be associated with particular motor actions. (We might give examples such as ‘I put my thumb here in my mouth, and my thumb feels damp’, but of course the infant does not yet have such a language to codify experience in this way.) Piaget wrote of the ‘myth’ of the sensory (or even perceptual) origins of scientific knowledge, and emphasised his view that the role of intelligence was to ‘transform’. He believed that knowledge was formed through operating on perceptions with logico-mathematical frameworks (Piaget, 1972a). There is a parallel here with Dewey’s ideas considered above (§1.5.1). Piaget demonstrated that children who have not undertaken formal instruction might still have constructed their own ideas about phenomena they experience in the world and their own meanings for words as they acquire language (e.g. Piaget, 1929/1973). Piaget and his co-workers undertook a wide range of empirical studies to explore what children made of various phenomena and situations. Some of this work was more naturalistic, based on observation or questioning in an everyday context, and some was in a clinical setting using research protocols designed for the purpose. Piaget found that children offered a range of ideas about the world at odds with accepted scientific thinking. So, in The Child’s Conception of the World, Piaget (1929/1973) reports various youngsters suggesting that • • • • • • •

The sun was given its name by the sky Walking causes the moon to follow us A twisted string knows it is twisted and wants to unwind A bicycle knows when it is moving because it feels the ground beneath it A fire is alive because it moves Clouds are made of the smoke produced by thunder Marbles won in a game were more likely to be lost in subsequent games, as they would have a tendency to return to their previous owner

Some of these ideas might be considered as ‘magical’, and are not too dissimilar from folk beliefs that have been identified in some societies. For example, how eating slippery foods during pregnancy may be considered to make birth easier (George & Glasgow, 1988). Although Piaget was not primarily interested in schooling, some of his examples clearly illustrated that children could come to school holding ideas that might be at odds with the target knowledge in the science curriculum. This work pre-empted much of the later research into learners’ ideas in science from within Science Education (e.g. see §6.1.3). Two key points about Piaget’s approach which can be seen to be reflected in much of the later (including current) thinking in Science Education were his focus on conjectured mental structures, something antithetical to mainstream ‘behaviourist’ experimental psychology through much of the first half of the twentieth century, and his basic constructivist position that individuals have to somehow construct their worldviews by acting on the world and interpreting it through their existing mental frameworks.

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Science Education As a Research Field Within a Domain of Enquiry

Criticism of Piaget’s Focus on the Individual Knower

Piaget’s early training was as a scientific naturalist and he conceptualised the epistemic subject (a typical human) as an animal developing in its environment. It is often suggested by critics that Piaget’s writing largely failed to make explicit the extent to which that environment was not just physical, but also had significant cultural and linguistic aspects (Bowers, 2007). Others have argued that Piaget offered a general model, but also “differentiated between physical, logico-mathematical, and social knowledge” (Bodner, 1986: 873). Indeed, some of Piaget’s studies were undertaken in social contexts, such as the method he reported for observing a child in school: ‘two of us followed each a child (a boy) for about a month at the morning class at the Maison des Petits de l’Institut Rousseau, taking down in minute detail and in its context everything that was said by the child’ (Piaget, 1959/2002: 5). In Piaget’s programme the unit of analysis tends to be the individual and his or her mind. However, Glasersfeld (1989: 4) comments that ‘to make the Piagetian definition of knowledge plausible, one must immediately take into account (which so many interpreters of Piaget seem to omit) that a human subject’s experience always includes the social interaction with other cognizing subjects’.

1.6.2

Vygotsky and Scaffolded Construction of Our Worlds

Another important psychological RP that was initiated in the early twentieth century (but largely unknown in the West at the time) was based in the Soviet Union (i.e. the USSR). The early Soviet Union represented a ‘brave new world’ where collectivism brought the benefits of what could be achieved by working together, instead of working for the benefit of some arbitrary ruler: a perspective expected to permeate all aspects of society. As Sutton (1983: 203) observed, ‘Soviet psychology exists to advance the remaking of humanity: its concern with children is not simply to record and understand how they develop but to contribute to the mutability and transformation of that development’. Whilst science, including psychology, along with personal freedom and economic growth, would in time suffer from over-adherence to communist dogma, the early days of the USSR offered an exciting time for intellectuals to contribute to their hard-fought new ‘democratic’ society. Lev Vygotsky (or Vygotskii) was contemporary with Piaget, although whereas Piaget lived a long and productive life, Vygotsky died tragically young (becoming ill at 24 and dying at age 37). Vygotsky was something of a polymath, who ‘managed to complete a law degree, write a dissertation on the psychology of art, teach and publish literary work before turning his attention and creativity to fundamental questions of human development and learning’ (Newman & Holzman, 1993: 5). In his relatively short career Vygotsky worked on a wide range of issues and problems. His work had a particular focus on what would now be called children with ‘special education needs’, but Vygotsky wrote about a wide range of topics in psychology, pedagogy and beyond: ‘he was also a defectologist, a skilled clinician, a teacher, an innovator in the philosophy

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and methodology of science and not inconsiderable figure in the development of Marxist thought’ (Sutton, 1983: 190). One of his topics of interest was memory, and Vygotsky’s daughter wrote of how he would sometimes, demonstrate to us his ability to remember large numbers of words. We would, working together, compile a list of 100 words … and hand it over to Lev Semonovich [Vygotsky]. He would slowly read each word, return the list, and then offer to recite it in any order. To our amazement and joy, he would, without mistake, repeat all the words on the list from beginning to end, and then repeat them in the reverse order. Then we would ask him to reproduce the 17th, 43rd, 61st, 7th, and so on, word, and he, without difficulty and without any mistakes, would do it. (Vygodskaia, 1999: 6)

Such feats of memory are similar to those reported in the case of a mnemonist studied by Vygotsky’s colleague and student Alexander Romanovich Luria (1987). However, Vygotsky is best known (in the West at least) for two books in English translation that summarise some of his key ideas. Thought and Language (Vygotsky, 1934/1986), sometimes translated as ‘Thinking and Speaking’, and Mind in Society (Vygotsky, 1978), the latter effectively a posthumous compilation of related writings, offer a useful complement to Piaget’s work. Vygotsky’s programme was socio-historical, i.e. it took the perspective that human psychological developments are mediated by culture and contingent on history (Cole, 1990). Vygotsky believed that from the age of about 2, development is closely influenced by the young learner’s interactions with other minds (Crain, 1992). Vygotsky was concerned with the way people, and so culture, provide a context for the construction of our understandings of our worlds. Vygotsky emphasised how teachers could lead pupils to higher levels of conceptual understanding than they would otherwise achieve (Edwards & Mercer, 1987: 20), and he considered any independent learning context, ‘without the assistance of others, without demonstrations, and without leading questions’ (Vygotsky, 1978: 80), to be – at least from an educational perspective – a contrived situation. Assessment by the individual student taking a test unaided was therefore seen as less useful than assessing a learner through a ‘teaching experiment’ where the success in acquiring some new generalised skill under conditions of carefully controlled support is documented (Sutton, 1983). The purpose was to identify the learner’s ‘zone of next development’ or ‘zone of proximal development’ (ZPD). Vygotsky considered how learning can be supported and facilitated (which can be considered to be a definition of teaching) by an adult or a more knowledgeable peer, through the cultural tools that allow shared understandings to be negotiated. The most powerful of these tools is language. The extent to which the focus of learning is on the individual or social processes (sometimes seen as ‘Piaget vs. Vygotsky’), has been an important theme in research into learning in science (see §5.4).

1.6.2.1

Two Types of Concept

The term concept is widely used in the cognitive sciences, although as with other key terms it is understood in a number of ways. A simple approach to concepts is that

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they are (or define, or describe) mental categories, so if a person could decide whether something is a dog or not; an element or not; a scientific theory or not; an abstract notion or not; etc., then they have a concept of dog; element; scientific theory; abstract notion; etc. The term concept has been defined as ‘an abstraction or general notion that may serve as a unit (or an “atom”) of a theory’ (Gregory & Zangwill, 1987). Vygotsky differentiated between ‘spontaneous’ concepts (which were not formal nor defined verbally) and ‘scientific’ concepts which were defined by culture and formally taught, and he saw conceptual development as involving building a synthesis between these intuitive and given concepts (Vygotsky, 1934/1986). The common translation of Vygotsky’s term as ‘scientific concepts’ does not necessary imply concepts from the natural sciences, and the alternative translation ‘academic concepts’ may better imply his meaning. Vygotsky disagreed with Piaget who considered such ‘reactive’ concepts as of limited interest to enquiries into children’s thinking, which should focus on spontaneous thinking. Vygotsky accepted the distinction, but emphasised how spontaneous and academic concepts had to be considered as part of a ‘single system of concepts formed during the course of a child’s mental development’. According to Vygotsky (1934/1994: 361), Piaget ‘only sees the gap, not the connection’. So in Vygotsky’s model, acquisition of meaningfully understood advanced concepts would seem to be contingent upon (i) access to the abstract concept communicated formally (i.e. symbolically), and (ii) having direct relevant experience to form the spontaneous concept that can be related to the academic concept, as well as (iii) the learner being able to relate the two (cf. Ausubel, see §1.9.2).

1.6.2.2

A Sociocultural View of Learning

Vygotsky’s colleague Luria (1976) undertook important field work in Soviet Asia (Vygotsky was not well enough to travel to the research sites), where the USSR was transforming society by introducing formal education, and showed that ways of thinking that are ‘naturally’ attained by all normal adults in literate societies were not common in non-literate communities. Some later commentators have criticized Luria’s stance as being biased to see the thinking patterns he found where ‘the masses had lived for centuries in economic stagnation and illiteracy’ (Luria, 1976: vi) as more ‘primitive’ than those characteristic of educated adults (Smagorinsky, 1995). Whilst Luria’s work did not demonstrate that the peasants in Uzbekistan and Kirghizia were incapable of following formal logical arguments, it certainly suggested that ways of arguing and drawing deductions that are taken for granted among ‘educated’ adults were culturally transmitted, and not part of some ‘natural’ course of human cognitive development. Vygotsky and his colleagues’ ‘socio-cultural’ or ‘socio-historical’ view on conceptual development – ‘materialist, dialectical and consistent with Marx’s socio-historical principle that human mental characteristics have been formed in the process of historical and social development’ (Sutton, 1983: 194) – led to the development of ‘Activity theory’ which has become widely influential in Education (Engeström, et al. 1999).

1.6

Influences from Psychological Studies of Development

1.6.2.3

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An Example of the Interaction of Science and Culture

Despite the significance that is now assigned to Vygotsky and his school, and the very real influence on activity theorists (Ryle, 1999), parts of Vygotsky’s programme of work were curtailed, and his writing sidelined (and for many years largely unknown outside the Soviet Union). Vygotsky’s early death meant he did not experience the irony of how the ‘thought-police’ mentality of Stalinist Russia (as part of the USSR) led to his work going out of favour and effectively being ignored for decades. It is well reported that under Stalin the communist party operated an ideological control over the institutions of science (Frolov, 1991). The most infamous case is the imposition of a pseudo-Lamarkian genetics under Lysenko (see §3.10.1). In a similar way, from the 1930s, the work of Vygotsky and his group came to be considered as derived from ‘bourgeois’ sources, as Vygotsky drew upon ideas from psychoanalysis, gestalt therapists and other Western movements, at a time when ‘Soviet psychologists were expected to derive psychological categories directly from the works of Marx, Engels, and Lenin’. This led to Vygotsky’s work being judged ‘eclectic’ and ‘erroneous’ (Kozulin, 1986: xliii). Key lines of enquiry were effectively banned by the 1936 ‘Decree against Paedological Perversions’ in the education system (Sutton, 1983: 1093). Vygotsky, who was of Jewish origin and had suffered the anti-Semitic rules in Imperial Russia, and who had embraced the new ‘fairer’ Soviet society, spent his final years subject to ideological censure. However, following the liberalisation of the Soviet system, Vygotsky’s work was championed by his colleague Luria, and popularised in the West, especially by the influence of Jerome Bruner. Vygotsky’s work highlighted how the (‘scientific’) concepts available to an individual are constrained by socio-historical context. Individuals learn in a social and linguistic context, and what they learn is contingent upon the conceptual resources available in that context.

1.6.3

Kelly’s Personal Constructs of the World

So where Piaget focused on the individual ‘epistemic subject’, Vygosky and his colleagues explored the way culture channels the individual’s construction of the world towards common understandings. However, even within a culture, each individual has his or her own unique take on the world. This was a notion adopted by the influential psychotherapist George Kelly who worked with troubled clients by eliciting their ways of construing their worlds (Kelly, 1963). Kelly’s position was that if we all construct our own internal models to interpret the world, then it is within our power to change our minds (i.e. change the way we construe the world), We assume that all of our present interpretations of the universe are subject to revision or replacement. … No one needs to paint himself [sic] into a corner; no one needs to be completely hemmed in by circumstances; no one needs to be the victim of his [sic] biography. We call this philosophical position constructive alternativism. (Kelly, 1963: 15, italics in original)

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Kelly’s therapeutic approach was therefore based on making explicit with his clients how they construed the difficult areas in their lives, as a starting point for identifying the causes of their psychological problems. Once a client’s system of personal constructs was elicited, it was possible to start work on modifying that system. The process of elicitation parallels both the process of diagnosis that Glasersfeld highlighted as being an essential part of teaching, and the approach taken by Piaget in his studies. Kelly described his position as ‘constructive alternativism’, and emphasised the way an individual’s knowledge was provisional: ‘in general man [sic] seeks to improve his constructs by increasing his repertory, by altering them to provide better fits, and by subsuming them with superordinate constructs or systems’ (1963: 9). Kelly’s central metaphor was of man-the-scientist (p. 4), a notion reflected in Driver’s focus on the pupil-as-scientist (see §4.1.3). Whilst Kelly’s concern was with psychotherapy, he developed his Personal Construct Theory in some detail, and was clear it applied in principle to all aspects of our understanding the world, In theoretical terms all constructs are personal. Even constructs drawn from say science or technology which have highly publicly specified relationships and implications and which have had their predictive validity tested and retested are still personal. They are personal in the sense that each person has to acquire them and integrate them into his [sic] total system. (Fransella & Bannister, 1977: 117)

Kelly developed a methodology, based on simple card-sorting techniques, to elicit his client’s construct systems, including those aspects that were tacit (see §7.3.2.4).

1.6.3.1

Concepts and Constructs

The term ‘construct’ is sometimes considered synonymous to ‘concept’: so one dictionary of psychology defines construct as ‘a term which some writers, such as Karl Pearson, have suggested as a substitute for concept’ (Drever & Wallerstein, 1964: 51). Kelly devised his ‘constructive alternativism’ around the notion of personal constructs, where he explained that he used ‘the term construct in a manner which is somewhat parallel to the common usage of “concept”… [to which] our construct bears a resemblance to the traditional usage’ (1963: 69–70), including both ‘the more concretistic concepts which nineteenth century psychologists would have insisted upon calling “precepts” [but also] involving abstraction’. Kelly’s constructs were bipolar, i.e. they were seen as dimensions or contrasts such as ‘large– small’, ‘light–dark’ and so forth, although the poles might not always be explicit. Watts and Pope have commented on how Kelly’s notion of a construct related to a constructivist interpretation of what a ‘concept’ is (i.e. that concepts are mentally imposed rather than captured from nature):

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Kelly has contributed to a long standing debate about the nature and status of ‘concepts’. What Kelly was rejecting was the ‘traditional school’, or abstractionist view of concept formation in favour of a current appreciation of concepts as personalised organisations of experience. … The first is representative of the notion that concepts are nature’s imprint on a passive mind, the second of the outcome of an active construction of meaning from experience. Given the growing acceptance of this second view, the distinction between a concept and a construct becomes increasingly blurred. (Watts & Pope, 1985: 9)

1.6.4

Perry’s Model of Intellectual Development

Piaget’s model (§1.6.1) included four major stages, the highest being that of formal operations that allowed ‘pure logico-mathematical relationships’ (Piaget, 1972b: 46), and was based on work undertaken with children of various ages. For example, Piaget undertook a study of moral reasoning, including the way children learned to play marbles (as an example of the young child, considered egocentric, learning to operate in a social context). Piaget (1932/1977) was interested in how children understood the authority of rules, i.e. as absolute, as dictated by adults or just human inventions that were transferred through culture and open to modification by consensus. Piaget’s study was based on talking to children from pre-school age to adolescence. One criticism of Piaget’s work is that it may not represent the most advanced form of human intellectual attainment, as much real-life problem-solving deals with poorly defined problems, and information that is either contradictory or insufficient to allow certain decision-making. It has therefore been suggested that in Piagetian terms there is a ‘fifth stage’ (Arlin, 1975) of ‘post-formal’ operations (Kramer, 1983) of particular relevance to adulthood. William G. Perry (1970) undertook an extensive series of studies looking at the intellectual and ethical development of a rather different group of learners. Perry’s subjects were college students (undergraduates) from the elite colleges of Harvard. Perry produced a stage model of development (similar to the type offered by Piaget) setting out the stages of development in the college students’ thinking (Finster, 1989), that may be considered to have developed out of Piaget’s programme (e.g. it shares the basic ‘hard core’ commitment to seeing development as occurring in identifiable stages). Perry’s work has been acknowledged as potentially highly significant for learning in science at college level (Finster, 1991) because it considers students’ view of the nature and sources of the knowledge they meet in class. In particular, students move beyond the notion that something is simply right or wrong (to consider, for example, the possibility that whether something is correct will quite legitimately be judged differently from different viewpoints). If Perry’s findings are generally applicable this would suggest that a student’s ability to appreciate, for example, the limits of scientific models, and the legitimacy of working with apparently inconsistent models and representations (e.g. wave and particle models of light), may well be contingent upon their level of development.

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Studies of Cognition

During the second half of the twentieth century a new field of cognitive science developed (Gardner, 1977) that encompassed psychology of learning, alongside aspects of work on language, artificial intelligence, and other areas that could collectively inform our understanding of cognition. It is fair to say that there is now considerable overlap between some studies of learning from Science Education and some of the work in Cognitive Science as both fields have matured in parallel. The potential for work in Science Education to be informed by perspectives from cognate fields is seen here as something to be welcomed in moving research in Science Education forward. Although some of this work used contexts from science, most was not explicitly linked to science learning (being concerned largely with general features of cognition), but, as Duschl and Hamilton (1992) point out (see §1.4), it offers a linked field, and developed a body of literature offering relevant findings, concepts and theories for those working in Science Education.

1.7.1

Introspection and Behaviourism

Some early studies in psychology were based on the technique of ‘introspection’, i.e. ‘observation by an individual of his own mental processes; systematic selfobservation’ (Drever & Wallerstein, 1964: 145). Whilst an individual undoubtedly has privileged (if certainly only partial – see §1.8.3) access to their own thinking processes and mental states, this approach is highly ‘subjective’ in the sense that there is no possibility of an individual’s findings being replicated by another observer. The behaviourist movement in psychology (which was especially influential in the United States for a large part of the twentieth century) sought to develop a RP in psychology that was totally ‘objective’, in that it only employed explanatory constructs that could be tightly defined and observed/measured. This attempt to exclude such unobservable features as mental states was seen by some as necessary to establish a ‘scientific’ psychology (Watson, 1967): a debate which resonates with the questions (considered in the next chapter) of whether educational research can, or should, be considered ‘scientific’. It is worth noting here that the natural sciences make regular use of explanatory models based on theoretical constructs that do not refer to physical or visible objects. The behaviourist programme then did not admit explanatory constructs (e.g. mentalistic constructs) that could not be observed and measured (Glasersfeld, 1983), but explored how stimuli (inputs controlled by researchers) were linked to responses, and much of the work was carried out with animals such as rats or pigeons – who would not have been able to report any mental states they may have experienced in any case. One of the much-quoted examples of this type of research was Pavlov’s demonstration of conditioned reflex behaviour, where a sound that had previously been presented in conjunction with food would trigger a dog to

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salivate. The stimuli had led to learning (a potential for a change in behaviour) such that an association formed between the sound and food, and which triggered a reflex that initially was only produced by presentation of food. However, it has been pointed out that ‘Pavlov himself … adopted a far from mechanistic position towards the role of cognition in learning and living’ (Sutton, 1983: 192). This RP produced detailed information about the types of reinforcement patterns that were useful to train behaviour – such as encouraging rats to pull levers, or pigeons to trace complex shapes – but were considered to have less immediate value to understanding conceptual learning in human learners. Whilst behaviourism has some applications in education, its approach was somewhat antithetical to the ‘humanist’ stance often taken by teachers and others working in education (Aikenhead, 2006). White has suggested that ‘it was unfortunate that behaviourism was dominant when Education began to penetrate universities and when teacher training expanded after the Second World War. … It formed attitudes to theory and research amongst teachers that, while no longer defensible, are now engrained’ (White, 1998: 61). Similarly, Glasersfeld argues that ‘the damage [in education] was formidable’ and that ‘the presumption that all that matters – perhaps even all there is – are observable stimuli and observable responses … has been appallingly successful in wiping out the distinction between training and education’ (Glasersfeld, 1983: 72–3).

1.7.2

Gestalt Theorists

One alternative tradition in psychology that was influential in the early twentieth century was that of the gestalt theorists, who were concerned with the nature of human perception and experience (Koffka, 1967). The term ‘gestalt’ refers to how humans tend to perceive whole patterns. We usually see and hear objects, people, words, tunes, etc., rather than patches of colour and tones. This commonplace observation is of great significance, as sensory information is highly processed before it is presented to consciousness. In other words, what we sense is interpreted at some pre-conscious level before we are aware of what we are experiencing. This is an insight of particular relevance to constructivist notions of teaching and learning. Gagné (1970: 14) described how ‘as conceived by these writers, learning typically takes the form of an insight, which is a suddenly occurring reorganisation of the field of experience’ when a person ‘has a new idea’ or ‘discovers a solution to a problem’. Although gestalt theory has ceased to be an important school in psychology, its insights into the subconscious organisation of perception remain important. The term ‘gestalt-switch’ has entered into the language to describe how one can suddenly ‘see’ or understand the world a different way. There are well-known illustrations of how the brain can suddenly reorganise perception of the visual field (Gregory, 1966) so that, for example, an image previously seen as a rabbit now appears to be a duck, or an abstract pattern suddenly becomes clearly an image of a dog. The change is sudden at the level of conscious thought, but this may be

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understood as the output of ‘processing’ (thinking) that is not open to conscious examination. The notion of gestalt-switch has come to be applied to changes in world view as well as more localised insights (see §3.2.6). The work of the gestalt psychologists highlights how raw stimuli have to be perceived through active processes of organisation, so that the same stimulus can give rise to very different perceptions in different individuals. This is clearly highly significant for teaching, as material presented to a learner may be perceived very differently by student and teacher, as well as by different students in the same class. The teacher has no direct access to the learner’s perceptions, and so cannot know what the student sees or hears, only his or her own perceptions of the stimuli presented. Whether the student learns what the teacher intends will in part be contingent on the extent to which the student’s organisation of stimuli (e.g. the teacher’s words) matches what the teacher hoped to communicate. It is common for people to ‘see’ what is not actually present, or to ‘hear’ different words from the ones actually spoken (Taber & García Franco, 2009). This insight links to Glasersfeld’s comments on the diagnostic role of the teacher (§1.5.2).

1.7.3

Learning Through Metaphor

There are several levels at which language can be analysed (Ellis & Beattie, 1986). For a student to perceive sounds vocalised by the teacher (or patterns on the printed page) as words is only one part of a process of interpretation. The words themselves need to be understood as representing some meaningful ideas. Lakoff and Johnson (1980b) have argued that the human conceptual system largely functions through metaphor, containing metaphorical as well as non-metaphorical concepts (p. 195). They define non-metaphorical concepts as ‘those that emerge directly from our experience and are defined in their own terms, [such as] … spatial orientations … ontological concepts … structured experiences and activities’ (p. 195). Metaphorical concepts ‘are those which are understood and structured not merely on their own terms, but rather in terms of a different kind of object or experience’ (p. 195, italics in original). For example ‘construction of learning’ is a way of understanding learning in terms of physical construction, such as building a house, a point revisited below. Lakoff and Johnson describe the metaphorical structure of cognition as ‘extremely rich and complex’ (p. 195). They claim that metaphorical concepts are grounded in experience (p. 204) and are ‘based on complex experiential gestalts’ (p. 201), by which they mean ‘a multidimensional structured whole arising naturally within experience’ (p. 202). A particular experiential gestalt is described as being either of the following (p. 205): • ‘[A] structure within a person’s experience that identifies that experience as being of a certain kind’ • ‘[A] structure in terms of which a person understands some external occurrence and that identifies that occurrence as being of a certain kind’

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We are not usually aware of the extent to which our understanding of communication is based upon metaphors. Deliberate use of metaphors for effect or as a creative device are likely to be noticed, where much of the metaphorical nature of language has become part of what is ‘taken-for-granted’ when we assign meanings to words and phrases. The term ‘constructivism’ when applied to learning was intended to offer a comparison with physical construction (as of buildings out of bricks and mortar): that is, construction of knowledge is in a sense like constructing buildings. However, as the metaphor becomes adopted as a standard way of talking, meanings shift so that in time the construction of knowledge becomes literal rather than metaphorical. It seems that for many communities of discourse (such as science educators in many countries) that process is well under way, and talk of construction of learning is no longer seen as a strange juxtaposition that highlights an analogy between two processes, but rather the root metaphor of construction carries largely accepted messages about the nature of learning (Bowers, 2007). Because much of language is taken-for-granted by those fluent in a language, failures to communicate what was intended may be difficult to spot. In terms of school learning, whether a learner is able to appreciate the teacher’s intended meanings will be contingent upon the extent to which they share language (i.e. beyond speaking the ‘same’ language, such as English) and, for example, understand and share the intended meanings for the metaphorical terms used in the teacher’s language. This is, of course, a two-way problem: asking a student to repeat back what was said (the form of words) in no way ensures that a meaning has been communicated.

1.7.4

Information Processing Models

References to levels of analysis of language, and perception as involving processing, itself reflects another key metaphor – that of mind as mechanistic. Our understanding of mechanism today may be catholic, but talk of nature, and then people and their minds, as machines, is based on analogy with actual ‘mechanical’ mechanisms, such as clockwork (Westfall, 1971; Richards, 1992). Saying that our bodies and our minds are like machines, has shifted to them being considered types of machines. The advent and familiarity of electronic computers has led to the brain/ mind commonly being compared to a computer (Young, 1978). One of the recognised influences on the development of the cognitive sciences is work into what is sometimes called ‘machine learning’, with the advent of electronic computers and interest in the field of ‘artificial intelligence’. Such studies were able to inform and be informed by developments in neurology that explored the physiological basis of human cognition. Cognition was modelled in terms of systems that processed information, and had identifiable components. It was not considered necessary to be able to identify the precise neural processes at work, and indeed it was recognised (Dawson, 1998) that cognition could be modelled at three distinct levels that could be studied independently (see §6.2.1). Indeed,

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a description at the ‘computational’ level could refer to human neural processing or some artificial intelligent system built from silicon-based components. Analysing cognition as a system involves identifying key functional stages – such as perception. For example, an important distinction is between the kind of memory that allows us to access information after some considerable time, and the ability to keep something ‘in mind’ (such as remembering a telephone number we have just located in a directory long enough to key in the number). Long-term memory and ‘holding something in mind’ are quite different in function (Baddeley, 1990), and considered to be dependent on different parts of the cognitive system. Long-term memory is fairly stable, whilst the more immediate form of memory is lost quickly, for example, simply by being distracted. This latter form of memory tends to be referred to as ‘working memory’ rather than ‘short-term memory’ emphasising that the distinction is not only in terms of timescale. Simple information processing models then divide a system up into discrete units. For example, sensors (e.g. eyes) convert information in the environment into sensory information that is then transferred to a processing device. Such models are useful, and may reflect the structure of some machines quite well. But human physiology tends to be quite subtle, so that it is not clear to what extent the brain contains discrete components of this type (see §1.8.2). In sight, the retina itself undertakes significant processing of data, and so should perhaps be considered as a remote part of the brain rather than just a sensory component. Information sent from the retina will be automatically processed at several levels before we are aware of what we ‘see’, and similarly with sound, so that ‘you can’t hear speech as noise even if you would prefer to’ (Fodor, 1983: 53). Certainly what we become conscious of seeing and hearing is not based purely on processing of sensory information, but is rather patterns imposed on the data (as recognised by the gestalt psychologists, see §1.7.2) in terms of prior experiences. In Piagetian terms (see §1.6.1), existing mental structures are used to act on information from the environment, to build up more complex mental structures. The extent to which specific ‘modules’ of mind can be identified which act as somewhat independent system components (whether physically discrete, or distributed spatially in the brain) has been the subject of considerable debate (Fodor, 1983). So Noam Chomsky has proposed the existence of a ‘language acquisition device’ that has co-evolved with human language and therefore both limits the structural form of human languages and enables the child to learn language effectively. Chomsky (1999) has strongly argued that without such a device through which to process heard speech in terms of an inherent grammatical framework, the available information could not be interpreted sufficiently for children to make progress at anything like the rate language is typically learned early in life. Whilst such debates are far from settled, they are clearly important for those interested in understanding learning sufficiently well to inform a science of pedagogy. Models of learning in science should clearly be consistent with what is understood about cognition: for example, theories in Science Education should not be inconsistent with the best available understandings of how knowledge may be represented in minds, and how minds may be ‘structured’ to enable learning processes.

1.8

Structure of Mind

1.8

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Structure of Mind

Information processing models treat processing systems as functionally distinct units that are responsible for such activities as perception, information storage, etc. It is assumed that a similar kind of analysis can be applied regardless of whether the system being studied is a computer or a person. This suggests that, functionally at least, the human mind can be considered to have structure. Indeed, Johnson-Laird (1983: 10) described the task of cognitive scientists as to ‘construct a working model … of a device for constructing working models’, i.e. the mind. ‘Mind’ is yet another widely used term that is not well defined (§1.2.4). The term mind is usually used as a complement to brain. Where the brain is a physical structure, mind refers to mental experience and the way it is constrained, enabled and organised. A materialist view would be that mind is dependent upon (and ultimately comprehendable in terms of) brain. (Other views might posit mind as involving, or at least having access to, some other non-material element, perhaps indicated as soul or spirit.) However, as suggested above, even if mental life can in principle be explained in terms of anatomy and physiology; that does not make that level the most useful for discussing mental life. So it is useful to be able to refer to the apparatus of mind, and the structure of mind, without necessarily being able to identify particular underlying brain structures considered responsible. This is a common assumption in cognitive science, that the mind can be studied independently from the brain. Psychology (the study of the programs) can be pursued independently from neurophysiology (the study of the machine and the machine code). The neurophysiological substrate must provide a physical basis for the processes of mind, but granted that the substrate offers the computational power of recursive functions, its physical nature places no constraints on the patterns of thought. This doctrine of functionalism, which can be traced back to Craik, and even perhaps ultimately to Aristotle, has become commonplace in cognitive science. (Johnson-Laird, 1983: 9)

1.8.1

General Processing Models

Piaget’s developmental stage theory (§1.6.1), which offers notions of the kinds of mental operations possible at different stages of development, is based on an approach that assumes that there are core processing abilities that can be applied relatively independently of the kinds of material being processed. This type of approach has been described as a kind of ‘horizontal’ structuring to the architecture of mind, where basic skills are assumed to be applicable to a wide range of domains (Fodor, 1983). As it could commonly be shown that in practice people may demonstrate more abstract levels of thought in some contexts than in others, it became clear that Piaget’s model needed some adjustment or interpretation, and the notion of décalage (uncoupling), or lag, was introduced (Flavell, 1963). The principle of horizontal décalage suggested that the learner’s Piagetian level represented the type of

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thinking possible in a familiar domain, but that may not be expressed in a context that was fairly novel for the individual. In terms of the Lakatosian (1970) model to be described in Chapter 3, it could be suggested that the ‘protective belt’ of auxilliary theory in the Piagetian RP was amended to protect the ‘hard core’ assumption that cognitive development occurs in stages.

1.8.2

Modular Minds

An alternative possibility is that mind is structured in such a way there are specialised areas that deal with particular domains, i.e. so called ‘vertical’ structure (Fodor, 1983). So, for example, a person may show very different propensities for developing skills in, say, chess and crosswords, because there are different specialised areas of mind that deal with these two different activities. Now it seems unarguable that the brain is structured in such a way that the human mind inevitably displays some degree of structure in both horizontal and vertical senses. The horizontal case is fairly clear, perception and recall from memory are clearly not undertaken by the same general-purpose apparatus but have specialist ‘organs’ or faculties. There is also clearly vertical structure at some stages of cognition – word recognition and face recognition have their own somewhat specialised apparatus. However, there is considerable debate about the extent to which there might be modularisation in terms of dealing with different domains of experience or knowledge (Fodor, 1983, Hirschfeld & Gelman, 1994). This is linked to the arguments about the nature of intelligence, and the extent to which this has a ‘general’ component (‘g’), rather than being a set of largely distinct intelligences (Gardner, 1993). Of particular relevance to Science Education is the argument that in evolution humans have developed specific faculties for thinking about key knowledge domains (Mithen, 1998), relating to the physical world (primarily related to manipulation of tools and materials); the biological world (i.e. in terms of gathering food, avoiding predators, etc.); and the social world (working as a group), something that is reflected in some of the debate about children’s alternative conceptions (§6.1.4).

1.8.3

Representational Redescription in Cognitive Development

Another useful model to suggest how learning of complex conceptual material may be achieved has been presented by Annette Karmiloff-Smith. Although her key focus was on processes of development, Karmiloff-Smith’s (1994, 1996) model is quite relevant to a number of the issues raised above in considering the nature of

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learners’ ideas in science. Karmiloff-Smith saw cognitive development as involving two parallel processes. The first of these was modularisation, and the second, something that Karmiloff-Smith called ‘representational redescription’. The notion that knowledge representation may be subject to some form of modular encapsulation (Fodor, 1983) may well be relevant to the question of how students relate their formal science knowledge to their everyday ‘folk’ knowledge of science. For example, Joan Solomon (1992) has argued that these are two distinct knowledge domains, which would clearly be significant for how students learn and access school and college science (this is explored further in Chapter 6). This can be linked to those models of the ‘architecture’ of the mind that argue for specific modules involved in processing information either at different stages in processing (at different ‘horizontal’ levels), or relating to different areas of experience (in different ‘vertical’ slices, as in the distinction between life world and scientific knowledge). Karmiloff-Smith argues that modularization occurs as part of a developmental process in cognitive development. In parallel to increasing modularisation, Karmiloff-Smith believes that development involves a process whereby the information represented in the cognitive system becomes increasingly more explicit and available to that system. In Karmiloff-Smith’s scheme knowledge can be successively represented at four levels within the system. At the first (I, ‘Implicit’) level information is encoded as bracketed (only available as a unit) representations, and allows quick, automatic responses, but is not available to consciousness. However, level-I representations can become re-represented at a second level (E-1, where E stands for explicit). This ‘representational redescription’ is not a change in the initial representation, but the forming of a new kind of representation (re-representation) of it. A level-E1 representation is an abstraction of a level-I representation. Explicit representations are not bracketed, so that their components can be individually linked to other parts of the cognitive system. According to Karmiloff-Smith, level-E1 representations are not directly open to conscious access, but are explicit in the sense that they can be manipulated within the cognitive system. In turn, level-E1 representations can be re-represented at level-E2 to give new representations that are accessible to consciousness (perhaps as imagery), although not directly reportable verbally; and these can be re-represented again at level-E3 in a form of coding that can be directly reported verbally. Whilst Karmiloff-Smith’s model has not to date been the focus of much attention in Science Education, it will be suggested in Chapter 6 that it offers a useful way of thinking about some key findings.

1.8.4

Mental Models and Representation

A good deal of research into learning in science concerns the ways that learners understand the science topics that are taught in schools and colleges. Research,

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therefore, probes how learners represent these topics mentally. The notion of mental models is used to describe the way people form mental representations that can be used to make sense of their experiences: ‘in interacting with the environment, with others, and with the artifacts of technology, people form internal, mental models of themselves and of the things with which they are interacting [which] provide predictive and explanatory power for understanding the interaction’ (Norman, 1983: 7). Norman suggests that in studying mental models in learners, it is useful to keep clear four distinct things: • The ‘target system’ that needs to be understood • The conceptual model of that system that ‘is invented [e.g. by a teacher or scientist] to provide an appropriate representation of the target system’ (p. 7) • The mental model itself • A representation of that mental model Norman describes mental models as ‘naturally evolving models that must be “functional”, in that people will continue to modify the mental model in order to get a workable result’ (p. 7). Williams, Hollan and Stevens suggest that “the ideas that seem fundamental to our conception of mental models [are] that they are composed of autonomous objects with an associated topology, that they are ‘runnable’ by means of local qualitative inferences, and that they can be decomposed” (Williams et al., 1983: 133). That is, mental models can be understood as comprising identifiable components organised into a scheme, and allowing certain ‘outputs’ to be predicted by simulating scenarios with particular ‘inputs’. Although research in Science Education more commonly labels the objects of research as ‘conceptions’ or ‘frameworks’ rather than ‘mental models’, we will see later (§5.3.4) that these terms are often used loosely and even interchangeably, and this area of research is of considerable significance to our field of study.

1.8.5

Metacognition

Another topic from psychology and cognitive science that has significance for our theme is that of metacognition. This can be paraphrased as ‘thinking about thinking’. Metacognition is important in problem-solving, where no automatic ready solutions are available, and the individual needs to plan a strategy for solving the problem (Phang, 2006). For those who see learning as primarily the responsibility of the learner, and education about supporting the development of autonomous learners (cf. Dewey, §1.5.1), metacognition is clearly a key concern. Certainly much of the ‘thinking’ that leads to learning occurs subconsciously (cf. §1.8.3), but that does not negate the importance of the learner in monitoring, marshalling and directing what becomes available to consciousness. Indeed, some studies of how conceptual change (i.e. major changes in beliefs about the world) occurs have

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Approaches to Instruction and Pedagogy

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focused on aspects of reasoning that involve the learner consciously evaluating his or her own ideas and beliefs (Posner et al., 1982).

1.9

Approaches to Instruction and Pedagogy

The ‘domain of enquiry’ (Duschl & Hamilton, 1992, see §1.4) in which Science Education has developed clearly offers a wide range of concepts, theories and models that are relevant to learning in science. Many of these derive from studies that are not explicitly linked to school and college learning. However, there are also some important traditions that have focused more directly on informing teaching.

1.9.1

Gagné and the Conditions of Learning

Robert Gagné (1970: 3) set out to explore the forms and conditions that supported human learning, ‘to consider the sets of circumstances that obtain when learning occurs, that is, when certain observable changes in human behaviour take place that justify the inference of learning’. Whilst somewhat influenced by the stimulus – response tradition of the behaviourists, Gagné (1970: 24) recognised that a full understanding of human learning had to consider both external and internal context, i.e. ‘one must look, first, at the capabilities internal to the learner, and second, at the stimulus situation outside the learner’. So Gagné (1970: 51) described concept learning (one of eight categories of learning he identified) as ‘a kind of learning that appears to be critically dependent on internal neural processes of representation for its very existence’. These kinds of internal representations are the kind of inferred non-observables that behaviourists abhorred, but have become a key focus of research into learning science (see §4.4). Gagné discussed the internal conditions of learning in terms of the ‘pre-requisites’ that needed to be in place, so that ‘the most important conditions [for learning a rule] are the pre-requisites for learning. The concepts to be linked must have been previously established’ (pp. 56–57). Gagné (1970) described the internal conditions for learning in terms of learning hierarchies, ‘the psychological organization of intellectual skills … often composed largely of rules’ (p. 203), which ‘represents what is expected to be a general pattern to be followed for all the students in the group: make sure that relevant lower-order skills are mastered before the learning of the related higher-order skill is undertaken’ (p. 240). Whilst being careful to reiterate that such a hierarchy only described the internal conditions for learning ‘the prerequisite capabilities that will provide the positive transfer to a new learning event’, he argued that ‘identifying these capabilities and assuring their availability are matters of critical importance for instruction’ (p. 242). These ideas have been applied to planning concept learning in science (e.g. Herron et al., 1977).

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1.9.2

Science Education As a Research Field Within a Domain of Enquiry

Ausubel

David Ausubel is well known for his adage that teaching should start from a learner’s existing knowledge: If I had to reduce all of educational psychology to just one principle, I would say this: The most important single factor influencing learning is what the learner already knows. Ascertain this and teach him accordingly. (Ausubel, 1968: vi)

Ausubel introduced the notion that learning needed to be meaningful (cf. rote), and this depended on the learner’s cognitive structure, and the nature of the material to be learned (Ausubel, 1961: 18; Ausubel & Robinson, 1971: 50–51). Ausubel and Robinson (1971: 53) suggest three conditions for meaningful learning to occur: 1. The material itself must be relatable to some hypothetical cognitive structure in a non-arbitrary and substantive fashion. 2. The learner must possess relevant ideas to which to relate the material. 3. The learner must possess the intent to relate these ideas to cognitive structure in a non-arbitrary and substantive fashion. So, from Ausubel’s model, learning depends upon new material being met being potentially linkable to existing knowledge available in ‘cognitive structure’, and being interpreted in some way in terms of existing ideas. The notion of cognitive structure is important, implying that however conceptual knowledge is represented (‘stored’) in minds, it is not an arbitrary arrangement, but rather the representation is structured (cf. Vygotsky, 1934/1986). This structure reflects (indeed, embodies) how the individual understands the concepts to be related. Ausubel also refers to intent to learn, and this is worthy of further comment. At one level this can be seen as related to motivation and engagement, i.e. that being in a class is not going to bring about effective learning unless the student is attending to and engages with the material. Of course, much human learning does not require intent, but we are here dealing with ‘academic’ or school learning rather than informal learning. However, Ausubel’s condition also links to metacognition (§1.8.5): potentially relevant ideas are only likely to be linked to new information if the learner perceives a link. The learner needs to be ‘able to effectively exploit his existing knowledge as an ideational and organizational matrix for the incorporation, understanding, and fixation of large bodies of new ideas’ (Ausubel & Robinson, 1971: 57). Ausubel has continued to refine his theory of learning (e.g. Ausubel, 2000), but his ideas were already widely influential in the 1970s – e.g. being reviewed in the context of learning science in Studies in Science Education (West & Fensham, 1974).

1.9.3

Bruner

Vygotsky’s work (§1.6.2) was disseminated and developed by Jerome Bruner, who concluded from studies of language acquisition in infants that in general people

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tend to have similar forms of mental organisation (Bruner, 1987: 87). Bruner worked from Vygotsky’s (1934/1986) observation that communication between minds had to be indirect, and it took place through language; and in particular, that thoughts had to be translated into words (p. 252). Nevertheless, from Bruner’s perspective two participants from different backgrounds can move towards coconstructing a dialogue through their attempts to converse. Bruner is known for his work on developing the theory of instruction, and in particular for proposing the importance of ‘guided discovery’ (Fox, 1993: 181). Bruner believed that the cultural invention of schooling led to new ways of thinking (Wood, 1988: 15, 84, 1991: 97; Carraher et al., 1991: 234), and that schools should be primarily concerned with developing thinking and problem-solving skills in the academic disciplines rather than imparting specific knowledge (Wood, 1988: 8, 136; Fox, 1993: 182). Bruner (1979: 87) believed that discovery methods encouraged children to become constructivists and effective learners. Bruner (1964/1977: 208) describes three levels of representing the world: the enactive level (through action), the iconic level (through mental imagery) and the symbolic level (through the manipulation of symbols), and he suggests that teaching that starts with the symbolic level will lead to rote learning. This reflects Vygotsky’s notion of conceptual development requiring academic concepts to be linked with spontaneous concepts (§1.6.2.1). Bruner has recommended the use of a ‘spiral curriculum’ where the same material is met at increasing levels of difficulty during a learner’s school years (Child, 1986: 363), and this approach has been used in planning science teaching, for example, in England (DfEE/QCA, 1999). Bruner has explored the Vygotskian notion of the ZPD. (see §1.6.2), and his group suggested the notion of ‘scaffolding’ (Tharp & Gallimore, 1991) whereby a learner is guided by an adult, but the degree of support is reduced as the learner is gradually able to undertake the task without assistance. The teacher acts as ‘a vicarious form of consciousness until such a time as the learner is able to master his own action through his own consciousness and control’ so that the learner can ‘internalise external knowledge and convert it into a tool for conscious control’ (Bruner, quoted in Meadows, 1993: 248). Bruner introduced the ‘hand-over’ principle: that the learner moves from being an observer to a participant (Rogoff, 1991: 78; Tharp & Gallimore, 1991: 50): that is ‘one sets the game, provides a scaffold to assure that the child’s ineptitudes can be rescued by appropriate intervention, and then removes the scaffold part by part as the reciprocal structure can stand on its own’ (Bruner, quoted in Wood, 1991: 109). One of Bruner’s co-workers has suggested that ‘it is hard to find problems that are impossible for a child, given some coaching and some external aids’ (Olson, quoted in Brown, 1977: 78), and another emphasises that ‘built well, such scaffolds help children to learn how to achieve heights that they cannot scale alone’ (Wood, 1988: 80). Although the details of the scaffolding process will vary, the principle is considered to be applicable to learners across a wide age range (Wood, 1991: 110). The notion of scaffolding becomes of methodological significance when considering techniques to explore student understanding in science, as well as relevant to ‘constructivist’ approaches to teaching.

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1.10

Science Education As a Research Field Within a Domain of Enquiry

The Field: Research in Science Education

The preceding sections (augmented by the material on the philosophy of science to follow in Chapters 2 and 3) offers a quick sketch of the wider ‘domain of enquiry’ which acts as the background into which Science Education has developed as a recognised field within Education. I conclude the chapter with an overview of some key features of Science Education as a discrete field of enquiry.

1.10.1

Curriculum Development

Science Education has been an active area of work for some decades. In particular, there were attempts to develop the science curriculum in ways that reflected the findings of research into learning processes. A particularly important example was the Nuffield initiative in the UK which led to a succession of projects relating to secondary school and college level (A level) courses in the separate sciences and in combined science. The charitable Nuffield foundation has continued to support developments in Science Education to the present time. The first projects were set up in 1961 to develop a teaching approach in science across the secondary years (from age 11) to the school leaving examinations (then ‘O’ level) in biology, chemistry and physics (Nuffield Curriculum Centre, 2006). In 1966, the project moved to an academic base at Chelsea College in London (which later became part of King’s College, London). Although the initial Nuffield projects were not directly linked to Science Education research, they were based on a philosophy ‘characterised by their reliance on practical work carried out by students and the spirit of inquiry that infused the teaching’ (Nuffield Curriculum Centre, 2006). This basis for science teaching and learning was heavily influenced by the ‘guided discovery’ approach advocated by Bruner (§1.9.3).

1.10.2

The Piagetian Research Programme in Science Education

Another development that took place largely within Science Education was that of pedagogic approaches based on Piagetian theory (§1.6.1). In the USA, J. Dudley Herron questioned whether many non-chemistry majors were equipped to understand the abstract nature of chemistry courses they studied: Available evidence strongly suggests that a substantial number of entering college students – perhaps as high as 50% in courses for non-majors – are unable to function at an intellectual level which is described by Piaget as formal operational. But the content of chemistry and the approach that we normally take in teaching chemistry require that the student operates at this formal operational level if he is to comprehend the concepts that are presented. (Herron, 1975: 146)

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The Field: Research in Science Education

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Herron cited some of the studies supporting the view that Piaget’s own programme had produced results that were too optimistic in terms of when people generally attain formal operations. He argued that ‘formal concepts are not really accessible to students who are not formal in their thought’ and proposed a response in terms of teaching using ‘concrete props which model the abstract concept’ to offer concrete experience that in some sense represented the chemical concepts with ‘surrogate concepts which can substitute for the real thing’ (Herron, 1975: 149). Herron’s language, for example, referring to how such an approach might ‘make the transition from the surrogate to the real fairly easy at some later time’, seems to imply that the concept to be taught was some form of final knowledge. In the present volume it is assumed that school and college science usually concerns curriculum models that represent the (‘real’) science, so his approach might be characterised as developing teaching models to support learning of the curriculum models. Herron then viewed such model-based approaches as pedagogically valuable, but as falling short of teaching the actual chemical concepts. However, he remained committed to teaching chemistry meaningfully in terms of its concepts rather than through rote teaching of descriptive accounts. He concluded that ‘we cannot assume that “good” students are formal but we can certainly help them to become formal’ (Herron, 1975: 150). In the UK, this area of research is especially associated with the work of Michael Shayer and Philip Adey. Shayer undertook work in a range of schools which led to him conclude that ‘given adequate exposure to a science course, the pupils’ performance is mostly determined by the level of thinking required by the course in relation to the stage of thinking the pupils have attained’ (Shayer, 1978: 126). Shayer and Adey undertook an analysis of the demands of the content of the secondary science curriculum in terms of adolescent levels of conceptual development (i.e. in terms of Piaget’s stage theory). They concluded that there was something of a mismatch, with a good deal of material to be taught likely to be too abstract for many of those at secondary school (Shayer & Adey, 1981). Whilst the Piagetian ‘levels’ model has faced a good deal of criticism, and not all those working in Science Education would accept that measurements of Piagetian level are good predictors of what students can learn, this work is of significant note in terms of the current volume. Shayer and Adey, with colleagues set up a project to develop materials, using the context of science, to bring about ‘cognitive acceleration’. The CASE (Cognitive Acceleration through Science Education) project and a sibling project in Mathematics Education have been widely adopted in schools, and there has been ongoing research into the projects and their effectiveness (Adey, 1992; Adey & Shayer, 1994, 2002). Unfortunately, most of the research exploring the success of CASE has come from the project team (who are clearly committed to both the approach and the particular conceptual framework that provides its rationale) rather than independent researchers, but this is hardly the fault of those involved. This may be because interest in exploring learning in science in such ‘cognitive’ terms (i.e. seeing the primary factors of interest as relating to an overall cognitive level of development) has attracted less attention than research based on ‘conceptual’ foci (i.e. those

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seeing the key features as concerned with the way student thinking links with specific features of particular topic subject matter). Of particular significance for the present volume is how this work forms an example of an extended ‘research and development’ tradition within Science Education, one that could be considered as an example of a RP (cf. Chapter 3): CASE was originally designed as a research project with actual funding from the British Social Economic Research Council from September 1984 until August 1987. Six years of applied research under the direction of Professors, Michael Shayer and Philip Adey, with support from Ms Carolyn Yates, beginning in 1982 at Chelsea College were needed to design, generate and hone the methodology. A further two years research by Messrs Adey and Shayer, from 1989 to 1991, enabled a finer-detailed description of the professional teaching skills required. (CASE Network, n.d.)

Indeed, a number of commentators (e.g. Gilbert & Swift, 1985) have compared and contrasted this programme of work with the ‘constructivist’ programme that is the main focus for the present volume.

1.10.3

Dissatisfaction with the Piagetian Perspective

So, Piagetian theory suggested that many secondary and college students were not capable of appreciating the abstract nature of a good many of the scientific concepts that were fundamental to understanding modern science. The widespread adoption of science curricula that look for understanding of principles and concepts (rather than learning of facts and application of routine heuristics to solve exercises) therefore produced, according to this perspective, target knowledge that was mismatched to students’ intellectual capabilities. Cognitive ‘acceleration’ might be possible, but in the Piagetian model could only offer the opportunities for taking the next step rather than short cut the slow process of development (where existing mental structures support action on the environment that lead to disequilibrium and eventually the formation of the next level of structure). Herron’s 1975 paper was quoted above. This has been described by one critic as ‘a much-cited article that is now regarded as the manifesto for chemical constructivism’ (Scerri, 2003: 468). Herron’s paper was very much within the Piagetian programme, but did reflect the problems of the approach. Herron accepted that for students who were not able to use formal operations, the version of the ‘taught concept’ they would learn ‘is not exactly the concept that we are trying to teach but it is a reasonable approximation and has considerable utility’ (Herron, 1975: 149). This phrasing does not reflect the ethos of much later writing in the constructivist tradition, where (as will become clear later in the book) the notion that there was a ‘correct’ version of a scientific concept that some students could fully attain will come to seem rather simplistic. But from Herron’s 1975 viewpoint, his recommendations for teaching necessarily take the form of a remedial approach to make do for those who are not up to studying the science (chemistry in this case):

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I am firmly convinced that we can identify many other topics in chemistry which are generally presented in a manner that requires formal thought but could be presented in such a way that a reasonable facsimile of the idea is available to those students who have not reached the level of formal operations. Still, I believe that it is misleading to assume that anyone who is not formal in their thinking can ‘understand’ chemistry. (Herron, 1975: 150)

1.10.4

Constructivism in Science Education

The focus on how to support the learning of specific concept areas in science (rather than on the cognitive structures needed for different forms of intellectual operations) led to the development of an alternative research tradition that became labelled ‘constructivism in science education’. It is this tradition (or ‘research programme’, as it is characterised in Chapter 4), that grew out of, and has been supported by, the broader domain of enquiry described in this chapter, and which forms the central focus of this book. Constructivism has been acknowledged as ‘something of a research orthodoxy within science education’ (Jenkins, 2000b: 7), such that ‘information processing and constructivist models of learning have supplanted behaviourism as the dominant theory’ (White, 1998: 61). By the mid-1990s, constructivism had become an explicit referent for science teaching (Tobin, 1993a), so that major texts on teaching and learning science were branded as taking a ‘constructivist approach’ (Fensham et al. 1994) or offering a ‘constructivist view’ (Mintzes et al., 1998). Constructivism in Science Education was considered a worthy focus of books in its own right (Tobin, 1993b; Matthews, 1998b). ‘Constructivist’ writing was seen as dominant (Erickson, 2000) and even an unavoidable orthodoxy (Jenkins, 2000b) in the research literature, and has been described in terms of a Kuhnian paradigm (Matthews, 1993; Solomon, 1994). Michael Matthews refers to the influence of constructivism ‘as if a period of Kuhnian normal science has descended upon the science and mathematics education communities’ (Matthews, 1993: 363). Kuhn’s model of science (see Chapter 2) has been widely influential, but in this volume it is argued that it is more appropriate, and useful, to consider constructivist research within Science Education as a ‘Research Programme’ in the sense used by Lakatos (see Chapter 3).

Chapter 2

‘Scientific’ Research in Education

This chapter explores the nature of research in Education, in the light of a broad post-positivist notion of science and scientific research. It is not suggested that all educational research must be seen as ‘scientific’, but rather the chapter argues that educational research can be ‘scientific’, and some of it should be considered that way. The chapter begins by considering how ‘science’ itself is currently understood and demarcated, before considering the nature of research in Education and the so-called paradigms of educational research. This provides a basis for exploration of some key basic epistemological and methodological issues, as they are understood in relation to the natural sciences, which will be drawn upon later in the context of educational research. Exploring how a post-positivist notion of science can encompass research in Education illuminates the types of criteria that educational research must match to be considered as scientific.

2.1

The Notion of Educational Science

Science Education is clearly part of Education (the use of upper case here is used to signify the academic discipline), which is classed as a social science rather than a natural science. The argument made in this book is that a key area of research in Science Education may be considered as a Scientific Research Programme (SRP), in the sense developed by Imre Lakatos. These two statements need not be inconsistent, as is it possible for SRP to be found in the social sciences. There are in effect two issues here: • Can research in Education (including Science Education) be viewed as ‘scientific’? • Can research in Education (including Science Education) be viewed as ‘scientific’ in the specific sense of demonstrating progressive (Lakatosian) research programmes? The present chapter considers the broader issue of research in Education, and argues that it can in principle be considered to fit current notions of what ‘science’ is. The chapter will draw upon, among other sources, the report of the US National K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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Research Council’s Committee on Scientific Principles for Educational Research (NRC, 2002). The next chapter then looks specifically at Lakatos’s (1970) model of SRP, and explains how this leads to a broad notion of ‘science’ that can in principle encompass educational research.

2.1.1

Why Do We Need to Put a Boundary Around Science?

Debates about what is and is not science, the ‘demarcation problem’, may seem to be something of an esoteric concern, although to be a scientist or scientific is generally considered as offering some form of status, even among those elements in society that seem to treat science with some suspicion. However, for those who study science professionally, such as historians of science and philosophers of science, it is clearly important to have a means of deciding what falls within the area of study. Demarcating Science is also important in Science Education. The teacher of science should have some notion of the extent of the group of disciplines that make up their teaching subject. There are important debates about the nature of science in the school curriculum that cannot be effectively engaged in without a warranted notion of what Science is. School science is not Science, but rather the outcome of a political process through which a curriculum is negotiated (or imposed), and so becomes an entity in its own right, and which at best reflects Science (Kind & Taber, 2005). The science teacher is increasingly expected to teach about Science as well as teach some science: that is, it is increasingly recognised that school science education should help students understand the nature of Science – its methodological procedures, the basis of its claims to offer reliable knowledge, its processes for reaching consensus, its relationships with society – as part of developing the basic scientific literacy to support full citizenship in a modern technologically advanced democracy (Millar & Osborne, 1998). Teaching about the nature of Science requires the teacher to have an explicit, and warranted, notion of what science is. Research suggests that the science teacher, whilst having a strong implicit notion of science, is often ill-prepared to engage with meta-discourses of science such as the philosophies of science, the history of science, and the sociology of science (Bentley & Fleury, 1998). For the present volume, a key issue is how the Science Education researcher can be considered a scientist. Many of those who are active in science education have a background in the natural sciences, before moving into education. A typical career path is to earn a degree in a science discipline, and in some cases a research degree in science, move into science teaching, and then – after gaining experience in the classroom – into research in Science Education. The transitions from the natural sciences to being a school or college teacher, and then to being a researcher in the social sciences involve shifts in professional identities (Kind & Taber, 2005). A researcher who has taken this route may well bring very different ‘baggage’ from another educational researcher who has a background in a social science discipline such as sociology or social psychology, and who comes to study Science Education as a

2.2

A Post-Positivist View of Science

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context for exploring learning and teaching issues. Those who teach in university science departments and who include educational enquiry in their research profile may comprise a third ‘type’ of science education researcher – especially where their formal research training may be limited to their natural science discipline and there has been no explicit shift of professional identify to becoming a social/behavioural scientist. It is very much a premise of this book that research in Education can be scientific, and that the tradition of research into learning science is best understood as a SRP. However, it is very important for those undertaking research in Science Education, and equally those who are expected to be informed by such research – science teachers – to clearly understand how and why this type of scientific research is often unlike much research in the physical sciences. From these perspectives, exploring the issues of ‘what is science’ and ‘how can educational research be scientific’ are not only a key part of the thesis presented in this book, but are actually matters that should be key concerns for all those working in Science Education, whether as teachers, curriculum developments, teacher educators or educational researchers.

2.2

A Post-Positivist View of Science

So it is important to consider the nature of science, and in particular how science can be considered to offer knowledge of the world. The notion of Science informing this book is wider than the so-called natural sciences (biology, chemistry, physics, geology, etc.), however, this case has not yet been made. This section may be read as being about the natural sciences, and later it will be argued that this should be considered to apply to some work in the social sciences (such as Education) as well. Certainly the key theorists discussed here (such as Kuhn and Popper) were largely thinking about the natural sciences. Reference to how Science can be considered to offer knowledge of ‘the world’ implies that there is some form of ‘objective’ world to know, and this is a point that needs to be dealt with before proceeding.

2.2.1

Positivism and Objective Knowledge

Descartes is perhaps, in part, responsible for the modern notion of the mind, having formally addressed the distinction between mental experience and the external world (e.g. Claxton, 2005) and so supported a notion of ‘dualism’ between mind and the physical world. Descartes’ famous conclusion that the only thing he could have certain knowledge of was his own mind was part of a long tradition of considering the origin of our knowledge. An extreme position here is a form of solipsism, where an individual concludes that he or she is the only person that exists, and that everything else is just fancy. There are clearly many intermediate positions between denying the existence of anything beyond our own mind, and trusting the senses to be able to reliably

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reveal the full nature of an external world. It seems reasonable to suggest that any meaningful science presupposes: 1. Some kind of external world beyond one’s own mind that is sufficiently distinct and stable as to be in some sense ‘knowable’ 2. That attempts to probe this world through observation and/or interaction can in principle lead to reliable knowledge, i.e. knowledge of the world that is in some sense ‘correct’ These are, of course, issues of ontology and epistemology that philosophers have discussed for centuries, coming to a wide range of positions. Ontology is about the nature of the world in which we live, and epistemology is about how we come to have knowledge of that world. An (ontological) assumption that there is an objective world to know does not imply an (epistemological) commitment to the possibility of obtaining true knowledge of that world. Positivism is considered to be a ‘foundationalist’ philosophy (or set of foundational philosophies): that is, holding a view that scientific knowledge can in principle be built upon totally firm foundations. There have been two main suggestions for what those foundations might be (e.g. Phillips & Burbules, 2000), and we met these in the previous section. The ‘rationalists’ (philosophers such as René Descartes, Gottfried Wilhelm Leibniz, and Baruch Spinoza) offered human reason as the basis: the starting point being what is revealed to us by rational thought (Lacey, 1995b). The ‘empiricists’ (such as John Locke, George Berkeley and David Hume) offered experience as the basis of true knowledge of the world (Lacey, 1995a). The two main contenders for the ‘foundations’ of our knowledge then are experience or pure rational thought. As we saw in the Chapter 1, Socrates reputedly took the rationalist route, but assumed that the human soul came equipped with innate knowledge directly from God. The platonic world of ideas was ‘pure’, whereas the world as revealed through the senses was not the ultimate reality. The alternative empiricist view was that we are able to find out about the world by observing and interacting with it – the assumption being that our sensory apparatus is able to offer true knowledge of an objective reality. In practice, much natural science proceeds as though science can produce ‘true knowledge’ that corresponds to the way the world is, provided that sufficient ingenuity is used to design studies and develop instrumentation. This does not imply that scientists would necessarily take such a ‘positivist’ viewpoint if questioned about their fundamental beliefs, but this certainly seems to be the stance that is widely adopted for practical purposes. An important point to note here is that ontological questions should be distinguished from epistemological ones: recognising that it would be possible, for example, to have a strong belief in a physical world that we all live in, whilst totally denying it is possible to ever have valid knowledge of it. As we will see later in the book (§5.2), any kind of constructivist perspective on the origins of knowledge is inconsistent with a belief that absolute knowledge of the world is possible. Unlike learning from the textbook, the world does not offer us special access to back pages with the right answers against which we can compare our own constructions. All we can ever do is build models, and check them

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against other models we have built. As Plato suggested, we work with filtered reflections of an objective world. However, scientists can take an instrumental view to their work. Rather than seek to ‘know’ the universe, scientists can build models that have clear utility value. To the extent that those models allow us to build the technologies we want: to cure disease, to feed the world, to insulate houses, to reduce pollution, etc. then science is producing successful outcomes. (Of course, those same instruments may well be put to work in ways that contribute to developing weaponry that can be used to dominate and oppress groups of people; that increase pollution from industrialisation; that are used for increasingly fast stripping of non-renewable resources and destruction of valuable habitats, etc.) From an academic point of view, good theories and models would be those that fit, explain and predict the data, and that is all we can hope for. Glasersfeld’s constructivism (see §1.5.2) takes a similar approach when considering the individual’s knowing about his or her world. (This point is further examined later in the context of considering criticisms of constructivism in Science Education – see §5.2.7).

2.2.2

Popper’s Three Worlds Model

Cartesian dualism can clearly lead to arguments about whether mind is a different sort of ‘stuff’ to the material world (such as the stuff the brain is composed of), or can be explored in terms of differences in the nature of sensory experience and imagination, etc. Bearing in mind the development of cognitive science, a modern perspective might be to assume that mind is contingent on brain but is a different level of description. That is, that we have a discourse of ideas, thinking, imagining, remembering, etc. that meaningfully relates to human experience of mental life – and which provides more useful constructs for discussing many aspects of such experiences than references to neurons, synapses, neurotransmitters, etc. Ultimately we may be able to link descriptions at these two levels, but even if it was in principle possible to reduce discussion of mental states to neuroscience that does not mean this would be the most useful way of discussing these phenomena. We might see a parallel here with chemistry. Most macroscopic chemical phenomena have been explained in terms of the nature and interactions between various ‘quanticles’ – hypothetical entities that behave as quantum particles (Taber, 2005b) – but that does not negate the value of the macroscopic descriptions that are more useful in some contexts (Taber, 2000c). Then again, chemical concepts such as aromaticity, nucleophile, and so forth could in principle be reduced to more fundamental physical principles, and that may sometimes offer useful insights; but the chemical concepts continue to have value and to be the preferred level of discussion in many chemical contexts. Karl Popper suggested it was useful to consider three distinct worlds that humans occupy (Popper, 1979a: 154): • The first is the physical world or the world of physical states. • The second is the mental world or the world of mental states.

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• The third is the world of intelligibles, or of ideas in the objective sense; it is the world of possible objects of thought: the world of theories in themselves, and their logical relations; of arguments in themselves; and of problem situations in themselves. Popper’s World 1 refers to what exists independently of human observers (assuming one takes a position that there is such independent reality, which Popper clearly did). World 2 is the world of subjective experience that cannot be directly shared with, or known by, anyone other than the ‘subject’ of that experience. Popper’s World 3 has something of the flavour of a Platonic realm, comprising ideas, theories, concepts, etc. in abstract. I suggest this is a Platonic type of world, because all that can be found of these ideas in the objective World 1 are representations. We can hold the idea of a circle (in mind, i.e. World 2), or we can describe one in words or as an equation (x2 + y2 = k), or we can draw a diagram (that will have a line of finite thickness and an approximately circular shape), but we can never find a real circle in World 1 (even though there are many examples of objects we would commonly describe as circular). A key feature of Popper’s ‘3 worlds’ model (that is important for Science Education researchers) is that it reminds us how the formation of Public Knowledge always involves mediation through mind, as ‘the second world, the world of subjective or personal experiences, interacts with each of the other two worlds. The first world and the third world cannot interact, save through the intervention of the second world, the world of subjective or personal experiences’ (Popper, 1979a: 155). The lack of direct connection between ‘reality’ and formalised knowledge is important when considering how scientists share their findings: but is also relevant when considering how public knowledge is taught (e.g. in school science), and when considering how it is possible to undertake research that reports the ideas and knowledge structures of individuals. Research reports that claim to offer reliable knowledge of how plants harness the sun’s energy, for example, offer World-3 knowledge of World-1 phenomena (e.g. photosynthesis) interpreted through the minds of the researchers (World-2). Research reports that claim to offer reliable knowledge of how students understand photosynthesis or energy, offer World-3 knowledge of World-1 phenomena (e.g. student answers to questions) interpreted through the minds of the researchers. However, in the latter case, the student comments themselves are an attempt to represent the students’ own subjective (World-2) experience as a result of attempting to interpret the researcher’s questions (Taber, 2008a).

2.2.3

Science, Realism and Objectivity

A key aspect of science, as it is normally understood, is that it deals with objective accounts of the world; i.e. accounts that do not depend upon the specific observer. (This, in turn, is considered to be so because the observers are independently exploring the same objective world – as discussed above.) This simple statement hides some important complexities. For example, two geologists might disagree

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about the age of a rock sample, just as two literary critics may disagree about the worth of a novel. In the case of the novel, it would be generally accepted that judging creative literature has a strong subjective component, so that a disagreement between ‘experts’ could not necessarily be moved to a consensus view by argument or attempts to seek further evidence. That is, there is not a ‘real’ or ‘correct’ quality to the book which could be eventually agreed upon by further careful study. In contrast, a key aspect of science is that it works towards consensus understandings. The assumption is that there is a correct age of the rock sample, one that can – in principle – be agreed upon. That is, that the rock was formed at some fixed period in time (an ontological stance), and that science seeks procedures for estimating this in ways that the scientific community considers to be reliable (an epistemological position). So, although objective knowledge is not always readily obtained it is the purpose of scientific research to work towards it (even if some would see that knowledge as of instrumental rather than absolute worth). In practice there are disputes in science, just as there can be very strong agreements over judgements in the art (Shakespeare is commonly held to have done some good work by those considered knowledgeable about such matters; Bach, Mozart and Beethoven are usually acknowledged as ‘great’ composers by musicologists even if not personal favourites). Art appreciation can certainly include relatively objective (‘technical’) judgement, but is also considered to be about personal taste. It is well recognised that subjective elements influence scientific judgements (made by fallible humans with personal histories and contexts), but the key difference is that science as a public activity is expected to offer safeguards to ensure that ultimately objectivity wins out. There is a reality to be explored, not just a set of personal views. Science then is inherently based on a ‘realist’ perspective: a view that the world is real, and independent of the observer. So in some sense galaxies, comets, elephants, mosses, calcite crystals, magnetic fields and methane molecules all exist whether human beings are around to observe them and investigate them or not. Clearly, the labels and categories are the products of human cognition, but they refer to genuine regularities in nature that would be here regardless of whether we were here to name and attempt to characterise them. This is not a trivial point, because if the social sciences are to be seen as part of Science then they must also meet some such criterion. There is an obvious caveat here – many of the phenomena of social science would not exist (at least on Earth) if there were no people, but the concepts must relate to regularities that exist regardless of the observer. It is not always clear how well this applies. Current understandings of evolution, for example, would probably not be vastly different without Darwin despite his major role in developing a theory of natural selection. Much of modern psychology may have looked very different though, without Freud. In one case we can imagine a possible delaying of developing knowledge, in the other quite possibly significantly different directions to the discipline. (Perhaps this would become less and less true as time passes: if psychiatry is part of a scientific psychology then perhaps we should expect the influence of any individual to diminish as other workers modify the constructs and models to better fit new datasets.)

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Certainly we can imagine that psychiatrists from different schools might offer very different interpretations of the underlying causes of a patient’s problems, suggesting that the ‘findings’ are to some extent dependent on the particular investigator. However, this may be interpreted as psychology being an immature science (that there is a reality to human psyche, but there is not yet good agreement on how to understand and model it). Similarly different therapists from the same school may well uncover different findings in their work with a client. However, whether this is best seen as evidence of subjectivity or differences in clinical skill might determine whether we view such work part of science. This issue is of concern to us, because a parallel situation is found in research into students’ thinking: where researchers of different ‘schools’ describe different types of findings, and specific results may well depend upon the particular questioning skills and styles of individual researchers (see Chapter 5). When we consider the nature of such research in terms of Popper’s ‘3 worlds’ model, the challenge of this area of work is quite clear. However, in both the cases of psychiatric investigations and research into student thinking there is an assumed ‘object’ of the investigation that is being explored, and that is assumed to exist with or without the investigator: e.g. a neurosis, an understanding, a fear of attachment, a belief in magnetic field lines, a notion about the nature of force, etc. (If this seems an obvious and trivial point, it is worth considering that some social constructivist perspectives would deny that intra-psychic phenomena are real, rather seeing them as the outcomes of social processes that become inappropriately assigned to individuals – see §5.4.2.) In both cases it may sometimes be claimed that what was found was in part planted by the investigative methods itself, and this is an issue we will need to consider, but questions of how research perturbs phenomena are slightly different from those about whether there is a potential objective phenomenon to investigate, i.e. the former concern is an epistemological issue of how we can find out about reality. Returning to ontological issues, views of the nature of reality in science have changed, and are open to dispute. The ‘clockwork’ mechanistic universe was challenged by ideas of quantum theory, and more probabilistic notions – famously criticized by Einstein in his widely reported observation that God did not play dice with the universe – became widely discussed in physics. Yet the principle that there is some kind of reality to be argued over remains and science is the label we give to the business of developing our understanding of that reality. An opposing view would be relativism, which suggests that there are multiple realities that are personal and culturally determined. A committed – ‘absolute’ (Biesta & Burbules, 2003) or ‘vulgar’ (Thayer-Bacon, 2003) – relativist would see differences in the ‘science’ of the ancient Egyptians or Chinese to that of Renaissance Italy, or to that of ‘Western’ science today as being based on the cultural capital brought to bear by those living in different contexts, rather than representing some kind of advance towards better objective knowledge. This debate is important to our topic, as constructivism is often associated with relativist assumptions about knowledge (an issue addressed in Chapter 5, §5.4).

2.3

Scientific Method

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Scientific Method

There are many theories and models of what science is and how ‘it’ ‘works’, i.e. what, if anything, is the nature of the ‘scientific method’ that enables us to produce reliable scientific knowledge of the world (i.e. the epistemology of science)? Much of the various scholarship that has evolved over the past century is often labeled as ‘post-positivist’ to distinguish it from earlier, so-called positivist approaches. Although ‘the positivists’ were anything but a uniform group, this label relates to their basic project to explain how it was possible to obtain assured knowledge of the world, i.e. ‘true’ knowledge. The positivist assumption that science has a method that leads to absolute (definitive or ‘positive’) knowledge of the world is now generally considered to be naive and unsupportable, as the previous section may have suggested. The model of ‘scientific method’ that probably reflects many people’s understanding is one of scientific knowledge being ‘proved’ through experiments (e.g. Driver et al., 1996). That is, the ‘experimental method’ offers a way of uncovering true knowledge of the world, providing that we plan our experiments logically, and carefully collect sufficient data. In this way, our rational faculty is applied to empirical evidence to prove (or otherwise) scientific hypotheses. This is a gross simplification, and misrepresentation, of how science actually occurs, but unfortunately it has probably been encouraged by the impoverished image of the nature of science commonly reflected in school science (e.g. in the English National Curriculum, see Taber, 2008d). There have been various critiques of positivist positions. A number of the issues raised are pertinent to considering whether educational research can be classed as ‘scientific’.

2.3.1

The Problem of Induction

A major issue is the ‘problem of induction’. The natural sciences were long considered to be inductive, meaning that it is possible to derive general laws from sufficient examination of specific instances: as William Whewell (who is credited with coining the term ‘scientist’) wrote in his history of the ‘inductive sciences’ ‘by Induction is to be understood that process of collecting general truths from the examination of particular facts’ (Whewell, 1857/1976). It was recognized for many years that although science seemed to depend upon such generalisations (salt dissolves in water, ice melts at 0 °C, birds hatch from eggs, electrons are emitted from hot metal filaments), there was no logically watertight argument to show how one could ever be certain of any general statements based on evidence from only some particular examples. The ‘problem of induction’ is that that we cannot possibly be sure of any of these things (as universally applicable general statements) based on testing only a sample of the examples that exist in the universe. Indeed, Whewell himself seems to have recognised that ‘induction’ has an intuitive appeal, but cannot be readily justified,

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This progress of knowledge, from individual facts to universal laws, – from particular propositions to general ones, – and from these to others still more general, with reference to which the former generalizations are particular, – is so far familiar to men’s minds, that, without here entering into further explanation, its nature will be understood sufficiently to prepare the reader to recognise the exemplification of such a process. (Whewell, 1857/1976: 9)

To ‘behaviourists’ (§1.7.1), induction might be understood in rather different terms: our generalisations are simply responses to the presentation of similar stimuli. There is adaptive value in evolving a mind that is able to abstract patterns and anticipate what will happen next. In a world where there are many such regularities (so palatable foods, dangerous predators, slippery surfaces, toxic berries, quicksand, sources of water, fertile soils, etc. offer very similar appearances on many occasions), the advantages of such a system, even when it sometimes anticipates incorrectly, make it clearly preferable to a mind which waits for unassailable but unlikely logical proof of what will happen next. There is considerable evidence that human cognition seems to work along such lines – generalisation processes that readily form rules, categories, associations, etc. seem to be common features of our thinking (e.g. D’Andrade, 1995). However, psychology and philosophy have rather different concerns here. Psychology may offer descriptions of how or why humans use induction, but that is a different matter from offering a logical justification of the process. The long-standing problem of induction was effectively made passé (rather than being ‘solved’) by Popper. Popper, in effect, suggested that there was no point in trying to find out how science formed generalisation by induction as science was not able to do that. In effect, accepted scientific knowledge may not be true after all, The fundamental difference between positivism and postpositivism is this: the latter does not entail acceptance of a foundational epistemology—the idea that some ideas are indubitably true and thus provide a foundation upon which others can be developed. Unlike positivists, postpositivists are united in their adherence to fallibilism—the idea that all scientific knowledge is potentially subject to the discovery of error, and thus should be regarded as provisional. (Swann, 2003: 253–254)

According to Popper (1934/1959), Science works through a process of testing hypotheses (so-called hypothetico-deductive logic) based on the attempt to exclude possibilities by falsification. Popper’s analysis moved beyond positivism by accepting that scientific knowledge is tentative: and open to review as more evidence comes in. So, even the experimental method, the ‘gold standard’ for research, does not automatically offer generalisable ‘objective’ knowledge. This creates a problem, as under a positivist view of science, it is possible to hold a notion of ‘scientific progress’ in terms of how science is gradually answering questions and accumulating knowledge. From such a perspective one could argue that science in 1900 had progressed since 1800, since more was known in 1900 than 1800. However, once it is accepted that scientific knowledge is never ‘proved’ conclusively, and so some of what was ‘known’ may at any time be downgraded to ‘previously believed but now considered false’ (like caloric, phlogiston, the ether, etc.) then such a simple model of progress becomes untenable. This is a major issue as it could be seen to admit a relativist perspective on knowledge. We might ask how – if we today no longer believe some of what was

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considered as ‘known and true’ a century ago, and what we believe today may be considered wrong in another century – we can step back from our particular context to decide who is actually right? If there is no criterion for scientific progress, then we have as much and no more reason to be considered right or wrong than previous or future generations. Accepting such a critique can lead to a view that the truth of any knowledge claims are relative to a particular culture, i.e. what is taken as true in a specific time and place. It then follows that ancient Greek cosmology has as much right to be considered true as that deriving from modern physics. As another example, beliefs among some peoples that disease is caused by spirits should be seen as valid as the scientific germ theory. From the cultural relativist perspective, these people and their ideas should be seen as no more ‘primitive’ (or advanced) than ourselves. This issue is highly pertinent to the present volume, as it could therefore also be argued that children’s alternative notions of the world are not inferior to those presented in the science curriculum, just different. One of the criticisms of ‘constructivist’ research in Science Education has been that it supports just such a ‘relativist’ view (see Chapter 5, §5.2.5). The view taken in this book does not support such a relativist stance. Whilst it is certainly considered here that seeing ‘children’s science’ as being part of a different culture to that of curriculum science is a useful and in some respects supportable perspective, I take the pragmatic view that the (representation of) scientific knowledge prescribed in an official curriculum is seen within education as being target knowledge established by ‘authority’, and so an appropriate basis for making normative judgements about students’ ideas. Whilst the authority of the curriculum is hardly considered here to be absolute and unquestionable, it is considered to be the body of legitimate representations of scientific knowledge that is itself believed to form something more than a set of cultural habits and idiosyncrasies. That is, scientific knowledge, whilst fallible, makes progress. As Whewell’s words (above) suggested in relation to induction, this is something that seems intuitively obvious, but is harder to logically justify, unless we measure scientific knowledge indirectly in terms of the fruits of its applications (whether gene therapy, faster Formula 1 cars, energy-efficient ‘light-bulbs’, or the possibility of carrying around a substantial music collection coded into an iPod that fits in a pocket and can deliver high-fidelity sound through tiny Bose in-ear headphones). A converse argument could be that science is regressive in facilitating the more ‘efficient’ exhaustion of resources and destruction of habitats.

2.3.2

The Problem with Deduction

According to Popper’s model, Science does not produce absolute knowledge, but still makes progress through the formation of hypotheses that are falsifiable, and preferably bold (not just predicting the obvious); and then attempting to prove them wrong. So according to this perspective, science is seen as a cycle

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of conjectures and refutations (Popper, 1989), and the hypothetico-deductive approach could not lead to absolute truth, but does lead to objective scientific knowledge (Popper, 1979a). If induction is logically fallible, because amassing more and more tests that fit our hypothesis cannot demonstrate it is true, then falsification seems to offer a logically superior approach as any one refutation logical disproves the hypothesis. In logical terms this sounds simple: that one negative result moves us on by showing where we are wrong, where any number of positive results fail to confirm that we are right. However, deduction also leads to logical difficulties. Just as no finite number of positive instances can logically lead to a universal rule, the refutation of a finite number of hypotheses can only lead to a logically necessary truth if there is a limit on the possible number of alternatives to choose between. This is the method of deduction that left only one possibility, allowing Sherlock Homes to deduce the facts in an ‘elementary’ way in the Conan Doyle detective stories: ‘when you have excluded the impossible, whatever remains, however improbable, must be the truth’ (Conan Doyle, 2007: 195). However, if there is in principle an infinite set of alternatives, then no mater how many of these we can deduct as disproved, we will never be left with a single option as the only candidate for truth. An analogy with graph plotting may be useful here. A small number of data points that seem to fit on a straight line or simple curve can never allow us to interpolate with certainty, as there are always many other patterns that could fit the points. We could draw various complex lines that would also pass through the points. In other words, we can find a great many equations that would include our data as solutions – some of which would be more complex equations than others. Each time more data is obtained that fit the simple pattern the new information will exclude many of these possibilities: the new data points do not fall on most of our lines – they do not reflect solutions to most of our equations. However, if there is no limit on the complexity of the allowed curves (and equations that represent them) then no matter how many data points we establish, it is always possible to find alternative curves that would fit the data. Of course, in practice we are often looking for simple patterns, and dismiss highly complex possibilities, as we may think that nature tends to be based on simple relationships – at least in the so-called exact sciences. However, this means that we are importing assumptions (‘scientific values’) that are external to the data (Laudan, 1984; Longino, 1990), and which are not based on it. If we claim that we are justified in doing this because nature usually offers simple solutions, then we are back to basing our decisions on the very principle of induction that the hypothetico-deductive process is meant to avoid.

2.3.3

Another Problem with Refutations

Another issue here is that the logic of hypothesis testing assumes that we are dealing with phenomena that allow predictions of necessary consequences. This is often true in the physical sciences, but may be less so in other disciplines, where

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it is impossible to separate out the interacting effects of complex phenomena, and where tendencies and general rules may be useful for dealing with more complex and less easily reduced phenomena. This clearly is the case in the social sciences such as education, but it may also be so in the (so-called) natural sciences. So in areas of biology, for example, statistical methods are used to interpret the results of experimental tests where control for extraneous factors can only be sidestepped (by hoping effects cancel in large-enough samples), and where findings offer probable ‘knowledge’. That is, a positive result is seen as something that would only be expected by chance at an arbitrary low level, such as less than once in twenty tests. This type of ‘statistically proviso-ed’ knowledge is very common in social science disciplines such as psychology, and in some types of educational research.

2.3.4

The Complication of Instrumentation

Even when there is an identifiable consequence that necessarily follows from a hypothesis, it may be less straightforward to be sure that a negative result really is a refutation. This presumes that the observation made by a researcher is valid and reliable. Scientific research undertaken by humans inevitable involves instrumentation, the means by which data are collected. The simplest scenario might be considered direct observation. That is, the researcher obtains immediate sensory impressions that indicate the outcome of some experiment, without the use of complex technical instruments. To consider a trivial example, a scientific theory might lead to the prediction that when the researcher holds his or her coffee cup a metre or so above the bench and then lets go the cup will hover in the air. The prediction is not sensitive to the precise start position, so there is no need to exactly measure the cup’s initial height above the bench. The notion of letting go may not seem ‘very scientific’, and we may wish a tighter definition, with a clear criterion to determine whether and when ‘letting go’ had occurred. However, let us assume that we agree that the researcher has let go. If the cup falls, this is clearly a refutation. But how would we know the cup falls? Presumably the researcher sees the cup fall, and hears the collision with the bench. In everyday practical terms that seems pretty straightforward and definitive. However, there is clearly some complex series of processes through which events that occur in the world lead to sense impressions that are then interpreted as falling (or hovering) cups. In other words, we rely on some sort of theory of instrumentation involving perception and cognition to be convinced that the researcher has indeed observed a falling cup. It was this possibility of being deceived by our senses that led to Descartes building his metaphysics from a rationalist foundation: I think, therefore I am (je pense, donc je suis/cogito ergo sum) as the only unquestionable belief. A researcher could lie about (i.e. deliberately report something different from) what they have seen, but leaving that aside, we would normally consider a report of this type as likely to be a reliable account of what had happened. However, people are considered to sometimes be subject to delusions, hallucinations, unconscious fabrications of memory,

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inaccurate recall and so on – so even honest people may not have seen what they claim to have seen. There is also the issue of how sense impressions are interpreted. A falling versus a hovering coffee cup may seem clear cut, but many observations made in science require much finer discriminations. Rutherford’s model of the atom depended upon Geiger and Marsden making observations of tiny flashes of light in a cramped dark space for long periods of time. Anyone who has ever watched the night sky will be aware that sometimes we are not sure if we are seeing one star, or two that seem to be along very similar lines of sight; sometimes we are sure we have seen ‘shooting stars’, but on other occasions we have an impression that we have just seen a meteor – but we are not quite sure. Observations that require matching colours against charts, measuring lengths, masses, volumes, temperatures, etc. all additionally rely upon instruments that are suitable when used within designed levels of precision and as intended. Other instruments act as intermediaries in observations. Recognising the shape of a bacterium under a microscope relies on assumptions about the process of magnification in such an instrument (e.g. that it can make images bigger without distorting shape). From our twenty-first-century perspective, Galileo’s critics who refused to look through his telescopes, and denied what he saw, seem ignorant and bigoted. Perhaps they were, but if they had no basis to trust the telescope as an instrument, then they would have also had no basis for making sense of what they might ‘see’ through it, and so have no basis for interpreting perceptions into meaningful observations. Instruments can only be trusted if we are confident in both the theoretical basis of their design, and the standards of their manufacture. Much modern science (in some fields more than others) has moved instrumentation away from the direct sensory experience of researchers, to automatic data collection, so that computers offer output that is already highly processed. Whilst this may remove the problem of relying on the human perceptual–cognitive apparatus to interpret raw data, it replaces this with a complex electronic process running algorithms based on a model set up by the researcher (and coded into a suitable machine language to run on the computer – a translation process that offers another link in the logical chain). This at least makes the processing explicit, which is clearly not the case when a human mind is at work. In either case, the results depend on both the instrumentation and the processing elements of the system. This means that part of any logical chain of inference from scientific research must be (whether made explicit, or not) the theory by which instruments and data processing are considered to allow data to be used to produce answers to research questions. So we say that observations are not pure records of phenomena, but rather are ‘theory-laden’. Lakatos, whose ideas (see Chapter 3) are central to the approach taken in this book summed up how ‘falsifications’ were never absolute, as ‘if factual propositions are unprovable then they are fallible. If they are fallible then clashes between theories and factual propositions are not ‘falsifications’ but merely inconsistencies’ (Lakatos, 1970: 99).

2.4

The Role of Theory in Scientific Research

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The Role of Theory in Scientific Research

Theory is indeed central to science. If absolute knowledge is considered unrealistic, then in pragmatic terms we seek ‘reliable’ knowledge (Ziman, 1978/1991) that supports us in making sense of the world, and in particular in generating predictions that allow us to plan, and to some extent control, our lives. Theory offers the means to do this. Science seeks to develop theory, and uses that theory both in its own development (i.e. to guide research) and in its applications. Generalisations are as dependent upon theory as observation. Tested samples of salt, ice, bird’s eggs, etc. behave in certain ways under certain conditions (and indeed are recognised as belonging to these categories because they fit certain patterns of behaviour). Theories are developed that define the nature of salt, ice, eggs, etc., and are able to offer explanations – models of how the behaviour depends upon the conditions. It is these theories, these models of what is going on, that allow scientists to predict what will happen to other samples of salt or ice, etc. One observation can never of itself lead to such a generalisation. But sufficient observations support the development of theories (through the formation of categories, and models) that lead to predictions, which can then be used to test the theories. The theories are not proved by testing (another sample of soluble salt proves little) but may be in principle be falsified this way (a sample of insoluble salt needs to be explained – whether by re-categorisation, questioning our instrumentation, or dropping or modifying our theory). Popper offered falsification as the basis of progress in science: that science proceeded by cycles of conjecture and refutation. But Popper was aware that this was not a simple matter. Science is a body of knowledge, but not a body of facts or truths, rather a body of conceptual knowledge (based around concepts developed by humans), i.e. of theoretical knowledge. Salt is not just considered soluble because a lot of samples of salt have been found to dissolve. Rather these observations were part of a process of forming a conceptual framework for understanding how and why (and under what conditions) salt will dissolve. This draws upon theory about the nature of salt, and solvation – e.g. notions of substance (a theoretical idea that does not unproblematically map onto real materials); and particle models that classify salt as ionic, water as polar, and which imbue ‘quanticles’ such as ions and molecules as having inherent kinetic energy that can lead to collisions. This is objective knowledge, but not absolute: it is always tentative and provisional. However, clearly, any suggestion that salt is not always soluble is not a simple counter-observation, but a challenge to the theoretical framework which explains salt solubility, and components of which are also tied to a vast amount of other observational data besides from salt dissolving.

2.4.1

Kuhn and Adherence to Theory

There are many examples of this theory-ladenness in science, and indeed much of Thomas Kuhn’s (1970c) notion of scientific revolutions was based on an idea

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that those working within a paradigm take certain things for granted that make it impossible to interpret results as falsifying key beliefs. (This model is explored in more detail in Chapter 3, §3.2.) Although Popper believed that scientists should seek to refute ideas, Kuhn thought that this seldom happened once ideas have become central to a field: so, for example, within a community that believed matter was composed of atoms, it would seem pointless and futile to attempt to disprove their existence. Even if research led to findings that suggested this assumption was false, these were likely to be explained away. Only a scientific revolutionary is able to recognize an anomaly as such and offer a new way of ‘seeing’. For example, in astronomy, a new planet may have been ‘seen’ and recorded as a star many times before someone realises that it does not behave as a star (i.e. anomalous behaviour), and so discovers it as a planet. Kuhn’s description of science is widely discussed but not by any means completely accepted. However, he did raise awareness of the theory-ladenness of all our observations. It may seem that a scientist must be foolish or dishonest to fail to accept clearly falsifying evidence in an experiment. Yet much modern science is based on advanced technology. An anomalous result may mean our idea is wrong; or that the apparatus is faulty or mis-calibrated (both quite common events in laboratories). If careful checking and recalibration of the apparatus do not remove the anomaly then logically we must adjust (some aspect of) our theory. However, we can always choose to believe the fault lies in the theory behind the instrumentation, rather than the key idea we may be committed to. When Galileo pointed telescopes towards the sky, he saw objects that the then current orthodoxy suggested should not exist. Some of those he persuaded to look for themselves denied seeing these objects. Perhaps they were lying. More likely, Galileo interpreted the fuzzy smudges of light as moons around other planets according to his ontological commitment, and other observers saw no more than blurs that had no significance. As they could not interpret the patterns within their ontology of the cosmos, they chose to make an epistemological judgement about the limitations of the telescope for showing clear images of cosmic bodies! According to Kuhn’s model the different observers held incommensurable paradigmatic commitments. Many have criticized Kuhn’s model, as it shows us that science is not only not positivistic (in the sense of being based on a sound foundation that allows absolute knowledge), but it admits that science always depends upon interpretation – judgements about how to interpret data. It is suggested that Kuhn therefore allows relativism into science, the view that all interpretations can be justified, and so there is no certain way of choosing between them. Kuhn’s analysis has been used in this way, although Kuhn himself claims not to be a Kuhnian, at least in this sense of absolute relativism (an issue explored further in Chapter 3, §3.3). Popper offers us a prescription for how scientists should be able to proceed, and Kuhn offers us a historically based model of what does happen in science. These have been considered as competing models of science, although they need not be seen this way. Popper’s approach may be seen as too idealistic, and Kuhn’s of supporting the view that science is nothing special, as paradigms (see §3.2) are largely

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cultural commitments that do not correspond to ‘truth’. In Chapter 3, I will consider a model of science that in some ways draws on both these sets of ideas, and opens up the notion of science to potentially include the social sciences.

2.5

Experimental and Naturalistic Research in Science

Another problem with Popper’s model, at least as it was initially understood, was that if falsificationism is seen as the demarcation criterion for science, then only experimental approaches (which seek to falsify the predictions from bold conjectures) should be admitted as scientific. Put simply, a scientist uses a universal theory about how the world is, to predict that, under specific conditions, a particular circumstance can be anticipated. The theory is then subjected to criticism that, crucially, involves checking to ascertain whether or not the prediction has been fulfilled. For this process to be scientific in the Popperian sense, the prediction must be sufficiently precise for there to be a risk that counter-evidence could be discovered. If it is not sufficiently precise, the process is mere soothsaying. The prediction should also be bold, in the sense of not being obviously consistent with prior expectations. The best predictions are specific, inconsistent with at least some prior expectations, and fulfilled. The next step is to devise an experiment by means of which the prediction could potentially be refuted. (Swann, 2003: 257)

Not all science is based on experimental techniques. For example, Darwin (1859/1968) proposed that evolution occurred by a process of natural selection. Darwin’s theory was largely based on an accumulation of a great deal of observational data. Darwin observed species, geological formations, fossils, etc. However, Darwin did not undertake any controlled experiments to test his idea of natural selection (although he did draw upon the ‘experiments’ of artificial selection as an analogy for his ideas). In the same way, it is not possible to undertake experimental tests in much of geology, cosmology, etc. These sciences build up theories based on the interpretation of observations. These observations may be systematically conducted, but they are not the result of experiments undertaken to find out what happens if the tectonic plates were a different size, or the earth’s crust was thicker, or glaciers retreated at a different rate, or if the earth was closer to the sun or had two moons, or if the conditions in a big bang were different. Under a strict view of falsificationism, topics such as these might be considered to fall outside science. However, clearly we would normally include naturalistic work such as this as part of science. It is not just nature collecting: it is a business of developing models and theories through systematic observations. According to the National Research Council Committee on Scientific Principles for Educational Research in the USA, ‘in science, measurements and experimental results, observational or interview data, and mathematical and logical analysis all can be part of the warrant – or case – that supports a theory, hypothesis or judgement. However, warrants are always revocable depending on the findings of subsequent inquiry’ (NRC, 2002: 3, 18). Science does not all involve ‘fair testing’ and controlled experiments. Indeed,

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some observers would argue that (natural) science has not proceeded by any readily identifiable single methodology: there exists no finite set of general rules that has substance (i.e. recommends or forbids some well-defined procedures) and is comparable with all the events leading to the rise and progress of modern science. Formal requirements defended by scientists and philosophers were found to be in conflict with developments set in motion and supported by the same group. (Feyerabend, 1987: 9)

2.5.1

Reductionism in Science and ‘Relational’ Perspectives

Science has traditionally used a reductionist approach to phenomena of interest: to divide them into the smallest component parts (which can be examined experimentally in the laboratory, and so understood piecemeal in building up a picture of the whole). Some critics of science have argued that such an approach is limiting and even distorting. For example, some feminist schools suggest that a reductionist science reflects a gendered approach to man’s relationship with nature, and that an alternative holistic approach better fits with a model of people integral within nature and interacting with (rather than objectifying and seeking to parse and control) nature (Bentley & Watts, 1987; Thayer-Bacon, 2000). Barbara ThayerBacon (2003: 7), for example, offers a ‘relational’ epistemology (or as she prefers, a ‘relational (e)pistemology’) which avoids the traditional scientific dualisms such as ‘absolute/relative, subjective/objective, mind/body, knower/known’. Whilst such an approach offers a considerable challenge to the traditions of Western science, it is more in sympathy with the way many indigenous cultural groups learn about and understand their environments (Thayer-Bacon discusses examples from among the Native American peoples). Typically, such groups have over thousands of years learnt how to live in balance with their surroundings, harvesting the natural resources at a sustainable rate – something that Western science and technology have clearly been unable to do in supporting the lifestyles adopted, or aspired to, in industrially ‘developed’ nations.

2.5.2

Traditional Ecological Knowledge

Although the knowledge developed within indigenous communities does not take the form of Western science (and indeed is an inherent part of culture that cannot readily be separated from the world view in which it has developed – e.g. there is often no distinction between a material world and a spiritual world), it has been found that this knowledge is much more than a set of anecdotes, observations or ritually informed practices. Rather, such ‘traditional ecological knowledge’ (Berkes, 1993) represents highly insightful ways of understanding the complex interactions between local species and between the living organisms and habitats (Freeman, 1992). Increasingly, it has been realised that many phenomena of interest in science (and Science Education) comprise complex systems (such as ecosystems) that can

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be studied at different levels (Wilensky & Reisman, 2006). Reductionist approaches may not always offer the best ways of understanding such systems, as many important features are emergent, and can only be observed in the system as a whole, rather than by isolating and controlling variables. Teaching and learning in science classes are highly complex phenomena, and later in the book we will meet criticisms of research that ignores context considered integral to the learning processes being studied (e.g. focusing on an individual’s learning and considering the social aspects of learning as background, §5.4). Chapter 7 will include consideration of methodological approaches suitable for enquiry into the complexity of classrooms.

2.5.3

A Post-Positivist Notion of ‘Science’ That Can Include Education

This consideration of the nature of science is very important to educational researchers who may wish to be part of an enterprise that could be considered scientific in terms of producing ‘reliable’ or ‘objective’ knowledge. If we adopt a post-positivist view of science (in accord with much scholarship from the last century) then we are not using controlled experimental research as the yardstick for deciding if we are being scientific. Indeed, D. C. Phillips argues that, The over-emphasis on using gold-standard methodology as the unitary criterion of scientific rigour detracts from the main question at hand when one is assessing an inquiry, which is this: Has the overall case made by the investigator been established to a degree that warrants tentative acceptance of the theoretical or empirical claims that were made? (Phillips, 2005: 594)

As the National Research Council (NRC) Committee on Scientific Principles for Educational Research has suggested, we do not need to limit ‘scientific’ research to experimental research. Rather, ‘methods can only be judged in terms of their appropriateness and effectiveness in addressing a particular research question’ (NRC, 2002: 3), A wide variety of legitimate scientific designs are available for educational research. They range from randomized experiments of voucher programs to in-depth ethnographic case studies of teachers to neurocognitive investigations of number learning using … brain imaging. To be scientific, the design must allow direct, empirical investigation of an important question, account for the context in which the study is carried out, align with a conceptual framework, reflect careful and thorough reasoning, and disclose results to encourage debate in the scientific community. (NRC, 2002: 6)

Even those who hold Popperian falsification as the keystone to a scientific approach may admit other types of enquiry as valid. Swann (2003: 260) argues that ‘the adoption of a Popperian science of education does not necessarily require largescale experiments [as] one well-conducted case study has the potential to cast doubt on existing assumptions’. Although a post-positivist view would imply that ‘nothing is proved when predictions are fulfilled, nor even when they are refuted’; Swann observes that it is still ‘possible to devise ethical and rigorous tests with the potential to challenge, and challenge constructively, existing expectations’.

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However, there may be a danger of defining post-positivist approaches simply in terms of the ways in which a truly positivist model of science falls short of offering a realistic [sic] model of how the sciences have ‘worked’. There are many post-positivist critiques of science, versions of what science is really like, which all agree that science makes progress towards more reliable knowledge, without agreeing on what the characteristics of science actually are, [postpositivists] are united in believing that human knowledge is not based on unchallengeable, rock-solid foundations – it is conjectural. We have grounds, or warrants, for asserting the beliefs, or conjectures, that we hold as scientists, often very good grounds, but these grounds are not indubitable. Our warrants for accepting these things can be withdrawn in the light of further investigation. (Phillips & Burbules, 2000: 26)

To simply argue that positivism is not a viable model of science, so therefore we can be undertaking scientific research (in Education or any other discipline) without being positivist, in itself, might admit any kind of activity claiming itself a science. This is not a very helpful approach, and so it is suggested that the ideas of one post-positivist thinker, Imre Lakatos can offer us guidance here. Lakatos can be seen as offering a view of how science proceeds (through programmes of research) that draws upon the kind of description Kuhn put forward, whilst taking a generally Popperian view of the way in which science may proceed by conjectures and refutations. Lakatos (1970) argued that science proceeds through the establishment, and development, of what he called ‘research programmes’ (RP). Several RP can coexist for extended periods (unlike the paradigms in Kuhn’s model which only coexist during revolutions), but to remain scientific a RP has to be judged ‘progressive’. This model is explored in more detail in Chapter 3.

2.6

Research Paradigms in Education

Educational research studies are often commonly considered to fit with one of two general categories of approach, often labelled as paradigms (e.g. Gilbert & Watts, 1983; Taber, 2007a). One educational research paradigm is characterized as positivistic, nomothetic and confirmatory, whereas the other is seen as interpretivist, idiographic and discovery. Gilbert and Watts (1983: 64) have described the former paradigm as the erklären tradition (‘in which explanation is the goal’), and the latter as the verstehen tradition (‘in which understanding is the goal’). It is arguable to what extent this use of ‘paradigm’ matches Kuhn’s notion of paradigms/disciplinary matrices. Certainly researchers in Education study a wide range of topic areas, drawing upon very different sets of concepts to develop their conceptual frameworks, so would not commonly share organising concepts, key terminology, or even specific methodological techniques. In this sense, there are certainly more than two research communities in Education. Indeed possible alternative paradigms in educational research are sometimes recognised: for example, the notion that work undertaken from a feminist standpoint makes up a distinct paradigm. However, much educational research is seen as fitting within a simple

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dichotomy, considered to be related to basic ontological and epistemological assumptions, organised around such polar constructs as positivistic–interpretivist; nomothetic–idiographic and confirmatory–discovery. These will be considered further, below.

2.6.1

The Significance of Judgements About Choice of Research Paradigm

Even if we do not accept the validity of this simplistic categorisation (which will be examined below), we have to be aware that such a typology is widely used, and is influential. Those being trained as educational researchers are expected (quite rightly) to locate their research projects in terms of their fundamental commitments in relation to the kinds of knowledge that are possible about the world, and the epistemological issues that have to be tackled in acquiring such knowledge. Educational research texts often use this type of division as a referent for discussing such issues, and students may be expected to label their own projects in terms of such markers as ‘interpretivist’. There certainly are educational research studies that clearly match these two forms of research well, and within the context of an educational research training course, students are likely to be encouraged to see that different approaches are suitable for addressing different research questions, and a simple dichotomy (even if a gross simplification of the range of educational research) can be a useful pedagogic device for introducing some key issues (Taber, 2007a). Researchers should explicitly address questions relating to the nature of what they are trying to find out, and the status they can claim for their findings. However, such a distinction, even if intended as no more than a ‘first approximation model’, can become reified and provide a way of understanding the world that can channel the way we perceive it. The ‘two paradigms’ model can act as an influential conceptual framework for thinking about educational research, and so that we may start to ‘see’ all such research through that particular pair of goggles – to borrow a commonly used metaphor (Pope & Watts, 1988). It is also possible that a conceptual distinction intended to be useful in matching research aims to appropriate methodology, can also become used as an evaluative tool, and this is certainly the case here. One educational research paradigm is commonly seen as ‘scientific’, and in some influential quarters this is considered as the type of research worth supporting. So Phillips argues that in the USA, government criteria used to fund research clearly values a particular form of research: [T]he view has become dominant that the focus of educational research ought to be the rigorous establishing of the causal efficacy of educational programmes or treatments (and, along with this, the accurate measurement of effect sizes), and there is renewed determination (supported by governmental funding) to weed out sloppy research … currently more than 80% of US federal discretionary research funds in education goes to work that is judged to be rigorous according to the notorious and narrow ‘gold standard’—namely, how closely the research design comes to the randomised controlled experiment or field trial (RFT). Quasi-experimental and regression-discontinuity designs that approximate the gold

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standard in rigor are grudgingly tolerated, but qualitative case studies, mixed-methods research and ethnographies are beyond the pale. (Phillips, 2005: 583–584)

Such judgements, then, lead to very significant practical consequences. It will argued in this book that research into learning in science cannot simply fit into one or other educational research paradigm as commonly portrayed, and that ensuring progress in this area of knowledge will depend upon coordination of different forms of research, collectively contributing to a coherent RP. This research programme will certainly be ‘scientific’ (in the post-positivist sense explored in this chapter, and in the more specific Lakatosian sense discussed in Chapter 3), but much of it would not match the ‘scientific’ pole of the common dichotomous distinction used in discussing educational research. It is useful then to examine the polar constructs often used to distinguish the main research traditions in Education.

2.6.2

Positivist or Interpretivist

So research that appears to be framed on the assumption that it is in principle possible to find absolute knowledge, is seen as positivist. Research that is based on the view that all knowledge is based on interpretation (for which there is no final arbiter) is seen as interpretivist.

2.6.2.1

Positivist Approaches

Positivism is often taken as being synonymous with ‘scientific’: so that educational research that is considered positivistic is usually considered to be modelled on natural science, and matched against the ideal of the controlled experiment used to test hypotheses. Positivism is seen as implying a knowable reality, which allows the objects of research to be operationally defined and measured, so that hypotheses may be formed and tested. However, as we have seen above (see §§2.2–2.5), such a positivist view of science is limited and impoverished, and in effect offers a caricature of the range of scientific activity under ‘ideal’ conditions. Research that is seen as falling under this heading uses experimental methods, or at least quasi-experimental methods. As in biology and psychology, it is well recognised that control of extraneous variables may be difficult, so statistical methods are often used to test hypotheses using inferential statistics. That is, if ‘subjects’ (usually learners in Education) are assigned randomly to controlled and experimental treatments, then it is possible to use statistical tests to see how unlikely the measured differences in outcomes between the groups would be by chance. Normally, if a difference, in the direction predicted, is found to have a less than 5% chance of occurring by chance, then that result is considered statistically significant. Such a process does depend upon the researcher being able to randomly assign subjects to the two groups. This is sometimes possible, but much educational research depends upon investigating intact classes, where the assignment

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of learners to groups is outside of the control of the researcher, who at best can assign the experimental treatment randomly to one or other group – clearly a much weaker design. Even when it is possible to randomly assign learners to treatment and control groups, this only controls for student characteristics, and not possible other variables: often teacher, time of day of sessions, teaching room, etc. may well vary. The teacher variable would seem likely to be the most significant variable in such a design, but if the same teacher was used then there are other complications (the teacher having worked with one group before the other can influence teaching factors other than the intended difference in treatment). Despite these problems, we have seen that these types of studies are sometimes seen as the pinnacle of educational research.

2.6.2.2

Interpretivist Approaches

Interpretivist research is based on a different set of assumptions about the nature of educational research. Rather than seeking some kind of absolute knowledge, interpretivist research acknowledges that the research process involves developing interpretations. Where positivist approaches assume that the researcher is carrying out a predefined procedure, and could be substituted by another researcher without influencing the findings, the interpretivist accepts that the researcher’s existing beliefs and understandings inevitably colour the interpretations made when collecting data. Such research inevitably has a subjective component. For an interpretivist, we can never move beyond interpretation (although we can have infinite regress of new interpretations, these simply substitute the new observer’s interpretations for those being reinterpreted): that is, ‘the belief that all knowledge claims are interpretations, and that there is nothing to appeal to in judging an interpretation but other interpretations’ (Schwandt, 2001: 68–69). Researchers holding such a view should acknowledge this rather than claim some impossible objectivity.

2.6.2.3

Research Questions

If this seems a rather defeatist approach to some readers, it may be helpful to offer examples. There are many phenomena of interest to educational researchers where a positivistic approach may not be appropriate. So phenomena such as the effectiveness of setting (putting students in different groups according to their measured levels of attainment) compared with students working in ‘mixed-ability’ groups; homework; grading of student work; peer-tutoring; group-work, etc. may be appropriate topics for interpretive studies. Certainly it is possible to pose research questions about these foci that are best framed by a positivist approach: ‘do girls spend longer on their science homework than boys’; ‘does regular grading of student work have motivational consequences’, etc. Such questions may be operationalised and appropriate forms of measurement designed. However, there are other questions we might wish to ask

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which do not lend themselves to unequivocal answers. A question such as ‘is setting a good idea?’ will not have a simple answer. Teachers may disagree (depending on their beliefs and experiences, and perhaps which sets they are assigned); pupils will have different views depending upon the set they are placed in, their confidence levels, whether they are separated from friends and so forth. When exploring such complex issues it may make more sense to set out to determine how the phenomena is understood and experienced by various individuals rather than attempting to objectify it. Of course, both types of research may be carried out: a study of setting could explore a simple objective notion of effectiveness (outcome grades) by some form of quasi-experimental design comparing matched cohorts who are set or mixedability; but could also explore the teachers’ and students’ experiences of teaching and learning in the different arrangements. (It is conceivable that better examination results may not be found in the form of organisation that most of those involved would prefer. In practice more complex findings are likely, so that even considering only examination outcomes, groupings that increase scores of some subgroups may have the opposite effect for others, e.g. perhaps males vs. females.) There is a relevant distinction here between those things that exist in the world independently of human thought, and those that are purely human constructions. The world would still contain, at least from a common-sense realist view, forces, compounds and mosses even if people were not here to observe then, to form concepts about them, and to give them names. Setting, homework, peer-tutoring, grades, group-work simply would not exist if people were not here to conceive and give meaning to them. Snakes may be imbued with different meaning in different cultures, but without their anatomy or physiology being influenced (which is not to say that aspects of their anatomy or physiology cannot be seen as having cultural significance, nor that knowledge of such features cannot be distorted by cultural views – as a trivial example, snakes are often thought of as ‘slimy’). However, homework and assessment grades simply do not exist to have meaning until people construct such meanings. The object of research into snake physiology (something stable) is different from research into cultural meanings associated with snakes (varying within and between cultures) and so appropriate methodology needs to be found in each case. This means that for some sorts of research the manifold or relative nature of the phenomena needs to be addressed. It is no coincidence that there is something of a parallel here with the ideas of Popper and Kuhn, with the comparison between the possibility of objective knowledge, and the idea that any knowledge is dependent upon interpretation through conceptual frameworks which determine how one sees the world.

2.6.3

Nomothetic or Idiographic

Research intended to establish general laws, about what is ‘normal’ is sometimes labelled nomothetic, whereas research that explores the specific nature of individual

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cases is described as idiographic. The idea derives from the philosopher Windelband, who used this distinction as the basis of the difference between the (nomothetic) natural sciences, and the (idiographic) ‘human sciences’ (Schwandt, 2001: 123). This is not necessarily a distinction between types of phenomena, as both types of study will investigate single instances. The difference is that whereas nomothetic research studies the individual case as the basis for developing generalisations, the idiographic study explores the individual for its own sake. Biographies can be considered as idiographic works. Ethnography is a concern with developing an understanding of a particular culture, and so can be seen as idiographic; and case study as a methodology has its primary rationale in the importance of understanding individual cases. This is an important issue for Science Education. If research in Science Education is to be a scientific enterprise it should be concerned with the development of generalised knowledge (that can ultimately inform pedagogy). Yet case studies, and even ethnographic approaches, have featured in research into learning science. To some extent the use of such research approaches reflects a concern with the ‘subjects’ of educational studies as human learners who are of intrinsic worth and interest as individual people. This certainly suggests an idiographic flavour to such studies. Indeed to refer to learners who assist us in our research as ‘research subjects’ may be seen as totally inappropriate on ethical as well as epistemological grounds (i.e. they are people who act as informants for us, not objects of study, and their active engagement in the research process is essential to its success). However, much research of this kind, despite having such an idiographic flavour due to methodological concerns, is intended to ultimately contribute to nomothetic knowledge. The complexity of phenomena such as learning, and the complications of individual differences, suggests that certain research questions of interest need to be explored through studies of individual cases, even if the ultimate aim is to produce general models relating to teaching and learning. The problematic issue of how one can generalise from such studies is a significant one, and will be revisited in Chapter 7.

2.6.4

Confirmatory or Discovery

A third construct commonly used to characterise research studies is confirmatorydiscovery. Research that tests predetermined hypotheses is referred to as confirmatory. This again clearly links with the prototypical ‘scientific’ experimental approach. The alternative pole relates to more open-ended enquiry that explores a situation through developing categories that are considered to be ‘grounded’ in the data collected. This approach is labelled as discovery, as in this type of research it is hoped to discover useful new concepts or models rather than test existing ones. Again, we see one pole appears to be aligned with the stereotype of scientific investigation, the experimental method, where a conceptual framework leads to predictions that can be set out as testable hypotheses, and concepts are given

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operational definitions that allow measurement which can confirm or refute the predictions. However, this is less a distinction between science and non-science than a question of what is appropriate at difference stage of the research enterprise. Even in the physical sciences there may be a period of exploration of a new phenomena to start to form some kind of mental model of what is being studied that necessarily precedes formal experimental work. Indeed, the Baconian method itself included a stage of organising naturalistic observations, and seeking to deduce significant variables that could then be investigated empirically (Russell, 1961).

2.6.5

Questioning the Dichotomy of Research Approaches in Education

These two research approaches are often presented as being competing paradigms, as ‘an intellectual either/or situation’ (Reynolds, 1991: 194), so that ‘researchers with different purposes … tend to see the others as engaged in the same enterprise as themselves, but simply doing it badly’ (Hammersley, 1993: xix). The dichotomy can lead to polarisation of the research community, On the one hand, there are influential figures who countenance only rigorous scientific research; they use as their model of science the randomised controlled experiment or field trial, and they point to experimentation in medicine as the ideal model for educational research. The existence of this group of hardliners fills many other members of the research community with feelings of despair and utter hopelessness. On the other hand – at the other extreme pole of opinion – there are those who see the members of the first group as advocating … a paradigm that is hopelessly modernist, positivistic and imperialistic; … This second position is so murky and fraught with danger that it is regarded by the advocates of scientific rigour as leading to the total extinction of the empirical research enterprise (how, for example, could an epistemology that eschews normativity lead to anything but relativistic chaos?) (Phillips, 2005: 578–579)

If we accept this notion of education researchers having to choose to work within one or other paradigm, then the choice is indeed something of a stark one. However, some observers (e.g. Carr & Kemmis, 1986: 105) would not agree that ‘scientific explanation and interpretative understanding are mutually exclusive categories’. Biddle and Anderson (1986: 239) have argued that ‘confirmationism and the discovery perspective’ can be integrated into a broader notion of how we can come to new knowledge in the social sciences (such as Education). Interestingly, according to Danziger (1995), the origin of the nomothetic– idiographic distinction was not meant to be the basis of distinguishing science from non-science, but rather Windelband ‘introduced his famous polarity in order to distinguish between two kinds of science … “sciences of law” (Gesetzeswissenschafren) and “sciences of events” (Ereigniswissenschaften) … both sciences, both explanatory, although in different ways’ (p. 115). Danziger explains that the historical or idiographic sciences seek a gestalt showing the interconnectedness of events, as ‘historical explanation deals in part-whole relations, not in logical subsumption under superordinate “laws” [whether] historical or otherwise’ (Danziger, 1995: 115).

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Windelband (1894/1980: 175) himself described his distinction as ‘a purely methodological classification of the empirical sciences’ depending upon ‘the formal property of the theoretical or cognitive objectives of the science in question’. He described how one kind of science was ‘an inquiry into general laws’ whereas the other was ‘an inquiry into specific historical facts’ thus together offering a link from the ‘general to the particular’.

2.7

Scientific Research in Education

The perspective taken here is that whilst different types of research questions should be addressed by distinct approaches, appropriate for the type of knowledge being sought, it is nonetheless possible to consider a wide range of types of educational research study as scientific, in the light of a modern post-positivist notion of Science. As Phillips (2005: 592) has suggested, not ‘all empirical educational research embodies an antiquated, positivistic view of science’, and ‘the broad postpositivistic position, which cannot be dismissed so readily, is quite commonly adopted, even in official reports’. This view is certainly supported by the views of the influential philosopher of science Paul Feyerabend, The idea of a method that contains firm, unchanging, and absolutely binding principles for conducting the business of science meets considerable difficulty when confronted with the results of historical research. We find, then, that there is not a single rule, however plausible, and however firmly grounded in epistemology, that it is not violated at some time or other. (Feyerabend, 1988: 14)

Feyerabend argues that this is not a matter of unfortunate slips, but rather that the progress of science depends upon researchers being prepared to step outside particular formulations of ‘scientific method’. Indeed as we do not yet know the nature of what is still to be discovered about the world, it would seem foolish, from Feyerabend’s perspective, to limit ourselves by adopting a preconceived notion of what methodology we should admit as scientific. A post-positivist view can certainly encompass a broad range of research. It need not do this by accepting all forms of educational research as equally valid, but rather by offering a more informed (and inclusive) view of how science proceeds, where it is accepted that 1. Absolute certain knowledge of the world is not possible; i.e. that ‘human knowledge is not based on unchallengeable, rock-solid foundations – it is conjectural’, yet ‘we have grounds, or warrants, for asserting the beliefs, or conjectures, that we hold as scientists’ (Phillips & Burbules, 2000: 26). 2. Understanding the implications of any particular research findings necessarily involves some process of interpretation, and so is dependent upon the specific conceptual frameworks applied to make sense of data. So as Phillips and Burbules (2000: 65–66) argue, ‘when science is viewed according to the postpositivist model – in which observations are theory-laden, facts underdetermine

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conclusions, values affect choice of problems, and communities of researchers must examine methods and conclusions for bias – then the perceived gap between social and natural sciences begins to disappear’.

2.7.1

A Post-Positivist Paradigm for Educational Research?

Post-positivist analyses of Science offer some guidance to how scientific research in Education might be characterised. It certainly could follow experimental (or pseudoexperimental) approaches, but this would not be necessary. This was recognised by the Committee of the US National Research Council when arguing that ‘methods can only be judged in terms of their appropriateness and effectiveness in addressing a particular research question’ (NRC, 2002: 3). Philips (2005: 594), as we have seen, suggested that the key question was ‘Has the overall case made by the investigator been established to a degree that warrants tentative acceptance of the theoretical or empirical claims that were made?’ The NRC (2002: 6) position reflects this, describing how ‘a wide variety of legitimate scientific designs are available for educational research [that] range from randomized experiments of voucher programs to in-depth ethnographic case studies of teachers to neurocognitive investigations of number learning using … brain imaging’. Here we have a liberal interpretation of scientific method, if not quite a Feyerabendian free-for-all. Methods must be fit for purpose. So the methods that suit an exploratory study may not be suitable to test more specific hypotheses. The NRC’s committee took the view that ‘advances in scientific knowledge are achieved by the self-regulating norms of the scientific community over time, not, as sometimes believed, by the mechanistic application of a particular scientific method’ and that ‘at its core, scientific inquiry is the same in all fields’. So according to the NRC (2002: 2), scientific research, • Is a continual process of rigorous reasoning supported by a dynamic interplay among methods, theories and findings • Builds understandings in the form of models or theories that can be tested That is certainly a view that will be accepted and adopted in this book.

Chapter 3

A Model of Science: Lakatos and Scientific Research Programmes

Chapter 1 described a field of study, Science Education, located within a much wider domain of enquiry that is concerned with aspects of learning, development, cognition, and coming to knowledge. As part of the discipline of Education, Science Education is classified as belonging to the social sciences, usually seen as being significantly different from the natural sciences. However, Chapter 2 explored different approaches to research, and it leads to a view that the demarcation of what is, or is not, considered science is perhaps best understood without regard of such labels (as ‘physical, ‘natural, ‘social’, ‘human’ science). The conclusion is that educational enquiry may (but need not necessarily) be scientific: just as enquiry into energy sources, transmutation of elements, or the origin of species may (but need not necessarily) be scientific. This chapter presents an account of the model of science as research programmes offered by Imre Lakatos as a way of evaluating research traditions (in any sphere) and so determining if they are ‘progressive’ and therefore ‘scientific’. The chapter explains the origin of Lakatos’s model in the debate between, in particular, Karl Popper and Thomas Kuhn, and introduces the central features of the Lakatosian model that will be adopted and applied in the subsequent chapters.

3.1

Lakatos: An Alternative to Popper and Kuhn

This chapter discusses the model of scientific research programmes (SRP) proposed as an analytical methodology by Imre Lakatos (1970). Chapter 2 considered the nature of research in science, in terms of a post-positivist view of Science that seeks to offer a basis for seeing science as the source of reliable knowledge about the world, despite the acknowledged difficulties with justifying any knowledge claims. It was argued that research in Education (and other social sciences) could be encompassed within a post-positivist notion of science, although not all research in Education would (or should) be considered scientific. Lakatos’s model offers a post-positivist model of how scientific progress can be gauged, that can encompass research in the social, as well as the natural, sciences. A strength of Lakatos’s model is that it offers criteria for examining Research Programmes (RP) to determine which are ‘Scientific’. For Lakatos, as we will see, a SRP needs to be K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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‘progressive’, something that the model offers means for us to judge. A progressive RP is scientific (whether from within the natural sciences, or beyond), where a RP that is not – has never been or is no longer – progressive, is not scientific. We might consider that before the advent of ‘modern’ chemistry, alchemists were doing science, as they certainly undertook systematic empirical investigations directed by a set of ‘theoretical’ (or metaphysical) principles. However, an alchemist today would not be considered to be working in a SRP, as that particular programme has long ceased to be progressive. Within the natural sciences, a RP that ceases to be progressive is likely to be abandoned, and indeed there are few conferences or specialist journals for any modern-day alchemists. Not all research in Education aspires to be ‘scientific’ (as was discussed in Chapter 2), but for educational researchers who do see their work as part of a broader ‘science’, Lakatos’s notion of SRP offers a model that can both support such a conceptualisation, and offer heuristic guidance on how to maintain a progressive RP. Lakatos presented his model of SRP in the context of an ongoing debate where the main protagonists were Karl Popper who saw science as proceeding through conjecture and refutation, and Thomas Kuhn who had described science in terms of ‘paradigms’ (see §2.4.1). Lakatos’s model of SRP draws upon and could be seen as attempting some form of synthesis of the thesis of Popper and the somewhat antithetical ideas of Kuhn. Therefore, although there are other key thinkers about science who have contributed to current thinking about the nature of Science, the positions of Popper and Kuhn are of particular interest in understanding Lakatos’s model. This is shown in highly simplified form in the following caricature: Thesis

Scientists should test theories by falsification – designing experiments to refute them – and abandon those that are falsified Antithesis But scientists work within a tradition (paradigm) that primes them to interpret data in certain ways, and so to explain away incongruous data Synthesis An individual experiment can never be critical in disproving a theory as an anomaly may relate to subsidiary issues, but within a RP we should expect to see clear progress in developing theory that can match and predict empirical facts

(Popper)

(Kuhn)

(Lakatos)

The present chapter will first provide the context of the Popper–Kuhn debate, and in particular the nature of the ‘paradigms’ in science which Kuhn felt were needed to make sense of scientific ‘revolutions’. Lakatos offered the notion of the RP as an alternative ‘unit of analysis’ in studying Science, one that overcame some of the objections to Kuhn’s analysis. The chapter will then introduce the key features (and terminology) of Lakatos’s model – the ‘hard core’ and associated ‘negative heuristic’, and the ‘protective belt’ and ‘positive heuristic’. Once the key components of the model are introduced, the chapter will explore Lakatos’s notion of a

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progressive (and therefore ‘scientific’) RP. The groundwork will then be in place to (in Chapter 4) characterise research into student learning in science as a SRP.

3.2

Paradigms As a Unit of Analysis in Science

The widespread use of the term ‘paradigm’ to describe mindsets in Science derives from the highly influential study into The Structure of Scientific Revolutions (TSoSR, Kuhn, 1996), first published in 1962. Kuhn’s description of Science consisting of researchers working in paradigms has been widely discussed in science studies (i.e. the history and sociology of science), although it is less commonly used by natural scientists themselves. In social science the term has been widely adopted to describe different sets of commitments in research, although it is arguable that this is a significantly different meaning to that used by Kuhn himself. (It should also be noted that ‘paradigms’ are used in experimental psychology, with yet another, more restricted, meaning: as a standard experimental design.) Kuhn’s ideas are not universally accepted, and it is certainly arguable that even if some theory-change in Science is revolutionary, the model may not always apply. The importance of these ideas here is twofold. As well as offering some background to the nature of the Lakatosian model of SRP that is adopted in this volume, Kuhn’s model of science led to criticisms that are strongly reflected in some of the debate about the ‘constructivist movement’ in Science Education. Arguments about relativism in Kuhn’s work, and the incommensurability of conceptual frameworks, have been revisited in the context of research into learning science (as will be discussed in Chapter 5), so the nature of these ideas, the criticisms raised, and Kuhn’s responses are all directly relevant to the research in Science Education that is the core concern of this book.

3.2.1

Revolutionary Science and Normal Science

Kuhn’s background was in physics, but he became interested in the history of science. Kuhn’s focus was on ‘scientific revolutions’, when major changes in scientific thinking occur, and he was interested in how these come about. Kuhn’s scientific revolutions refer to specific scientific theoretical changes, and should not be confused with ‘The Scientific Revolution’, a term which is sometimes used to describe the period when Science developed its dominant role in society, i.e. c.1550–1700 (Hall, 1981). A scientific revolution requires at least one individual to suggest that accepted ways of thinking about the world are wrong, and then persuading others to agree so that a new way of thinking becomes the basis of the consensual view. After the revolution the previous way of thinking is recognised as having been flawed. The status of the theory/model that had previously been ‘objective’ or ‘reliable’ knowledge becomes downgraded from being a consensual scientific model, to being a historical one (Justi & Gilbert, 2000).

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A simple Popperian model (see Chapter 2) would suggest that this process is straightforward: that once the accepted view is refuted, because it fails to pass tests based on its logical consequences, an alternative is found which fits all the previous data and the new results. Of course it was well recognised, including by Popper, that in practice this would not happen. As we saw in Chapter 2, there is usually a chain of logical connection between theories and empirical data, and only some of those links are directly consequential on the theory. So results are in effect a test of the substantive theory, plus all the auxiliary theories relating to instrumentation and the like, and a failure only shows that one of the links is flawed. In practice, in any active scientific field, there is always a wealth of data, including some that prima facie refute the consensus view. This data can be explained away by making assumptions that are not linked to the substantive theory of interest. The question is, then, how is a point reached where prima facie refutations are judged to actually provide a refutation of an accepted theory? Kuhn’s analysis led him to divide periods of scientific work into ‘normal science’ and ‘revolutionary science’, the latter periods being relatively rare, and characterised by a shift between consensus models/theories. Although rare, these revolutions could be quite extended affairs, leading to periods where there was no consensus in the scientific field, and where different schools of thought could be considered to be competing.

3.2.2

The Notion of a Paradigm

Kuhn was interested in how new scientists were prepared for work in Science. He realised that many scientific ideas were not taught by definition but by working through standard examples. In the learning of languages such examples are sometimes called paradigms, and Kuhn adopted the term. This meaning is perhaps closer to the usage in psychology for a standard experimental set-up. However, Kuhn expanded the term to have a much wider meaning. Indeed in TSoSR, Kuhn tended to use the term loosely, with a range of specific and more general meanings. One critic counted 21 distinct meanings, including as a universally recognised scientific achievement; as a myth; as a ‘philosophy’, or constellation of questions; as textbook, or classic work; as a whole tradition; as an analogy; etc. (Masterman, 1970: 61). As a result of this criticism, accepted by Kuhn (1977b), he later suggested the term ‘disciplinary matrix’ for the more general sense, although by this time the term ‘paradigm’ had been widely adopted.

3.2.3

Normal Science

As the name may suggest, normal science is what is going on most of the time. Many scientists will spend their entire careers involved in this activity. In Kuhn’s terms they are working within an established paradigm (or disciplinary matrix,

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see §3.2.4). Kuhn used this term to describe the mindset and rules (maybe including some unwritten, unspoken and not openly acknowledged) which apply to scientists working in a particular area of science. The paradigm 1. 2. 3. 4.

Forms the theoretical basis of the sub-branch of science Is accepted by all the workers in the field Determines what is judged to be the subject of legitimate research in the field Determines the procedures, rules and standards that apply in the field

During the process of obtaining a science degree, and then more specialised research training, the novice scientist is gradually initiated into a paradigm – a type of apprenticeship process that has been described in widely differing contexts as starting with legitimate peripheral participation (Lave & Wenger, 1991). The trained scientist approaches his/her work having adopted and accepted a good deal of the culture and assumptions of a field, and so is ready to work on ‘normal science’. During normal, or paradigm-led, science a great deal of routine research is done. However, according to Kuhn’s model, this does not set out to falsify the theoretical basis of the paradigm. Much of this work is better seen as ‘tidying-up’ the edges and loose ends of a field of research. Kuhn thought that (despite Popper) scientists seldom plan experiments intended to falsify well-established theory, as that would be considered as a waste of time. In this model, the basic theoretic assumptions that have become accepted in a field are adopted by new scientists, many of them unquestioned (having come with the authority of Science and their teachers) and even held tacitly. In addition to not setting out to overthrow the paradigm, the initiated scientist is likely to underplay the significance of any anomalies that arise during experiments (having learnt during her or his period of ‘induction’, e.g. undergraduate laboratory courses, that even the most standard laboratory exercises sometimes offer the ‘wrong’ results, and more experienced scientists, e.g. postgraduate demonstrators and supervising lecturing staff, seldom find this reason to question the underlying principles the exercises are meant to demonstrate). A result that could offer a prima facie refutation of the fundamental theory that underpins a field is more likely to be conceptualised as an annoying failure of experimental apparatus or procedure, or simply ‘human error’, rather than evidence that all those labouring away in an established paradigm are basing their professional work on flawed foundations. Whilst this might seem at odds with the stereotype of the careful open-minded scientist, most anomalies are due to something other than a fundamental failure of basic theory, so a mindset that does not immediately see an unexpected result as the basis for overthrowing the theoretical underpinnings of a field is usually going to be appropriate.

3.2.4

The Disciplinary Matrix

Kuhn (1977b: 294) acknowledged that his use of ‘paradigm’ in TSoSR had shifted, ‘ranging from “a concrete scientific achievement” … to a “characteristic set of

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beliefs and preconceptions” … the latter including instrumental, theoretical, and metaphysical commitments together’. In his words, ‘paradigms took on a life of their own’, Having begun simply as exemplary problem solutions, they expanded their empire to include, first, the classic books in which these accepted examples initially appeared and, finally, the entire global set of commitments shared by the members of a particular scientific community. (Kuhn, 1977b: xix)

Kuhn (1977) responded to the criticism that he used the term paradigm in a number of ways, by introducing a new term, disciplinary matrix, for the ‘shared elements [that] account for the relatively unproblematic character of professional communication and for the relative unanimity of professional judgment’ (p. 297). The disciplinary matrix was ‘the common possession of the practitioners of a professional discipline’, and is ‘composed [of] ordered elements of various sorts’ such as ‘symbolic generalizations, models, and exemplars’.

3.2.5

Scientific Revolutions

According to Kuhn’s model, a scientific revolution is only initiated when an anomaly is noticed, and its significance is understood. Once this happens science enters a new phase as fertile new ideas are conjectured, and tests are proposed to compare the rival ideas. As experimental results are published and checked there will gradually be a move towards a consensus: either, the old paradigm will be found to be basically sound, or a new paradigm will take over – a scientific revolution has occurred. Once the new paradigm is accepted, science returns to its normal phase. It ceases to appear profitable to test the central dogma of the (new) paradigm, and only routine work is planned. This is referred to as a paradigm-shift, a notion that has been compared to a gestalt-shift.

3.2.6

Gestalt-Shifts and Paradigm-Shifts

The notion of a gestalt is that of a pattern that is perceived as a whole (see §1.7.2). The human perceptual–cognitive system tends to recognise patterns as units rather than perceive the world in terms of raw perceptual data. For example, the reader of this text will ‘see’ words, rather than a series of black marks of various shapes made up of straight and curved lines of various extent and orientations (i.e. the symbols for letters). Most readers will be familiar with various ambiguous figures that are capable of being seen as representing different objects (such as a rabbit or duck). Figure 3.1 shows the Necker cube, an image that is meant to give the impression of a threedimensional object, i.e. demonstrating ‘depth perception’. However, it is ambiguous (being a two-dimensional image), as there are two alternative faces that can

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Fig. 3.1 The Necker cube

‘appear’ to be at the ‘front’ of the cube. Staring at the cube allows a ‘shift’ in perception, so that the ‘front’ face recedes (instantly) to the ‘back’ and vice versa. One can see (this element of) the world one way, or another, but not in both ways at the same time. This provides an analogy for how a paradigm-shift leads to a new way for scientists to understand an aspect of the world. Such revolutions may not be clear-cut. In Kuhn’s description of scientific revolutions, some established scientists never accept the new ideas (their careers and reputations having been built on the old paradigm), but the younger workers adopt the more promising framework. Eventually the older scientists retire (or die) and the revolution is complete. This description suggests that scientists’ judgements are influenced by strong subjective factors.

3.2.7

Incommensurability of Paradigms

However, Kuhn was not suggesting that scientists were (generally) being deliberately obtuse, or ‘bloody-minded’, but rather that scientists working in the different paradigms (from within different disciplinary matrixes) held different commitments that gave them ‘incommensurate’ world views which made it impossible to interpret evidence in the same ways. For Kuhn, this incommensurability of paradigms effectively means that scientists were working in different worlds, Examining the record of past research from the vantage of contemporary histiography, the historian of science may be tempted to exclaim that when paradigms change, the world itself changes with them. Led by a new paradigm, scientists adopt new instruments and look in new places. Even more important, during revolutions scientists see new and different things when looking with familiar instruments in places they have looked before. (Kuhn, 1996: 111)

This is, of course, the ultimate implication of the theory-laden nature of observations, that we can only see what the available perceptual and conceptual frameworks guide us to see. As Thagard’s (1992) work has suggested, the decision not to shift to the new paradigm being adopted by most of your colleagues may seem a perfectly rational decision for an individual with a well-developed understanding of the overthrown paradigm (see §6.2.2.21).

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Criticisms of Kuhn’s Model

Although Kuhn’s analysis has become widely discussed and very influential, his work has been subject to some strong criticisms. In Chapter 2 it was suggested that part of the basis for Science was a belief in an objective reality, one that existed independent of the observer. Yet Kuhn’s work seemed to suggest that truth was dependent on the observer – that scientific truth had to be considered relative to a specific culture, a particular time and place. This would imply that paradigm shifts could only be said to lead to different scientific beliefs, but not ‘better’, more accurate ones. Scientists tend to find this view objectionable, as if Science is seen as culturally relative, then it can be seen to be just one approach to knowledge, with no more claim to be trusted that any other (such as reading tarot cards or patterns in tea leaves). This argument has been very influential in some countries, particularly in debates over the status of the scientific theory of evolution (i.e. natural selection) in the school curriculum. If this is just the view that (most) scientists currently hold, and could well be ‘dropped’ in the future (in the way phlogiston and caloric and the clockwork universe are no longer generally accepted), then natural selection should only be taught as one story of human origins alongside versions based on creation from dust and transplants (i.e. the Biblical account of Adam and Eve); or indeed infanticide, castration and incest (the Greek myths); or vomiting due to severe stomach ache (the Boshongo, a Bantu tribe of Central Africa, Silverman, 1970). Such myths take on much more significance than mere stories in the cultures that hold them: reflecting and representing something of the way people in that culture understand their relationship with the world (see §2.5.2 and §5.1.5). Indeed, the argument that the biblical creation stories of Genesis 1 and 2 should be taught as alternatives to the current scientific view has been strongly argued in the USA, and is being loudly voiced in other countries such as Australia and the UK. Kuhn’s model can be seen as admitting such anarchy into Science, as the incommensurability of paradigms means that it is never possible to stand outside one particular world view and make an objective evaluation. Each paradigm is clearly superior, when viewed in its own terms. On such a basis there is no objective notion of progress in Science, and paradigm shifts become little more than trends in fashions. This is clearly not the way most scientists understand their work, believing that such developments as the heliocentric model of the solar system, Newtonian physics, the discovery (sic, not invention) of oxygen, germ theory, natural selection, quantum theory, plate tectonics and modern genetics, inter alia, all represent progress in Science, not just passing fads. Another criticism that can be made of Kuhn’s work is that although it offers a view of scientific revolutions, much theory change in Science appears to occur by much more evolutionary processes, without major debates between opposing camps and sharp discontinuities in research traditions (Toulmin, 1970). This does not in itself negate Kuhn’s model, but suggests it only relates to some types of scientific theory change, and not that which occurs within that Kuhn would call ‘normal science’.

3.3

Criticisms of Kuhn’s Model

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Relativism and Subjectivity

Whilst some have adopted Kuhn’s model to argue a relativist position, Kuhn (1970b: 264) himself has commented that from such a perspective he himself is not a ‘Kuhnian’, and that ‘in one sense of the term I may be a relativist: in a more essential one I am not’. He argued that, scientific development is, like bio l evolution, unidirectional and irreversible. One scientific theory is not as good as another for doing what scientists normally do. In that sense I am not a relativist. (Kuhn, 1970b: 264)

Kuhn found statements that science moves closer to the truth as problematic, because of the tendency for them to become tautologies, Unless, as one of my critics suggests, we simply define the approach to truth as the result of what scientists do, we cannot recognize progress towards that goal. Rather we must explain why science – our surest example of sound knowledge – progresses as it does, and we must first find out how, in fact, it does progress. (Kuhn, 1970a: 20)

As all our observations are theory-laden (see §2.2.2), it is difficult to obtain an objective comparison of different paradigms. Yet Kuhn (1970b: 261) also suggested that there are criteria that stand outside particular paradigms (i.e. what we might call ‘scientific values’) that could be used to consider scientific progress, i.e. ‘accuracy, scope, simplicity, fruitfulness, and the like’. According to Kuhn (1970b: 264) an independent observer would be able to decide which of two theories ‘descended’ from the other, using criteria such as ‘maximum accuracy of predictions, degrees of specialization, number (but not scope) of concrete problem solutions’. This would seem to suggest that although values are external to particular paradigms, they are shared by Science as a whole, a position that could itself lead to a tautology if those values become seen as demarcation criteria for what counts as science. Larry Laudan has explored this issue in some depth, and suggested that the aims claimed for science have themselves shifted and cannot be seen as something external to science that can be applied from without. He offers a ‘reticulated’ model where the theories, methods and aims of science should not been as hierarchical, but rather as interacting levels. Laudan argues that (despite Kuhn’s claims of revolutions) scientific developments usually occur at one of these three levels at a time, and need to be justified in terms of the relationship between the levels (Laudan, 1984). Whilst denying any external absolute values that can be applied, Laudan’s approach offers a model of development within a tradition (e.g. a science will develop new methods justified by existing aims and constrained by existing theories) as a means for analysing and evaluating ‘progress’. So the work of Kuhn and Laudan undermines a notion of science being open to evaluation against external criteria that are in some ultimate sense ‘objective’. This is an uncomfortable position for those who have been taught to expect science to be that area of human activity that is capable of objectivity – of providing knowledge that is independent of any particular viewpoint or position. Science is meant to transcend specifics and offer generalised knowledge: thus the common

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practice of giving accounts of empirical work in a form of language which excludes specification of who carried it out. These thinkers set out to show that we are misguided if we feel we can stand outside of any particular tradition, and apply external criteria that allow us to evaluate paradigms or theories or research in any absolute sense: there are no totally objective criteria. However, this argument can be used to develop an absolute, or ‘vulgar’ (Thayer-Bacon, 2003: 54), relativist position – such that, for example, whether we consider astronomy or astrology to offer more reliable knowledge depends entirely upon the choice of criteria (e.g. those deriving from astronomy or from astrology), and that choice cannot be guided from any external, ‘objective’ basis. In other words, at the end of the day, the decision to adopt any particular criteria – predictive success, explanatory coherence (Thagard, 1992), logical form, economy of premises, etc. – is itself little more than a matter of taste, or indoctrination into a cultural tradition. The prestige given to scientific knowledge in modern industrial societies is, from this perspective, little more than a historical fad, likely to pass out of fashion, as did other once respectable sources of knowledge such as the Oracle at Delphi and necromancy. Such a claim seems ridiculous to most of us born into and educated in industrially developed nations – but then (the relativist position suggests) it would, of course. When the world view of modern science, with its root metaphor of nature as a machine that can be dismantled to find out how discrete parts work (Westfall, 1971), is compared with more holistic views of humans as part of nature, held by many traditional cultures (that tend to harvest natural resources in a sustainable way without damaging habitats) and informing their knowledge systems (Thayer-Bacon, 2003), it is less clear that modern science necessarily represents progress over other cultural world views (see §2.5.2).

3.3.2

The Myth of the Framework

Kuhn’s incommensurability principle implied that scientists working within two different scientific paradigms could not discuss the relative merits of their position in any objective way (Phillips, 1987: 22). Kuhn’s argument was that scientists working in different paradigms, having different world views, or indeed in a sense inhabiting different worlds, did not have a shared basis – a common framework – for discussing the merits of their different positions. This position was severely criticized by Popper (1970: 56), who characterised Kuhn’s position as a ‘widely accepted and indeed a fashionable thesis’ of relativism, i.e.: • The rationality of science presupposes the acceptance of a common framework. • Rationality depends upon something like a common language and a common set of assumptions. • Rational discussion, and rational criticism, is only possible if we have agreed on fundamentals.

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Popper described Kuhn’s view as ‘the Myth of the Framework’. His response to this position reflects the view of Kelly (see §1.6.3) who despite believing that we each develop our personal set of constructs for making sense (and, in particular, discriminations) of the world also thought that ‘no one needs to paint himself [sic] into a corner; no one needs to be completely hemmed in by circumstances; no one needs to be the victim of his biography’ (Kelly, 1963: 15). Popper wrote: I do admit that at any moment we are prisoners caught in the framework of our theories; our expectations; our past experiences; our language. But … if we try, we can break out of our framework at any time. …The central point is that a critical discussion and a comparison of the various frameworks is always possible. … The fact is that even totally different languages … are not untranslatable. … The Myth of the Framework … simply exaggerates a difficulty into an impossibility. (Popper, 1970: 56–57)

In response to such criticisms Kuhn (1977a: xxii) restated his position using language that made his difference with Popper more one of degree, i.e. that effective communication was difficult, and an impediment to discussion: ‘the result was an incommensurability of viewpoints and a partial breakdown of communication between the proponents of different theories’. However, where Popper suggested this is a problem that can be overcome, Kuhn reiterated his view that there can only be a partial solution, Proponents of different theories (or different paradigms…) speak different languages – languages expressing different cognitive commitments, suitable for different worlds. Their abilities to grasp each other’s viewpoints are therefore inevitably limited by the imperfections of the processes of translation and of reference determination. (Kuhn, 1977a: xxii–xxii)

Jerome Bruner, who was strongly influenced by Vygotsky’s work (§1.9.3), has argued that language can be a means of ensuring that we are sharing meaning, that is of ‘constant transactional calibration’ (Bruner, 1987: 87) so that we can understand one another’s minds and one another’s worlds (p. 88). Usually in conversation we understand what the other is saying, and – if not – we are usually aware of this, and have accepted ways of checking on meanings – i.e. what Bruner described as ways of ‘calling for repairs in one another’s utterances to assure such calibration’ (p. 87). Kuhn pointed out that different languages divide up the world in different ways. This is the Sapir–Whorf hypothesis, that the language available to the speaker determines the world view of the speaker (Levin, 1993). From this perspective, translation between the languages (and therefore worlds) of two speakers would inevitably involve some change in meaning (Kuhn, 1970b: 268): thus the ability to grasp another’s viewpoint is not absolute.

3.3.3

Qualified Relativism

Absolute relativism can then be seen as a position that questions and undermines the status of scientific knowledge, but one which it is difficult to challenge without being accused of employing criteria that are a part of what we are trying to evaluate.

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However, it has been argued that more pragmatic positions are useful in moving away from absolute distinctions, as dualisms such as that between absolute and relative notions of knowledge are unhelpful. A view of human knowledge as deriving from the experience of people acting in the world as part of an interacting system suggests that the notion of a purely objective scientist investigating nature from the outside is untenable. For example, Dewey’s approach, discussed in Chapter 1 (§1.5.1), moves ‘beyond the traditional opposition of objectivism and subjectivism’ (Biesta & Burbules, 2003: 13), by considering knowledge as deriving from individual experience which is itself informed by existing knowledge (and so earlier experience). However, Dewey avoids a vision of absolute relativism, with each individual building his or her own isolated and solipsistic world view, through acknowledging the importance of intersubjectivity, Dewey argued, however, that when individuals act together in order to achieve a common goal, they need to adjust their individual approaches, their individual perspectives and patterns of action in such a way that a coordinated response becomes possible. In this process their individual worlds are transformed. These worlds do not become identical, but what does happen, Dewey argued, is that the partners in interaction create a shared, intersubjective, world. (Biesta & Burbules, 2003: 12, italics in original)

Building upon this approach, Barbara Thayer-Bacon has argued for a position she calls ‘qualified relativism’. She acknowledged that ‘knowledge cannot be neutral and unbiased, because people, as constructors of knowledge, are fallible, flawed, limited human beings’ (Thayer-Bacon, 2000: 3), so that ‘all knowledge is provisional and perspectival’. She considers that any claims for absolute knowledge ‘require a leap of faith that cannot be warranted by our reasoning abilities, as fallible, embedded and embodied social beings’ (Thayer-Bacon, 2003: 58). The qualified relativist needs to be aware of and acknowledge their own ‘situatedness’, something that we learn about by ‘our social interactions with others not like us’ (2003: 64). ThayerBacon offers the metaphor of a ‘quilting-bee’ (a communal activity concerned with producing quilts that she argues is found in various societies worldwide) for the process of knowledge construction, and sees her own knowledge as akin to a patchwork quilt, drawing upon a wide range of thinkers who have influenced her. This image is useful in pointing out the diverse sources, and piecemeal accumulation of much of our knowledge. However the two-dimensional associations of the image of a quilt underplays the complexity of knowledge, e.g. where different patches of the ‘quilt’ are inconsistent although can still be sewn into the same overall structure (i.e. are represented in the same individual’s conceptual structures). Helen Longino makes some similar points developing a position she calls ‘contextual empiricism’ (Longino, 1990). Longino agues that the background assumptions that are used in interpreting evidence in science derive from the scientific community, and so to the extent that the community is diverse, assumptions will be questioned. However, to the extent that the scientific community is a closed group that excludes certain viewpoints, common background assumptions will be taken for granted and so will go unnoticed and unquestioned. So qualified relativists while acknowledging they cannot acquire knowledge that is absolute believe that, given this, they can recognise the situatedness of their

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positions, and learn from the challenge of dialogue with others from different contexts. This reflects Popper’s argument that although such dialogue can be impeded by the different languages available to the speakers, this need not prevent communication.

3.3.4

Progress and Non-Revolutions

In all cases of a true scientific revolution there is period of conflict between the supporters of the new ideas and those who defend the old paradigm. But not all examples of scientific progress involve such a conflict. Indeed, since Kuhn first published his account of scientific revolutions, many commentators have suggested that the type of paradigm-shift Kuhn discussed is unusual, with science normally undergoing more evolutionary rather than revolutionary changes. Of course, Kuhn’s use of the term ‘normal science’ itself acknowledges that revolutions are occasional discontinuities that interrupt science’s ‘business as usual’, but he does suggest that major theory change is revolutionary – with anomalies leading to ‘crises’ (Kuhn, 1996). This has been disputed by others who have studied the history of scientific thought (Toulmin, 1970; Laudan, 1984). Lakatos goes as far as to assign Kuhnian revolutions as ‘myths’ (Lakatos, 1973/1978: 6).

3.4

Parallels Between Science and Science Education?

Although these debates were centred on the practice of professional Science, it is noticeable that there are some interesting parallels with debates in Science Education. Certainly the argument about whether different world views should be considered equally valid has been raised in the context of research into students’ ideas about the world. Researchers have sometimes been considered to pay learners’ ideas in science a little too much respect, as if unschooled scientific thinking should be considered a worthy alternative to the consensus models of Science. As will be discussed in Chapter 5 (§5.2), this is certainly not an approach taken by most researchers in Science Education, although such an impression has clearly been given by some authors. The debate about interpreting the world through particular conceptual frameworks is clearly directly relevant to much research in Science Education. It is the ‘conceptual frameworks’ that learners bring to class which are considered to often lead to them interpreting what they see and hear in ways that distort the intended teaching (§4.9). Kuhn’s model offers a parallel to the challenge of communication between teachers and students working within different conceptual frameworks that may lead to learning difficulties; as well as to the challenge of communication between those students and researchers attempting to explore and characterise their thinking.

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Popper’s argument about the ability to escape the prisons of our frameworks is clearly (at least sometimes) applicable, as students are (sometimes) able to shift towards adopting new frameworks akin to those of the curriculum science. The ability to adopt a new framework, if only for the purposes of debate, whilst retaining an existing framework, clearly has relevance to the work of science education researchers exploring student thinking (as it does to the historian of science attempting to understand historical scientific models, and why they may have been held onto in the face of anomalous data). It is also of significance when interpreting student thinking to know that an individual may hold several alternative conceptual frameworks for thinking about the ‘same’ topic area, making the task of understanding and characterising students’ ideas that much more complex. There is a distinction here, of course, between holding several ‘competing’ ways of understanding a topic, because some are adopted as models of others’ thinking; and having a belief system that includes several inconsistent ways of understanding a topic. There need be no inconsistency in the individual’s beliefs in the former case, as ‘my understanding of topic X’ does not need to be consistent with ‘my understanding of how Y understands X’. However, actually holding multiple frameworks of a topic area oneself (as one’s own knowledge of the world) admits further complication: perhaps the individual is not aware of the inconsistencies because they do not parse the world in the same way and so do not need a uniform approach across the topic area (perhaps seeing everyday ‘life-world’ and curriculum science contexts as unrelated); or because they just have not noticed any inconsistency; or perhaps the individual does not have a commitment to consistency (as a ‘scientific value’ for knowledge); or perhaps the individual is aware of the inconsistency but not yet sure which view to commit to; or perhaps the individual considers the different frameworks as imperfect partial models of an aspect of the world that it is difficult or impossible to model in a consistent way (in the way particle and wave models are used to reflect different aspects of the ‘quantum world’). These are clearly issues which confuse research exploring student understanding of scientific topics (and will reappear at various points in later chapters). Finally, if Kuhn’s model refers to ‘revolutionary’ changes in scientific world view, and yet such scientific revolutions are quite rare, then most theory change in Science occurs without revolutions and the discontinuities implied by paradigmshifts. This again has a parallel in research into learning science, where conceptual change is also often considered to be either straightforward or radical. The extent to which this is a dichotomy, and may reflect very different underlying mechanisms, is a key area of interest in the field (see Chapter 6, particularly §6.2.2).

3.5

Lakatos and RP As Units of Analysis

As an alternative to Kuhn’s model, with its central concept of paradigm (or disciplinary matrix) Lakatos suggested that Science was better understood and evaluated in terms of research programmes (RP),

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It is a succession of theories and not one given theory which is appraised as scientific or pseudo-scientific. But the members of such series of theories are usually connected by a remarkable continuity which welds them into research programmes. This continuity – reminiscent of Kuhnian ‘normal science’ – plays a vital role in the history of science; the main problems of the logic of discovery cannot be satisfactorily discussed except in the framework of a methodology of research programmes. (Lakatos, 1970: 132)

Lakatos (1971/1978: 110–111) presented a model of what he understood by such a RP, which, • Acts as the basic unit of appraisal • Which has: 1. A conventionally accepted (and thus by provisional decision ‘irrefutable’) ‘hard core’ 2. A ‘Positive heuristic’ which defines problems, outlines the construction of a belt of auxiliary hypotheses, foresees anomalies and turns them victoriously into examples, all according to a preconceived plan The ‘hard core’, ‘positive heuristic’, and the ‘protective belt’ of auxiliary hypotheses are key features of the Lakatosian model, which will be explained further below. Lakatos’s (1971/1978: 110) model explained scientific revolutions in terms of this notion of RP, i.e. that ‘scientific revolutions consist of one research programme superseding (overtaking in progress) another’. However, not every change in scientific theory made up a revolution, rather most theory change occurred within the continuity of an existing RP, which is considered ‘a special kind of “problemshift” [that] consists of a developing series of theories’ (Lakatos & Zahar, 1976/1978: 178–179).

3.6

The Key Features of a SRP

Lakatos set out a structure for RP. He introduced new terms for the key features of this structure, It has a tenacious hard core, like the three laws of motion and the law of gravitation in Newton’s research programme, and it has a heuristic, which includes a set of problemsolving techniques. … Finally, a research programme has a vast belt of auxiliary hypotheses on the basis of which we establish initial conditions. … I call this a protective belt because it protects the hard core from refutations: anomalies are not taken as refutations of the hard core but of some hypothesis in the protective belt. (Lakatos & Zahar, 1976/1978: 178–179, italics in original)

In effect a RP can be understood to have four components, two of which primarily relate to the theoretical content of the programme, and two of which indicate the manner in which the RP is considered to guide researchers in taking forward their studies. One way of relating these four components is offered in Fig. 3.2. There is a very significant distinction between the two theoretical components, the ‘hard core’ and the ‘protective belt’ of the programme. During the development of a

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A Model of Science: Lakatos and Scientific Research Programmes Invariant element

Progressive element

Theoretical component

Hard core

Protective belt

Heuristic component

Negative

Positive

Fig. 3.2 The main components of a Lakatosian RP

RP, some theoretical commitments do not (cannot) change, i.e. those in the hard core, whereas for the RP to be considered ‘progressive’, the protective belt will be undergoing modification.

3.6.1

The Hard Core and the Negative Heuristic

The hard core of a RP then is the set of theoretical commitments (assumptions) that are so basic to the programme of work that they cannot be changed without undermining the basis of the programme. The commitments are the starting points, in effect the axioms, of the RP. A RP asks, ‘Given this, what else?’ The distinctive, conjectural metaphysics (or hard core) underlying a given scientific research programme will, in turn, exert an important, distinctive regulative influence on theory construction within the programme in the sense that each theory that is produced within the programme will not only be built around but will also imply the fundamental set of statements constituting the distinctive metaphysics. In other words, Lakatosian methodology highlights how the specific metaphysics of a scientific research programme regulates the construction of theories by suggesting a certain range of theoretical possibilities. This, in turn, implies that the specific metaphysics explicitly rules out a range of other theoretical possibilities. (Glass & Johnson, 1991: 34)

So, for example, if geocentric astronomy is considered to have been a RP, then core theoretical commitments might be that the Earth is at the centre of the universe, and that the heavenly bodies move in perfect circles. Astronomers would attempt to produce models of the system that would allow the future positions of the heavenly bodies to be predicted with as much accuracy as possible. Various devices (e.g. epicycles) may be introduced to achieve this, but within the RP no one would develop a model that did away with the Earth’s centrality, or circular motion. So the negative heuristic of the RP would guide researchers away from such ideas as ‘try putting the sun at the centre’, or ‘replace the circles with ellipses’. From a modern perspective, it may seem that the attachment to these two central commitments retarded scientific progress, whilst not being based upon sound scientific evidence. However, the movement of the Earth certainly did not seem likely at the time (and apparently sound arguments were easily formed against the possibility that we are all whizzing through space), and even today circular motion is commonly thought to be natural, and not require explanations (McCloskey, 1983). Certainly a stationary Earth would seem to be the simplest starting point for a cosmology, and circles offer elegance in a model of planetary motion. These may be strictly arbitrary criteria, but they are still ‘scientific values’ widely used today.

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Another example could be drawn from molecular biology. The Crick–Watson– Franklin–Wilkins elucidation of the basic structure of DNA must be one of the most significant specific breakthroughs ever made in the life sciences. In reporting their model Crick and Watson (in one of the great understatements of scientific reporting) acknowledged that ‘it has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material’ (Watson & Crick, 1953). This work underpinned much of our modern understanding of genetics and hereditary. As part of the scheme developed it was argued that genetic information was stored in DNA, which coded for RNA, which in turn coded for proteins. Although the original presentation of this idea was more subtle (Moran, 2007), the version which became popularised in many textbooks suggested a simple one-way flow of information: DNA ⇒ RNA ⇒ protein It is now known that information flow is not limited to this direction, but the idea became known as the ‘central dogma’ of molecular biology, i.e. part of the hard core of theory taken for granted by those working in the field. The suggestion is that within a RP where this is considered to be a central assumption, the negative heuristic of the RP would have guided researchers away from any studies that would have tested the principle – they would not have seriously considered setting up experiments that could only be successful if the central dogma was wrong and RNA could code for DNA. As Lakatos (1970: 135) says, ‘the negative heuristic specifies the “hard core” of the programme which is “irrefutable” by the methodological decision of the protagonists’.

3.6.2

The Protective Belt

In the Kuhnian model, discussed earlier in the chapter (§3.2), it was suggested that those working in a paradigm (or disciplinary matrix) interpret evidence in terms of particular conceptual frameworks that bias them to fail to recognise refutations, or to explain away anomalies. It was suggested above that any particular empirical ‘fact’ that does not seem to fit key commitments can be considered to be due to flaws in theory that is supplemental to the central ideas in the paradigm, e.g. in the theory of instrumentation. In Lakatos’s model, some theoretical commitments are ‘hard core’ (and so irrefutable within the RP), but other ideas that are used in the RP are considered as peripheral and open to modification as needed. Indeed, in one sense, the work of a RP is to develop this peripheral theory so that it makes sense of available evidence in ways fitting the hard core, which is itself ‘tenaciously protected from refutation by a vast ‘protective belt’ of auxiliary hypotheses’ (Lakatos, 1974/1981: 118). It is always possible to invent some conjectured entities or mechanisms, albeit perhaps complex and seemingly unlikely ones, to ‘save the phenomenon’ and make empirical

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evidence fit theories. Whether a RP can remain ‘scientific’ (or ‘progressive’) whilst doing this is another matter, and is considered further below (§3.8). Lakatos sees the peripheral theory that does not form part of the hard core as a ‘protective belt’, which by being open to change is able to protect the hard core itself from refutation, All scientific research programmes may be characterized by their ‘hard core’. The negative heuristic of the programme forbids us to direct the modus tollens [destructive hypothetical syllogism] at this ‘hard core’. Instead, we must use our ingenuity to articulate or even invent ‘auxiliary hypotheses’, which form a protective belt around this core, and we must direct the modus tollens to these. It is this protective belt of auxiliary hypothesis which has to bear the brunt of tests and get adjusted and re-adjusted, or even completely replaced to defend the thus-hardened core. (Lakatos, 1970: 133)

Within the Newtonian programme the ‘three laws of motion’, and the law of universal gravitation, are taken for granted; as the invariance of the speed of light is in Einstein’s programme. As a college teacher, the author’s students regularly produced experimental data that on the face of it refuted the law of conservation of momentum (and so Newton’ laws). However, the author assumed, and his students accepted, that the fault lay elsewhere. (Sadly, the quality and state of school and college apparatus often provides a ready alternative focus for the anomalous findings of students.) It is this process that was alluded to earlier in considering Piaget’s programme of genetic epistemology (§1.8.1). Data that suggested students were demonstrating different levels of cognitive capability in different knowledge domains were not seen as undermining the principle that all individuals pass through a series of invariant stages of cognitive development (a ‘hard core’ assumption of Piaget’s programme). Instead such evidence was interpreted in the light of this assumption, and auxiliary concepts were developed to explain why the appearance of behaviour characteristic of the (conjectured) general stage of development would not be detected at the same time in different contexts.

3.6.3

The Positive Heuristic of a RP

It is the so-called positive heuristic of a RP that ‘saves the scientist from becoming confused by the ocean of anomalies’ (Lakatos, 1970: 135). The term research ‘programme’ implies that research within a RP is planned strategically, and is not simply an iteration of studies following up the most recent specific findings, Few theoretical scientists engaged in a research programme pay undue attention to ‘refutations’. They have a long-term research policy which anticipates these refutations. This research policy, or order of research, is set out – in more or less detail – in the positive heuristic of the research programme. (Lakatos, 1970: 135)

According to Lakatos (1970: 135), the positive heuristic of a RP ‘consists of a partially articulated set of suggestions or hints on how to change, develop the “refutable variants” of the research-programme, how to modify, sophisticate, the

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“refutable” protective belt’. He described this as ‘a powerful problem-solving machinery, which, with the help of sophisticated mathematical techniques, digests anomalies and even turns them into positive evidence’ (1974/1981: 118). As one example of how science can be understood in this way, it is worth considering Charles Darwin’s theory of natural selection, as presented in his Origin of Species (Darwin, 1859/1968). Darwin’s achievement has widely been hailed as a work of genius and one of the major developments in science. Although technically Darwin should be considered as the co-discover of the theory (Darwin & Wallace, 1858), his co-discover, Alfred Russel Wallace had a wide range of scientific interests (Raby, 2001) whereas Darwin made the development of the argument for natural selection the main focus of decades of scholarship. It is also well known that Darwin was initially reluctant to publish his ideas, and a range of reasons have been presented for this. Some of these reasons relate to his concerns about the interpretation and reception of his ideas (and the intensity of debate outside of scientific circles over his ideas over a century later suggests this was well judged), but he was also aware that despite the evidence he had amassed for his ‘one long argument’ (Mayr, 1991), there was an aspect of the theory which was weakly warranted. Whatever acted as the medium of inheritance would surely be diluted in successive generations, yet Darwin’s theory relied upon the possibility of traits being inherited undiluted, and so required a mechanism that avoided this dilution effect. It was many years before Mendel’s statistical evidence for this type of inheritance was widely known and considerably longer before the actual material basis of genes and so the mechanism of reproduction could be proposed. Watson and Crick’s (1953) ‘specific pairing’ that suggested ‘a possible copying mechanism for the genetic material’ referred to above (§3.6.1), came almost a full century after Darwin’s Origin. Yet Crick and Watson had actively been developing models of the structure of DNA in the hope this would help illuminate the very problem of how inheritance worked (Watson, 1968/1980) – i.e. assuming the hard-core tenet of the neo-Darwinian RP that specific traits could be passed undiluted from one generation to the next. In this sense, their suggestion was anything but an unpremeditated insight, but was informed by the positive heuristic of the RP. As a more contemporary example, I am writing this paragraph on the day when a new particle accelerator has been powered up at CERN, the Large Hadron Collider, in an experiment motivated by the positive heuristic of a RP in high energy particle physics – and in particular, the attempt to confirm the existence of a conjectured entity, the Higgs boson, that is currently part of a refutable variant within the protective belt of the RP that those in that field refer to as ‘the standard model’.

3.6.4

Models As Part of the Protective Belt

Lakatos (1970: 135) considered the positive heuristic of a RP to establish a research strategy in terms of a plan for developing increasingly sophisticated models, ‘a

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chain of ever more complicated models simulating reality’, and suggested that ‘the scientist’s attention is riveted on building his models following instructions laid down in the positive part of his programme’ so that he or she ‘ignores the actual counterexamples’. Again there seems to be a suggestion here that theory does not need to always match evidence. However, any particular scientific model is only a partial representation of the world, which only matches observations within a certain range of conditions, and with limited precision. The significance of a particular model depends upon its role within a succession of models, and so – Lakatos (1970: 136) argues – the researcher presenting a new model knows that it ‘is bound to be replaced during the further development of the programme, and one even knows, more or less, how’. The individual models are the ‘refutable variants’ of the RP, and their replacement does not refute the programme itself.

3.7

Refutation in RP

In many ways Lakatos’s position on falsification in science is as radical as Kuhn’s in terms of contradicting Popper’s prescription that science should proceed through conjectures and refutations. Whereas Kuhn suggested that a scientist’s paradigmatic ‘goggles’ usually prevent them seeing anomalies as potential refutations, Lakatos see scientists as deliberately ignoring obvious potential refutations. Not only this, Lakatos (1970: 176) argues that ‘carrying on regardless’ is the appropriate response to anomalies when working in a RP, and that scientists ‘are not irrational when they tend to ignore counterexamples or as they prefer to call them, “recalcitrant” or “residual” instances, and follow the sequence of problems as prescribed by the positive heuristic of their programme, and elaborate – and apply – their theories regardless’. From his reading of the history of Science, Lakatos felt that the idea that theories were tested and rejected did not reflect the way Science proceeds, as the outcomes of a single experiment could rarely be taken as offering a crucial test, One of the most important points one learns from studying research programmes is that relatively few experiments are really important. The heuristic guidance the theoretical physicist receives from tests and ‘refutations’ is usually so trivial that large-scale testing – or even bothering too much with the data already available – may well be a waste of time. (Lakatos, 1970: 151)

This position relates to the earlier discussion of the way that any experiment is a test of the substantive theory (which for Lakatos was only ever a work-in-progress anyway) and the supplementary theories relating to instrumentation and so forth: so according to Lakatos (1970: 120) ‘the very term “counterevidence” has to be abandoned in the sense that no experimental result must be interpreted directly as “counterevidence” ’. For Lakatos, then, the relationship between theoretician and empiricist was not a one-way matter of experimental scientists testing and refuting theories. The theorist could reinterpret negative findings in terms of revisions of the supplementary theories through which data are interpreted to test the substantive theory,

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[W]e have established an appeal procedure in case the theoretician wishes to question the negative verdict of the experimentalist. The theoretician may demand that the experimentalist specify his ‘interpretative theory’, and he may then replace it – to the experimentalist’s annoyance – by a better one in the light of which his originally ‘refuted’ theory may receive positive appraisal. (Lakatos, 1970: 130)

Given that neither confirming instances nor counter-examples logically ‘prove’ anything, most individual experimental tests carry very limited weight. Lakatos (1970: 120) does not deny the role of crucial experiments, but suggests that it is only later that the scientific community is in a position to recognise such a test, i.e. ‘that “crucial counterevidence” – or “crucial experiments” – can be recognised as such among the scores of anomalies only with hindsight, in the light of some superseding theory’. Lakatos was not suggesting that the notion of ‘falsification’ should be completely dropped, but rather that given the logical incompleteness of any proof or refutation in science, judgements were to be made in relative rather than absolute terms. That is, an idea would not be rejected purely because it did not seem to fit all the evidence, but only when an alternative candidate became available which could do a better job, ‘Falsification’ in the sense of naive falsificationism (corroborated counterevidence) is not a sufficient condition for eliminating a specific theory: in spite of hundreds of anomalies we do not regard it as falsified (that is, eliminated) until we have a better one. (Lakatos, 1970: 121)

The key judgement, then, in considering falsification, is in how one theory might be considered better than another. Lakatos offers two features to be considered, in terms of what the theories predict (akin to Popper’s call for ‘bold’ conjectures), and the extent to which the predictions match the data available. Based on these criteria a relative judgement can be made about whether one theory should be adopted to succeed another, where ‘the crucial element in falsification is whether the new theory offers any novel, excess information compared with its predecessor and whether some of this excess information is corroborated’ (Lakatos, 1970: 120).

3.7.1

Quarantine of Anomalies

So Lakatos’s apparently casual approach to evidence should not be taken to suggest that science is not based on empirical evidence, and that negative results can just be ignored completely. The ‘scientific values’ referred to earlier, that would seem to be a tacit if not explicit basis for most scientists’ work, are premised upon the existence of an objective reality, which offers regularity, and which is sufficiently knowable to make scientists’ attempts to model it worthwhile. If nature is regular (e.g. if hydrogen was an element yesterday, it will be today) then when we have effective models we find that findings are consistent with our theories and one another. Rather, Lakatos is suggesting that science would soon grind to a halt if every apparent refuting instance were considered as a problem that needed an immediate response. Available empirical evidence will play its role in choosing between

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theories, but no theory should be discarded until there is a properly elaborated alternative and a balanced comparison may be made, But consistency … must remain an important regulative principle … and inconsistencies (including anomalies) must be seen as problems. … On the other hand, this does not mean that the discovery of an inconsistency – or of an anomaly – must immediately stop the development of a programme: it may be rational to put the inconsistency into some temporary, ad hoc quarantine, and carry on with the positive heuristic of the programme. (Lakatos, 1970: 143)

For example, Mendeleev’s attempts to organise the chemical elements into a table based upon a periodic law led to a model with ‘gaps’ that did not fit any known elements. Mendeleev was confident in his system, and made predictions of the properties of elements (eka-boron, eka-aluminium, eka-silicon) that would be discovered (and later named gallium, scandium and germanium) to plug the gaps (Scerri, 2007).

3.8

Evaluating RP

So Lakatos’s model offers a ‘rational’ explanation for how anomalies could, indeed should, be tolerated with a RP. But he was also clear that RP could not continue indefinitely ignoring apparent refutations, which were to be placed in quarantine, rather than dismissed permanently. So a RP could certainly continue without a constant threat of falsification, but only as long as an overall judgement on the RP continued to show it offered a productive approach. Any scientific theory has to be appraised together with its auxiliary hypotheses, initial conditions, etc., and, especially, together with its predecessors so that we may see by what sort of change it was brought about. Then, of course what we appraise is a series of theories rather than isolated theories. (Lakatos, 1970: 117–8)

Lakatos’s analysis here links two related questions: • When should a RP be abandoned? • What makes a RP scientific? In effect the Lakatosian model offers criteria for deciding whether a RP remains scientific, or ‘progressive’, and so worthy of a scientist’s attention. However, although this is clearly central to decisions about abandoning a RP, Lakatos also suggests that this is only likely to happen if there is a suitable alternative RP to adopt.

3.8.1

Progressive RP

Lakatos used the terms progressive and degenerate to categorise RP. A RP could be progressive despite not offering a perfect fit between theory and evidence, as long as its development continued to refine theory (to offer novel predictions) in ways

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that suggested an overall better fit with data. For Lakatos, a RP ‘is theoretically progressive if each modification leads to new unexpected predictions and it is empirically progressive if at least some of these novel predictions are corroborated’ (Lakatos & Zahar, 1976/1978: 179, italics in original). As one example, I referred above to the Darwinian RP. Darwin’s ideas on evolution, although hugely influential at the time of their first publication, were to some extent set aside in biology for some decades until the rediscovery of Mendel’s work, and the development of suitable statistical tools – the ‘sophisticated mathematical techniques’ that Lakatos (1974/1981: 118) considered part of the apparatus of a RP – allowed a new ‘synthesis’ that supported progress in the twentieth century. The tradition that then developed is sometimes referred to as ‘neo-Darwinian’, to acknowledge that some details of Darwin’s scheme were no longer accepted, and that his original model had been supplemented by input from other sources. However, from a Lakatosian perspective it seems reasonable to suggest that Darwin set out a RP with hard-core commitments, supported by a protective belt of auxiliary conjectures, but that progress was delayed until other scientists found suitable ways to meet the challenges of the positive heuristic of the programme.

3.8.2

Degenerate RP

The key judgement to be made in evaluating a RP is how changes to theory are made, as ‘it is always easy for a scientist to deal with a given anomaly by making suitable adjustments’, but where such adjustments are only informed by an attempt to better fit existing data, then ‘such manoeuvres are ad hoc, and the programme is degenerating’ (Lakatos & Zahar, 1976/1978: 179, italics in original). As Lakatos points out, perhaps with some understatement, ‘scientists rightly dislike ad hoc devices for countering anomalies’ (Lakatos & Zahar, 1976/1978: 179). So whereas ‘in a progressive research programme theory leads to the discovery of hitherto unknown novel facts’, in a degenerating RP ‘theories are fabricated only in order to accommodate known facts’ (Lakatos, 1974/1981: 119).

3.8.3

Competition Between RP

According to Lakatos, a degenerate RP is not worthy of the attention of a scientist, but for a scientist who wishes to remain working in a particular field, a RP can only be abandoned if there is a viable alternative available, [the] objective … reason to reject a programme, that is, to eliminate its hard core and its programme for constructing protective belts … is provided by a rival research programme which explains the previous success of its rival and supersedes it by a further display of heuristic power. (Lakatos, 1970: 155)

In Lakatos’s model it should be clear when one RP offers a better candidate for further progress than another, as ‘one research programme supersedes another if it

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has excess truth content over its rival, in the sense that it predicts progressively all that its rival predicts and some more besides’ (Lakatos & Zahar, 1976/1978: 179). This of course requires the scientists to be able to appreciate the extent to which the two RP are able to make predictions, and be corroborated by the empirical data available.

3.9

Relating Paradigms, Programmes and Frameworks

Lakatos commented that ‘where Kuhn sees “paradigms”, I also see rational research programmes’ (Lakatos, 1970: 177). Indeed, in some ways Lakatos’s model can be seen as an adaptation of Kuhn’s influential model, designed to address some of the common objections to Kuhn’s portrayal of science. Kuhn’s model can be seen as implying that most of the time scientists work within paradigms, i.e. during ‘normal science’, but that the interesting developments (from the perspectives of the history and philosophy of science) take place in the rare events that Kuhn considers scientific revolutions. Certainly common readings of Kuhn’s model seem to consider much of normal science as explained by some form of socialisation process (induction into the paradigm), so that it is the paradigm-shifts which need to be explained as this is where a scientist is prepared to suggest something that contradicts the widespread commitments (and perhaps beliefs) of colleagues in the scientific community. However, ‘normal science’ is more than just ‘tidying-up’ the details of wellaccepted theories, and most theory change takes place within what Kuhn would see as a single paradigm. Lakatos’s model put as much emphasis on how change occurs within the continuity of a paradigm, or, as Lakatos would characterise, a RP. In focusing on change within RP, Lakatos emphasised that theory change within a programme was not arbitrary, as there was a ‘requirement that the auxiliary hypotheses should be formed in accordance with the positive heuristic of a genuine research programme’ (Lakatos, 1970: 182, italics in original). However, in common with Kuhn, Lakatos accepted that within a RP certain concepts and terminology would be developed that would make up a specialised language for those working in the framework, and would therefore provide a conceptual framework which would channel thinking, so offering metaphorical ‘goggles’ through which the world would be ‘seen’, the negative and positive heuristic gives a rough (implicit) definition of the ‘conceptual framework’ (and consequentially of the language). The recognition that the history of science is the history of research programmes rather than of theories may therefore be seen as a partial vindication of the view that the history of science is the history of conceptual frameworks or of scientific languages. (Lakatos, 1970: 132)

Despite this, in Lakatos’s (1970: 104) analysis, it should be possible for scientists to make an effective comparison of competing RP, and so change their allegiances – ‘conceptual frameworks can be developed and also replaced by new, better ones’ – because ‘it is we who create our “prisons” and we can also, critically, demolish

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them’. In this regard, Lakatos sided with Popper (rather than Kuhn) in considering that the conceptual framework adopted by scientists should not prevent them from being able to take onboard an alternative framework, and to then make some kind of ‘objective’ comparison. Lakatos’s position can then be seen as an attempt to offer some kind of synthesis of the Popper–Kuhn debate, my concept of a ‘research programme’ may be construed as an objective, ‘third world’ reconstruction of Kuhn’s socio-psychological concept of paradigm: thus the Kuhnian ‘Gestalt-switch’ can be performed without removing one’s Popperian spectacles. (Lakatos, 1970: 179)

However, in presenting his synthesis, Lakatos (1973/1978: 6) seeks to replace what he sees as two flawed approaches, as ‘the history of science refutes both Popper & Kuhn: on close inspection both Popperian crucial experiments and Kuhnian revolutions turn out to be myths: what normally happens is progressive research programmes replace degenerating ones’.

3.10

Scientific RP and the Social Sciences

Popper had suggested falsification offered a demarcation criterion for Science, i.e. that scientific work proceeds by the hypothetico-deductive approach, where theories were tested by their consequences, and could be falsified by empirical refutation. This is in effect a prescription for how science should proceed under ideal conditions. In practice, for reasons we have considered in Chapter 2, this is often not what seems to happen, Popper’s criterion ignores the remarkable tenacity of scientific theories. Scientists have thick skins. They do not abandon a theory merely [sic] because facts contradict it. They normally either invent some rescue hypothesis to explain what they then call a mere anomaly or, if they cannot explain the anomaly, they ignore it, and direct their attention to other problems. (Lakatos, 1973/1978: 4–5)

As we have seen above, it is not possible to operationalise a simple falsification model in practice, as any ‘test’ is actually a test of the conjectured hypothesis plus a range of auxiliary assumptions; and a negative result only offers a refutation to the overall system of assumptions, allowing the hypothesis to be protected from definite refutation. Lakatos also pointed out that most scientific theories were developed through sequences of models (§3.6.4), and any particular failure of a model to ‘pass’ a test would not undermine the process of developing the underlying theory. Thus, whilst Popper’s position might suggest that a scientific idea is one which can be shown to have definitive consequences which could be empirically tested, this does not imply that – in practice – scientific ideas should be readily abandoned because of prima facie refutations. Falsification does not therefore offer a useful demarcation criterion for judging which activities should be considered science, as in practice scientists normally quarantine anomalies rather than see them as reason to consider a theory falsified.

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The Significance of Demarcation

It was suggested in Chapter 2 that having a warranted demarcation criterion for Science was important for those who work in Science Education, such as teachers and curriculum planners/developers as well as for researchers (see §2.1.1). Lakatos felt that the demarcation issue had very important practical consequences. He gave the example of genetics under the Stalinist regime in the Soviet Union (cf. §1.6.2). As Darwin’s ideas were felt to be at odds with the basis of the Marxist state, Mendelian genetics (which offered the mechanism for Darwinian inheritance) was declared ‘psuedoscientific’ (Lakatos, 1973/1978: 7) and excluded from scientific study. Instead a pseudo-Lamarkian genetics was imposed by Lysenko, who redefined hereditary as ‘the property of a living body to require certain conditions for its life and its development and to react in a certain manner to one condition or another’ (quoted in (Frolov, 1991: 146) ), and who denied the particular roles of genes, Heredity … is inherent not only in chromosomes, but in a living body generally, in any of its particles. It would be wrong, just because chromosomes posses a hereditary property, to consider them a special hereditary substance or hereditary organ. (Frolov, 1991: 147)

Genetic heredity might have been required under the positive heuristic of the Darwinian RP (§3.6.3), but it was inadmissible in Soviet science due to the negative heuristic of Stalinist interpretations of Marxist-Leninism. That the Darwinian programme still dominates evolutionary biology, including in Russia, could be seen as a comment on which of the two RP were found to be progressive (and so scientific) in the longer term. This political interference in scientific matters had great human cost, both to the scientists who worked in the field, who became punished as if criminals, and to the general population when Lysenko’s Lamarkian approach failed to bring sufficient grain harvest to feed the population. This was a case where a judgement about what was scientific was not just of consequence to philosophers, but led to much misplaced scientific effort, a good deal of misery, and a tragic loss of life (quite possibly millions starved who could have been otherwise fed). 3.10.1.1

A Contemporary Example from School Science

The significance of this topic will not be lost on science educators. The theory of evolution by natural selection is the basis of much modern biology, and is represented in the school science curriculum widely, for example, in the USA, the UK, and Australia. Yet there have been widespread movements in each of these countries to either exclude evolution as a compulsory school topic, or to ensure its presentation is ‘balanced’ by the inclusion of alternative views – usually what used to be called ‘creation science’, i.e. literal scriptural versions of human origins, sometimes presented as ‘intelligent design’. These arguments include • That Darwinian natural selection has never been conclusively proven • That some scientists today do not believe in it

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• That even those who do, do not actually accept all aspects of Darwin’s model as he presented it (i.e. in 1859!), but may actually work with different variants of the basic model This is meant to show that natural selection is not sound reliable knowledge, but just one view among many – not shared by the Boshongo, (see §3.3) for example – and therefore it is inappropriate to present it in the curriculum with the authority of Science. To most scientists or science teachers, each of these ‘criticisms’ of natural selection falls well short of making it dubious science, but such a position can only be argued from a coherent notion of what Science is. The debate is complicated because arguments for teaching ‘creation science’ come from fundamentalists, particularly fundamentalist Christians, who argue for the literal reading of scripture, and see the consensual science models as contradicting their deeply held convictions. They argue that the scientific theory is unproven and one possible way of interpreting the evidence (which of course it is, as we have seen earlier), and therefore claim that such a view should not be taught in school as if factual. They are right that evolution should not be taught as factual, but rather it should be presented – as with the rest of science – as a current understanding, albeit supported by a vast evidence base. Natural selection is not ‘just’ a theory: but rather one that has supported a theoretically and empirically progressive RP over many decades. The complication arises because whereas the fundamentalists will argue that scripture offers a literal report of creation, the accounts of creation in Genesis are only two of many such creation stories from around the world. Scientists generally considers these narratives as creation ‘myths’, and so not relevant to science. Yet many of these myths are still part of the world views of traditional communities around the world. Often these communities do not make the same distinctions between poetic and literal accounts or spiritual truths and scientific knowledge (see §2.5.2), so it may not be possible to simply exclude the myths from the science classroom without also excluding the well-developed traditional ecological knowledge of the community. This issue has been raised as the basis of a major objection to constructivist Science Education, and will be considered in Chapter 5 (§5.1). 3.10.1.2

A Contemporary Example from Public Science

Lakatos (1973/1978: 7) gives as another example, to show that this is not a matter only for totalitarian states, of how ‘the new liberal Establishment of the West also exercises the right to deny freedom of speech to what it regards as pesudoscience, as we have seen in the case of the debate concerning race and intelligence’. By coincidence, as I have been drafting this chapter some decades after Lakatos chose this example, the same issue has been the basis of a major news story. The public was ‘warmly invited to attend a lecture, jointly organised by the European Dana Alliance for the Brain, the Science Museum’s Dana Centre and Oxford University Press, by the world renowned scientist: James D. Watson’ who is ‘one of the greatest living scientists, awarded the Nobel Prize in 1962 for his part in the discovery

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of the structure of DNA’ (this invitation was posted on the University of Bristol’s website, for example). The lecture was due to take place on the evening of the day that I was originally drafting this section, but, the event was cancelled as views that had reportedly been recently espoused by Watson were considered beyond the limits of scientific debate. Watson was reported to have suggested that people of African descent – or more correctly perhaps, more recent Africa descent, if Africa is considered the ‘cradle’ of all mankind (Darwin, 1871/2006) – typically, had lower intelligence than ‘ours’ [sic]. He later denied saying this, and claimed that he believed there was ‘no scientific basis for such a belief’ (quoted in the Independent, 19 October 2007). The (London-based) Science Museum placed a notice on its website reporting ‘that Nobel Prize winner James Watson’s recent comments have gone beyond the point of acceptable debate and we are as a result cancelling his talk at the museum this Friday’. Somewhat ironically, earlier the same week the Science Museum (the National museum for Science in the UK) had presented an event on ‘Scientific Racism: A history’. This example shows the importance, particularly for educators having to represent such high-profile comments by scientists in their teaching, of having a notion of what is considered canonical ‘scientific’ knowledge, and so part of normative science.

3.10.2

Normative Knowledge and RP

Lakatos (1970) initially proposed SRP as a methodology for analysing the history of the ‘growth’ of knowledge in the natural sciences (1970), but in this volume the RP model is used to discuss a social science (education), and this deserves comment. Lakatos himself discussed aspects of sociology and psychology in terms of this perspective (i.e. that ‘ Marxism, Freudianism, are all research programmes’, p. 5), and suggested that the ‘methodology’ of RP was suitable for application ‘to any normative knowledge, including even ethics and aesthetics’ (1974/1978: 152, n. 5), thus extending the range of convenience of his ideas beyond those of Popper and Kuhn.

3.10.3

Progressive and Scientific RP

Lakatos’s model of science in terms of RP offers an alternative criterion for recognising Science, based on his notion of a progressive RP. Lakatos suggests that there are two ways that a RP can be progressive, relating to how theories are changed in response to data, and the outcomes of subsequent tests of the refined models. Within a RP, theory is developed through a process of refining models. When empirical evidence does not match the predictions of current models, then those

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models can be adjusted. The adjustments that are made can be judged in two ways. The first type of judgement can be made immediately, and relates to whether or not the adjustment made is undertaken within the spirit of the RP. As we saw above, an adjustment to the theory that is purely designed to patch it up to fit existing data without an underlying rationale is considered ad hoc, and is not considered a scientific approach. However, if adjustments made refine the model to give it more sophistication, based on a rationale derived from the programme, then it is likely that the refined model will offer new predictions that can themselves be tested. Such a refinement to the model is considered to be theoretically progressive. As an example from the school curriculum, consider the Ideal Gas equation (IGE), which offers a fairly good match to empirical data (up to a certain level of precision) within a certain range of conditions. This is a simple model (PV/T is a constant), but is known to ‘break down’ under some conditions. The Van der Waals’ equation offers a refined model that better fits empirical data, i.e. that would seem to ‘refute’ the IGE. The additional terms in the van der Waals’ equation can be rationalised in terms of the assumptions behind the IGE. An ‘ideal gas’ is assumed to have particles that have negligible volume compared with the gas (reasonable, until particle density is high) and which have no forces between them (a reasonable approximation when the particles have a large mean separation and higher velocities). The adjustments made to the IGE can be directly related to the way these assumptions compromise the model: and can be seen to give a new model that approximates to the IGE under those conditions where its assumptions can be expected to be reasonable (low pressure, high temperature); whilst offering new predictions for how gases behave at high pressures and at temperatures close to the condensation point. From the logic of the RP the refinements to the IGE are heuristically guided by previous work in the programme, rather than being ad hoc adjustments just to make the numbers work. It might be worth noting that although there is a superficially a similar relationship in terms of the predictions from Newton’s dynamics and those of special relativity (i.e. the former offers good approximations to the latter over a wide range of conditions), Einstein’s programme is based on rather different hard-core commitments to those of relativity theory, so Einstein’s work cannot readily be seen as a refinement within the Newtonian programme – as what is challenged is not a refutable variant of the programme, but the core commitment to space and time as absolutes that are independent of observers. In Lakatos’ scheme, van der Waals’ equation would be considered theoretically progressive over the IGE. For Lakatos, this was a criterion for a RP remaining scientific. This type of adjustment is permitted, and indeed appropriate, within a scientific research programme (SRP). This would be the case regardless of whether the new predictions offered by the refined model were to be found later to be corroborated by new experiments. A RP remains a SRP as long as it is developed in this spirit. Being theoretically progressive is not necessarily sufficient, however, for a RP to survive indefinitely, as it may well be that an alternative RP is also theoretically progressive, and also offers an alternative heuristic for developing theory which

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has more success in being corroborated by empirical evidence. Lakatos therefore distinguished between theoretically progressive RP and empirically progressive RP, Let us say that such a series of theories is theoretically progressive (or ‘constitutes a theoretically progressive problem-shift’) if each new theory has some excess empirical content over its predecessor, that is, if it predicts some novel, hitherto unexpected fact. Let us say that a theoretically progressive series of theories is also empirically progressive (or ‘constitutes as empirically progressive problemshift’) if some of this empirical content is also corroborated, that is, if each new theory leads us to the actual discovery of some new fact. Finally, let us call a problemshift progressive if it is both theoretically and empirically progressive, and degenerating if it is not. We ‘accept’ problemshifts as ‘scientific’ only if they are at least theoretically progressive; if they are not, we ‘reject’ them as ‘pseudoscientific’. Progress is measured by the degree to which a problemshift is progressive, by the degree to which the series of theories leads us to the discovery of novel facts. We regard a theory in the series ‘falsified’ when it is superseded by a theory with higher corroborated content. (Lakatos, 1970: 118)

So there is a distinction here between a SRP and a (fully) progressive RP. As a minimum a RP must be theoretically progressive for it to be considered scientific. However a SRP that is not also empirically progressive is a candidate for replacement by an alternative RP able to develop theory that (through the testing of its predictions) demonstrates its models offer a more precise account of phenomena.

3.10.4

RP in Science and Psuedoscience

As an example of a RP that he did not consider scientific, Lakatos discussed Marxism. For Lakatos (1973/1978: 5), Marxism represented an example of a RP where ‘theories are fabricated only in order accommodate known facts’. Lakatos argues that the Marxist programme certainly made some bold predictions, but had ‘never’ ‘predicted a stunning novel fact successfully’. Rather it led to ‘some famous unsuccessful predictions’ (p. 5), which were then ‘explained’ by ‘auxiliary hypotheses [that] were all cooked up after the event to protect Marxian theory from the facts’ (p. 6). A SRP leads to novel facts, i.e. makes predictions later corroborated, where Marxism was an example of a RP that ‘lagged behind the facts and has been running fast to catch up with them’ (p. 6).

3.11

The Origins of a RP

Lakatos’s use of the term ‘programme’ was meant to be taken literally, in the sense that he expected a RP to be planned at its outset. The ‘heuristic’ of a RP guided the directions that research would take, so that the way theories succeeded each other reflected the programme. So there would be ‘a certain continuity which … evolves from a genuine research programme adumbrated at the start’, following ‘methodological rules: some tell us what paths of research to avoid (negative heuristic)

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and others what paths to pursue (positive heuristic)’ (Lakatos, 1970: 132). Lakatos (1970: 175) suggested that ‘in an important sense … novel auxiliary theories, are anticipated’ because ‘in the positive heuristic of a powerful programme there is, right at the start, a general outline of how to build the protective belts’.

3.11.1

Nursing RP

Lakatos’s distinction between a RP being theoretically progressive and empirically progressive offers SRP sufficient ‘breathing space’ to become established. A SRP must be theoretically progressive, responding to apparent refutations by modifying theory in ways that lead to new testable consequences, and this is something that should be readily demonstrated. However, it may take much longer to know if the new ‘empirical content’ (the predictions) will lead to new ‘facts’ (corroborating the theory). For example, a quantum hypothesis of electromagnetic radiation was introduced as a device to help make theory fit observations, when the existing theory of blackbody radiation predicted a very different spectral frequency curve than that observed in experiments. The ‘fudge’ gave a very good fit, but was initially seen more as a way of saving the phenomena than a good model of nature. Later empirical evidence, such as Einstein’s work on the photoelectric effect, supported the model. Similarly, quantisation was again seen as a useful trick to explain atomic spectra without necessarily revealing anything profound about atomic structure, but was developed into a theory that produced a good deal of ‘bold’ conjecture – and has now come to be considered as an area where theoretical predictions have been highly successful and match empirical findings with great accuracy. Lakatos explained that it could take considerable time for a theoretically progressive RP to also become considered an empirically progressive RP, to give a stern ‘refutable interpretation’ to a fledgling version of a programme is dangerous methodological cruelty. The first versions may even ‘apply’ only to non-existent ‘ideal’ cases; it may take decades of theoretical work to arrive at the first novel facts and still more time to arrive at interestingly testable versions of the research programmes, at the stage when refutations are no longer foreseeable in the light of the programme itself. (Lakatos, 1970: 151)

Lakatos (1974/1981: 120) cautioned against premature dismissal of new RP, suggesting that ‘one must treat budding programmes leniently: programmes may take decades before they get off the ground and become empirically progressive’. It is interesting in the light of his warning, that one RP that Lakatos himself did not consider to meet criteria of a SRP, Freudian psychology, is now being reassessed in some quarters. So Guy Claxton (2005: 182) suggests that Freud offered ‘something that had the form, at least, of a well-worked-out scientific theory’, and that ‘though many of his theories turned out to be highly fanciful, his evidence weak and his reasoning flawed, nevertheless the empirical enterprise which he has launched has continued, and is at last making … sound and significant progress’.

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Summary

This chapter has considered how Lakatos responded to perceived weaknesses in both Popper’s prescription of Science, and Kuhn’s model of paradigms, by offering a view of Science that was able to accommodate the logical impossibility of proof or refutation of individual theories, without the need to see judgements of scientific progress as only possible from within entrenched positions. The model (or Lakatos would say methodology) of SRP allows Science to be judged at a larger grain size than individual cases of conjectures and refutations, and – like Kuhn’s approach – allows counter-evidence to be interpreted within a particular conceptual framework: something that clearly happens in science and is essential to stop the whole business grinding to a halt. However, adjustments to theory within a SRP have to make sense from the logic of the programme and offer new predictions that are testable, rather than just include ad hoc additions to fit the existing data. A RP that behaves in such a theoretically progressive manner can be considered as scientific, rather than a pseudoscience. Theoretically empirical RP, i.e. SRP, that do not seem to immediately lead to empirical corroboration should be humoured, especially when new, as it may take considerable time for the programme to develop models that are sophisticated enough to become empirically progressive (corroborated). However, even if a RP is theoretically progressive, it cannot continue indefinitely quarantining inconvenient empirical evidence without challenge. Eventually a competing RP will offer an approach that is better able to make progress, and will seem to offer a more fertile home for most researchers. In Chapter 2 it was suggested that educational research (or at least, some educational research) could fit into a post-positivist view of Science. The present chapter has detailed the arguments for, and the nature of, the Lakatosian model of Science, which draws on the influential work of Popper and Kuhn, whilst avoiding some of the key criticisms of their models. It has been argued that RP in the social sciences can be characterised as SRP if they meet Lakatos’ criteria. Chapter 4 will apply the Lakatosian model of RP to the ‘constructivist’ tradition of research into learning in science.

Chapter 4

A Scientific Research Programme Within Science Education

Chapter 3 introduced Lakatos’s model of Scientific Research Programmes, which offers a way of conceptualising research traditions and determining whether they should be considered as ‘scientific’. Earlier in the book it was suggested that Science Education has become an established research field, concerned with teaching and learning in science. Although a relatively ‘new’ field, Science Education is part of a much broader domain of enquiry, some parts of which have long been established (§1.4). This has allowed Science Education to draw upon theories and concepts from cognate fields. In particular it was suggested that two research traditions concerned with learning in science are well established within Science Education. The tradition based upon Piagetian notions of stages of cognitive development was considered briefly in Chapter 1 (§1.6.1). The present chapter offers an account of the establishment of an alternative tradition that has come to dominate much thinking in the field, and is strongly associated with constructivism. It is shown that a good deal of this work can be understood as making up a Lakatosian Research Programme (RP) that was set out in a series of seminal papers around 1978–1983. This highly influential corpus of literature provides both the ‘hard core’ commitments for a RP, and the ‘positive heuristic’ indicating directions for research within the programme.

4.1

Constructivism As a Research Orthodoxy in Science Education

This chapter will set out the basis of a Lakatosian RP into learning science, by demonstrating how a significant body of research literature in Science Education can be understood to be based on a common core of basic commitments, and to be concerned with exploring the same basic set of research issues and top-level questions. This RP overlaps with much of the research in Science Education that is commonly labelled as ‘constructivist’. Lakatos argued that a RP is in outline set out from its very beginnings (§3.11). For Lakatos (1970: 175), a key feature of a RP is its heuristic power, such that ‘not only novel facts but, in an important sense, also novel auxiliary theories, are anticipated’ as a PR has ‘right at the start, a general outline of how to build the protective K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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belts’. Thus, if constructivist research into learning science qualifies as a RP then it should be possible to demonstrate that the initial establishment of the programme implied directions for the movement, i.e. that key aspects of the positive and negative heuristics were present from the establishment of the programme. Constructivism has been acknowledged as ‘something of a research orthodoxy within science education’ (Jenkins, 2000b), and has been described in terms of a Kuhnian paradigm (Matthews, 1993; Solomon, 1994). This volume offers a normative model of constructivist research in Science Education: characterising constructivism in Science Education in terms of the establishment of a RP within the field of research into learning and teaching of science. This provides a model of what this programme of research is centrally ‘about’; the range of issues and questions that studies within the RP will be addressing; and some key assumptions that research in this programme would share. In setting out a RP, boundary conditions are constructed around studies considered to fall within the programme, so potentially excluding other work that may share some commonality with included research. It is probably not possible to make general (non-trivial) statements that would apply to all of the work in Science Education that could be identified as constructivist, and, indeed, this is unlikely to be helpful to those looking for a conceptualisation of the field, or in particular heuristic guidance on productive directions for future research. It is important here (and in particular for the chapters that follow), then, to appreciate that this volume sets out a model of a body of work that is considered to share basic commitments and aims, and to specify that programme, rather than attempt to characterise all those studies that may be considered ‘constructivist’ by their authors or readers. In order to make this distinction, I have elsewhere referred to the RP to be set out here as the Active Construction of Knowledge in Science RP, or – as a key feature relates to the way learning is contingent (e.g. on prior learning; on the ideas circulating in the culture; on linguistic resources; on curriculum context) – as the Contingent Learning and Science Teaching RP (Taber, 2006a). Chapter 1 provided a sketch of the main areas of work from cognate fields that had informed Science Education, and there it was suggested that much of this work highlighted the way human conceptual learning is highly contingent – not only on prior knowledge, but on a whole range of features of the learning context. Following common convention the RP elaborated in this chapter would be referred to as the constructivist programme, but – as will become clear later in the book – there may be good reasons to avoid such a label (as, in particular, constructivism has a wide range of associations that do not always map onto what is essential in the RP as defined here). In Chapter 3, the main components of a Lakatosian RP (hard core, protective belt, heuristics) were explained. This chapter will make the case for considering constructivist research into teaching and learning science as a SRP by: 1. Identifying a hard core of basic assumptions for the RP 2. Identifying elements of a positive heuristic directing research in the field

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3. Demonstrating that key aspects of the positive and negative heuristics were present from the establishment of the programme The Emergence of a Research Programme Tobin (2000: 232) has dated the start of this programme within Science Education to the late 1970s and early 1980s: ‘somewhere during the five year period 1978–1983 the seeds were sown for constructivism to become a dominant way of making sense of mathematics and then science education’. The development of a discrete research tradition in Science Education exploring student learning with a particular stress on the learners’ own ideas, can, as Tobin suggests, be dated to the period 1978–1983. Indeed, 1982–1983 could be considered as something of an Annus Mirabilis for those interested in the role of learners’ ideas in the learning of science. A Seminal Corpus Among the papers that have been especially influential were two studies in the journal Science Education (Gilbert, Osborne & Fensham’s (1982) ‘Children’s science and its consequences for teaching’ and Osborne & Wittrock’s (1983) ‘Learning Science: A generative process’) and three review articles in Studies in Science Education: Driver & Easley’s (1978) ‘Pupils and paradigms: A review of literature related to concept development in adolescent science students’; Driver & Erickson’s (1983) ‘Theories-in-action: some theoretical and empirical issues in the study of students’ conceptual frameworks in science’; and Gilbert & Watts’ (1983) ‘Concepts, misconceptions and alternative conceptions: changing perspectives in science education’. These works are considered here to offer what might be considered as a ‘seminal corpus’ of literature for the RP.

4.1.1

Pupils, Paradigms and Alternative Frameworks?

The first of these seminal papers, by Rosalind (Ros) Driver and Jack Easley, was published in 1978 in the review journal Studies in Science Education. Sjøberg (forthcoming: 6) comments that ‘in hindsight, we may say that this article is a starting point for what we now label the constructivist tradition in science education’. The paper began with an extract from two 14-year-old pupils discussing thermal expansion, and referring to the molecules expanding, and to the ‘heat molecules’. Driver and Easley (1978: 61) asked whether such statements represented ‘misconceptions, errors, partial understandings or misunderstandings?’ They argued that the Ausubelian (§1.9.2) term ‘preconceptions’, would not acknowledge how such notions could have the status of models and theories (p. 62). The alternative term ‘misconception’ implied a misunderstanding of formally taught material, and excluded intuitive theories – ‘the situation in which pupils have developed autonomous frameworks for conceptualising their experience of the physical world’ (p. 62). They suggested instead the more inclusive term alternative frameworks. Gilbert (1995: 180) has commented that ‘the appearance of the seminal paper by

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Driver and Easley (1978), triggered a boom in empirical studies [into “the development of understanding by learners”], to judge from other journals in the following years (e.g. IJSE) which were influenced, with varying degrees of explicitness, by personal construct psychology’.

4.1.2

The Notion of Children’s Science

In 1982, a paper by John Gilbert (Surrey, UK), Roger Osborne (Waikato, NZ) and Peter Fensham (Monash, Australia) used the term ‘children’s science’ to describe the ‘conceptual structures’ which children used to understand the world prior to formal instruction (Gilbert et al., 1982: 627). Gilbert and colleagues contrasted children’s science with scientists’ science – the consensual scientific view of the world and meaning for words (p. 627) – and with teachers’ science – which was different again, but could usually be considered to fall somewhere between the two (pp. 627–628). Gilbert and colleagues also recognised that the ‘viewpoint presented’ in science classes matched none of these, and was the result of teachers’ science being mediated through the presentation of the curriculum (p. 628). If anything, this seemingly complex description is a simplification, as the curriculum contains a set of models of scientist’s science; teachers’ own understandings are likely to be an amalgam of this curriculum science, their understanding of some aspects of scientists’ science, and various idiosyncratic ideas; the view presented in class is often likely to be something different again – a set of teaching models devised to mediate learning of the teacher’s understanding of the curriculum models for a particular group of learners. Gilbert and colleagues (1982) considered the possible outcomes of the interaction of children’s science with curriculum science, and suggested a spectrum of possibilities, from the learners’ ideas being readily displaced by exposure to teaching to student frameworks so stable that they were completely unaffected by teaching.

4.1.3

Considering Pupils As Scientists

Ros Driver (1983) published a book on the theme ‘Pupils as Scientists?’, asking whether learners’ behaviour in science classes reflected that of professional scientists. This was a notion that was being discussed by others developing the field. So when Gilbert and Swift (1985) presented an early account of the burgeoning RP, they described how individuals make sense of the work through a process of hypothesis formation, testing and evaluation (see §4.3.2 for a consideration of the Gilbert & Swift account of the field). Shortly before Driver’s book was published, Watts and Pope (1982) were exploring the question of what kind of scientists pupils might be, and mooting that they could be Lakatosian scientists. Driver’s own analysis was strongly influenced by Kuhnian notions of how science proceeded, and how existing commitments may distort the interpretation of evidence.

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Driver (1983: preface) referred to pupils’ construct systems as ‘spectacles of their own preconceptions’ which acted so that many learners ‘have difficulty in making the journey from their own intuitions to the ideas presented in science lessons’. She compared this ‘journey’ to ‘paradigm shifts in their thinking’ (Driver, 1983: 9). Driver (1983) pointed out that in practical work conceptual frameworks may ‘restrict empirical observations’ (p. 65, and see p. 27, p. 35, cf. Kuhn, 1970c: 79) and there may be attempts to ‘save the phenomenon’ (Driver, 1983: 39). These concerns reflect the issues raised by historians and philosophers of science, discussed in earlier chapters. Driver also noted how some ideas elicited from children were similar to historical scientific ideas (p. 76), something that had previously been noted by Piaget (Driver & Easley, 1978).

4.1.4

Students’ Conceptual Frameworks in Science

Driver used the terms ‘conceptual framework’ and ‘alternative framework’ to refer to aspects of an individual learner’s cognitive structure, i.e. for ‘the mental organisation imposed by an individual’ (Driver & Erickson, 1983: 39) which was utilised ‘for conceptualising their experience of the physical world’ (Driver & Easley, 1978: 62). Driver and Erickson (1983) suggested that that whereas scientists have to closely relate their formal conceptual knowledge to their experiences of the world, school children did not generally demonstrate such integration within cognitive structure. They reported that the two different domains of knowledge could be elicited by different modes of data collection. Driver and Erickson thought that stable alternative frameworks were more likely to interfere with learning of topics where learners will have rich early experiences (such as heat, mechanics and light). Driver and Erickson (1983: 39) set out empirical premises (see §4.3.1) claiming that students often have alternative conceptual frameworks through which they interpret the world; that these frameworks lead to confusion when they are inconsistent with what is taught in school science; but that in principle teaching could be developed to take the frameworks into account.

4.1.5

Concepts, Misconceptions and Alternative Conceptions

Gilbert and Watts (1983: 45–65) highlighted the need to distinguish between ‘an individual’s psychological, personal, knowledge structure’ – e.g. the ‘concept’ as inferred to be in the learner’s head – and aspects of ‘the organisation of public knowledge systems’, i.e. the orthodox academic version of the ‘concept’ as presented in the textbooks, etc. Phillips (1987: 139) has criticized the error of confusing these two distinct phenomena, ‘disciplinary structure and cognitive structure’,

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in the work of Piaget, and indeed failure to clearly make this distinction has been a characteristic of many reports in the field (as will be discussed later, §5.3.4).

4.1.6

Personal Constructivism

The Surrey-based PCK (Personal Construction of Knowledge) group, tended to look to George Kelly (§1.6.3) for the primary source of their constructivist thinking (Pope, 1982), i.e. ‘constructive alternativism’, which proposed that individuals construct models of their environment, based on tentative hypotheses, which are then tested against experience and modified as required (Pope & Gilbert, 1983: 196–7). Kelly’s (1963: 75) ‘personal construct theory’ (PCT) proposed that learning was ongoing and central to personality, and his central metaphor of man-the-scientist (p. 4), was also reflected in Driver’s focus on the pupil-as-scientist (Driver, 1983; Driver & Erickson, 1983). Pope and Gilbert (1983: 197) recognised that the notion of ‘alternative frameworks’ could be related closely to Kelly’s PCT, where each learner held a unique, and dynamic system of personal constructs. Kelly thought that differences between the construct systems of two individuals could be overcome by the ability of individuals to ‘construe the construct system of the other’ (Pope & Gilbert, 1983: 197).

4.1.7

Learning Science As a Generative Process

People have a predilection to make sense of their environment, and to arrange their memories of perceptions in some sort of pattern that acts as a framework for making sense of future experience (cf. §1.5.1). Osborne and Wittrock’s generative learning model (1983) combined the ‘fundamental premise’ that ‘people tend to generate perceptions and meanings that are consistent with their prior learning’ (1985: 64) with insights from information processing models of cognition. In a review paper developing their model, Osborne and Wittrock set out a series of postulates (1985: 64–66): i. The learner’s existing ideas influence what use is made of the senses and in this way the brain can be said to actively select sensory input. ii. The learners’ existing ideas will influence what sensory input is attended to and what is ignored. iii. The input selected or attended to by the learner, of itself, has no inherent meaning. iv. The learner generates links between the input selected and attended to and parts of memory store. v. The learner uses the links generated and the sensory input to actively construct meaning. vi. The learner may test the constructed meaning against other aspects of memory store and against meanings constructed as a result of other sensory input.

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The ‘Alternative Conceptions Movement’

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vii. The learner may subsume constructions into memory store. viii. The need to generate links and to actively construct, test out and subsume meanings requires individuals to accept a major responsibility for their own learning. There are a number of themes here that recur in constructivist accounts of learning in science: knowledge construction being an active process (iii, iv, v); the importance of prior knowledge in interpreting new experiences (i, ii); and the responsibility of the learner in the learning process, and the testing-out of ideas against experience (vi, viii). In addition Osborne and Wittrock’s model took into account the need to consider the nature of the processes by which memories are formed, accessed and modified (vii) – issues which tended to be outside the main foci of much of the early writing within the Science Education literature.

4.1.8

Early Evidence of the Significance of Learners’ Ideas

Nussbaum and Novick (1982) reviewed ‘numerous reports’ then available on alternative frameworks and concluded that almost all suggested that such frameworks interfered with intended learning. Ault, Novak and Gowin (1984), studied learners’ notions of the molecule concept working with the same individuals on two occasions (in second grade, and then in seventh grade) and concluded from their study that the differences in the conceptions in the early grade were significant for later understanding, and that the learners’ meanings as grasped in primary grades would effect their understanding years later (p. 459). Children’s alternative conceptions were being seen as significant for learning, suggesting that research into children’s ideas has the potential to inform teaching.

4.2

The ‘Alternative Conceptions Movement’

Within 2 years of the key papers of Driver and Erickson (1983) and Gilbert & Watts (1983) being published, two edited volumes appeared discussing results from a range of core science topics (Driver et al., 1985; Osborne & Freyberg, 1985). Over a period of just a few years, the study of learners’ ideas about science topics developed into a major international research activity. Over the next decade, this produced a vast literature on learners’ understanding of science (Carmichael et al., 1990; Duit, 1991; Gilbert, 1994). By the end of the 1980s, Driver (1989: 481) was able to report that ‘there is an extensive literature that indicates that children come to their science classes with prior conceptions that may differ substantially from the ideas to be taught’. A popular book appeared reviewing findings in all the main topics taught at secondary school level (Driver et al., 1994). Studies continue to accrue, as reported in the regularly updated bibliography compiled by Reinders Duit under

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the (current) heading Students’ and Teachers’ Conceptions and Science Education (Duit, 2007).

4.2.1

Major Projects: LiSP, CLiSP and SPACE

The RP was in particular catalysed by a series of major projects. The Learning in Science Project (LiSP) based at Waikato, New Zealand, has had several phases (Bell, 2005), but included an early stage focused on student understanding of a range of science topics (Osborne & Freyberg, 1985). In the UK, a major project based at Leeds University, under Ros Driver, was established ‘to develop revised teaching approaches which would be informed by research on children’s thinking in science and current theoretical developments in cognition’ (Driver & Oldham, 1986: 105). The Children’s Learning in Science Project (CLiSP) explored secondary school pupils’ ideas in a number of key topic areas such as plant nutrition (Bell & Brook, 1984), basic ideas in chemistry (Briggs & Holding, 1986), particle theory (Brook et al., 1984), energy (Brook & Driver, 1984), heat (Brook et al., 1984) and light (Ramadas & Driver, 1989). The CLiSP team started working with data collected as part of a National Assessment programme undertaken under the auspices of a section of the Education ministry, the Assessment of Performance Unit (1989). However, as well as working with written test items, and interview data from individual learners, the team undertook case studies of classroom teaching and learning (Brook et al., 1986; Wightman et al., 1986), and looked to develop constructivist approaches to teaching and learning (Johnston & Driver, 1991). The Primary Science Processes and Concept Exploration (SPACE) Project, ‘a five year programme of research and development with non-specialist teachers of science in primary (elementary) classrooms in England’ (Russell & Osborne, 1993: 1) and based at the University of Liverpool, had a two-stage design, exploring pupils’ understanding of key topic areas, and then undertaking a teaching intervention. As well as research reports on key topics – the Earth in space (Osborne et al., 1991), electricity (Osborne et al., 1991), evaporation and condensation (Russell & Watt, 1990a), growth (Russell & Watt, 1990b), light (Osborne et al., 1990), materials (Russell et al., 1991), sound (Watt & Russell, 1990) – the project informed the development of the Nuffield Primary Science resources, i.e. teaching guides and student books.

4.2.2

Constructivism Becomes Widely Taken-for-Granted

A good deal had happened in Science Education over the period from the early 1980s to the early 1990s. Constructivism had become a buzzword, and the basis of wide-ranging and arguably (§5.5) highly influential research. However, it was

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Conceptualisations of the Research Programme

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already beginning to be seen in some quarters as being past its prime as a useful perspective for informing research in Science Education (Solomon, 1994). Joan Solomon described the extent to which the constructivist research put emphasis on learners’ ideas that did not match the scientific models, Now what had been commonplace and unremarkable became significant, and what was too well known to be thought worthy of comment, was suddenly the substance of illuminating research. (Solomon, 1994: 6)

Solomon (1994: 17) suggested that ‘if constructivism obscures other perspectives, either by its popularity or its blandness, that could be damaging’. If the constructivist research is understood as primarily an attempt to catalog and describe the ‘commonplace’, instances of learners holding alternative ideas about science topics, then it should indeed now be considered ‘unremarkable’, and unworthy of obscuring other approaches to understanding learning in science. It is argued in this book both that the constructivist programme is not only so much more than that, but also something that is informed by and informs rather than obscures a range of other approaches. This argument has two aspects. Firstly, that whilst accepting that the criticisms of Solomon and others (see Chapter 5) are not entirely ungrounded, a considerable body of research undertaken over the last 30 years in Science Education can be conceptualised as a coherent RP that goes well beyond collecting accounts of students’ ideas. Secondly, that by acknowledging this, and drawing upon the heuristic power of a RP, we can help shape future directions for this area of work (see Chapter 7) so that it can continue to work towards the initial aim of understanding learning better to inform teaching. Within this way of thinking about ‘constructivism’ in Science Education, the ‘alternative conceptions movement’ should be seen as just one phase of a much more ambitious project: one that can truly contribute to progressing Science Education.

4.3

Conceptualisations of the Research Programme

There have been a number of previous discussions of this field in terms of Lakatos’s ideas. Driver and Erickson (1983) referred to this area of work as a research programme, although they did not explicitly draw on Lakatos’s model. Gilbert and Swift (1985) did explicitly refer to the Lakatosian methodology of SRP as early as 1985, although at that early stage the analysis was understandably limited. Later Niaz (1993) explored this approach in more detail. These earlier conceptualisations will be discussed before considering the model presented here. In addition, Watts & Pope (1982) discussed the related question of whether Lakatos’s model was a useful way of thinking about students as scientists. Although Watts and Pope were using Lakatos’s methodology of SRP as the basis of their analysis, their paper was not considering the field but how students may be modelled as scientists during conceptual learning in science. That is an issue that can be considered to be part of the RP (§6.2.2), rather than being about the RP, so it is not considered further in the present context.

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Driver and Erickson Set Out Premises for a RP

In their 1983 paper, Driver and Erickson set out ‘the argument used by researchers, either implicitly or explicitly, to justify their research programme’ (Driver & Erickson, 1983: 39). Their specification consisted of three ‘empirical premises’ and a ‘value premise’: Empirical Premise One. Many students have constructed from previous physical and linguistic experience frameworks which can be used to interpret some of the natural phenomena which they study formally in school science classes. Empirical Premise Two. These student frameworks often result in conceptual confusion as they lead to different predictions and explanations from those sanctioned by school science. Empirical Premise Three. Well-planned instruction employing teaching strategies which take account of student frameworks will result in the development of frameworks that conform more closely to school science. Value Premise One. One should conduct research which will lead to a better understanding of school science by students. (Driver & Erickson, 1983: 39–40)

Driver and Erickson (1983: 40) concluded from the conjunction of these premises that the community ‘ought to engage in research endeavours which will uncover student frameworks, investigate the ways they interact with instructional experiences and utilise this knowledge in the development of teaching programmes’.

4.3.2

Gilbert and Swift Suggest a Lakatosian Analysis

As early as 1985 it was possible for Gilbert and Swift (1985) to set out ‘towards’ a provisional Lakatosian analysis of what they labelled the ACM (alternative conceptions movement), identifying as the hard core: • The world is real. • All observations are theory-laden. • Individuals use personally appealing explanatory hypotheses to cope with events in their environment. • The individual tests these hypotheses through interaction with reality against personally appealing criteria. • Reality provides guidance as to the adequacy of these hypotheses so tested. • When hypotheses are judged inadequate by such testing, either the hypotheses or the test criteria by which they were judged are modified or replaced. Given that one common criticism of the constructivist programme is its association with relativist perspectives (see §5.2.5), it is interesting to note that this version of the RP starts from an explicit realist position: i.e. ‘[t]he world is real … [t]he individual tests these hypotheses through interaction with reality … reality provides guidance as to the adequacy of these hypotheses.’ Gilbert & Swift’s model considers the student to be acting as a rational scientist (in the sense of Driver’s (1983) ‘pupil as scientist’, §4.1.3). So although observations

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are theory-laden (point 2, cf. the discussion of Kuhn’s ideas in Chapter 2), the individual develops ‘explanatory hypotheses’ (point 3), a creative act to make sense of the world, and then tests these ideas (point 4), being prepared to reject or modify those found inadequate (point 6). The characterisation of the ACM as a RP was accepted by Robin Millar in 1989, despite his being critical of some aspects of the claims made within the programme, Over the past decade or so, an approach to research in science education has grown rapidly in prominence. Its characteristic is that it involves probing learners’ understanding of specific topics in science or of specific science concepts. Despite being geographically dispersed, this work clearly forms a distinctive research programme. (Millar, 1989a: 587)

4.3.3

A Descriptive and Pre-Theoretical Movement?

Gilbert and Swift’s (1985) paper discussed the ACM and the Piagetian tradition of research in Science Education (see §1.10.2) as alternative RP into learning in science. However, Niaz (1993) took issue with this, arguing that for the ACM to be considered a rival RP it would need to explain the successes of the Piagetian programme, and go beyond it, Contrary to what has been suggested in the literature, it is argued that the concept-learning perspective (Alternative Conceptions Movement, ACM) and the developmental perspective (Piagetian School, PS) cannot be considered as rival research programs, as the ACM at its present stage of development cannot explain the previous success of its rival (PS) nor supersede it by a further display of heuristic power. (Niaz, 1993: 187)

Niaz suggested that there was indeed a potential rival RP to the Piagetian programme, one that explored patterns in student problem-solving based on the Theory of Constructive Operators, due to Pascual-Leone. However Niaz (1993: 186) characterised the research undertaken within the ACM as (at the point in time he was writing) ‘essentially descriptive and pretheoretical’. Niaz (1993: 186) claimed that ‘work done by the ACM has led to a valuable catalogue of students’ misconceptions in science and their resistance to change, which is essentially descriptive and pretheoretical … what is still an open question is the fact that the ACM does not have a theoretical framework which could explain its findings’. There are two aspects to Niaz’s criticisms, which should be considered separately. The argument about seeing PS and ACM as rival programmes has some merit, but that is not how the constructivist programme is seen here. Rather the constructivist RP is here considered to have largely focused on aspects of learning that may be seen as complementary to those that have concerned the Piagetian programme (i.e. primarily conceptual rather than in terms of cognitive operations). However, Niaz’s description of the ACM as largely descriptive and pre-theoretical seems harsh. As Niaz (1993: 186) himself points out, the Piagetian programme began with a good deal of ‘descriptive’ data, so the nature of the empirical evidence does not itself exclude ACM from being the basis of a programme. Moreover, it is certainly not accurate to describe the ACM as pre-theoretical in 1993. Indeed, the

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hard core of the programme had been established for at least a decade at this point, and had included a good deal of theorising. The extent to which research across the RP offered a coherent view of the relationship between theory and evidence may well have been sub-optimal, but basic theory for developing cumulative research (i.e. that allowing a dialogue between evidence and theory) was certainly in place.

4.3.4

A Recent Suggestion for the Hard Core of the RP

In a more recent study, Mintzes and Chiu (2004: 111–112) have defined the Lakatosan hard core of constructivism in terms of three premises related to knowledgeconstruction, the aim of Science Education, and the role of the teacher. They set out ‘in its simplest form, the major assertions of constructivism, now taken as Lakatosian hardcore assumptions’ as: (1) That human beings are meaning-makers (2) That the principal goal of science, mathematics and education therein is the construction of shared meanings (3) That shared meanings may be facilitated by the active intervention of wellprepared teachers Whilst these various attempts to understand constructivism in Science Education as a RP all have some merits, it is useful here to revisit the key early papers that have become established as seminal to the field to identify the key programmatic elements that were, in Lakatos’s (1970: 132) term, ‘adumbrated at the start’.

4.4

Characterising the Research Programme

Although the Lakatosian terminology for describing RP was not explicit in the early seminal corpus of literature, a clear programmatic element can be seen in these papers (e.g. Driver and Erickson’s empirical premises from their 1983 review paper). With the benefit of hindsight, it is possible to characterise the programme based upon those key principles set out in the seminal corpus of literature.

4.4.1

A Model of the Hard Core

I have previously argued that the constructivist RP in Science Education was built upon seven basic axioms, which can be considered to provide the hard core of the programme (Taber, 2006a, b). Whilst I have no doubt that slightly different permutations of this hard core could be proposed without fundamentally changing the nature of the RP (see, e.g. Sjøberg, forthcoming) these premises would seem to

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represent the basic commitments shared by those doing research in this field. This hard core is: Premise 1. Learning science is an active process of constructing personal knowledge. Premise 2. Learners come to science learning with existing ideas about many natural phenomena. Premise 3. The learner’s existing ideas have consequences for the learning of science. Premise 4. It is possible to teach science more effectively if account is taken of the learner’s existing ideas. Premise 5. Knowledge is represented in the brain as a conceptual structure. Premise 6. Learners’ conceptual structures exhibit both commonalities and idiosyncratic features. Premise 7. It is possible to meaningfully model learners’ conceptual structures. This can be considered to provide the rationale behind constructivist research in Science Education, and was clear in the seminal corpus. To many working in science education today these statements may seem self-evident, and little more than common sense (cf. Solomon, 1994) – but that was clearly not considered the case by referees of the original papers setting out this position, and is, I would argue, evidence of the wide influence of the constructivist programme within Science Education. Whilst this particular characterisation of the hard core is quite different to that offered by Gilbert and Swift back in 1985, each of the premises can be found in the seminal corpus of papers (see Table 4.1). Research based on these premises would be undertaken from a commitment to these ideas, and (from a Lakatosian perspective) that commitment would direct researchers away from any attempts to falsify these basic premises. Thus, I would argue, the negative heuristic of the constructivist RP was well established by 1983.

4.4.2

A Positive Heuristic for the RP

These seven tenets of the RP each lead to key research questions that may collectively be considered to set up the positive heuristic of the RP. This is illustrated in Table 4.2, which offers the general questions suggested by the hard core.

4.4.3

Building the Protective Belt of the RP

Research directed to answering these questions has led to the adoption, invention and development of a wide range of theoretical constructs that are the ‘refutable variants’ of the RP (these are explored further in Chapter 6). Some of these ideas

Table 4.1 The hard core of the RP can be identified in the seminal studies that initiated the programme Driver & Easley, 1978: 62, 70 Premise 1. Learning science is an active process of constructing personal knowledge Gilbert et al., 1982: 624 Driver & Erickson, 1983: 39 Gilbert & Watts, 1983: 83 Osborne & Wittrock, 1983: 492 Premise 2. Learners come to science learning with Driver & Easley, 1978: 67 existing ideas about many natural phenomena Gilbert et al., 1982: 623 Driver & Erickson, 1983: 38 Gilbert & Watts, 1983: 72 Osborne & Wittrock, 1983: 489 Premise 3. The learner’s existing ideas have Driver & Easley, 1978: 78 consequences for the learning of science Gilbert et al., 1982: 624, 628 Driver & Erickson, 1983: 39, 48 Gilbert & Watts, 1983: 71 Osborne & Wittrock, 1983: 490, 491 Premise 4. It is possible to teach science more Driver & Easley, 1978: 78 effectively if account is taken of the learner’s Gilbert et al., 1982: 625 existing ideas Driver & Erickson, 1983: 39, 50 Gilbert & Watts, 1983: 83 Osborne & Wittrock, 1983: 492 Premise 5. Knowledge is represented in the brain as a Gilbert et al., 1982: 623 conceptual structure Driver & Erickson, 1983: 39 Gilbert & Watts, 1983: 84 Osborne & Wittrock, 1983: 490 Premise 6. Learners’ conceptual structures exhibit both Driver & Easley, 1978: 74 commonalities and idiosyncratic features Driver & Erickson, 1983: 42 Gilbert & Watts, 1983: 69 Premise 7. It is possible to meaningfully model learners’ Driver & Erickson, 1983: 40, 43 conceptual structures Gilbert & Watts, 1983: 69 Osborne & Wittrock, 1983: 503 Table 4.2 A characterisation of the positive heuristic of the RP (Based on Taber, 2006a) Tenet Broad research questions 1. Learning science is an active process of constructing personal knowledge 2. Learners come to science learning with existing ideas about many natural phenomena 3. The learner’s existing ideas have consequences for the learning of science 4. It is possible to teach science more effectively if account is taken of the learner’s existing ideas 5. Knowledge is represented in the brain as a conceptual structure 6. Learners’ conceptual structures exhibit both commonalities and idiosyncratic features 7. It is possible to meaningfully model learners’ conceptual structures

How does knowledge construction (i.e. learning) take place? What ideas do learners bring to science classes, and what is the nature of these ideas? How do learners’ ideas interact with teaching? How should [‘constructivist’] teachers teach science (in view of tenets 1–3)? How is knowledge represented in the brain? How much commonality is there between learners’ ideas in science? What are the most appropriate models and representations?

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Knowledge Construction

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were imported into the programme and adopted from other research traditions and cognate areas of study. Others originated within the RP itself. However, in a Lakatosian analysis, these refutable variants must all be (a) consistent with the hard core; (b) related to the positive heuristic, i.e. attempts to form theory addressing the key research questions in the RP; (c) considered falsifiable, in terms of their ability to explain and predict empirical ‘facts’. The rest of the chapter fills out the model of this area of research as a Lakatosian RP by discussing how the positive heuristic, built upon the hard core, has led to construction of a protective belt for the RP. This material is arranged thematically: • • • • • • •

Knowledge construction Learners’ scientific ideas Implications for learning Implications for teaching Learners’ knowledge structures Individual differences Researchers’ representations

These headings relate to the key tenets I have identified as the hard core of the programme, and the associated general research questions of the positive heuristic. The different nature and status of the axiomatic hard-core commitments will become clear through this treatment.

4.5

Knowledge Construction

The first hard-core axiom is that Learning science is an active process of constructing personal knowledge, which leads to the general research question: how does knowledge construction (i.e. learning) take place? Reddish (2004: 9) has argued that ‘what we are particularly interested in is fine-grained constructivism. We want to analyse knowledge into more fundamental components in order to understand how that construction takes place’.

4.5.1

Learning Science is an Active Process of Constructing Personal Knowledge

This is the central commitment of the constructivist RP. It is a strong emphasis in early writing from within the RP. The reference to ‘active’ construction of knowledge suggests that constructivists do not see knowledge as something that exists in the world in a form that people can ‘take in’, or make facsimile copies of, from their environment. In Chapter 1, a number of the key thinkers influencing the adopting of constructivist ideas in science education were introduced. Dewey saw knowledge as the outcome of interaction with the world (§1.5.1); Piaget saw the individual as able

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to bootstrap cognitive development through acting upon the world with existing structures, and the subsequent assimilation and accommodation of the resulting experience (§1.6.1); Kelly believed that individuals could learn to adjust their system of personal constructs (§1.6.3); and Vygotsky (§1.6.2) saw meaningful (cf. Ausubel, §1.9.2) conceptual learning as requiring active involvement of the learner, concepts do not simply represent a concatenation of associative connections assimilated by the memory of an automatic mental skill, but a complicated and real act of thinking which cannot be mastered by simple memorization. (Vygotsky, 1934/1994: 356)

So Driver and Bell (1986: 444), writing for teachers, refer to how ‘learning involves an active process in which each learner is engaged in constructing meanings whether from text, dialogue or physical experiences’. Novak, in arguing for what he calls a ‘human constructivism’ notes, Creating new knowledge is, on the part of the creator, a form of meaningful learning. It involves at times recognition of new regularities in events of objects; the invention of new concepts or extension of old concepts; recognition of new relationships (propositions) between concepts; and, in the most creative leaps, major restructuring of conceptual frameworks to see new higher order relationships. (Novak, 1993: 183)

4.6

The ‘Transfer’ Model of Learning

To appreciate the significance of claims that knowledge construction is an active process, it is important to consider what an alternative assumption might be. The constructivist position is often contrasted with the ‘transfer’ model. In this model, it is assumed that teacher has information stored in her or his mind, and by the process of teaching that knowledge can be transferred to the mind of the learner. Driver and Bell (1986: 444) refer to ‘one commonsense view of learning as absorbing knowledge, being reflected in everyday phrases such as “I could not take it in” ’. Bodner refers to this view as an ‘accepted model’, Until recently, the accepted model for instruction was based on the hidden assumption that knowledge can he transferred intact from the mind of the teacher to the mind of the learner. Educators therefore focused on getting knowledge into the heads of their students, and educational researchers tried to find better ways of doing this. (Bodner, 1986: 873)

4.6.1

The Status of the Transfer Model

Although it is very easy to find texts that discuss and advocate constructivist teaching approaches, and despite studies often referring to the alternative ‘transfer’ model, there is something of a dearth of material describing the transfer approach and recommending it to teachers (Scerri, 2004). Where constructivist models of teaching are (well, may be) based on a theory of learning, the transfer model does not derive from any established body of formal

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The ‘Transfer’ Model of Learning

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theory, so ‘construction’ versus ‘transfer’ of knowledge may seem a rather uneven contest. Indeed, given the lack of authority usually offered for a transfer model, it may seem to be something of an intellectual ‘scarecrow figure’, i.e. an idea that no one actually advocates, but which is a convenient fiction as it may be readily deposed in argument. However, the lack of formal support for the transfer model is less a sign of it being a fiction and more a reflection of the nature of the model – which is of particular interest given the subject matter of this book. Hammer (1996: 99) helpfully refers to the transfer model as ‘the naive, generally tacit view that students are “blank slates”, according to which instruction constitutes a transfer of information from the teacher (or textbook, or demonstration, etc.) to the students’. Whilst the transfer model may not be based on a formal theory, and has probably never been explicitly ‘taught’ in teacher education courses, there is, nevertheless, considerable evidence that teachers have commonly based their teaching around such a model (Fox, 1983). Duit (2002) discusses preliminary findings from a study exploring the teaching of a sample of 14 German physics teachers, incorporating video recording and in-depth interviews. He reports that most of the teachers ‘do not hold explicit theories about the teaching and learning process’ and that ‘their view of learning seems to be transmissive rather than constructivist’ (p. 12). Hennessy (1993: 8) reported how a 1990 study she reviewed, that investigated ‘student teachers’ conceptions concerning the nature of science, teaching and learning produced depressing results; almost half of those questioned believed in a transmission model, namely the passive accumulation of a body of knowledge which has independent reality’. In other words, the transfer model of teaching would seem to be something of a common ‘alternative conception’ or ‘intuitive theory’ about learning. This is perhaps not surprising when we examine the model, as its basis is simply the idea that human beings can learn information by the process of being told things by other human beings. This would seem to be part of a ‘theory of mind’ that would be considered part of ‘folk psychology’ (see §6.1.4.7). In other words, a transfer model of teaching is based on ‘common sense’ knowledge that we can learn things by being told them. Teaching becomes a formalisation of this process, by having classes (economy of scale), teachers (those with the knowledge) and a curriculum (an authority’s view of what knowledge should be transferred). When seen this way, the transfer model of teaching is perhaps best not considered ‘wrong’ (as people do sometimes learn things by being told), but rather as a way of making sense of an important and common phenomena. Russell and Osborne report that some of the primary teachers involved in the SPACE (Science Processes and Concept Exploration, §4.2.1) project were uncomfortable when asked to teach without seeking to directly transmit knowledge. According to Russell and Osborne (1993: 5) the prescription that ‘teachers should make every effort to listen to children and to accept their ideas as interim theories or explanations’ challenged assumptions that science teaching involved ‘the direct transmission of those facts using a didactic pedagogy’. Russell and Osborne reported that Even those teachers who were able to empathise with children’s views found it difficult to hold back from correcting them or ‘handing over’ the conventional scientific explanations

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of the phenomena under consideration. Some teachers felt initially that to fail to teach directly was tantamount to professional neglect. (Russell & Osborne, 1993: 5)

Taking these considerations together, it would seem that we can consider the transfer model of learning as an element of folk psychology that makes up a common alternative conception of the learning process.

4.6.2

Objections to a Transfer Model of Coming to Knowledge

An obvious problem with the transfer model is that it does not offer testable mechanisms to explain failures of transfer of knowledge, i.e. when people fail to learn what they have been ‘taught’. In the transfer model such failures may be ‘explained’ (in keeping with the metaphor) by the intended transfer missing its target – ‘going over their heads’ – or passing through – ‘in one ear and out the other’. A second objection that constructivists would offer is that it is just plain wrong to consider that knowledge is actually transferred: the knowledge the learner has gained cannot be a straight copy of the teacher’s knowledge. Even when the knowledge concerned is a simple fact such as ‘Paris is the capital of France’, the teacher and student will have very different associations for the terms Paris and France. In crude terms, a student who learnt that ‘Paris was the capital of France’, but thought France was a district of Texas, would not have the same knowledge as the teacher. More subtly, the phrase would have different meanings for a pupil who had lived in Paris for some years and therefore had a vast store of personal associations with Paris than for a pupil who simply knew Paris was a city; something like the few she had personal experience of (may be Birmingham, Portsmouth and Durham; or Perth, Darwin and Melbourne). This view of the nature of ‘personal’ knowledge is inconsistent with the transfer model as a description of learning.

4.6.3

Personal Knowledge and Personal Construction

The reference to ‘personal’ knowledge here is significant. The constructivist tradition in Science Education largely developed from the work of ‘personal constructivists’ such as Piaget and Kelly (see Chapter 1) who focused on how individuals came to make sense of their worlds. Piaget’s programme considered how individuals came to knowledge of the world, something that was described in terms of a learner experiencing the world by acting upon it guided by existing mental structures, and so assimilating new experiences, and accommodating existing mental structures to them. Evolution has led to humans having a brain that can ‘boot-strap’ itself through such interactions, and ‘ratchet’ itself up through successively abstract operational competences. On Piaget’s model, a baby abandoned on a desert island and somehow able to survive

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should in principle be mentally equipped to pass through the same stages of cognitive development as anyone else, having the developing apparatus ready to unfold through cycles of feedback from interaction in the environment. However, a theory of learning that informs teaching should not be restricted to considering how cognitive abilities develop, and allow the individual to model and operate with information from their environment (as was Piaget’s central concern), but also needs to be concerned with how people in a society are inducted into the public knowledge that is part of the cumulative cultural heritage. Researchers influenced by socioconstructivist thinking, and in particular the work of Vygotsky and his colleagues (see §1.6.2), have argued that Piaget’s personal constructivism underplays the social element of learning. This is a very important and nuanced debate, and will be explored later in the book (see §5.4). The reference to personal knowledge here should not be seen as necessarily excluding social constructivist considerations for how we come to knowledge, but is meant to distinguish between the knowledge of an individual, and scientific knowledge, which ‘must be public and consensible’ (Ziman, 1968: 11). This is linked to the idea of Popper’s ‘3 Worlds’ model (§2.2.2). Popper (1979a) distinguished between the world of objects (World 1), the world of personal subjective experience (World 2), and the world of objective knowledge (World 3) – i.e. formal theories, propositions, etc. These worlds refer to ontologically very different entities, so to confuse them is to make a serious error of mis-categorisation. As pointed out in Chapter 2, World 3 consists of Platonic forms or Kantian ideals – theories in themselves, principles in themselves, propositions in themselves, etc., which only have an ideal existence. The contents of World 3 may be represented in World 1 (e.g. in books, on websites, in lectures etc.). The contents of World 3 may also seem to be the subject of thought: i.e. represented and operated upon in World 2: we may think of a circle, recall Avogadro’s number, apply Ohm’s law, decide if an organism should be considered a fungus, etc. However, as the actual World 3 entities only exist in the abstract, there is a sense in which they cannot be directly incorporated in our thought processes. No one can show me a circle, only an object that is said to be circular or some sort of model of a circle (e.g. some marks drawn on paper). I therefore only have experience of representations of World 3 entities. So from this perspective, we should distinguish between ideas as abstract principles (Popper’s World 3), and ideas as experienced (Popper’s Word 2). But ideas as experienced are based on the way an individual knower perceives the world, and their interpretation of experiences, including their experiences of the things they are told and shown by others. But such speech acts and demonstrations are not ideas that can be perceived, but representations of ideas in speech, or through gesture, or by demonstrating a model or instance that is considered to reflect the idea. So we can show a child a plant, and tell her that it is a plant; we can drop zinc in magnesium and say the outcome is a reaction; we can demonstrate how it is harder to close a door by pushing near the hinges and explain this is due to the moment of the force being less when it is applied near the pivot – but the ideas ‘plant’, ‘reaction’ and ‘moment’ (the ideas we label with the words ‘plant’, ‘reaction’ and ‘moment’) exist in World 3, and our actions happen in World 1.

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Whilst Popper’s ‘3 Worlds’ notion is useful here, it is not necessary to give credence to Popper’s World 3 to accept this argument. Even if we do not see any need for such ideal notions of plant, reaction or moment, it is still the case that the teachers’ ideas that are labelled with these terms are part of one individual’s subjective experience, and have to be represented in language and other actions before they become publicly available to others. The learner, then, has sensory experiences that allow her to perceive the teacher’s representation. The constructivist view is that the learner will then ‘actively’ (but not necessarily consciously or deliberately) attempt to make sense of these perceptions, and so will subjectively construct meanings for ‘plant’, ‘reaction’, ‘moment’, etc. The learner will therefore construct personal versions of the knowledge they find represented in their contacts with others (whether in class or in other social and informal learning contexts). In this sense the RP in Science Education is concerned with learning as the development of personal knowledge (whether or not considered to be mediated through social processes) – the knowledge that people can be said to ‘hold’, rather than knowledge as abstract ideas or the public knowledge of science. Of course, both the ideas in themselves, and the notion of public scientific knowledge (and its development), and the relationships between these different types of knowledge, are relevant to the RP. The key point here is the need to carefully distinguish between them.

4.7

How Does Knowledge Construction (i.e. Learning) Take Place?

It was suggested above that whereas a transfer model of teaching is best seen as part of an informal folk psychology, that is atheoretical – simply describing the common observation that teaching sometimes but not always leads to the intended learning – the alternative constructivist perspective, that learning is an active process of knowledge construction, has the potential to be more than this. The ‘constructivist’ RP can be considered theoretically progressive to the extent that it engages with the question of how knowledge construction can take place. (As Chapter 3 suggests, a theory can be considered scientific to the extent that it is, for example, able to offer testable predictions.) So, for example, from consideration of their ‘generative learning’ model, which attempted to combine a constructivist approach with an information processing perspective, Osborne and Wittrock (1985: 79), set out a series of research questions. One of these was: ‘which aspects of memory store do links tend to be generated to, and how much and in what way, are these influenced by the nature of the sensory input and the existing ideas in memory store?’ A useful starting point for thinking about how knowledge construction takes place was available in Piaget’s approach (§1.6.1), here summarised by Glasersfeld, The learning theory that emerges from Piaget’s work can be summarized by saying that cognitive change and learning take place when a scheme, instead of producing the expected result, leads to perturbation, and perturbation, in turn, leads to accommodation

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that establishes a new equilibrium. … His theory of cognition involves a two-fold instrumentalism. On the sensory-motor level, action schemes are instrumental in helping organisms to achieve goals in their interaction with their experiential world. On the level of reflective abstraction, however, operative schemes are instrumental in helping organisms achieve a coherent conceptual network that reflects the paths of acting as well as thinking which, at the organisms’ present point of experience, have turned out to be viable. (Glasersfeld, 1989: 6)

There are two key ideas here that recur throughout much of the work exploring learning undertaken in Science Education. Firstly, there is the principle that an existing internal scheme of some form is available for making sense of the individual’s experience in (or action upon) their environment. Secondly, that learning involves the development of such schemes, and in particular changes made in response to apparent inconsistencies between what the scheme leads the individual to expect, and what they actually experience. There is a clear basis here for comparing human learning to scientific research, with theories used as the basis for predicting outcomes, and being open to revision when predictions are not met. This is reflected in Kelly’s notion of ‘man the scientist’ (§1.6.3), and Driver’s ‘pupil as scientist’ (§4.1.3). This perspective, of course, opens up the question of how to know when it is sensible to change our minds, and so introduces a consideration of all the issues that were raised when considering how science proceeds (see Chapter 2). It should be noted that a key difference is that science is a public consensual activity, where proposed changes have to be explicitly justified to the community, whereas the processes that lead to an individual to change their model of the world need not be explicit (and may often be dependent on subconscious processes). It was in this context that Watts & Pope (1982) discussed the question of whether Lakatos’s model (see Chapter 3) was a useful way of thinking about how and when students would change their minds.

4.8

Learners’ Scientific Ideas

The second hard-core axiom is that learners come to science learning with existing ideas about many natural phenomena, which leads to the general research questions what ideas do learners bring to science classes, and what is the nature of these ideas?

4.8.1

Learners Come to Science Learning with Existing Ideas About Many Natural Phenomena

The work of Piaget (§1.6.1) had revealed that even quite young children developed a wide range of ideas about the natural world that were untutored. This suggests that teachers should not assume pupils know nothing about a topic just because it has not

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featured in their formal curriculum. Indeed, from a constructivist perspective, new learning always depends upon some existing mental ‘scheme’ for making sense of a new experience (such as a teacher’s exposition of new course material). That this could lead to an infinite regress, suggests that people are born with some kind of innate structures (§1.5) for directing their initial attempts to make sense of the world. Exactly what level of structure is specified in this way remains an issue for research. Tabula Rasa The idea that humans arrive in the world with minds that are like a ‘clean slate’, or tabula rasa, is found in the work of Aristotle, and was taken up by Locke who as an empiricist saw the mind as starting out like a black sheet of paper, and to which access was via the senses (Woolhouse, 1995). This is one reasonable ‘common-sense’ view, that the human mind begins ‘empty’ and that its contents must depend on experiences. However, some animal instincts can be understood as genetically coded ‘knowledge’, and in humans it seems clear that if we are not born with access to formalised knowledge (as Socrates believed, see §1.5), then our cognitive apparatus is such as to be biased towards learning certain types of concepts. The debate here would seem to be the extent to which our knowledge is biased by such genetic factors. Such a debate is admissible under the positive heuristic of the RP, and this theme will recur in Chapter 6 when research into the nature and origins of learners’ ideas are considered. However, even assuming that the child is a tabular rasa at birth would in no way imply that an 11 year old (say) meeting the concept of quanticles (i.e. particles at the submicroscopic level such as molecules, atoms, ions) for the first time as part of school lessons would have no previous knowledge relatable to the topic. Indeed (according to the hard core of the RP), meaningful learning is only possible providing the learners can find such relationships between what they are told, and what they already ‘know’ (Ausubel, 2000). Children learn from their experiences of the natural world, and develop their own mental models based on their interpretations of the patterns they perceive. These personal models may or may not match the scientific concepts they meet represented in school science. Children also learn from friends, family, and the media. Whether such secondary sources are reliable, or whether such incidental learning is structured such that the child’s understanding has fidelity with what they read and are told, is of course another issue (see Chapter 6).

4.8.2

What Ideas Do Learners Bring to Science Classes?

Even critics of the ‘constructivist’ programme in Science Education tend to agree that it has been very successful in developing an extensive knowledge base on the range of ideas that learners bring to science classes (Solomon, 1994; Johnstone, 2000a). Indeed reported studies, from a range of national contexts, cover most school science topics, at various age ranges (Duit, 2007). Studies have been reported at different educational levels: primary, secondary, college, undergraduate and beyond (e.g. teachers in training). Only a subset of these studies can be seen to describe pre-tutored ideas. Most have been undertaken after some formal teaching,

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and therefore reflect ideas available after exposure to some formal curricular models representing scientific knowledge. Despite this, it has commonly been found that students hold ideas about science topics at odds with the target knowledge they are asked to learn in school. This is not to suggest that students never present ideas matching school science: however, student thinking is not on a continuum from no relevant knowledge to successful learning of taught material, but is commonly found to be more complex, i.e. reflecting ideas different to, often inconsistent with, and sometimes actually directly contradicting the target knowledge in the school curriculum.

4.8.3

What Is the Nature of These Ideas?

These ideas have been characterised in various ways, and a range of labels has been used. The labels used here are important in two ways. For one thing, labels carry connotations: whether children’s ideas are described as notions, conceptions, frameworks, theories, models, etc. carries a message about status and significance. It is also unfortunate that although suggestions were made in the seminal corpus of works on how to describe student ideas, the research community has not been able to adopt an agreed meaning for terms and so different authors have tended to use the same terms for different things or different terms for what seems to be the same thing. A number of terms were used in the seminal corpus of literature. The 1982 paper by Gilbert, Osborne and Fensham prominently used the term ‘children’s science’ to describe the ‘conceptual structures’ which children used to understand the world prior to formal instruction. The terms ‘alternative conceptions’ and ‘alternative frameworks’ were also widely used (see §5.3). The ideas that were elicited from students were said to have particular characteristics. In 1983, Driver reported that research indicated that alternative frameworks did not seem to be extinguished by teaching (p. 76). Other commentators disputed these claims, and this became a key issue in the RP (see §6.1.4).

4.9

Implications for Learning

The third hard-core axiom is that the learners’ existing ideas have consequences for the learning of science, which leads to the general research question how do learners’ ideas interact with teaching? The key principle here is summarised in Ausubel’s (1968: vi) adage reported in Chapter 1 (§1.9.2), that ‘the most important single factor influencing learning is what the learner already knows’. From a constructivist perspective, learning depends upon the existing mental structures: in Piagetian terms the schema used to assimilate, and which become accommodated to, new ‘input’. Glasersfeld (1989: 11) argued that ‘it is essential that the teacher have an adequate model of the conceptual

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network within which the student assimilates what he or she is being told’ as otherwise ‘teaching is likely to remain a hit-or-miss affair’.

4.9.1

The Learners’ Existing Ideas Have Consequences for the Learning of Science

If learning is considered to be an active process of building up knowledge (axiom 1), and students arrive in science classes with ideas that (they feel) are relevant to the class topic (axiom 2), then it is a reasonable conjecture that any learning that takes place as a result of teaching will in part be determined by the learners’ prior knowledge. In 1982, Nussbaum and Novick reviewed the ‘numerous reports’ on alternative frameworks and concluded that almost all suggested that such frameworks interfered with intended learning (p. 184). Osborne and Wittrock (1985: 64) ground their model of ‘generative’ learning in constructivism, claiming that ‘generative learning … is central to the constructivist tradition. … The fundamental premise of generative learning is that people tend to generate perceptions and meanings that are consistent with their prior learning’. Glasersfeld makes a similar point more forcefully, in effect suggesting that like some standing orders requiring large majorities to support major changes of policy, there is a bias towards maintaining the status quo, This pattern of maintaining categorizations, concepts, and, indeed, whole theories until some experience makes their adequacy questionable, is a universal pattern from the constructivist point of view. The difference is that, where theories and concepts that have proved useful in the past are concerned, there is a considerable vested interest in maintaining the status quo. That is to say, the proponents of a theory will assimilate new experiences as long as they possibly can, even in the face of considerable perturbations. (Glasersfeld, 1988: 3)

Driver explained that where learners were presented with material at odds with their existing cognitive structures they had to both understand the new ideas, and be prepared to move outside of their existing modes of thinking – ‘to make the intellectual leap of possibly abandoning an alternative framework which until that time had worked well for them’ (Driver, 1983: 9). Prerequisite Knowledge Indeed, the principle that new learning is influenced by previous learning is at the basis of the principle of identifying ‘prerequisite’ knowledge that needs to be in place before setting out to teach a complex or advanced concept. This principle is found in the work of Ausubel, Gagné and Bruner. Ausubel (§1.9.2) saw meaningful learning as depending upon the learner making a connection with existing cognitive structure; Gagné (§1.9.1) offered guidance on how to plan teaching to build up concepts hierarchically; and Bruner (§1.9.3) proposed that curriculum should have a ‘spiral’ design so that concepts could be met at increasingly sophisticated levels during schooling.

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The Significance of Alternative Conceptions If the appropriate ‘building blocks’ need to be in place as the foundations for effectively building new knowledge, then inappropriate building blocks will not be suitable (or rather, will lead to the construction of somewhat different structures to those intended). Again the constructivist perspective does not see the alternatives to be no relevant prior learning, so no new learning vs. pre-requisite learning in place – intended learning possible, but also admits the possibility that building on different foundations is possible, and will lead to a different construction from that the teacher had intended.

4.9.2

How Do Learners’ Ideas Interact with Teaching?

Given the assumption that learners’ ideas have consequences for the learning process, an obvious question is the nature of the interaction between prior knowledge and teaching. Gilbert, Osborne and Fensham (1982) considered the possible outcomes of the interaction of children’s science with curriculum science (see §4.1.2). There is a spectrum of possibilities. At one extreme the learners’ ideas may be readily displaced by exposure to teaching. At the opposite pole the student frameworks might be so stable that they were completely unaffected by teaching. Either of these possibilities would reduce the whole issue to a purely academic one rather than a matter of serious practical concern for science teachers, and in practice there were other possible outcomes. Neither total stability nor complete lability of ideas as a general pattern would be adaptive from a biological perspective (with learning being impossible in the former case and effectively meaningless in the latter). Gilbert et al. (1982: 630) discussed these different outcomes possible in teaching situations: sometimes there was a ‘unified scientific outcome’, where the learned meanings closely matched the intended. This outcome matches what would be expected in a naive ‘transmission’ notion of teaching, where the ‘transfer’ of knowledge is considered simply a matter of effective communication. In other cases though there would be a two perspectives outcome, where newly learnt material is acquired ‘alongside’, as it were, previous ideas, so that ‘the learned amalgam of children’s science and teacher’s science can co-exist’. This could allow students to be successful in school tests whilst retaining their ‘children’s science’ for informal use (p. 624). In this situation curriculum science would be effectively rejected for use as a personal model of the world (Pope & Gilbert, 1983: 199). This outcome has significance when considering whether the learning of formal science needs to result in the replacement of other ways of understanding nature and the environment that may have value in the family or wider culture. For example, TEK (traditional ecological knowledge) may appear contradictory to scientific models and theories, but can have considerable value both to the ‘traditional’ societies themselves, but also potentially to the global community (§1.3.1). Sometimes ‘children’s science’ would be largely undisturbed by ‘teaching’ (Pope & Gilbert, 1983: 201). This is of course at the crux of teachers’ frustration – how they

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could have ‘taught’ something without it having apparently been learnt. Gilbert et al. suggested that there could also be a less helpful (in terms of learning school science) outcome than this. Sometimes there could even be a reinforced outcome where the material presented is (‘mis’) understood to support the learner’s existing ideas. So, for example, new terms are used to label existing ideas (Ault et al., 1984: 459). An example might be when students meet a model of the atom based on quantum theory, and adopt the new term ‘orbitals’, but as a new name for the electron ‘orbits’ in the familiar ‘planetary’ model of the atom (Taber, 2005b). Alternatively, there could be partial learning of ideas, as only so much new material could be learnt at one time (e.g. see §4.11), so that ideas would not be fully integrated in cognitive structure, and could be contradictory. The different possibilities that Gilbert and colleagues raised in this paper emphasise the complexity of teaching and learning as processes, and suggested questions that would be central to work in this field: • How and when are students’ ideas stable? (cf. ‘what is the nature of these ideas [that learners’ bring to science classes]’) • How can students hold several inconsistent ways of thinking about the same topics? (cf. ‘how is knowledge represented in the brain?’ – see below, §4.11.2) • How does teaching interact with existing knowledge? Osborne and Wittrock (1985: 79), drawing upon their ‘generative learning’ model, set out a number of research questions, including several relating to how learners’ existing ideas interacted with ‘input’ (i.e. from an information processing perspective, sensory experience whether from watching or listening to the teacher, reading the text book, taking part in practical work, etc.): • How much do the learner’s existing ideas influence what use is made of the senses in learning science informally and/or formally in specific contexts? • How much do the learner’s existing ideas influence what sensory input is attended to and what is ignored in various learning situations? • How do the constructed meanings compare and contrast with ideas existing in memory for a given sensory input? • On what basis do pupils decide whether a constructed meaning is to be accepted and, if it is accepted as valid, whether it will be assimilated, accommodated or stored somewhat independently of existing ideas? Questions such as these have motivated much empirical and theoretical work within the RP (as will be discussed in Chapter 6).

4.10

Implications for Teaching

The fourth hard-core axiom is that it is possible to teach science more effectively if account is taken of the learner’s existing ideas, which leads to the general research question how should teachers teach science? Section 4.9 reviewed Ausubel’s claim that ‘the most important single factor influencing learning is what the learner already

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knows’, and as reported in Chapter 1 (§1.9.2), he followed this with the prescription to teachers to ‘ascertain this and teach … accordingly’ (Ausubel, 1968: vi).

4.10.1

It is Possible to Teach Science More Effectively if Account Is Taken of the Learner’s Existing Ideas

A possible deduction from the previous axioms is that if students come to science classes with relevant prior learning which is different to the desired prerequisite knowledge (axiom 2), and this interacts with teaching to distort intended learning (axiom 3), then teachers need to redesign instruction to find the best way to arrive at the target knowledge from the students’ actual conceptual starting points. If instructional design was based upon a planned sequence of learning steps (Gagné & Briggs, 1974), and if those steps are compromised by learners’ alternative ideas, then in principle more effective designs informed by knowledge of learners’ ideas are possible. An assumption behind the RP was then that learning more about learners’ ideas and how they interact with teaching could inform more effective pedagogy. Thus, although the RP may be seen as an academic exercise, it was justified (at least in part) by its potential utility in improving practice. As will become clear in Chapter 5 (§5.5), this has been one area where the RP has faced some criticism, as not all commentators consider the programme to have been especially successful, or – in some cases – even to have a significant potential to improve science teaching.

4.10.2

How Should Teachers Teach Science?

A starting point that it is possible to teach science more effectively if account is taken of the learner’s existing ideas leads to the obvious question, of how the ‘constructivist’ teacher should teach. Driver (1983: 76) suggested that one part of the learning process should involve learners’ theories being made explicit so that they could be compared and challenged, and this was indeed a key part of the teaching schemes developed by her CLiSP research group, and also of the approach used in the primary SPACE project (see §4.2.1). This links to Bodner’s (1986: 876) suggestion, that ‘the only way to replace a misconcept is by constructing a new concept that more appropriately explains our experiences’. As a research project, CLiSP was intended to ‘devise, implement and evaluate teaching materials and strategies which attempt to promote conceptual change in selected topic areas’ (Driver & Oldham, 1986: 108). This would involve: 1. Devising learning materials which take account of students’ prior ideas 2. Developing ways of working in classrooms which encourage students both individually and collectively to become active in the learning process 3. Making explicit the implications of adopting a constructivist perspective for classroom practice

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Pope and Gilbert (1983) suggested that learners should be encouraged to reflect on their ideas, and thought that their role as constructors of theory should be explicit. Ault, Novak and Gowin (1984: 460) suggested that learners should learn to spot the ‘tangles’ and ‘twists’ in their own conceptual schemes. Osborne and Wittrock highlighted the potential role of metacognition in learning in the ‘generative learning’ model. One of the research questions they considered to be suggested by their model was ‘how much can an understanding of the key postulates of the generative learning model by teachers and pupils influence teaching and learning behaviours?’ (Osborne & Wittrock, 1985: 79, italics added). Bodner (1986: 876) suggests that a constructivist approach requires a reconceptualisation of the role of the teacher, ‘a subtle shift in perspective … from teaching by imposition to teaching by negotiation’. Bodner argues that the teacher needs to appreciate not only the learners’ specific ideas, but also the overall nature of their partial perspective on a topic. To motivate learning, the teacher has to offer the learner some basis for seeing a point to learning the material being taught. He observes that ‘the classical sequence of topics in introductory chemistry courses is perfectly logical to someone who has already constructed this knowledge’, but students who ‘never know where you are going to be in a few weeks [and] have a hard enough time remembering where you have been … need to know that a problem exists before they are willing to accept an explanation’ (p. 877). Driver and Oldham offered a series of questions that should be addressed in evaluating CLiSP’s (§4.2.1) approach in developing constructivist teaching sequences (Driver & Oldham, 1986: 120): • To what extent do the revised teaching approaches take account of students’ prior ideas? • Do they offer opportunities for students to construct their own meanings and if so how do students make use of those opportunities? • How do students respond to the revised strategies – are they comfortable with them or do they find them strange and threatening? • How do teachers feel about the revised approaches? How workable are they? What are the problems involved in implementing them? • What has been learned about the effectiveness of the strategies adopted and how might this be communicated to other teachers?

4.11

Learners’ Knowledge Structures

The fifth hard core-axiom is that knowledge is represented in the brain as a conceptual structure, which leads to the general research question how is knowledge represented in the brain? Glasersfeld has argued that teachers need to model students’ mental worlds: Because there is no way of transferring meaning, i.e., concepts and conceptual structures, from one head to another, teachers, who have the goal of changing something in students’

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heads, must have some notion of what goes on in those other heads. Hence it would seem necessary for a teacher to build up a model of the student’s conceptual world. (Glasersfeld, 1992)

4.11.1

Knowledge Is Represented in the Brain As a Conceptual Structure

In its most general form this assumption is something that most people take for granted without comment: ‘there is consensus about the fundamental basis of the paradigm; that is, an individual’s knowledge represents a mental construct’ (Coll & Taylor, 2001: 218). The claim has two parts. Firstly, that knowledge is in some sense ‘represented’ in human brains. That is that a human brain is able to in some sense encode information, such that it can influence future behaviour, and in particular be accessed in some form. The second claim, the reference to structure, suggests that this is not a process where information is represented as a series of independent discrete memories, but rather that memory is structured in (i.e. non-random) ways that are significant for learning and for recall and application of what has been learnt. Memory Metaphors The common metaphor of memory as a ‘storage’ device (a metaphor often linked to digital electronic applications) might imply memory is some kind of ‘space’ or ‘container’ where incoming information is stored away. Talk of knowledge retrieval might also suggest that material ‘stored’ in memory can be readily accessed by being brought out of memory. Human memory is much studied, but is currently only partially understood (Baddeley, 1990). Models of human memory are often based on information processing perspectives, which refer to basic cognitive modules (such as working memory) and processes (accessing information in long-term memory) that are not necessarily readily understood yet in terms of the underlying physiology. Metaphors can be insidious in the ways they influence thinking. What is widely assumed in the constructivist programme (and beyond of course) is that the human brain has plasticity of structure and associated cognitive apparatus such that brain structure can be modified in response to experience (including, e.g. what we are told in science lessons), in ways that can influence later behaviour (including, e.g. the answers we give to a researcher’s question or to an examination question). Thus the term: ‘memory traces’. Furthermore, it is generally accepted that some aspects of memory are under deliberate control – that is by deliberate efforts of attention and concentration we are able to influence what is ‘committed to’ and ‘retrieved from’ memory. Finally, it would seem to be generally accepted that – at least some times – what is ‘remembered’ can be experienced as similar to the original experience. In other words, sometimes the mental experience of ‘having’ a memory can be very vivid. (Of course, a skeptic might well ask how we can subjectively measure the fidelity of any memory except in terms of our memory of the original experience!)

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Conceptual Memory There are commonly considered to be different kinds of ‘memories’, so that some memory is said to be episodic, and we can remember perceptual impressions such as an unusual smell. However, the nature of scientific knowledge and academic education is such that research into learning science tends to be concerned largely with semantic memory: the ability to learn conceptual material that can be represented in such forms as propositions. Students in science classes are expected to remember a vast amount of material of this nature: carbon has a valency of four; plant cells have walls; momentum is a vector having the same direction as the velocity; alcohols have the –OH functional group; the human retina has two main types of light-detecting cells; the measured speed of light in free space is invariant regardless of the speed of the observer relative to a particular frame of reference, etc. Students are said to learn such material (or not) because they are able (or not) to respond to questions that require them to recall and apply these ideas (§1.2.1). The material is therefore believed to be in some form represented in the brain. Whilst it is not clear how ‘alcohols have the –OH functional group’ can be coded in the synapses of neural circuitry (the assumed physical substrate for long-term memory), it is clear that whatever physical changes occur in ‘laying down’ a memory trace, it allows the learner to later initiate thinking that enables them to make statements and apply principles in such ways that we consider they have remembered the ‘original’ information. Of course, this does not always happen, but my point here is that our (admittedly limited) understanding of brains makes it clear that memory is not about putting something away and getting it out later – it is about representing our ephemeral thoughts and perceptions now (presumably experiences based on electrical activity in some parts of the brain), in terms of structural changes in the brain in such a way that the new structures can be used to trigger something similar to the original perceptual experience. And we demonstrate this when we express these reconstituted thoughts in actions in the public arena for others to interpret. I am labouring this point, to emphasis how the substance of memory is something very different to the experienced memory. To again borrow Popper’s ‘3 Worlds’ model (see §2.2.2), when we are not accessing it, the memory does not exist. Rather, there is something in World 1 (a brain structure, presumably in terms of modifications of synaptic connection strengths within the brain – more dendrites, smaller synaptic gaps, etc.) which in some way represents the subjective (World 2) experience we had before, and which somehow allows us to trigger a very similar experience (i.e. ‘remember’) later. Our ideas are represented in long-term memory.

4.11.2

How Is Knowledge Represented in the Brain?

Given that students’ existing knowledge has consequences for their further learning (axiom 3), and that an individual’s knowledge is represented in memory in a

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structured way that reflects the individual’s understanding; then research in the RP to inform pedagogy by exploring learners’ ideas should not simply look to identify particular conceptions, but should also explore the way knowledge is actually structured when it is represented in memory. The Construct of Cognitive Structure So the representations in longer-term memory are structured, rather than being represented in some random or chronological sense. This statement does not necessarily refer to the spatial arrangement of the ‘engrams’ (traces). This level of organisation could be similar (note, without implying that other aspects of the analogy should be assumed) to the way disk space in used on magnetic hard drives, where the actual blocking of information representations on the disk may not reflect the way that information is itself organised. However, the information stored on even a highly fragmented computer disk is structured in terms of the catalogue system that enables the information to be accessed. It is at that level that conceptual memory must be structured. When a computer disk is reformatted, most of the coding is unchanged, but the information becomes inaccessible as the catalogue has been deleted – the information can no longer be readily accessed as the segments of files cannot be identified to be copied in the computer’s ‘memory’. Human memory must also have some system for representing information in such a way that it can be accessed when needed. Conceptual Structures Represented in Cognitive Structure So in terms of our understanding of any large capacity memory device, we would expect some form of index/catalogue system to be involved in human memory. However, there are good reasons to consider human memory to be structured in a much more significant way. Whilst the parallels between computers and minds are suggestive, it is also important to bear in mind the comparison has limitations. Computer files are stored as discrete entities that do not interact (except when a ‘worm’ is saved which when activated then starts rewriting over other programmes!) Human memories appear to be represented in a way that allows linkage. As Vygotsky (§1.6.2) commented, concepts do not lie in the child’s mind like peas in a bag, without any bonds between them. If that were the case, no intellectual operation requiring coordination of thoughts would be possible, nor would any general conception of the world. Not even separate concepts as such could exist; their very nature presupposes a system. (Vygotsky, 1934/1986: 197)

The evidence for this comes both from common experience of how one memory can trigger another one, and from formal studies that explore associations between concepts represented in memory in such terms as the frequency and delay in different associations that are elicited. This principle has actually been used in science education research when word-association tasks have been used as a means of exploring aspects of cognitive structure (Novak, 1985). So in ‘laying-down’ a trace representing some new conceptual learning, changes are made in the parts of cognitive structure representing other (what are perceived to be) related aspects of conceptual knowledge. This assumption, that concepts are represented in memory in ways that reflect their semantic meaning, is closely tied to the constructivist notion of new learning

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being built upon the ‘foundation’ of existing knowledge. In Piaget’s scheme, the individual ‘assimilates’ new information into himself or herself, but also ‘accommodates’ to that information. In terms of conceptual learning, new concepts are linked into the existing conceptual structure, which alters the meaning of existing concepts to some extent. Certainly this must be so when concepts are understood in relational terms – i.e. the meaning of a concept depends upon all its associations. Where the changes lead to some disruption in the existing structures (e.g. introduce inconsistency) there may later be further adjustments made to increase overall coherence (Thagard, 1992). In this understanding of memory, memory formation is not a discrete once-andfor-all event, but rather new memories are consolidated over extended time periods (e.g. months), and may be ‘strengthened’ by regular review. Do the Conceptual Structures Exist in the Brain? A common-sense (‘folk psychology’) view of memory might suggest that material is either stored in memory or not, perhaps being more or less readily accessed. Yet it seems unlikely that the way information is coded in memory allows us to be confident that a brain actually stores anything that can be unequivocally described as a conceptual structure. What is clear is that the brain represents ideas from thought in forms that allow (substantially the same) ideas to be revisited, and it does so in ways reflecting the semantic relationships that were originally understood. However, memory is not always hi-fidelity in terms of the original ideas that are being represented, so information may be partially remembered or misremembered (i.e. the representation in cognitive structure triggers somewhat different thinking when the trace is activated). This should not be seen as a purely negative aspect of human memory. Accessing memories can allow us to have insights that were not available in the original thinking that was represented. Memory is also very sensitive to context: so that how much and which details we can remember can be influenced by physiological and emotional states, cues in our environments, and what we have been thinking about recently. This clearly creates severe methodological problems for researchers who have to rely on the public accounts learners provide of their thinking in particular contexts, in response to a researcher’s probes. The researcher can build a model of the conceptual structure that seems to be represented in a learners’ cognitive structure, but this actually reflects the researcher’s interpretations of the account the learner was willing and able to give of the thinking that was triggered in a particular context. That thinking draws upon the representation in memory, but is sensitive to and so contingent upon many factors besides.

4.12

Individual Differences

The sixth hard-core axiom is that learners’ conceptual structures exhibit both commonalities and idiosyncratic features, which leads to the general research question: how much commonality is there between learners’ ideas in science?

4.12

Individual Differences

4.12.1

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Learners’ Conceptual Structures Exhibit Both Commonalities and Idiosyncratic Features

It is common experience that individual people have different ideas: but also that many (substantially equivalent) ideas are widely held. This is to be expected given that: • All human beings have similar enough genetic codes for us to be the same species, with the same basic anatomy (including the brain). • People share natural environments which are similar (e.g. experience of gravity is much the same anywhere on earth). • Most people are brought up within the social context of a particular society with established cultural traditions, and learn to converse about the world through one of a limited number of human languages. but • Most people have unique genetic coding (clones such as homozygotic twins excepted) that makes their genetic resources slightly different from anyone else. • Everyone has somewhat unique individual experiences of their world. • There is variation in the experiences available in different environmental (e.g. urban living versus rural) and social settings (‘sub-cultures’, language variants). So the development of ‘similar but different’ personal knowledge is to be expected, and is what is found.

4.12.2

How Much Commonality Is There Between Learners’ Ideas in Science?

Taking, together with the belief that knowledge of learners’ ideas can inform pedagogy (axiom 4), the view that there is some commonality, but also variety, in learners’ thinking becomes important for us for the RP. Where learners commonly have the same alternative ideas it is possible to approach pedagogy by informing teachers of these ideas; showing how and why they influence learning; suggesting appropriate classroom responses. At the other extreme, where individual learners have idiosyncratic ideas, research cannot help in this way. If such individual ideas are relatively rare compared with common alternative notions then it might make sense to concentrate most research effort on identifying these common ideas and planning teaching approaches that take them into account. However, if learners commonly have (different) uncommon alternative ideas, a different approach is needed to support teachers when pre-designed strategies are not available. Pedagogic support here would have to enable the teacher to develop diagnostic skills and design their own classroom strategies to respond to the ideas elicited with particular individuals and groups of learners.

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Driver and Easley (1978) compared nomothetic studies with ideographic studies (§2.6), and – whilst seeing the utility of both types of research – emphasised the role the latter type of research had to play. They felt it was important to look in detail at learners’ ideas, at ‘the alternative frameworks which arise from students’ personal experience of natural events and their attempt to make sense of them for themselves, prior to instruction’ by using ‘idiographic studies … [where] the focus is on an individual’s personal experience.’ (p. 68.)

4.13

Researchers’ Representations

The seventh hard-core axiom is that it is possible to meaningfully model learners’ conceptual structures, which leads to the general research question what are the most appropriate models and representations?

4.13.1

It Is Possible to Meaningfully Model Learners’ Conceptual Structures

It has been suggested above that this area of work is complicated by the nature of both human knowledge and our cognitive processes. Teachers and researchers have access to student thinking only indirectly through their reports and other behaviour that reflects this. So a student’s comments and questions, their written work, their gestures (and role-plays, etc.), the models they build and diagrams they draw are all acts that can represent their subjective (World 2) experience in the public domain. The extent to which an observer can in some sense reproduce the student’s thinking processes depends upon both the communication skills of the learner, and the ability of the observer to interpret the learner’s public behaviour through their own cognitive systems. There will always be a question mark over whether a teacher really understands what the individual learner is thinking, as this will necessarily depend upon processes of representation by the student and interpretation by the teacher. (Of course, there are techniques that can give us more confidence – but never certainty.) For researchers exploring students’ ideas there are additional complications. For one thing, although we can only collect data that reflect a students’ current thinking, we are usually more interested in stable patterns of thought that are considered to reflect the underlying conceptual structures as represented in memory, rather than transient thoughts or romanced notions created to answer particular questions on what seems a whim. From the discussion above, it is clear that our only way of finding out about conceptual structures represented in memory is by tapping into a student’s current thinking. So the researcher is building personal interpretations of student behaviours that are communicative acts (when the student is motivated to

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offer them) intended to represent thought, which we believe is in itself constrained and resourced by a hypothetical ‘conceptual structure’ represented in long-term memory. Finally, for such research to be of any use in the scientific, rather than the personal, domain, the researcher has to re-represent their own mental models of the learners’ ideas in the public domain in research reports. There is clearly a considerable chain of inference operating here, even in terms of the status of the outputs of such research within the RP (i.e. without considering whether the contents of research reports are in a format suitable for informing teaching). The process is represented (sic) in Fig. 4.1. For the RP to make progress, researchers have to believe that despite the complex nature of this process, it is in principle possible to develop models of learners’ ideas that are meaningful representations of learners’ conceptual structures.

4.13.2

What Are the Most Appropriate Models and Representations?

Given the convoluted process by which learner’s conceptual structures are modelled (see Fig. 4.1), an obvious task within the RP is to develop forms of representations of learners’ ideas that are able to move the programme forward. According to Lakoff and Johnson (1980b: 205), ‘a representation of a concept is a mathematical model of the structure of a category of personal experiences or a model of a structure in terms of which we understand external occurrences’. They commented that ‘it is one of the principal goals of Cognitive Science to work out an adequate theory of representations for human concepts. This is both an empirical and a mathematical endeavor. At present no adequate theory exists’ (p. 206). It is clear from Fig. 4.1 that questions of the extent to which such models are ‘accurate’ representations are unlikely to offer straightforward answers. However, as the task is to provide models, success in this aspect of the programme should be judged in analogous terms to models in other areas of scientific research: do they provide tools for thinking within the RP and for informing pedagogy for use in teacher education/development and teaching.

4.14

Applying the Model of the RP

The remainder of the book draws upon the conceptualisation of the Research Programme (RP) into learning in science that has been presented in this chapter. I will argue that the RP remains progressive, and can continue to guide research in this area. I do this by considering • Common criticisms of ‘constructivist’ research in science education, from the perspective of the RP (in Chapter 5)

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A Scientific Research Programme Within Science Education The figure represents the development of a researcher’s model of some aspect of a learner’s conceptual structure.

researcher’s public model of learner’s conceptual structure thinking is represented in communicative acts

The first (left-hand) column in the diagram represents actions in the public world that can be observed (Popper’s World 1).

researcher thinking about the mental model

thinking calls upon conceptual structures represented in memory

researcher’s interpretation of student’s behaviour

mental model in long-term memory

understanding of student ideas committed to memory

perceptions interpreted through available conceptual frameworks

interpretive frameworks available in long-term memory

perceptions formed from sensory input

student’s public representation of their thinking

thinking is represented in communicative acts

behaviour is observed, through perceptual system

The third (right-hand) column refers to knowledge structures that are represented in memory. These structures only exist in a formal sense (they are World 3 objects). They are coded into the physical world through neural circuitry, but can only be accessed to the extent that they can act as resources for thinking. As working memory is limited, they are accessed piecemeal, although patterns in access (cuing) support the notion of the representations in memory having meaningful structure. Three complications that are not explicity represented here are:

• thinking may be conscious or subconscoius

student’s thinking about a scientific topic

thinking calls upon conceptual structures represented in memory

The central column concerns the subjective mental experience of individuals (World 2), that can only at best be reported (represented) to others.

student’s personal knowledge of topic represented in long-term memory

• cognitive structure influences perceptions as well as thinking • cognitive structure is dynamic: thinking effects memory as well as viceversa

Fig. 4.1 Developing representations of students’ conceptual structures

• How far the RP has progressed in terms of its initial aims, i.e. progress towards answering the research questions set out above (in Chapter 6) • Priorities for research into learning in science (given progress in the RP to date), as informed by the ‘positive heuristic’ of the RP (in Chapter 7)

Chapter 5

The Negative Heuristic and Criticisms of Constructivism in Science Education

Chapter 4 modelled the dominant research tradition in Science Education as a Research Programme (RP), and identified the programme’s hard core and heuristics to guide research. That tradition has commonly been labelled as ‘constructivism in science education’ although this term is used in diverse ways by different commentators. This chapter uses the RP model to examine a number of key criticisms of the notion of constructivism and associated research in Science Education. The chapter explains the nature of the criticisms, and considers how they relate to the RP detailed in Chapter 4. Some criticisms are shown to refer to views that are irrelevant to the RP’s hard core and therefore cannot be seen as criticisms of the RP itself. Others may be excluded by the ‘negative heuristic’ of the RP because they are based on premises that are actually inconsistent with the hard-core commitments of the programme. It will be shown that other criticisms relate to specific ‘refutable variants’ that have been proposed within the RP and these criticisms should be considered as part of valid scientific debate within the programme rather than criticism of the programme itself. Finally, the suggestion that the research tradition itself has ceased to be a useful referent for the field is acknowledged, but deferred to Chapter 6 which will evaluate progress in the RP. It is widely accepted that the constructivist programme (or ‘movement’) has been highly influential within the field, and that a good deal of published research is explicitly linked to the constructivist position. However, the constructivist programme has not been without criticism. This chapter examines some of the most common and significant criticisms from the perspective of the Lakatosian RP set out in Chapter 4. In particular, it will respond to six rather different areas of criticism of constructivism in Science Education: • That constructivism is based on false premises and misleading metaphors about learning that contribute to cultural imperialism, and undermine traditional ecological knowledge • That constructivism in Science Education has a confused philosophical basis, and commonly offers a relativist view of science which is at odds with the stance of most scientists and science teachers • That constructivist research is atheoretical, and/or makes use of invalid or unsupported theoretical constructs

K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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• That an approach based on personal constructivism is inappropriate as learning has to be understood in social and collective, not individual, terms • That whilst the research has produced a great deal of literature, it has had minimal impact on educational practice • That the constructivist approach has ceased to offer useful new insights, and should now be abandoned for more promising approaches These areas of criticism will be addressed in this chapter, although the main response to the final point will be followed up in more detail in the following chapters.

5.1

Constructivism As Culturally Imperialist Movement That Is damaging to Many Traditional Cultures

The first area of criticism that will be considered here is one that considers constructivism in education (not just in Science Education) as a negative influence that undermines many of the world’s cultures, and which also has the potential to contribute to ecological damage in many important habitats. My main source for exploring this criticism will be C. A. Bowers’s account of ‘The False Promises of Constructivist Theories of Learning’ (Bowers, 2007), which is a powerful critique of how the influence of Western ways of thinking about education can undermine traditional community values and knowledge systems across the world. One of Bowers’s key arguments is that constructivism is based on a false premise – i.e. that knowledge cannot be transferred. This immediately offers the option of invoking the negative heuristic when considering how Bowers’s arguments relate to the RP being discussed in this book. The argument would be that as the impossibility of transferring non-trivial knowledge is firmly part of the hard core of the constructivist RP, Bowers’s work falls outside that programme, and cannot be engaged with from within that programme. However Bowers’s denial of this basic constructivist tenet is separate from his claim that adoption of such constructivist thinking is highly damaging, and given the importance of this claim, it is important to consider whether indeed the RP discussed here is indeed contributing to a kind of cultural imperialism, and so indirectly to ecological damage. It is clearly impossible to do justice to the full detail of Bowers’s work in the space available here, but in offering a brief summary of my reading I hope not to misrepresent the basic argument. In view of the importance of the issues raised, I would refer the reader to the original source for a full account of this critique of constructivism. Bowers argues that certain key constructivist thinkers, and he cites Dewy, Freire and Piaget in particular, have influenced a way of thinking about education that dominates teacher education and curriculum development in the West: ‘the core assumptions of Dewey and Freire were being merged together, along with the ideas of Piaget and the jargon of current multiculturalism thinking, into a new orthodoxy

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for teacher education and classroom practice’ (Bowers, 2007: x). Further, this orthodoxy is increasingly being adopted by less industrially developed countries – either because governments choose to follow the lead of the USA and other Western countries as part of industrialisation strategies, or in order to secure support from international organisations such as the World Bank. Bowers reports how ‘at last count, 29 nonWestern countries were introducing the theories and strategies of constructivism into their teacher-education programs and into their schools’ (p. ix). Bowers argues that this approach focuses on the autonomy of the individual learner, and the downgrading of the value of traditional, culturally available, knowledge. He further argues that such a development has a number of effects, and in particular it facilitates the adoption of Western assumptions that support consumerism and the adoption of global brands and practices over local traditions; and it undermines the traditional ecological knowledge that communities have historically used to effectively and sustainably live in balance with their environments. He cites as an example, the Quechua and Aymara peoples of South America whose ‘understanding of the varied characteristics of microclimates and ecological niches has led to the development of one of the world’s most diverse approaches to the cultivation of plants [including] over 3,000 varieties of potatoes’ (p. 62). Yet, according to Bowers, educational policies have been introduced by national governments such that ‘in effect, the intergenerational knowledge that has sustained the Quechua and Aymara in a wide range of ecologically challenging niches and has led to the development of one of the world’s greatest diversity of edible plants, was to be replaced with the knowledge that students constructed from their encounter with the supposedly objective and scientifically based knowledge attained in the West – and from their own supposedly subjective experience’ (p. viii). There are clearly a number of aspects to Bowers’s arguments, and there seems little doubt that he is raising awareness of issues relating to both culture and ecology that are of importance both in terms of local settings, and from more global perspectives of the value of human cultural diversity (and the rights of selfdetermination of particular ethnic groups), and the sustainable management of the ecosystem. These are important matters, and although it will argued here that they are not central to the main subject of this book, this is not intended to in any sense suggest that the issues themselves should be dismissed. However, a reading of Bowers’s take on constructivism, suggests that despite his fervent criticism of the central doctrine that knowledge cannot be transferred, the meaning of constructivism within the RP in Science Education is better aligned with Bowers’s own views of learning than his vilification of the notion would suggest.

5.1.1

Bowers’s Version of Constructivism

Bowers (2007) characterises ‘constructivism’ in terms of four dogmas, • ‘The most important of these dogmas is that “knowledge cannot be transmitted” – only discovered by the student.’ (p. 15)

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• ‘A second dogma found in all the textbooks is that the curriculum must be appropriate to the student’s stage of cognitive development.’ (p. 21) • ‘The third dogma, which is actually the overall goal of constructivist-based education, is that aligning the curriculum to the student’s stage of cognitive development will lead to the autonomous individual.’ (p. 21) • ‘The fourth dogma is that critical enquiry and experimentalism should be at the centre of a process-oriented learning experience.’ (p. 21). When presented like this, it may seem difficult to see what is objectionable about these ‘dogmas’, as they would seem to parallel a set of statements about effective teaching and learning such as: • Knowledge cannot be transmitted wholesale, so it must be presented so that it can be reconstructed by the student. • Effective teaching must take into account the students’ current knowledge and level of understanding. • By organising learning around the students’ current knowledge and level of understanding it is possible to ensure meaningful learning rather than rote learning of material as presented. • Active learning requires students to think through and explore ideas, so bringing about the construction of meaningful new learning. It seems doubtful that when presented in this way these principles of pedagogy (reflecting hard-core assumptions of the RP as set out in Chapter 4) would seem too objectionable to most people working in Science Education. So it is necessary to explore in a little more depth what Bowers does find so dangerous in constructivist thought.

5.1.2

Levels of Cognitive Development and Ways of Knowing

Bowers is critical of ‘constructivist’ educational ideas that use Piaget’s model of cognitive development and which prioritise scientific modes of thought. Bowers points out that Piaget’s training was in science, and that he was ‘an expert on mollusks’ (Bowers, 2007: 21). This may be a valid observation about Piaget’s earliest academic work, but he certainly built on this background with decades of empirical studies of children’s thinking. Bowers notes that Piaget described his work as genetic epistemology, and argues that Piaget thought ‘intelligence should be understood as a biological process of development that is genetically driven’ (p. 22). This description ignores the significant aspect of Piaget’s model that involved interaction with the environment, If intelligence is adaptation, it is desirable before anything else to define the latter. Now to avoid the difficulties of teleological language, adaptation must be described as an equilibrium between the action of the organism on the environment and vice versa. (Piaget, 1950/2001: 8)

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Piaget’s use of the phrase ‘genetic’ in the name he gave to his theory was not related to genes (still hypothetical entities when Piaget did much of his early work), but rather ‘the very term ‘genetic epistemology’ indicates, we think there is a need to study the origins of knowledge’ (Piaget, 1972b: 15 – present author’s emphasis). Indeed, contrary to the impression given by Bowers, Piaget argued that ‘hereditary transmission thus seems to play only a limited role in the development of cognitive functions’ (Piaget, 1972b: 58). Nonetheless, Bowers is correct to associate Piaget’s model of levels of cognitive development with notions of readiness for learning which are particularly relevant to the logical and rational – modes of knowing especially associated with ways of understanding the world in subjects like science. This point notwithstanding, the constructivist RP does not heavily depend upon Piaget’s stage theory, and indeed – as we have seen (§1.10.3) – can to some extent be seen to have developed as an alternative approach to complement the Piagetian programme in Science Education. Bowers (2007: 18) also criticized Dewey for his adoption of a way of thinking about learning as reflecting the approaches used in science, that is, that Dewey’s way of equating intelligence with the utilization of the scientific mode of enquiry, where a hypothesis or plan of action has to be tested in the reconstruction of problematic situations, led him to view traditions (habits) as impediments to intelligent, experimentally oriented behaviour.

It will be noted that Bowers offers ‘traditions’ as a synonym to Dewey’s ‘habits’. The traditions that Bowers is primarily concerned about are those represented in cultures – traditional ecological knowledge relating to such activities as farming, rather than the individual habits that Dewey suggested could be developed – by the intervention of thinking – into intelligent habits that could support intelligent action in the world (Biesta & Burbules, 2003: 38). Dewey valued the experimental method of science as a model for how individuals might approach knowledge acquisition and problem-solving (Biesta & Burbules, 2003). Dewey also valued the development of this way of thinking as important for individuals capable of critical reflection and so empowered to contribute to democracy, and Bowers argues that this link has been widely adopted: Indeed, the connection between the student’s self-construction of knowledge and a democratic society is taken for granted by all the constructivist-learning theorists – and by all the classroom teachers who try to avoid ‘transferring’ knowledge out of a concern that they are thwarting the students’ ability to think for themselves. (Bowers, 2007: 97)

What Bowers actually means by avoiding transfer of knowledge is important, and will be considered below. Bowers identifies this perspective as ‘reactionary’ in the modern global context, representing ‘an attempt to go back to a way of thinking that is now being widely recognized as contributing to an industrial-market-oriented culture that is, for all its benefits, the source of cultural imperialism and environmental devastation’ (p. 20). The focus of this present book is Science Education, where it is reasonable to privilege the rational and logical, and to teach ‘scientific’ modes of thinking and

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knowing the world. Within the wider curriculum context, education would be expected to offer a more balanced vision of human ways of knowing and relating to the world (Hirst & Peters, 1970). It would seem, therefore, that Bowers’s criticism of applications of Piagetian-type stage theory is not generally pertinent to the RP discussed here, and that criticism of Dewey’s focus on a mode of thinking modelled on what is appropriate in experimental science is more relevant to the overall nature of schooling than Science Education specifically (where we might reasonably expect such an emphasis). Despite this, considering what is at stake – in terms of cultural and ecological resources – the question of whether constructivist Science Education might be undermining traditional ecological knowledge will be revisited after considering Bower’s apparent objection to the central tenet of constructivist educational thought: that knowledge cannot simply be transferred to students.

5.1.3

An ‘Absurd’ Assumption

Bower’s (2007: 40) argues that ‘the constructivist claim that “knowledge cannot be transferred” is an example of abstract thinking that has no basis in everyday reality’. He refers to this as a ‘mistaken idea’ (p. 58), and indeed one that is absurd, If theorists such as Dewey, Freire, and their many followers who now occupy professorships in English-speaking colleges of education are unable to recognise the absurdity of the idea that knowledge cannot be transferred, how can their students be expected to adopt a different way of thinking? Foreign students … are even less likely to speak up in class when they hear that a constructivist approach to learning avoids the backwardness of the cultural transmission model of learning. (Bowers, 2007: 16)

There is a clue here to the strength of Bower’s distaste in constructivism, in that he contrasts it with, and suggests it is inconsistent with, the notion of cultural transmission. This is not an empty rhetorical device, as for Bowers a cultural transmission model of knowledge is something the constructivist theorists that he criticizes, ‘all reject’ (p. 32). So Bowers is arguing that worthwhile knowledge within a culture is passed to the young, something that he feels is inconsistent with constructivist approaches to education. Of course, the ‘constructivist’ RP discussed in this volume has largely arisen in the context of finding effective ways to allow youngsters to access something of the cultural knowledge developed by science, and would therefore (in this respect) seem to align with Bowers’s concerns. Indeed, as Bowers develops his argument it seems less antithetical to notions that knowledge cannot be transferred, I have deliberately used the word ‘transmission’ in order to clarify that I am arguing from a culturally informed perspective that the constructivist theories reject. Yet I find the metaphor, when it is associated with a sender/receiver model of communication, to be deeply problematic. Now that I have made the point that I am challenging the most basic assumptions shared by the constructivist learning theorists, I will use the phrase ‘intergenerational renewal’ as an alternative to ‘transmission’ in making the case that what we experience as ‘reality’ is culturally constructed and that in varying degrees, depending upon the culture,

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the cultural patterns are given individualized expression that may lead to their modification. (Bowers, 2007: 32)

This extract reveals two key features of Bowers’s position. Firstly, the view that the metaphor of communication in terms of a sender and receiver is ‘deeply problematic’ would seem to align with constructivist thinking (cf. §4.6). Bowers acknowledges that this ‘sender/receiver model of the language and communication process … has been widely accepted in the West’, but claims that this ‘highly problematic tradition’ supports constructivist positions: that is, ‘is especially important to maintaining the keystone of the constructivist positions that represent intelligence as an attribute of the individual – or, in Dewey’s case, as individuals sharing their intelligence in a way that conforms to the scientific method of enquiry’ (p. 45). Yet the impossibility of simple transfer of complex knowledge is a fundamental basis of the constructivist position, and here Bowers seems to also be rejecting the very transmission model of teaching/learning that is denied by the thinkers he criticizes. Secondly, although Bowers is critical of the constructivism he associates with Dewey, Freire and Piaget; he himself supports a view that experienced reality is (socially) constructed, and open to individual modification. Bowers’s position in relation to the RP in learning science seems then to raise two points of significance. In terms of the focus of knowledge construction, he questions the emphasis on the individual in relation to the social. So, rather than place him outside of the discourse of the RP, Bowers’s views can be considered alongside other critics (considered later in this chapter, §5.4) who have argued that there is too much emphasis on ‘personal’ construction when much construction of knowledge in the science classroom is better seen as a social process. His labelling of the tenet that knowledge cannot be transferred as mistaken and absurd would appear to allow us to invoke the negative heuristic of the RP and dismiss his work as falling outside the programme of work we are interested in. However, a closer examination shows that Bowers’s position is not actually inconsistent with a constructivist model of teaching and learning where knowledge is a social construction, and cannot be unproblematically communicated to students. Indeed, Bowers offers a description of how students have to make sense of teaching in terms of existing conceptual resources that would seem perfectly in line with the hard-core tenet of the RP, that ‘the learner’s existing ideas have consequences for the learning of science’, the student’s thinking is largely a matter of giving an individual interpretation (and often misinterpretation) that is influenced by the conceptual categories and assumptions that have been passed on … as the taken-for-granted ways of thinking. …[T]he understanding of what is new is influenced by the interpretive frameworks the observer brings to it. Put another way, the new is understood in terms of the already familiar. (Bowers, 2007: 45–46)

This would appear to describe a committed constructivist position. It is useful to shift attention from constructivism as learning theory to application as pedagogy to appreciate why Bowers considers constructivism as a ‘Trojan horse’ for Western imperialism. An important clue can be found in Bowers’s reference to ‘the dogma held by the constructivists that knowledge cannot be transferred – but must be discovered and constructed by the child’ (Bowers, 2007: 70).

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5 The Negative Heuristic and Criticisms of Constructivism in Science Education

Constructivism and ‘Content’ in the Curriculum

The form of constructivist pedagogy that Bowers objects to so strongly is not one that looks to find ways to help teachers facilitate learners in constructing their own personal versions of target knowledge set out in the curriculum; but rather one that expects learners to discover knowledge about the world with minimal direction from teachers. Bowers’s argument here takes the form that according to constructivist learning theories: • • • •

Students must decide what is worth learning. Students must discover knowledge for themselves. Teachers must facilitate, but not direct. There can be no set curriculum based upon what has previously been taken as knowledge.

If pedagogy based upon such principles is even feasible, it is certainly not the kind of pedagogy that would derive from the RP explored in this volume (§5.5.4). Bowers’s vision of constructivism does not reflect constructivist teaching as generally understood in Science Education. Bowers’s notion of constructivist education takes Dewey’s notion of learning by enquiry to require a form of discovery learning, Constructivist pedagogies, in being based on the assumption that students learn more effectively when they construct their own knowledge, requires that teachers play the role of facilitator. This view of the teacher’s role … contributes to reducing the potential intelligence of students to what they can learn from their own direct experience. (Bowers, 2007: 10)

Bowers therefore contrasts ‘the constructivist’s understanding of learning as a process of inquiry and the construction of new knowledge’ which ‘places the responsibility on the student for determining what is important to learn’ against learning through ‘the patterns of everyday socialization’ that ‘usually involves an adult, peer, or someone with the knowledge that is being shared who make the initial decision about what is important to learn’ (p. 123). According to Bowers, ‘all of the constructivist-learning theorists make a virtue of not exposing students to knowledge in any systematic way’ (p. 98), so that ‘the teacher must not impede the student’s construction of knowledge by expecting them to learn about existing knowledge’ (p. 21). The RP discussed in this volume has a central concern with helping learners understand the scientific knowledge represented in the curriculum whereas according to Bowers such a curriculum would be ‘ignored’ (p. 110) by constructivist teachers. Indeed, according to Bowers, teachers trained in this tradition (‘in the various constructivist schools of thinking’), lack ‘background knowledge’ needed to act as cultural mediators, and ‘do not know what they do not know’ (p. 110). The argument that constructivist teachers teach by open-ended discovery learning, and so do not need subject knowledge, and are indeed ignorant of the subjects they teach is one that has been made by other critics (Cromer, 1997), and will be considered later in the chapter (§5.2.9). (It should not spoil the tension too much

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to note that I will argue that such a view of constructivism in Science Education is at odds with the RP into learning in science.) However, Bowers’s argument is a little more subtle that this, as he is primarily concerned not with the teaching of the consensus models of formal science, but the traditional ecological knowledge that offers complementary knowledge systems in many parts of the world.

5.1.5

Science Education Undermining Traditional Knowledge Systems

I have argued that despite his criticisms of ‘constructivism’, Bowers’s own ideas about learning do not appear inconsistent with the kind of constructivist principles built into the RP in learning science; and that the approach to pedagogy that he characterises as ‘constructivist’ is at odds with the recommendations for science teaching deriving from the RP. Yet, despite finding some fairly significant points of disagreement with Bowers’s thesis, there is still a major aspect of his argument that remains of considerable concern. In many parts of the world, local populations have lived in the same areas for generations, developing close knowledge of their environment and specific technologies that enable people to make sustainable use of available resources. These communities have achieved this through the development of systems of knowledge, traditional ecological knowledge (TEK, §2.5.2), which is passed down to each successive generation. There is an argument then that would take the form: 1. TEK is of value to maintaining the community’s sustainable harvesting of local resources. 2. TEK is not interchangeable with formal scientific knowledge because (a) it is based on close familiarity with local conditions; and (b) it does not take the form expected of formal scientific knowledge. 3. TEK is part of culture transmitted through the young being inducted into legitimate participation with their elders. 4. TEK is not codified in ways that make it available through formal schooling. Given (for argument’s sake) these premises (which I have phrased to avoid any reference to Bowers’s or anyone else’s version of constructivism), it would follow that if the introduction of formal Science Education were to replace the acquisition of TEK, then that knowledge would be lost, and with it, the capacity for sustainable harvesting of natural resources. It would therefore follow that if we accept the premises, then we should be concerned about formal Science Education (whether or not taught along what Bowers or anyone else considers constructivist lines) coming to replace the cultural transmission of TEK. As Bowers argues that such a process of replacement is what is happening in many parts of the world, then there seems a moral imperative at this point to consider whether the premises are ones which are warranted.

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Traditional Ecological Knowledge Is of Value to Maintaining the Community’s Sustainable Harvesting of Local Resources

Bowers (2007) argues that TEK enables indigenous populations to make use of the local resources in a fully sustainable way. His example of the Quechua and Aymara peoples, can be supplemented by accounts from studies of a wide range of other cultural groups from diverse geographic locations (Inglis, 1993). The value of such knowledge has become clearer as it has been realised that traditional knowledge held by indigenous cultures is far more than descriptive accounts of local species and their behaviour, but is truly ecological, concerning ‘the workings of ecosystems, or at the very least biological communities, containing many interacting species of animals and often plants, and the determinative role played by certain key biological and physical parameters in influencing the behaviour of the total biological community’ (Freeman, 1992). That is, the knowledge is of the system as a whole and able to offer ‘predictive outcomes in respect to matters of practical concern’. It is now widely recognised (e.g. by the International Union for the Conservation of Nature and Natural Resources) that there is much to learn from TEK, in areas such as biology/ecology, resource management, conservation education, development planning and environmental assessment (Berkes, 1993).

5.1.5.2

Traditional Ecological Knowledge Is Not Interchangeable with Formal Scientific

The potential of TEK derives from experience over many generations of communities living in and interacting with local ecosystems (van Eijck & Roth, 2007). It has been argued that such advanced knowledge is only possible from a close familiarity with the specifics – literally a kind of ‘local’ knowledge. As one example, van Eijck and Roth discuss the example of a successful worker in salmon hatcheries who was able to repeatedly, and apparently readily, successfully apply techniques where other more learned colleagues repeatedly failed. Although following the same set of procedures ‘on paper’, the successful fish culturalist apparently had developed local knowledge that could not be readily identified or documented, but which was clearly important in practical terms. Van Eijck and Roth suggest that it is only possible to convert TEK into transcendent scientific knowledge by converting the local context itself so that it can be treated as science laboratory. TEK, then, is considered to be a type of knowledge that is ‘very different’ in form to scientific knowledge (van Eijck & Roth, 2007: 943), which has to be of a general and symbolically specifiable form, and which ‘transcends local contexts’ (p. 927). Van Eijck and Roth go further in arguing that ‘TEK and scientific knowledge, though being simultaneously available cultural means of production, are incommensurable and cannot be reduced to each other’ (p. 935). That TEK has been considered as genuinely ecological knowledge, knowledge of systems of interacting species and habitat, is in keeping with the form that

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this knowledge has commonly come to take. Where laboratory-based scientific knowledge often depends upon reducing, and when possible removing, complexity by isolating and controlling variables, such an approach is not feasible in learning about complex ecologies from within. Rather, ‘ecological theories seek to describe humanity and nature in an inclusive, biological manner as biocentrically connected. They emphasize principles of w/holistic unity and systematic integration, internalistic life-movements, and organic balance’ (Thayer-Bacon, 2003: 185). Indeed TEK has been contrasted with ‘scientific’ knowledge along a number of dimensions (Berkes, 1993): • • • • • • •

Being mainly qualitative (cf. quantitative) Having an intuitive component (cf. being purely rational) Being holistic (cf. reductionist) Considering mind and matter together (cf. separation of mind and matter) Being moral (cf. supposedly value-free) Being spiritual (cf. mechanistic) Being based on empirical observations and accumulation of facts by trial and error (cf. experimentation and systematic, deliberate accumulation of fact) • Being based on data generated by resource users themselves (cf. by a specialized cadre of researchers) • Being based on diachronic data, i.e., long time-series information on one locality (cf. synchronic data, i.e., short time-series over a large area) 5.1.5.3

Traditional Ecological Knowledge Is Part of Culture Transmitted Through the Young Being Inducted into Legitimate Participation with Their Elders

Barbara Thayer-Bacon (2003: 141) describes Berger and Luckman’s notion of ‘legitimation’ as ‘the process we develop to explain and justify to the next generation what seems self-evident to us, by means of our own recollection and habituation’. Lave and Wenger (1991: 29) describe how novices ‘inevitably participate in communities of practitioners and that the mastery of knowledge and skill requires newcomers to move toward full participation in the sociocultural practices of a community’. They describe the novice’s initial involvement as legitimate peripheral participation. Traditional ecological knowledge is primarily transferred through such processes of situated learning, i.e. learning in the situation of actual practices by taking the role of an apprentice. Ruddle (1993) argues that ‘the transmission of traditional knowledge among generations is a complex and fundamental process embedded within the deep socio-cultural structure’ where ‘the curriculum and process of knowledge transmission is culture itself’. The culture is not passed on through abstracted formal classes, but is ‘transmitted in the form of social attitudes, beliefs, principles and conventions of behaviour and practice’ (Berkes, 1993).

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Traditional Ecological Knowledge Is Not Codified in Ways That Make it Available Through Formal Schooling

Such ways of learning are at odds with the forms of education common in industrially developed societies based upon formal schooling, with timetables, examinations at prescribed grade levels, teachers who do not usually practice the subjects they teach (at least, outside of the educational context), and an official curriculum where target knowledge is specified in terms of abstract and discrete objectives. Whilst it would be wrong to suggest either that learning traditional knowledge within indigenous communities never occurs as discrete lessons, or that formal schooling cannot adopt elements of apprenticeship (Hennessy, 1993), it is clear that there is a major difference between the typical mode of learning in these different contexts. From the foregoing analysis, it would seem that the major problem has little to do with constructivist pedagogy, but rather that TEK is not codified as a series of learning objectives that can be treated as a suitable basis for discrete and carefully sequenced lessons. Moreover, is seems that TEK could not readily be reformulated in such terms because much of it is inherent in practices (which need to be undertaken in response to environmental conditions, not according to a preordained timetable) rather than explicitly itemised; and because it is understood in a holistic way that does not separate humans, other living things and their habitat as discrete components, and does not dichotomise mind or spirit against matter, and the knower against an external known reality. This would suggest that if Science Education within formal schooling comes to replace the transmission of traditional ecological knowledge, then that knowledge is likely to be lost at cost to both the particular communities concerned and the rest of the global community.

5.1.6

Constructivism and TEK

Bowers argues that the constructivist approach of much Western education can undermine the learning of TEK. He argues that learning about ‘ethnic approaches to the growing and preparation of food, healing, and mentoring in the art of how to live lightly on the land, are also to be replaced by the students’ own construction of knowledge – including their subjective decisions about what they want to learn’ (Bowers, 2007: xi). He is correct in observing that ‘learning the principles of ecological design, which requires relying upon local knowledge of weather patterns and physical characteristics of the land and animal population, and on the skills of local farmers [etc] … cannot be achieved by students constructing their own knowledge’ (p. 74). Yet the present analysis suggests there is nothing in constructivism per se which would exclude this curriculum, rather, that it is the nature of TEK that it does not fit the form expected of a formal science curriculum suitable for school learning. Bowers suggests that ‘the constructivist emphasis’ has a ‘built-in bias against all forms of intergenerational knowledge’ (p. 67), yet science curricula around the world values the learning of Newton’s laws, Darwin’s theory of natural selection, Dalton’s

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atomism, Crick and Watson’s structure for DNA and so on. Much of this science derives from people of a particular tradition, that of ‘White European males’, but that does not stop it being intergenerational knowledge that science educators, including most ‘constructivist’ science educators, feel is worth passing on to further generations. Bowers argues that ‘learning about the traditions of the different cultural groups would be a waste of time for teachers who hold to the idea that students construct their own knowledge and values’ (p. 33), but in practice what most constructivists in science education seek is to facilitate students constructing their own understandings of forces, evolution, atoms, DNA, etc. that are robust and suitably reflect the scientific models proposed, developed, and judged culturally useful by the older generations. When Bowers suggests that ‘there is nothing in the constructivist text-books used in the teachers’ professional courses that suggests the importance of students learning to take account of the knowledge of the older members of the community, or to learn about the traditions that the older generations want to retain’ (p. 43), he appears to ignore a great deal of literature exploring students thinking in science and suggesting to teachers how it can be shifted towards the knowledge that the older members of the community (teachers, scientists, policymakers in curriculum agencies) want to retain. However, while rejecting Bowers’s thesis as a criticism of constructivism (in Science Education at least), it has to be acknowledged that he is less concerned with whether students can learn to apply Newton’s third law or explain how the structure of DNA facilitates sexual reproduction, and more concerned with ensuring that youngsters continue to learn the knowledge that supports sustainable relationships between communities and their environments. He is right to be concerned, because the form of TEK makes it a poor fit with formal schooling. However, Bowers’s arguments about the nature of constructivist pedagogy only apply to an extreme form of discovery learning widely considered non-viable in Science Education (as we will see later in the chapter, §5.5.4). The ‘constructivist’ RP into learning in science highlights the varying factors that influence learning, and upon which effective learning is contingent. To borrow, and adapt, Bowers’s view, the constructivist assumptions that knowledge [can] be intergenerationally transferred, that the languaging processes [do] influence the child’s earliest patterns of thinking, that children [do] learn by observing the behaviour patterns of peers and adults in their family and community … [illuminate] all the pathways of learning that constitute the interactive relationships that sustain the commons and that children interact with on a daily basis. (Bowers, 2007: 43, 59–60)

If the situation described above – the mismatch of TEK and formal Science Education – is to be overcome so advantages of introducing formal education are not cancelled by the interruption of the transmission of TEK, then it becomes more important than ever to understand the nature of learning processes so that effective pedagogy can be found which does not marginalise or exclude, but rather facilitates, the learning of TEK. Bowers (2007: 124) argues that ‘all of the constructivist-learning theorists, as well as a majority of their followers, ignore the ecological crisis and the differences in cultural ways of knowing’. Ecological issues are often included in the science curriculum, although they may ‘fall’ between science and geography to some

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extent. Traditional ways of knowing may not fit well with formal disciplinary structures that separate out science from arts, technology, literature, languages and religious studies. Here is the real challenge: to find pedagogy that allows TEK to be included in the curriculum such that it can be taught in authentic ways. Perhaps this is not feasible, and a more realistic approach might be to ensure that where Western approaches to schooling are introduced into communities with very different traditions, (a) such schooling is seen as supplementing and complementing rather than replacing traditional modes of cultural transmission; and (b) that teaching about TEK as valuable knowledge is included within the curriculum. One place where non-trivial attempts to incorporate TEK within the formal school curriculum have already been established is Aotearoa/New Zealand (Bell, 2005). This is significant, as that curriculum has been strongly influenced by constructivist thinking (Bell et al., 1995). Whilst only time will tell if the inclusive intentions of the Aotearoa/New Zealand curriculum policy can be realised (Coll, 2007), it offers an example of a major national system where the value of indigenous culture is being taken seriously in curriculum design. It is also perhaps worth noting that those very features of much TEK that make it unsuitable to be considered as part of a formal science curriculum could also make studying the nature of TEK alongside the more usual contents of the science curriculum a potentially powerful way to illustrate the nature of science (as well as the nature of more traditional ways of knowing), something increasingly recognised as a key aim of Science Education (McComas, 1998). That Bowers can be so critical of constructivism, whilst seeming to offer views consistent with much of the ‘constructivist’ programme in Science Education as it is understood in this volume, is certainly a reminder of how the label of ‘constructivism’ has such wide-ranging interpretations (§5.2.6) to limit its value, and make it seem something of a liability in the context of certain discourses. Although Bowers’s critique has been found to have a somewhat different target to the RP championed in this book, he has nonetheless highlighted a very important issue about how TEK might be included as part of the educational experience when Western approaches to schooling are being introduced in traditional communities. It is certainly the case that developing suitable pedagogy here will need to carefully allow for the contingent nature of learning, for as Bowers argues, The mediating role of the teacher needs to be based on a common sense understanding of the interplay of the social context of learning, the students’ interests and level of background knowledge, what represent the most appropriate approach to learning (embodied, explanations, inquiry, ethnographic-based, etc.), and the cultural patterns that the teacher needs to make explicit. (Bowers, 2007: 110)

5.2

The Philosophical Stance of the Constructivist Programme

It has been claimed that the philosophical stance of constructivist research in Science Education is confused, and that where the basis of constructivism is treated, it draws upon a relativist view (Matthews, 1993; Coll & Taylor, 2001; Scerri, 2003).

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As was discussed in Chapter 3 (§3.3.1), relativism is often seen as inappropriate or even antithetical to the nature of science. Some ‘constructivist’ research has been criticized as implying that learners’ ideas should be considered of equal validity to currently accepted scientific knowledge (Millar, 1989a; Matthews, 1993; Scerri, 2003) – an interesting contrast to Bowers’s criticisms of ‘constructivist’ education undermining students’ traditional knowledge systems (§5.1).

5.2.1

Philosophical Commitments Informing Research

In any area of research it is important that researchers have clear views about the nature of what they are studying, the types of knowledge that they can hope to acquire, and the suitability of available approaches used in the field for particular types of studies. Whilst all three of these areas (ontology, epistemology and methodology) are complex and potentially problematic, and so unlikely to offer clear and simple guidance, ignoring these issues may well lead to research decisions that can undermine the very aims of a study (see the discussion of examples in Taber, 2007a). In educational research it is normally suggested that new researchers design their research starting from ‘paradigmatic’ commitments (of ontology and epistemology), as these will inform the choice of an appropriate methodology (i.e. research strategy: survey, ethnography, case study, experiment, etc.), which needs to be made before detailed planning can begin of the timetable for the research and selection of the data collection and analytical techniques to be included in the study. Educational research students may be asked to present separately their conceptual framework (their conceptualisation of the current state of the research field which forms the basis for identifying useful research aims or questions), and their theoretical framework (their basis for arguing that a particular choice of methodology is consistent with their ontological stance to what is to be researched, and their epistemological commitments relating to what it is possible to find out). Failure to work through these stages explicitly can lead to collecting data that treat the ‘objects’ of research as something other than how the researcher understands them, or even an approach that claims a kind of knowledge that the researcher does not believe is possible! These possibilities are summarised and illustrated in Table 5.1. These may seem like rather unlikely scenarios as experienced researchers might be expected to intuitively design their research consistent with their fundamental beliefs. However, it will become clear later in some of the examples discussed that these can be very real issues in research. To some extent, professional researchers (as opposed to novices undertaking research degrees) are less likely to be asked to set out this chain of logic in as explicit a way as novices. Although it is a standard expectation of journals that research reports begin with a conceptualisation of the topic being studied and include a methodology section, there is considerable variation in the amount of detail expected by referees and editors (who have to balance the quality of a report with the availability of journal pages, cf. Pope & Denicolo, 1986).

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Table 5.1 Two types of error in matching research to underpinning commitments Type of error Nature of error Illustration The researcher has a view about A researcher offers a description of how concepts are organised in a learners’ the nature of the phenomenon cognitive structure (see Chapter 4, and investigated, but the research in particular Fig. 4.1) approach inherently reveals a different kind of entity Epistemological The researcher claims knowledge An intention to identify common ways of error of a status that cannot derive understanding a topic would not be for the type of research supported by in-depth studies with a undertaken small number of volunteers from a single educational context (see Chapter 7)

Ontological error

This is an area where Kuhn’s analysis (§3.2) may be informative. According to Kuhn’s model, within a particular field there is a ‘disciplinary matrix’ that includes a repertoire of methodological approaches and specific techniques that are standard tools in the field. This aspect of Kuhn’s work can be accepted without a commitment to his model of scientific change necessarily taking the form of scientific revolutions as paradigm-shifts, and can be fitted to Lakatos’s notion of successions of RP (§3.8). Something like a disciplinary matrix can operate within a RP, but without the Kuhnian premise that the matrices of rival or successive RP need necessarily lead to incommensurability. That is, rival RP, may share a good deal, without having adopted the same hard-core commitments. Justification of a particular approach given in many studies may be little more than an acknowledgement that the design draws upon methodology used in previously published work in the area. (Indeed, often with common techniques, this is implicit in the published report, and there is no discussion of the pedigree or suitability of the approach for the particular study.) This may be particularly so in the natural sciences. Research in the social sciences shows less clear evidence of the ‘paradigmatic’ disciplinary structure Kuhn proposed (see Chapter 2). That is, although in the natural sciences there is often a clear dominant (if not consensus) view of how research should proceed in a particular area, in the social sciences there may well be several alternative views on appropriate ways to develop valid knowledge. In education, much research has traditionally been considered to be either broadly positivist or interpretative. This distinction was discussed in Chapter 2 (§2.6.2), where it was also suggested that a range of different research approaches could be accommodated under a broad post-positivist stance. Although naive realism was considered untenable, it was argued that interpretative ‘discovery’ approaches can be used alongside ‘confirmatory’ research. Indeed, these two strategies were considered complementary, with exploratory interpretive research discovering ways of understanding phenomena that can be used to identify the concepts and categories to be tested in later confirmatory stages of the research cycle. Yet interpretative research inevitably has a subjective element, admitting the researcher as part of the context that is reported (not just as an uninterested

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observer), and acknowledging research outcomes as the researcher’s constructions (or co-constructions with informants). This can be seen to align interpretivist research with relativism, the notion that there are many possible constructions of reality, each as valid as the others.

5.2.2

Constructivism As a Label for a Research Paradigm

The term ‘constructivism’ has a range of common meanings. Its adoption in science education was largely influenced by the personal constructivism of Piaget (§1.6.1) and Kelly (§1.6.3) and refers to the nature of learning. It is this meaning which underpins the characterisation of the RP presented in Chapter 4 as ‘constructivist’. However, it has been noted that ‘the term constructivism is used with a number of distinct and sometimes contradictory shades of meaning across the social sciences’ (Potter, 1996: 35 - see also Good et al., 1993; Bickhard, 1998; Hacking, 1999). As interpretivism is a stance that considers research as having a subjective component, and about the construction of different accounts of reality, some authors have adopted ‘constructivism’ as a signifier for this type of research. Indeed ‘constructivism’ is sometimes used as a label for the general methodological approach to social research also known as ‘naturalistic enquiry’, i.e. an alternative to the conventional positivist paradigm in social science research. At one time known as ‘naturalistic inquiry’, but now known as ‘constructivism’, it offers a more ‘informed and sophisticated’ set of assumptions about the nature of reality (ontology), the relationship between observer and observed (epistemology), and the appropriateness of various tools for inquiry (methodology). (Beld, 1994: 99)

Bickhard (1998: 111) warns us that ‘constructivisms abound’ and so there are dangers in assuming all constructivists are making similar claims. Many of those labelling themselves as ‘constructivists’ take the view that the social phenomena they study are human constructions, and that the significance of such constructions derives purely from meanings people give them (Gergen, 1999). So, for example, Kvale (1996: 14) refers to the qualitative research interview as ‘a construction site for knowledge’. The ‘constructivist’ label therefore carries connotations of commitments beyond those of the ‘constructivist’ RP in Science Education (i.e. the hard core outlined in §4.4), and which are neither necessary, nor always adopted, by those in the Science Education field who adopt constructivism as a perspective on learning science.

5.2.3

Philosophical Critiques

Although constructivism in Science Education has been described as a movement or paradigm, it is something of a diverse movement – certainly in terms of claimed philosophical underpinning (Matthews, 1998b; Good et al., 1993; Phillips,

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2000a, b). One of the criticisms made of constructivist research in education is that it is founded upon confused philosophical foundations: that is ‘critics of constructivism believe that the ontological and epistemological picture is muddled and lacking a coherent view’ (Coll & Taylor, 2001: 219). The flavour of some of this debate is illustrated by the conclusion to a paper by Suchting (1992: 247) who characterised the version of constructivism presented in an influential paper by Glasersfeld (1989) as ‘unintelligible’, ‘confused’ and unsupported. Scerri (2003: 468) wrote of ‘philosophical confusion’ in chemical education research, drawing attention to an ‘aspect of research into chemical education that I and others believe to be harmful to the reputation of the field … what can only be described as dubious and abstract theoretical issues revolving around the themes of constructivism, relativism and other philosophical –isms’. Scerri’s criticisms (see §5.2.8) were focused primarily on what he had experienced in the USA, and another commentator has suggested that in the USA ‘many constructivists [in science education] are pure empiricists because of their ignorance of the scientific process (Cromer, 1997: 20).

5.2.4

Relativist Leanings in Constructivist Writing in Science Education

One area of criticism of ‘constructivist’ writing in Science Education, then, is the perceived adoption of a relativist stance on knowledge: that ‘constructivism appears to require a relativist ontology’ (Coll & Taylor, 2001: 219). Professional natural scientists would find such a position difficult to accept, and often carry out their work as if there is an objective world that can be known through science. From such a perspective, earthquakes, draughts, infectious diseases and the like are considered to reflect some underlying regularities in the world, and to force their significance upon us, despite how we may wish to construe them. Certainly examples of scientific concepts such as the class of substances which are described as ‘acids’ or the set of phenomena considered ‘oxidation’ are certainly ‘culturally relative’, in the sense that the accepted definitions have changed over time in response to developing theory. Nonetheless, to most scientists, concepts such as ‘gold’, ‘electron’, ‘carbon dioxide’ or ‘noble gas’ do map onto some aspects of an objective world in a highly meaningful way. Coll and Taylor (2001: 218) suggest that ‘inherent in a constructivist approach to learning is a shift away from the conventional positivist proposition based on a realist ontology in which science is seen as a codified body of knowledge that can be transmitted to the learner’. According to Matthews (2002: 121), ‘educational constructivism is a heady mixture of the supposedly psychological thesis that “children must construct their own knowledge” and the supposedly Kuhnian epistemological thesis that “all knowledge is relative and paradigm dependent” ’. Matthews alludes here to the

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distinction between what might termed psychological or pedagogic or cognitive (or sometimes ‘trivial’, see §5.2.6) constructivism (about learning processes) and broader issues of truth and reality. Scerri (2003) has criticized as confused the writings of some educators advocating constructivism in the USA (Herron, 1975; Spencer, 1999; Bodner, Klobuchar, & Geelan, 2001). Scerri argues that these writers either advocate philosophical positions (such as relativism) that may be inconsistent with the purposes of science teaching, or claim to be constructivist whilst holding views about scientific knowledge inconsistent with the way ‘constructivism’ is commonly understood in philosophy and social studies, I think that if one looks closely at the basic philosophical positions offered by some contemporary chemical constructivists one sees many radical themes that are not only open to serious questioning but can also be construed as being anti-scientific. In other cases I will argue that chemical educators who describe themselves as constructivists are unwittingly arguing for a very traditional conception of scientific knowledge that sits rather uncomfortably with constructivism as generally understood in the context of scientific theories. (Scerri, 2003: 468)

Cromer (1997: 11) argues not only that constructivists in Science Education are relativists, but also that this is due to such science educators being ignorant of science themselves, and so ‘by devaluing scientific knowledge – bringing it down, so to speak, to the level of everyday knowledge – constructivist educators with no knowledge of science have increased their own power in science education relative to educators with scientific knowledge’. Matthews, in reviewing a ‘constructivist’ volume (Fensham et al., 1994) comments how ‘the authors of one of the essays say that their “science lessons are student centred” and that teachers need not know their subject. Admission of teacher ignorance “has benefits for the students: it gives them confidence”. This seems counter-intuitive, and contrary to the notion of a professional and competent teaching service’ (Matthews, 1994a: 168). This quote seems to support Cromer’s criticism, and suggests that in Australia (where the quoted authors work), as in the USA, constructivist teachers do not value knowing any science. The context of the quotation Matthews offers is part of an introduction to a series of chapters on primary science teaching, where the authors offer encouragement to other primary teachers who may feel they lack specialised science knowledge (in common with many primary teachers worldwide). My own reading of this comment in its original context is not that it is being suggested that teacher ignorance of the topic being studied is a good thing, but rather that it is not necessary for primary teachers to feel they need to know all there is to know about a topic before they can feel comfortable teaching it, To become confident they need to realize that they do not have to know everything, they must learn to say, ‘I don’t know but let’s find out together’. This also has benefits for the students; it gives them confidence. The realization that learning does not stop, that everyone is learning all the time, even adults, helps to take the fear out of learning. (Duke, Jobling, Rudd, & Brass, 1994: 99)

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Evidence of Relativist Sympathies?

Yager (1995: 38) suggests that ‘constructivists do not consider knowledge to be an objective representation of an observer-independent world. For them, knowledge refers to conceptual structures that persons consider viable’. However, it would be wrong to assume that such a perspective is common throughout the RP. Indeed, in Gilbert and Swift’s (1985) analysis, discussed above (§4.3.2), a notion of objective reality features strongly within their proposed hard core. Quale (2008) has recently published an argument for science to be taught from a relativistic position consistent with radical constructivism, but this is not representative of most work in Science Education informed by constructivism. One of the key points that have been made in many research papers from within the RP is that learners’ ideas were important, and should be taken seriously. This reflects two of the premises that are considered here to be among the hard-core assumptions of the RP (see Chapter 4): • The learner’s existing ideas have consequences for the learning of science. • It is possible to teach science more effectively if account is taken of the learner’s existing ideas. In justifying their research within the RP, authors often therefore emphasised that learners’ ideas needed to be taken seriously, as in the following examples of points made in the ‘constructivist’ literature in Science Education: • Teachers should not think of ‘a matter of not understanding but of understanding differently from what was intended’ (Nussbaum & Novick, 1982: 184). • It is necessary ‘to explore and empathise with children’s frameworks’ (Watts et al., 1982: 27), because they had ‘both important epistemological value and high educational status’ (p. 7). • Learners’ ideas are ‘personally viable constructive alternatives – rather than the result of some cognitive deficiency, inadequate learning, “carelessness” or poor teaching’ (Gilbert & Watts, 1983: 67). • Alternative frameworks uncovered in Watts’ research were described as ‘coherent, internally logical conceptual frameworks based upon [pupils’] own experiences which are very successful in explaining everyday events’, and it was suggested that they should be given ‘due status’ (Pope & Gilbert, 1983: 198) as they were not only ‘plausible’ but also ‘fruitful’ for the pupils (p. 199). • Learners’ alternative frameworks were ‘in keeping with their experience and in this respect … not “wrong” … perhaps just not as inclusive as the accepted “scientific” view’ (Driver, 1983: 87–88). According to Coll and Taylor (2001: 221) ‘critics of constructivism believe that relativist stance held by most adherents of constructivism undermines the successes of science and the role of the teacher, partly because it affords students’ views too much importance’. Yet, it is clear that most of these comments were not in any sense suggesting that learners’ views should be given the status as scientifically important, but rather as pedagogically significant,

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Students’ interpretations of phenomenon are natural and understandable, not somehow deviant or willfully misguided. As far as the physics teacher is concerned they may be inappropriate, and even undesirable, but that does not negate the normality and personal importance of the constructs of the students. (Pope & Watts, 1988: 106)

As Solomon describes, such writing shifted learners’ alternative ideas from being an irritation or irrelevancy, into a major focus of attention: ‘what had been commonplace and unremarkable became significant, and what was too well known to be thought worthy of comment, was suddenly the substance of illuminating research’ (Solomon, 1994: 6). Yet in emphasising the importance of learners’ ideas – requiring ‘the teacher to recognise pupils’ or students’ scientific constructs as having both important epistemological value and high educational status’ (Pope & Watts, 1988: 106) – the constructivists can be considered to have provided ammunition for critics such as Matthews (1993) and Scerri (2003) to accuse them of being ‘relativists’. Russell and Osborne (1993: 4) sum up the tension between beliefs that teaching is about guiding students towards established thinking, and that learning is a process of building upon current conceptual resources when they argued that ‘although the approach [used in the SPACE project, see (§4.2.1)] can be described as “childcentred”, each teacher had a clear agenda as to the direction in which children’s understanding should be helped to proceed [even if this was] not to suggest that the achievement of understanding in conventional scientific terms was the invariable expectation’. A simple gloss is that although working from children’s current understandings will often limit the amount of progress towards the target knowledge that is feasible under normal classroom conditions, such an approach will be more effective (i.e. make more progress in shifting children’s thinking) than simply ignoring where children’s conceptual shifts are starting from.

5.2.5

Flavours of Constructivism

Despite the apparent relativist leanings found in some of the constructivist studies in the literature, the constructivist RP in Science Education is not inherently relativist. The hard core of the RP, as outlined in Chapter 4, does suggest that learners’ ideas in science are important, and should be studied, but is not based on a view that anyone’s ideas are equally valid as models of the world. However, the issue is clearly complicated by a number of issues that should be distinguished. A key issue is that there are different types of flavours of constructivism that have been given various labels. So Bodner and colleagues (2001: 12–13) discussed the following forms of constructivism as potential influences on work in Science (chemistry) Education: • • • •

Personal constructivism deriving from Piaget ‘[A]n alternative form of personal constructivism’ provided by Kelly Novak’s ‘human constructivism’ Social constructivism (see later in this chapter) that ‘the role that social effects might have in modifying the ideas these individuals construct’

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• Social constructionism (after Gergen) that ‘focuses on the role of language in the development of knowledge … rejecting the notion that knowledge resides within individuals’ • Critical constructivism (after Taylor) that ‘examines the barriers that must be overcome to create a constructivist classroom environment’ • Contextual constructivism (after Cobern) that ‘considers the effect of culture and world view as central forces in the development and organization of students’ ideas’ Of particular relevance to the constructivist RP in Science Education is a distinction between a ‘strong’, or ‘radical’ version of constructivism, and a weaker approach labelled ‘trivial’ (at least by proponents of the radical view). Although these terms are used in some literature, they are not preferred here, as the so-called trivial version of constructivism upon which the RP in Science Education is based, is clearly seen as anything but trivial, being part of the hard core of the RP. This will be referred to instead as ‘cognitive’ constructivism, after Grandy (1998). As discussed below, it is possible to be a constructivist in ones thinking about teaching and learning (i.e. a cognitive constructivist), whilst being a realist in terms of science itself (so not a radical constructivist). That is, learners’ ideas may well be considered to have minimal scientific validity, because they do not match the validated models of science, yet still to be of central importance in teaching about those models. Secondly, of course, few scientists are naive realists, and one does not have to be a vulgar relativist believing that knowledge only reflects current human whims to hold skeptical views about the possibility of revealing the true nature of the world (as was seen in Chapter 2). In particular, Glasersfeld, sometimes presented as something of a dangerous radical peddling relativism, sets out a strong instrumentalist position, which is somewhat different from rampant relativism as will be shown below. Finally, it should be recognised that there are important issues about the nature of ‘Science’ being ‘ethnocentric’ (as well as anthropocentric) that admit positions somewhere between accepting that ‘anything goes’ and excluding from the label ‘scientific’ anything that does not fit with the current consensus of the international scientific community. In other words, it may be premature to assume without further consideration that ‘folk science’ that has developed in different cultural contexts is necessarily inferior to ‘Science’. This is an important issue when learners’ own thinking derives from ideas that are respectable and valued in their own cultures (see §5.1). The present analysis will then explore the criticisms of the philosophical basis of constructivist Science Education through two distinct routes. Firstly, the nature of ‘radical’ constructivism will be explored, to determine the extent to which it can be seen as a relativist perspective – leading to the view that there is little in the philosophical basis of constructivism which would be of great concern to most practicing scientists. Secondly, it will be argued that the hard core of the programme is such that, as a RP, constructivism in Science Education cannot be considered to be committed to a particular view on the status of scientific knowledge.

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169

Glasersfeld’s ‘Radical’ Constructivism As an Instrumentalist Perspective

A number of writers within Science Education who identify themselves as constructivist cite Glasersfeld as a source and influence. So for example, Bodner (criticized above by Scerri) suggests two central tenets from Glasersfeld’s ideas (Bodner et al., 2001: 12): • Knowledge is not passively received; it is actively built by the individual. • The goal of cognition is to organize our experiences of the world by making these experiences meaningful. The first point here is clearly central to the constructivist RP, being equivalent to premise 1 as set out in Chapter 4 (§4.4.1). The second point is of significance to the present discussion. Making experiences meaningful does not necessarily imply understanding those experiences in terms of some objective external reality: that is, this view does not see the goal of cognition as being to ‘know’ the nature of the world, to understand reality, or to build models that are true representations of reality. Certainly, ‘making experiences meaningful’ can be understood to be a process of forming models to represent the nature of reality, but in the sense of forming mental models of an external world as perceived and experienced, rather than as in some sense ‘true’. Such ‘truth’ might be judged in terms of the model comprising entities and relationships between them that have a direct correspondence to the entities and relationships between them that exist in the external world (Popper, 1979b). So if our model contains an entity ‘the electron’ which is electrostatically attracted to positive charges, then our model is only considered true to the extent it reflects electrons and their properties as existing in the real world. Whether this (i.e. ignoring the ‘truth’ status of our models) is considered a problem may first depend upon the context of the ‘goal’ of cognition. If this is meant as a description of the individual naive knower, the young child for example, then this perspective (which is informed by Piaget as Glasersfeld readily acknowledges) may generally seem unobjectionable. However, if such a perspective is extended to describe cognition in the cause of professional science, then it becomes embroiled in considerations of the nature of science, and clearly contradicts the realist programme – which sees science as something more than developing models that are useful. In considering this debate previously, I have strongly argued that the constructivist RP in Science Education is centrally about the learning of individuals in relation to the context of formal science instruction, and so an educational researcher’s position on the goals of Science is not directly relevant to their work within the RP (Taber, 2006b). This remains my view (that the criticism is about issues orthogonal to the RP as characterised here), and is discussed in more detail below. However, in view of the strong feelings that have been expressed on this issue as a key criticism of the constructivist programme, it is important to examine the debate in more detail.

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5 The Negative Heuristic and Criticisms of Constructivism in Science Education

Neural Solipsism Imbedded in an External Reality

At one level, this might seem a debate that should easily be settled. Critics of ‘radical constructivism’ accuse it of being a relativist perspective or at least of encouraging such a perspective, yet Glasersfeld explicitly stated that his view did not deny the existence of a single external reality. Nor did Glasersfeld suggest that such a reality would be irrelevant to our experiences and so to the constructions we make – quite the opposite. Yet this seems insufficient to appease his critics, as he does claim that external reality is ultimately unknowable. According to Glasersfeld (1988: 4) ‘radical constructivism … does not deny an ontological ‘reality’—it merely denies the human experiencer the possibility of acquiring a True representation of it’. The position is perhaps summarised well by Reddish (2004: 8) in a principle he describes as ‘neural solipsism imbedded in an external reality’, that is that ‘there is a real world out there and every individual creates his or her own internal interpretation of that world based on sensory input’. So a radical constructivist considers himself or herself to exist in some form of external reality, but does not believe such a world can ever be objectively known. This is clearly in opposition to a realist notion of science that holds that in some sense scientific enquiry can move us towards an understanding of the world that is better because it is truer to its real nature. For Glasersfeld, as Dewey (§1.5.1), our models of the world are based on the interpretation of experience, and can only be tested by further experiences that we interpret, so there is no possibility of some external means of verifying whether the models actually match to reality. This does not make reality irrelevant to our models – it provides rather significant constraints on the experiences we can have! – but, it does make ‘match to reality’ an irrelevance when judging our models as it is not a viable criterion, The goal of the endeavor is to see whether we can construct what is called knowledge without making assumptions about the character or structure of a prefabricated reality. As any other rational theory, constructivism presupposes a world and a knowing agent whose presence it cannot explain. (Glasersfeld, 1997: 6)

This is seen as a rational position to take, as although reality constrains our experiences, these experiences always underdetermine the nature of the external world, for ‘radical constructivism does not suggest that we can construct anything we like, but it does claim that within the constraints that limit our construction there is room for an infinity of alternatives’ (Glasersfeld, 1998: 8–9). Therefore, ‘true’ knowledge of the world is not possible, so although ‘constructivism has never denied an ulterior reality; it merely says that this reality is unknowable and that it makes no sense to speak of a representation of something that is inherently inaccessible’ (Glasersfeld, 1992). This view, that we can never objectively measure our models of the world against ‘reality’ (rather than against our experiences in the world), leads to a pragmatic shift in what it makes sense to consider ‘knowledge’ (as indicated earlier, §1.2.2). If we limit ‘knowledge’ to verified true knowledge of the world, then

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(for a radical constructivist) we have no knowledge: ‘constructivism drops the requirement that knowledge be “true” in the sense that it should match an objective reality. All it requires of knowledge is that it be viable, in that it fit into the world of the knower’s experience, the only “reality” accessible to human reason’ (Glasersfeld, 1992). To retain ‘knowledge’ as a meaningful and useful construct, it needs to be understood differently, If the view is adopted that ‘knowledge’ is the conceptual means to make sense of experience, rather than a ‘representation’ of something that is supposed to lie beyond it, this shift of perspective brings with it an important corollary: the concepts and relations in terms of which we perceive and conceive the experiential world we live in are necessarily generated by ourselves. In this sense it is we who are responsible for the world we are experiencing. (Glasersfeld, 1990: pp. 8–9)

Glasersfeld himself offers the following summary of radical constructivism, (1a) Knowledge is not passively received either through the senses or by way of communication; (1b) knowledge is actively built up by the cognizing subject. (2a) The function of cognition is adaptive, in the biological sense of the term, tending towards fit or viability; (2b) cognition serves the subject’s organization of the experiential world, not the discovery of an objective ontological reality. (Glasersfeld, 1998: pp. 8–9)

We build models that are viable, and modify them when we have experiences that require this: but we can never be sure to what extent the model (of the experienced reality) is ‘truly’ the way the external world inherently is: only how well the model allows us to function in the world. This includes the constructivist model itself which must also be held ‘only as a working hypothesis that may or may not turn out to be viable’ (Glasersfeld, 1998: 4). Because of this limitation, Glasersfeld does not believe it makes sense to talk of our building ‘representations’ of the external world. So although everyone has their own version of experienced reality, Glasersfeld is not arguing that ‘reality’ is relative to the knower or culture, but rather that as something unknowable it is best not made the focus of a theory of knowing: ‘radical constructivism is an attempt to develop a theory of knowing that is not made illusory from the outset by the traditional assumption that the cognizing activity should lead to a “true” representation of a world that exists in itself and by itself independently of the cognizing agent’ (Glasersfeld, 1992). Glasersfeld avoids this because ‘radical constructivism assumes that the cognizing activity is instrumental’, i.e. it concerns only ‘the experiental world of the knower’ that is ‘constituted and structured by the knower’s own ways and means of perceiving and conceiving’, It is the knower who segments the manifold of experience into raw elementary particles, combines these to form viable ‘things’, abstracts concepts from them, relates them by means of conceptual relations, and thus constructs a relatively stable experiential reality. The viability of these concepts and constructs has a hierarchy of levels that begins with simple repeatability in the sensory-motor domain and turns, on levels of higher abstraction, into operational coherence, and ultimately concerns the non-contradictoriness of the entire repertoire of conceptual structures. (Glasersfeld, 1992)

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Bodner (1986: 874) uses a lock-and-key analogy to illustrate the difference between the realist requirement for knowledge that ‘matches’ reality and the less demanding instrumentalist requirement of it ‘fitting’ our experiences to date. If we accept a ‘correspondence’ view of knowledge, then ‘individuals with the same knowledge must have similar copies or replicas of reality in their minds’, whereas if we expect knowledge to ‘fit’ reality as experienced to date then the knowledge of different individuals may reflect ‘many keys, with different shapes, [that] can open a given lock’, Each of us builds our own view of reality by trying to find order in the chaos of signals that impinge on our senses. The only thing that matters is whether the knowledge we construct from this information functions satisfactorily in the context in which it arises. The constructivist model is an instrumentalist view of knowledge. Knowledge is good if and when it works, if and when it allows us to achieve our goals. (Bodner, 1986: 874)

Radical constructivism, as so defined, seems in many ways highly reasonable. Unless it is possible to offer a means by which our knowledge can be shown to match reality (a subject of long-standing and ongoing debate in the philosophy of science), then it seems rational to accept that our understandings of the world are just our attempts to make sense of our experience of living in the world, and not to make claims for a kind of knowledge that is unjustifiable. Novak, one of those proposing the adoption a constructivist perspective on epistemology as well as pedagogy in Science Education, makes it clear that his radical constructivism acknowledges external reality. From this perspective, ‘knowledge is a construction based on previous knowledge and constantly evolving over time’, however, ‘we shall never know when we are moving closer or further away from describing that reality as we construct new schemes to explain how the world works’ (Novak, 1993: 169). Novak suggests that ‘the history of the “hard” sciences provides many examples to support radical constructivism, and theories in the social sciences show even greater mutability’ (p. 169). Of course, this argument can be used to suggest that ideas that are currently broadly accepted in science and taught in schools may come to be discarded: including (in principle) such ideas as evolution by natural selection, and the likelihood that human actions may be leading to major and potentially irreversible changes in the environment, such as climate change. As Bodner (1986: 875) reiterates, this type of constructivism is one that – like science itself – sees knowledge as provisional, and open to review: ‘construction is a process in which knowledge is both built and continually tested’. However, such constructions are not arbitrary. We cannot select any key; it must be one that fits: ‘individuals are not free to construct any knowledge, their knowledge must be viable, it must “work” ’. Yet, Glasersfeld suggests that this perspective is ‘radical’ in that it requires a major shift in the understanding of fundamental terms, One cannot adopt these principles casually. If taken seriously, they are incompatible with the traditional notions of knowledge, truth, and objectivity, and they require a radical reconstruction of one’s concept of reality. Instead of an inaccessible realm beyond perception and cognition, it now becomes the experiential world we actually live in. This world is not an unchanging independent structure, but the result of distinctions that generate a physical and a social environment to which, in turn, we adapt as best we can. (Glasersfeld, 1998: p. 4)

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So the ‘reality’ we talk about and make sense of is our ‘experienced’ reality, not the external reality. It would seem to be comments such as this, though, that are considered to support a relativist thesis. I offer a caricature of the radical constructivist position in the table below (Table 5.2), in comparison to a realist and relativist position. There are many possible nuances around such gross positions, but the key point here is that radical constructivism of the kind advocated by Glasersfeld sits between realist and relativist positions. The focus in radical constructivism is on the knowledge of different ‘individuals’, but Glasersfeld recognised, as Dewey, that experience of the world includes interactions with others, and so we expect our ideas to fit with our understandings of what others tell us – at least when we feel that communication approximates what Habermas would call an ideal speech situation – ‘one in which there are no external constraints preventing participants from assessing evidence and argument, and in which each participant has an equal and open chance of entering into discussion’ (Giddens, 1985: 131). Habermas argued that although there was no absolute basis for human knowledge, vulgar relativism could be avoided as there were universal notions of rational communication that allowed reasoned argument and so supported the evolution of a rational consensus (Giddens, 1985). This perspective reflects the qualified relativist position (§3.3.3) such as that of Thayer-Bacon (2003) who argues for a relational ontology and epistemology. This position is also shown in Table 5.2 as placed between the realist and (‘vulgar’) relativist positions, although this might be better considered to be orthogonal to realism–relativism as

Table 5.2 Radical constructivism as intermediate to realist and relativist positions Realist Radical constructivist Qualified relativist Relativist An objective external world exists, and science seeks to build up true knowledge of it

External reality is the reference point for our knowledge Focus on the nature of external reality

The external world constrains the viable models of it that we can build, but never sufficiently to allow us to be confident we have objective knowledge of the external world External reality is not a useful reference point, as we have no direct access to it Focus on the viability of constructed models of ‘experienced’ reality

People are a part of the world, and knowledge is always situated – but intersubjectivity allows us to moderate our knowledge

Each individual or culture constructs its own version of reality, and interprets the world accordingly

Experience deriving from interacting in the world is the basis of our reality Focus on ecological relationship (rather than human–nature or mind–matter dualisms)

The notion of external reality is meaningless, as reality is constructed Focus on the constructed realities of individuals or cultures

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it does not accept the dualistic distinctions by which those positions are commonly defined (§2.5.1). Whilst this ‘qualified’ approach avoids some of the difficulties of reconciling the radical constructivist view with ‘common-sense realism’ (Popper, 1979b); it has not (to date) been widely adopted as a basis for positions taken in ‘constructivist’ studies in Science Education.

5.2.7

Matthew’s Criticisms of Radical Constructivism

Matthews (1994b: 149), like Scerri, sees Glasersfeld’s version of constructivism as relativist, as it lacks a ‘preferred epistemic conceptual structure’. Matthews (2002: 125) offers a summary of what ‘can be referred to as von Glasersfeld’s principle, or perhaps von Glasersfeld’s philosophy (VGP)’: 1. Knowledge is not about an observer-independent world. 2. Knowledge does not represent such a world; correspondence theories of knowledge are mistaken. 3. Knowledge is created by individuals in a historical and cultural context. 4. Knowledge refers to individual experience rather than to the world. 5. Knowledge is constituted by individual conceptual structures. 6. Conceptual structures constitute knowledge when individuals regard them as viable in relationship to their experience; constructivism is a form of pragmatism. 7. There is no preferred epistemic conceptual structure; constructivism is a relativist doctrine. 8. Knowledge is the appropriate ordering of an experiential reality. 9. There is no rationally accessible, extraexperiential reality; the term ‘world’ is shorthand for ‘our experience’. It would seem that most of these points are fair representations of Glasersfeld’s position, with – I would suggest – the exception of 7, which might suggest a vulgar relativism at odds with Glasersfeld’s own claims. Matthews finds this view of knowledge broadly unacceptable, as it (in his view) confuses knowledge, in the Socratic tradition of reasoned true belief with belief per se, In both cases [Piagetian personal constructivists; social constructivists] there is a routine, but devastating, confusion of belief with knowledge: a psychological matter is confused with an epistemological one, and the consequence is educational havoc. Most of what constructivists maintain about knowledge is completely mistaken, but if “belief” is substituted for knowledge in their accounts, then a lot of the claims are perfectly sensible and some of them may even be right. Whether they are right or wrong is a matter of psychological investigation, that simply has nothing to do with epistemology or with deciding whether some claim constitutes knowledge. Children and adults have, since time immemorial, discussed matters with friends and have come to various beliefs about the natural and social world. This in itself has absolutely no bearing upon the truth of their beliefs, or on their claims to be knowledgeable. There was no end of discussion and agreement among Nazis about the subhuman status of the Slav peoples, likewise millions of Maoists during the

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Cultural Revolution came to believe that the educated class were counter-revolutionary running-dogs of capitalism, and millions of Hindus have for thousands of years believed that wives should accompany their deceased husbands into the next world. And of course, before Copernicus, there was no amount of agreement about the sun orbiting the earth. None of this mass agreement means anything for the truthfullness of the Nazi, Maoist, Hindu, or pre-Copernician claims. (Matthews, 2002: 126)

Matthews is right in pointing out that knowledge has traditionally been distinguished from belief. However, from a constructivist perspective, there is a difficulty with a Socratic notion of true reasoned belief. According to Matthews, a person holds knowledge when they believe something that is true and hold appropriate grounds (‘good reasons’ p. 127) for doing so – so that false knowledge is an oxymoron. Yet in Glasersfeld’s radical constructivism, we can never know for certain which beliefs are true. It would be possible therefore to jettison the notion of knowledge, and simply discuss people’s beliefs. However, constructivists usually keep the notion of knowledge although qualified in various ways: personally constructed knowledge, socially negotiated knowledge, public knowledge, etc. (Adopting the term ‘belief’ as a description of personal knowledge is also problematic – see §1.2.3.) It might be suggested that a constructivist position can never offer sure foundations as the basis for correct decision-making in the world. This is true, but reflects the gist of post-positivist understandings of science, in that we can never have certain knowledge. This is surely the human condition. Given this, it is surely better to acknowledge the limitations, and help learners to appreciate this. We will never be certain that climate change is primarily due to human activities: but the current consensus of scientists, deriving from rational debate considering the available evidence, is that this is likely to be the case and that action needs to be taken to avoid severe environmental damage. Given this (as one example), then an important aspect of scientific literacy should be having an understanding of why it is more rational to act on some uncertain ‘beliefs’ than others.

5.2.7.1

‘Just Say No’

Matthews (1994b: 158) recognises that the flavours of constructivism propounded by science educators are often of the type that von Glasersfeld calls trivial, but he nevertheless warns that ‘constructivist epistemology is fraught with grave … educational implications’ and that ‘constructivism leads directly to relativisms of all kinds’, Although constructivism began as a theory of learning, it has progressively expanded its dominion, becoming a theory of teaching, a theory of education, a theory of the origin of ideas, and a theory of both personal knowledge and scientific knowledge. … Constructivism has become education’s version of the “grand unified theory,” plus a bit more. (2002: 121)

Once again, the conflation of so much under the constructivist mantle, suggests that it is important to characterise and demarcate the nature of the (‘constructivist’) RP in Science Education so that it can be clear what is being claimed – and so which

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criticisms apply to the constructivist position inherent in the programme, and which are only relevant to some of the other variously labelled constructivist positions.

5.2.8

Scerri’s ‘Philosophical Confusion’

One of the harshest critics of constructivism in Science (particularly chemistry) Education is Eric Scerri, a philosopher of chemistry, who has in particular targeted the work of constructivist educators in the USA. Scerri has tended to restrict his writing to chemistry education, but like Matthews offers criticisms of the confusion of epistemological and pedagogic issues in constructivist writing. For example, Scerri takes issue with the accounts of constructivism reported in various articles in the Journal of Chemical Education. Scerri criticizes a ‘constructivist’ position that allows for several right answers to assessment questions, Unless the author is prepared to qualify the bland statement that ‘exam questions have one answer’, which he implies to be mistaken, I don’t believe he is expressing any position whatsoever. If the exam question is something along the lines of ‘what is the velocity of light?’ then even a radical constructivist would have to concede that there is indeed only one correct answer, unless one is referring to the possibility of quoting the velocity to varying degrees of accuracy. I am of course choosing my example rather deliberately since the velocity of light in any particular medium is completely invariant. In this instance there is absolutely no possibility of there being more than one response to the question of its velocity. (Scerri, 2003: 470)

This is a strong challenge. As Scerri points out, the scientific view that the velocity of light is invariant is well established and has passed many tests. The speed of light in vacuo may be 3 × 108 ms−1, or 2.998 × 108 ms−1, or even 186 miles per second, but from the scientific perspective it would simply be wrong to state it as 5 × 108 ms−1 or as fourteen furlongs per fortnight. Of course, the speed of light could be said to be relative to the medium – answers of 2.4 × 108 ms−1 or 1.8 × 108 ms−1 could well be correct depending upon what light was passing through. However, this is clearly not what Scerri intends. Most science teachers and scientists would be uncomfortable with constructivist science educators advising that there could be a number of correct answers to ‘what is the speed of light?’ because the speed of light was relative to a particular cultural tradition or historical epoch. Yet, despite this seeming to be the implication of Scerri’s criticism, it is difficult to identify any mainstream examples of such recommendations being made. Here Scerri (2003) criticizes Spencer (1999), who discusses constructivism in a paper in the Journal of Chemical Education reviewing new approaches in chemistry teaching. Spencer’s paper is meant as a general introductory discussion of educational approaches and as such offers a fairly superficial account of a number of complex issues and certainly lacks clarity in places. Scerri rightly criticized Spencer for describing the naive transfer model of teaching (§4.6) as having ‘its roots in what is called “behaviorism”, which is the belief that an idea can be transferred intact from the mind of the instructor to the mind of the student’ (Spencer, 1999: 567). As

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will be clear from Chapter 1 (§1.7.1), notions such as ‘ideas’ would be considered non-observables and therefore should not feature in any behaviourist description of teaching. Spencer also contrasted (what he labelled) ‘objectivist’ and ‘constructivist’ views of teaching and it was in this context that a constructivist view was contrasted with the statement that ‘exam questions have one correct answer’ (Spencer, 1999: 567). This seems to be the origin of Scerri’s comments that ‘to claim that … the majority of exam questions have more than one answer is, I believe, the height of folly’ (Scerri, 2003: 470). However, Spencer does not seem to be making such a claim. Rather he contrasts the statement that ‘exam questions have one correct answer’ with a constructivist view that ‘the ability to answer with only one answer does not demonstrate student understanding’ (Spencer, 1999: 567). This seems to mean that a constructivist would not be satisfied with a rote-learned answer, but will want to probe the understanding lying behind it. Spencer conflates constructivism with what he terms ‘the cognitive paradigm’, and passes over the whole matter without any deep exploration of the issues. Scerri is right to accuse Spencer of offering a confused account, and one does not have to be a constructivist teacher to suspect that correct answers may not always indicate full understanding. However, Scerri’s implications that constructivists do not consider that examination questions can have a single correct answer is not in any sense supported by a reading of Spencer’s paper, and seems to be a convenient ‘scarecrow argument’ to attack. Scerri has criticized constructivist science educators for adopting a position supported by relativism, which would be unacceptable to most scientists and science teachers, I cannot believe that any scientist would seriously contemplate relativism as a viable philosophical position regarding the nature of scientific knowledge, nor can I believe that science educators would be prepared to accept such a view. And yet this is precisely what the above-cited authors are recommending, in the belief that it represents a more enlightened and more modern philosophical position. (Scerri, 2003: 471)

Yet we have seen limited evidence of vulgar relativism in the writings of constructivists in Science Education, rather that ‘radical’ constructivists adopt a more pragmatic instrumentalist view. Laudan (1984) suggests that whilst it is often claimed that any retreat from realism would be an affront to practicing scientists, many would actually be perfectly content with an instrumentalist perspective, often being quite content to work with models and entities on just such a basis.

5.2.9

Equating Constructivism with Ignorance

In the previous section it was suggested that Scerri’s criticism that constructivists would admit alternatives to accepted science knowledge as ‘correct’ answers did not seem to be supported by any evidence that this was being recommended. It was

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argued that concerns about constructivism in Science Education being founded on (vulgar) relativist views were unfounded, although it was admitted that some proponents of constructivism did offer a confused philosophical basis for their recommendations. Cromer has gone further than Scerri in accusing science educators of being ignorant not just of philosophy, but of science as well. In an otherwise interesting book Cromer (1997: 11) suggested that ‘constructivist educators with no knowledge of science have increased their own power in science education relative to educators with scientific knowledge’. According to Cromer, In the United States, pre-high school science education, such as it is, is controlled by professional science educators, trained in schools of education which have been notorious for a hundred years for their low academic standards. Rare is the science educator who knows even the science expected of an eighth grader. It’s this group which has enthusiastically endorsed constructivism because it allows them to speak only about process (whatever that is) rather than content (of which they are ignorant). And it’s this group that writes the frameworks, standards, and textbooks for elementary and middle schools. (Cromer, 1997: 11)

Although the US school science curriculum is guided by the National Science Foundation and the American Association for the Advancement of Science, Cromer, who was a Professor of Physics in a US University, considered that the National Science Education Standards reflected constructivist ‘jargon’ (Cromer, 1997: 10). The notion of constructivist science teaching that Cromer criticizes would appear to be based on a naive discovery learning approach, that is considered below (§5.5.4). The position that Cromer attacks is that such an approach is meant to base science teaching upon the ideas children construct from their own investigations, and so as teachers (if following such an approach) should not import the formal notions of science, then they do not actually need to know the accepted models of science themselves. A similar position was also labelled ‘constructivist’ by Bowers (see §5.1) when considering the dominant perspective in Western education in general (Bowers, 2007).

5.2.10

Teaching Science As a Consensual Body of Knowledge

Yet, of course, such an argument would seem to be non-viable in any formal educational context that employed an official curriculum, including in the USA where there are established ‘standards’ for science teaching (National Research Council, 1996). Indeed, such a position is in some ways the very opposite of what most constructivists would argue, as will be explained below. Such an extreme, and readily dismissed, critique is unfortunate as it deflects attention from the very real issue that was explored by Robin Millar (1989a), that of the need to reconcile (a) taking learners’ ideas seriously with (b) science as a body of consensually agreed knowledge.

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The type of approach criticized by Cromer would appear to be of the form ‘the processes of science are all that matter, and so as long as students come to conclusions that have been derived by due process (the ‘scientific method’) then it is not important what those conclusions are’. Yet when Driver and Oldham (1986) discussed a constructivist model of curriculum development they identified ‘four main types of input’ – subject content; knowledge of learners’ ideas; a model of the learning process; practical knowledge about classrooms, motivating and organising groups of learners, etc. Of these, ‘the first and most conventional one is the decision on “content” [where] we can specify those experiences which students should be exposed to and we can suggest what ideas they may construct from these experiences’ (p. 112). They referred to ‘national policy statements’ which highlighted the intended outcomes of secondary school science teaching as ‘including the development in pupils of practical skills, processes of thinking, knowledge of scientific concepts as well as the development of more general attitudes to knowledge and the environment’ (p. 109, present author’s emphasis). Even Glasersfeld, a popular target of criticisms of constructivist thought in education (§5.2.8), seems to clearly recognise that teachers are guiding knowledge construction in the direction of set target knowledge. He argued that ‘two things are required for the teacher to [guide the student in the conceptual organization of certain areas of experience]: on the one hand, an adequate idea of where the student is and, on the other, an adequate idea of the destination’ (Glasersfeld, 1983: 67). So, according to a key researcher within the RP (Driver) and a key theorist much cited within the RP (Glasersfeld), learning in constructivist science classes has a predetermined destination. Learners’ ideas are afforded a considerable status by constructivists, but that status is related to the perceived educational significance of those ideas, because of their potential value in informing pedagogy, rather than because they are in some sense considered to offer valid alternatives. It is certainly true that many alternative conceptions may be of value in a social context, or even as useful heuristics in practical contexts, but within the context of the science classroom there is inevitably a curriculum that sets out ‘target knowledge’. So, for example, where some critics (Matthews, Cromer, Bowers) associate constructivism with open-ended learning, Leach and Scott argue from a sociocultural position that constructivist approaches are needed because what needs to be learnt is not open to ready individual discovery, Scientific knowledge is not there to be seen in the material world. Rather, it exists in the language, practices and semiotic systems used within specific communities to account for aspects of the material world. Learners will not stumble upon the formalisms, theories and practices that form the content of science curricula without being introduced to them through teaching. (Leach & Scott, 2002: 121)

The everyday experience of science teachers is that their students are assessed (and so their own teaching judged) in terms of convincing assessors and examiners that students have learnt and understand the versions of scientific knowledge represented in the curriculum. The hard core of the constructivist RP encompasses the premises that the learner’s existing ideas have consequences for the learning of science and that

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it is possible to teach science more effectively if account is taken of the learner’s existing ideas (§4.4) – principles that are ground in an assumption that Science Education involves helping learners to acquire knowledge that as far as possible matches target knowledge. As reported above (§4.3.4), Mintzes & Chiu (2004: 111–112) define the hard-core assumptions of constructivism in education as including ‘that the principal goal of science, mathematics and education therein is the construction of shared meanings … facilitated by the active intervention of well-prepared teachers’. Of course, constructivists may well argue that: • The professional models of science may not be suitable for learners, so the target knowledge prescribed for different groups of students should be various simplifications of scientific knowledge. • Given a learners’ current understanding, a viable learning goal might be some transitional model that bridges between a learner’s current idea and the prescribed target. • No individual student will ever attain a scientific understanding that is a replica of the formal scientific model (indeed using Popper’s ‘3 World’ model would suggest that such an identity is meaningless rather than unobtainable). But none of this should confuse the general view that a large part of Science Education is about deliberately shifting students’ thinking towards an understanding of the prescribed curricular models that are themselves designed to be approximate representations of accepted scientific theories and models. Science educators do aim to teach process skills, and develop student’s general cognitive skills, and allow students to engage in debate about socio-scientific issues to which there are no scientifically right answers (should we build more nuclear power stations; should there be more genetic testing of unborn babies?): but they also want students to appreciate and understand Newtonian mechanics; Darwinian evolution; the particulate nature of matter; and the general arrangement of bodies in the solar system – as accepted in science as a consensual body of knowledge. That is certainly not to suggest that prescribed scientific content should be taught as some form of catechism. Just as important as teaching subject matter, science educators want learners to appreciate the difference between scientific laws, theories, models and hypotheses, and to understand why although nothing in science is known absolutely, the ways science relates ideas to evidence lead to ‘reliable knowledge’ (Ziman, 1978/1991). Furthermore, the prescribed science is the set of representations or models of science in the curriculum, which are intended to reflect the models of science itself (Gilbert et al., 1982). These curriculum models may, or may not, be considered to be authentic reflections of ‘professional’ science (Taber, 2003c; Kind & Taber, 2005), but nonetheless provide a very definite ‘target knowledge’. So for example, it is open to debate whether presenting a notion of temperature as being a measure of the concentration of heat energy is appropriate when introducing thermal physics. Commentators may well agree that this notion distorts the current consensus scientific concept, yet disagree on whether it is an appropriate teaching model.

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So such an idea has been proposed as a useful simplification that can be used to help learners appreciate some of the difference between heat and temperature (Carlton, 2000), and criticized as an over-simplification that can lead to learning difficulties (Taber, 2000b). Similar debates can occur in all areas of the science curriculum, but this perfectly proper argumentation does not prevent curriculum authorities setting out curriculum models as the current target knowledge for the students in their jurisdiction. In the research undertaken within the RP, the focus on learners’ ideas is usually concerned with informing teaching that moves learners towards the target knowledge. So Russell and Osborne (1993) refer to exploring learners’ ideas in the SPACE project (see §4.2.1) in the context of ‘eliciting children’s ideas prior to helping children to develop their thinking in the direction of conventional scientific understanding’. Driver and Oldham report that in their model of constructivist teaching the scientific models may well be suggested by students during the elicitation of learners’ ideas: but regardless of whether this happens, the target knowledge will be deliberately and explicitly introduced by the teacher, Some pupils may have constructed the scientific view from prior experiences; hence it may have been presented and tested along with a range of alternative conceptions. Whether or not this has happened, the teacher will present and explain it at some point, providing opportunities for pupils to construct meanings for it by empirical tests, and language activities. This input of the scientific view and the chance for pupils to begin to make sense of it takes place at various points (Driver & Oldham, 1986: 188)

Leach and Scott’s (2002) notion of ‘learning demand’ (see Chapter 6, §6.3.3) is explicitly about identifying the difference between a learners’ current thinking and the target knowledge as part of the process of moving learners’ thinking on towards that target. A constructivist does not need to be an instrumentalist to see the value of such a strategy. A science teacher who is a naive realist, and who sees the established models of science as corresponding directly to the nature of reality, has just as much reason to be concerned with identifying learning demands as a radical constructivist. The realist might wish to convince learners because the scientific models are true; the instrumentalist because they are useful, but a vulgar relativist would surely have little concern with the whole business of trying to teach anybody anything? Matthews would surely agree with this point, showing that the types of ‘constructivism’ he is primarily attacking has little in common with the ‘constructivist’ RP which seeks to find ways to better support students’ learning of accepted scientific ideas. We may therefore separate from radical models of constructivism a form of constructivism that Glasersfeld see as trivial, but which Phillips (1997) refers to as psychological, and Grandy (1998) as cognitive. Matthews (1994a: 167) himself refers to ‘soft’ constructivism, explaining that what is labelled as constructivist teaching is often ‘good, innovative, or engaging teaching, where children are respected and their ideas are given some attention or credence, and where teachers do not dominate classrooms’. However, a truly constructivist approach to teaching has to do more than just give children’s ideas ‘attention or credence’, but rather to see them as starting points and resources to be developed towards target knowledge.

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Cognitive constructivism tells us that learning is a process of building new conceptual understandings – a process which is restricted by the limitations of human cognitive apparatus, and biased by existing cognitive structure providing the interpretive frameworks for making sense of what we are told and shown. That is, cognitive constructivism offers insights into some of the key contingencies that constrain and channel student learning. This makes the process of facilitating learning that ‘matches’ (if we believe that possible) or ‘reflects’ target knowledge – or even just ‘fits with target knowledge in terms of enabling desired behaviour in assessment contexts’ – very challenging for teachers regardless of how we view the target knowledge in relation to scientific knowledge, or what status we assign to scientific knowledge itself. Grandy (1998: 133) suggested that it is possible to ‘distinguish the claims of cognitive constructivism from those of metaphysical constructivism, which is almost entirely irrelevant to science education’. This key distinction is reflected in Table 5.3. Even Scerri seems to accept that cognitive constructivism, i.e. the constructivism inherent in the hard core of the RP, is not objectionable. He argues that it is important to make the distinction between ‘the radical claims’ of those who oppose ‘the traditional belief that scientific knowledge results from investigating the way the world actually is’ from the ‘more modest’ claims of most constructivists working in education that ‘students develop their understanding of science in a constructivist manner because of any preconceptions and misconceptions which they might bring to chemistry classes’ (2003: 471). Scerri acknowledges that such views about learning can be held without thinking that ‘scientific knowledge itself is arrived at by a process of social negotiation’. Scerri goes on to argue that ‘as I see it, the majority of educators are understandably attracted to educational constructivism, but overstate their case by drawing support from the more extreme and often anti-scientific writings of constructivists’ (p. 472). There would certainly seem to be some philosophical confusion in writing about constructivism in Science Education, as Scerri has suggested. This raises the question

Table 5.3 Foci of two main forms of constructivism Flavour of constructivism Philosophical constructivism Also known as

Radical, metaphysical, hard

Ontological focus

Nature of reality

Epistemological focus

How we come to knowledge of the world/nature and limits of our knowledge of the world Drawn upon by influential writers, but not tied to the hard core of the programme

Relationship to constructivist RP (cf. §4.4) in Science Education

Cognitive constructivism Trivial, psychological, pedagogic, soft, educational Nature of cognitive structures/ conceptual (mental) representation How learners can be helped to understand target knowledge set out in the science curriculum Sets out the basic concerns of the RP – informs hard-core commitments and positive heuristic

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of whether it is possible for such a range of fundamentally different viewpoints to be reflected within a single coherent RP. Although such positions are important and clearly colour researchers’ work, they need not be an obstacle to identifying a coherent RP. The RP outlined in Chapter 4 is about learning and teaching science, and so all those considered to be working in the RP must accept the hard-core commitments of the RP: which relate to how learning occurs; how existing ideas influence learning; how best to understand and represent learners conceptions; and how to best teach school and college science. None of this is reliant on a relativist view of science, or any other specific philosophical position. So as Grandy, Matthews and Scerri suggest it is possible for science educators to commit to the hard core of the RP despite it being associated with the constructivist tag, without regard to their epistemological commitments in relation to science and scientific knowledge.

5.3

The Status of Theory in the RP

Another criticism of constructivist research in Science Education has been that it tends to be atheoretical, and largely descriptive (Furnham, 1992). It has also been argued that the constructs that are used to characterise learners’ ideas (such as ‘intuitive theories’ or ‘conceptual frameworks’) are invalid or at least ill-defined (Matthews, 2002).

5.3.1

Natural History and Science in the RP

Driver and Erickson (1983: 55) recognised from the outset that there was what they described as ‘a danger in a proliferation of “natural history” studies of student ideas … being documented in the absence of any systematic rationale’. Similarly, a decade later, Russell and Osborne (1993: 15) were arguing that ‘theory building at this level would seem to be necessary to take constructivism in science education forwards so that it has greater explanatory and predictive value’. Adrian Furnham, in a 1992 review on informal learning in science, acknowledged ‘extremely important theoretical and applied reasons why the acquisition of scientific knowledge’ warranted attention, and recognised that over 20 years there had been ‘a plethora of small-scale studies of various sorts’ (p. 61). Furnham observed that at that time it was ‘difficult to determine the epistemic, or indeed, practical yield of this research effort’, and suggested three reasons for this: the atheoretical nature of much research; the limitations of specific methodology (see Chapter 7); and that ‘many researchers seem either unwilling or unable to move out of the disciplinary boundaries they feel constrained to inhabit to examine research and methodology in other areas’. Furnham argues that first and foremost, research is rarely guided by (psychological or educational) theory; hence the findings are not integrated into a corpus of knowledge and remain piecemeal.…

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many studies are strikingly interesting, but atheoretical, one-off studies by committed but often amateurish researchers. The result is a plethora of research findings and a paucity of integrative theory…unless in-depth interview or simulation studies are driven by theory, their rich findings fall on stony ground. (Furnham, 1992: 61)

Such concerns have therefore been voiced both by those centrally concerned in the research area, and others less directly involved. The attempt to conceptualise this area of research as a SRP by identifying the hard core and heuristics (§4.4) shows both that such concerns, whilst important, should not be overstated, and offers guidance to those entering the field – e.g. graduate students who may contribute a single ‘one-off’ study – so that their work will not be seen as atheoretical, but can contribute to the cumulative development of the field by being located in a RP.

5.3.2

Validity of Theoretical Constructs

Two distinct criticisms have been made of the use of theoretical terms in constructivist writing in Science Education. One, made by Matthews (2002), is that the apparently theoretical terms used in constructivist writing often amount to little more than jargon that restrict communication rather than enhance meaning. It is also argued that where researchers did offer theoretical accounts of the phenomena they were studying, (a) the terminology and accounts given varied between researchers; and (b) these accounts were contradicted by available empirical evidence. In particular, accounts of student conceptual frameworks and intuitive theories have been criticized for offering a much more principled account of student thinking that is justified by the evidence.

5.3.3

Needless Constructivist Jargon

Matthews (2002: 130) has described how constructivist writing has ‘introduced some new words and meanings, it has borrowed terminology from progressive education traditions, and it has appropriated concepts from postmodernist sources’. Matthews claims however that ‘whereas natural science uses theoretical terms to simplify complex matters, social science, at least in the [examples cited by Matthews], is using theoretical terms to make simple matters more complex’ (p. 131). Matthews offers a lexicon of constructivist terms (he includes, inter alia, conceptual ecology, accommodation, community of discourse, personal construction of meaning, mediational tools, conversational artifacts) and some translations from what he calls ‘constructivist new speak’ to ‘orthodox old speak’. While it is certainly possible that in particular contexts the (constructivist new speak) terms ‘mediational tools’ and ‘conversational artifacts’ may well refer to ‘graphs’ and ‘diagrams’ respectively (as Matthews translates), it is clear that the terms mean something other than graphs and diagrams per se. Similarly a ‘community of discourse’ in science teaching may well be a ‘group’; but conceptualising

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a teaching group as a community of practice is a deliberate act that provides information about the teacher’s intentions towards, and understanding of, the dynamics of groups in learning contexts. Matthews translates ‘accommodation’ (in constructivist new speak) as ‘theory change’ (in orthodox old speak). However, in its original Piagetian meaning, accommodation concerns part of a process (of assimilation-disequilibration-accommodation), that is tied to a particular model of conceptual change, that is not reflected in ‘theory change’. In the same paper as Matthews criticizes constructivists for describing learners’ beliefs as ‘knowledge’ (something Matthews reserves for true, justified, beliefs), he is content to describe the organisation of those beliefs within a learner’s mind as ‘theory’. That learners’ conceptual ‘beliefs’ may be described as ‘theories’, but not as ‘knowledge’, could be considered somewhat arbitrary. As a final example, Matthews’ translates ‘conceptual ecology’ (a notion arising from the philosopher Toulmin) as ‘ideas’. The notion of conceptual ecology is intended to describe the complex set of considerations internal to a learner’s mind which can influence the way new information is received (see Chapter 6, §6.2.2.24). This includes such matters as epistemological commitments and metacognitive understanding as well as existing knowledge (beliefs). In the same paper Matthews points out that ‘teaching a body of knowledge involves not just teaching the concepts, but also the method, and something of the methodology or theory of method’ (p. 129), and the use of the ‘conceptual ecology’ notion is meant to acknowledge the importance of such issues for learning science. Matthews also argues in this paper that science teachers ‘make use of metaphors’, and it has been argued that when discussing the complexities of student learning in science, that ‘the notion of a conceptual ecology is metaphorical, but fertile’ (Taber, 2001c: 750). To reduce the concept of a conceptual ecology to being the learners’ ideas is a gloss that loses much of the meaning intended by the term. Matthews is a well-respected and influential scholar in the field of Science Education, and no doubt appreciates the nuances that can be given to some of the terms he dismisses as jargon. That he should feel such strong criticisms are justified, despite the potential value of some of the notions described by the labels he seems to dismiss, is perhaps explained by the lack of consistency in the application of some of these terms. That is, in my view, terms such as ‘conceptual ecology’ and ‘community of discourse’ represent useful notions with particular connotations, but can also be adopted casually by those who have not taken onboard the wider theoretical framework in which these concepts can do useful work within the RP. So in principle I would disagree with Matthew’s argument here, although in practice his criticisms may sometimes be well judged, in view of the general lack of consistent use of terms in the literature.

5.3.4

Confused Terminology

Considering just the literature relating to physics learning, diSessa has commented on how ‘there is no agreement on terms of description. … Intuitive physics is

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described as a theory, a systematic but alternative framework, or a series of isolated misconceptions’ (diSessa, 1993: 119). The criticisms that different research groups or individual researchers used a range of different terms to label the phenomena being studied, without necessarily linking their preferred terminology with that of other researchers, is a fair reflection of the literature (Abimbola, 1988; Black & Lucas, 1993). Driver and Easley’s seminal (1978) paper suggested the term ‘alternative frameworks’ (p. 62). The use of the term ‘frameworks’ by different researchers has been inconsistent and sometimes unclear, and attempts to clarify it have not been successful (Black & Lucas, 1993: xii), so, for example, the term ‘conception’ has often been used synonymously with ‘framework’ (Watts & Gilbert, 1983: 161; Hewson, 1985: 154). The term ‘misconception’ is often avoided in scholarly writing, but as recently as 2004 Reddish (2004: 24) has argued that ‘the term misconception be reserved to mean a knowledge structure that is activated in a wide variety of contexts, is stable and resistant to change, and is in disagreement with accepted scientific knowledge’. Such lack of consistency and coherence between researchers is more than an irritation, The literature reported on children’s ideas, their alternative paradigms, mini-theories, conceptions, misconceptions, etc. The variety in terminology reflects ambiguity and some confusion over the status of what one observed. This, of course, also has implications on how to act on such observations. If you face a “misconception”, you can simply try to correct the misunderstanding. If, on the other hand, the child’s explanation has the character of being a paradigm, an alternative way of seeing the world, well integrated with other strongly held beliefs, then the educational task is indeed very different! (Sjøberg, forthcoming: 7)

Phillips (1987: 139) has criticized writing which does not clearly distinguish between the structure of an academic discipline, cognitive structures inferred in learners’ minds, and researchers’ representations of aspects of learners’ thinking. Lakoff and Johnson (1980b: 206) describe this difference between the ‘structures through which we categorize personal experiences and external occurrences’ and representations ‘which we … construct as models’ of these structures as a ‘most important distinction’. As reported in Chapter 1 (§1.8.4), in his discussion of mental models, Norman (1983) suggested keeping clearly distinguished a ‘target system’; the conceptual model constructed of that; the mental model (within an individual’s mind); and any representation of the mental model. Errors of confusing what needs to be kept distinct undermine scholarly writing, and indeed a number of the early papers in the field demonstrated explicit care to be clear on this point. Gilbert and Watts (1983: 64–65) highlighted the need to distinguish between ‘an individual’s psychological, personal, knowledge structure’ and aspects of ‘the organisation of public knowledge systems’; that is in terms of Popper’s ‘3 Worlds’ model (see §2.2.2) between entities in Worlds 2 and 3. Ault, Novak and Gowin (1984) are careful to distinguish cognitive structure itself from the representation that is a product of their analysis. They use research data to infer a ‘conceptual structure’ that is ‘a best approximation of cognitive structure, the “true object” of interest’ (p. 446). Glasersfeld has commented that Understanding what other speakers mean by what they have said, therefore, cannot possibly be explained by the assumption that we have managed to replicate in our heads the

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identical conceptual structures they intended to ‘express’. At best we may come to the conclusion that our interpretation of their words and sentences seems compatible with the model of their thinking and acting that we have built up in the course of our interactions with them. (Glasersfeld, 1988: p. 6)

However, the different ways that the same terms are used as labels for different entities by different authors may well lead to readers conflating quite different things when they are given the same labels. This is not an argument that technical terms are not useful in research into student learning (cf. §5.3.3), but rather that confused, ambiguous and contended terminology is counterproductive. For example, Fig. 5.1 shows the relationship between three of the types of entities commonly discussed in the research literature: The two independent distinctions in Fig. 5.1 are (a) between features of learners’ minds and the representations researchers’ construct of them, and (b) between the focus on individual learners and on the ‘typical’ features found among groups of learners. The arrows are meant to imply a necessary temporal relationship. The models that researchers build to represent features of learners’ mental structures pre-assume the existence of those structures, and the identification of common features presupposes some existing models based on interpretations of individual cases. It could be argued that survey approaches can ‘short’ this connection, but valid survey items needs to be based on features that have previously been identified in data from individuals (Taber, 2007a, cf. Treagust, 1988). It should be noted that one of the cells in Fig. 5.1 is marked with a question mark. A personal constructivist approach assumes that cognition occurs in individual minds, each of which represents knowledge in some sense. The collective dimension in the figure therefore refers to an aggregation process or highlighting of common

individual learner

learners as a group

Fig. 5.1 Possible meanings for ‘alternative frameworks’

world 2

world 3

individual conceptual structures

expressed model of researcher’s inferences

?

expressed model of common features of researcher’s inferences

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themes and similarities in models based on individual cognition, and from such a perspective the cell marked ‘?’ is ‘empty’. However constructionists would argue that cognition and knowledge exist on an interpersonal plane (see §5.4), and would therefore populate this cell (rather than the cell shown above it). Any models that constructionist researchers might build of group cognition and knowing cannot be seen as automatically equivalent to the collective models built from a personal constructivist approach. This is signified by the arrow which has been shown as ‘crossed out’ in the figure. For present purposes it is important to note that the three labelled cells in Fig. 5.1 are all of interest to the RP that is discussed in this book, being linked to key aspects of the positive heuristic (§4.4): • How is knowledge represented in the brain? • What are the most appropriate models and representations [of learners’ conceptual structures]? • How much commonality is there between learners’ ideas in science?

5.3.4.1

Ontological Status of Alternative Frameworks

One of the most common terms used in the RP when discussing learners’ ideas is that of ‘alternative frameworks’, but this term has been given to (at least) two quite distinct sets of things – that should be designated separately. Both Driver and Erickson, and Gilbert and Watts, publishing in the same volume of Studies in Science Education, recognised the problem. Driver and Erickson (1983: 46) referred to how ‘the manner in which the frameworks are articulated vary considerably’, and Gilbert and Watts (1983: 69) acknowledged that ‘[t]he use of the phrase “alternative frameworks” as a descriptor … is limited because there is little consensus in current literature to help explicate a common usage’. Similarly, Driver and Erickson acknowledged how ‘this diversity results in some confusion, especially when an attempt is made to compare the findings across one or more students. The confusion stems in part from the unit of analysis adopted by researchers to define student frameworks’ (p. 46). According to Driver and Erickson (1983: 39), the term alternative frameworks is used to label ‘the mental organisation imposed by an individual on sensory inputs’, whereas according to Gilbert and Watts (1983: 69), the term alternative frameworks is applied to ‘thematic interpretations of data, stylised, mild caricatures of the responses’ students make when asked about science topics. It is not that one of these terms is correct, but rather that different research groups decided to use the label in different ways. Using Fig. 5.1 as a guide, it seems that we need to distinguish alternative frameworks as features of a learners’ cognitive structure (alternative frameworks1); alternative frameworks as the researchers’ models of those features inferred from behavioural data such as responses to interview questions (alternative frameworks2); and alternative frameworks as researcher’s models of the common features of the models constructed of individual thinking (alternative frameworks3).

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Clearly, researchers in the RP are concerned with aspects of learners’ thinking, and engaged in building models both of individuals’ cognitive structures and of common features found across learners. The positive heuristic set out for the RP asks both ‘how is knowledge represented in the brain [as a conceptual structure]?’, and ‘what are the most appropriate models and representations [of learners’ conceptual structures]?’ The signified of all three types of alternative frameworks are therefore a proper part of the concern of the RP, but are ontologically quite distinct – so should be clearly discriminated. Yet it is clear that the use of ‘alternative framework’ in the literature encompasses these quite distinct meanings. Similar issues could be raised about the use and relationship of a range of other terms such as intuitive theories, alternative conceptions, and mental models. Rather than discuss these problems here, the view is taken that these are matters to be argued about from within the RP programme itself, and the discussion here informs the sketch of the progress in the RP in Chapter 6 (see §6.1.4). 5.3.4.2

Significance of the Criticism

This criticism of unclear terminology and research constructs has some relevance to the general argument of this book. In a progressive RP, as envisaged by Lakatos in the natural sciences, it could be agued that we should expect those researchers working in the field to share a basic vocabulary. Certainly, in an ideal case, the initial setting out of the RP might be expected to establish terminology and certain basic ontological commitments (to the kind of entities being investigated) that might form part of what in Kuhn’s model (§3.2.4) would be ‘the disciplinary matrix’ (of a scientific paradigm). This certainly was not the case here. This can be understood in part in terms of the complexity of the phenomena being studied, which were only open to indirect elicitation, and in part to the diverse backgrounds of the researchers who came to work in this area. The RP was not developed entirely from dissatisfaction with a previous shared programme. Although some workers came to the constructivist approach from a more mainstream Piagetian programme, others were influenced more by Kelly’s work (with its emphasis on the individual’s construing) or from work looking at misconceptions and learning difficulties from the perspective of instructional design (i.e. the work of Gagné, etc.). It is here considered that this confusion was certainly unfortunate but probably to be expected in a RP in the social sciences. (In the Afterword to the book I argue that even if a reader is not convinced that the evolution of constructivist research in Science Education matches what would be expected in Lakatos’s model of SRP, that does not necessarily negate the heuristic value of researchers now choosing to conceptualise this research area in those terms.) 5.3.4.3

Alternative to What?

The terms ‘alternative frameworks’ and ‘alternative conceptions’ both imply that these entities are ‘alternative’ to something else. That something else is the target knowledge set out in the curriculum. That is, a learner may have a conceptual

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framework for chemical bonding that is alternative to that in the curriculum, or a conception of energy at odds with the scientific conception. In suggesting the term ‘alternative framework’ Driver and Easley (1978) were intending to signify something more than ‘just’ a misconception or a preconception, and thus to elevate the status of students’ ideas. I was therefore interested that one of the reviewers of a draft of the manuscript for this book commented on how the term could appear arrogant. I take this to mean that as such ideas are alternatives (to scientific or curriculum-endorsed notions), they are seen as of less importance. This view offers an interesting balance to that of critics discussed above who argue that elevating learners’ ideas to be alternatives to officially sanctioned knowledge could be taken to imply they are just as important, and reflects a relativist position. The term ‘alternative’ could be read as one of the available or possible alternatives, but the anonymous reviewer is right to point out that to label something ‘alternative’ carries with it the implication of being alternative to something else, something specific that would be more normal, more appropriate, or simply more commonly anticipated. In the context of the RP, students’ alternative frameworks or conceptions are indeed judged alternative when compared to the normative standard of the curriculum. However, it is worth reiterating here that target knowledge itself should not be seen as an absolute standard. School science is the outcome of a political process, i.e. under the influence of various power groups with different interests (Kind & Taber, 2005), designed to represent a subset of what is considered currently accepted scientific knowledge (itself open to revision) in a suitable form for particular groups of learners. Moreover, as will be discussed in Chapter 6, students do not necessarily hold a single alternative conception or framework, but may well exhibit manifold conceptions or multiple frameworks, with various degrees of overlap with, or match to, target knowledge.

5.3.5

Empirical Support for Theoretical Constructs

A second criticism here is potentially much more serious. This is that although research claims students have conceptual frameworks and intuitive theories and the like which have been characterised in such terms as tenacious, theory-like, extensive and so forth, the empirical evidence does not support this (Solomon, 1992; Claxton, 1993; Kuiper, 1994). Kuiper (1994) claimed that specific alternative frameworks reported in the literature could not be replicated. Claxton (1993) argued that learners’ ideas were actually labile, highly context-dependent and largely take the form of isolated notions. Solomon (1992) pointed out how children’s notions changed over time as well as being multifaceted and dependent upon context (p. 28), and how children seemed to quite readily move between applying different ideas to the same context, even within a single interview (p. 24). If this line of criticism is valid, then much of the rationale for the RP is undermined, so this needs to be addressed here. If learners’ ideas shift readily then they are of

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much less significance to teaching, and an extensive programme to catalogue and characterise them seems less of a priority. The literature (Duit, 2007) is equivocal on this point, with different researchers, using a variety of methods, to explore the thinking of different groups of learners in different topic areas reporting very different kinds of findings. Some of the criticism here relates to the issue discussed above of the lack of consistency in the use of terminology. So Kuiper’s (1994) failure to replicate alternative conceptual frameworks for force reported by Watts (1983) can largely be explained in terms of a misreading of the nature of Watts’ findings. Watts reported what would be labelled – in the terminology introduced in the previous section – alternative frameworks3 (alternative frameworks as researcher’s models of the common features of the models constructed of individual thinking), but in his ‘replication’ study Kuiper failed to find evidence of alternative frameworks1 (i.e. precisely the same patterns in features of different learners’ cognitive structure) among his sample that matched Watts’ alternative frameworks3 (Taber, 2007a). But, of course, there is no reason to expect that (individual) alternative frameworks2 (that is Kuiper’s own constructions representing students’ alternative frameworks1) will directly replicate (generalised) alternative frameworks3. To simplify terminology later in the book it is proposed to refer to alternative frameworks as personal (i.e. alternative frameworks1) or generalised (i.e. alternative frameworks3). There are important methodological issues here. Assumptions about the nature of the phenomena being studied (ontological commitments) necessarily frame the types of research questions asked; and so views about the kind of knowledge sought (epistemological commitments); and so the methodology that will help answer research questions (Taber, 2007a). For example, survey type approaches may readily assess how commonly a particular conception reflects a specific aspect of student thinking, but are not suitable for identifying the nuances of individual student thinking. This is an issue that will be revisited in Chapter 7, where potentially fertile directions for further research are considered. However, it is not possible to dismiss all the examples of studies that come to contrary views about the nature of learners’ ideas as reflecting artifacts of the methodologies chosen for different studies. The view taken here is that the lively debate about the nature of learners’ ideas – their stability, coherence, range of application and so forth – should not be seen as a criticism of the RP, but rather as part of the valid and appropriate debate within the programme itself, directed by the positive heuristic. These debates will therefore be taken up in see Chapter 6 which considers how much progress has been made in the RP.

5.4

The Social Constructivist Perspective

One area of criticism that has been addressed to the ‘constructivist’ research in Science Education relates to the social aspects of human learning (Solomon, 1987). The basis of the RP characterised in this book (see Chapter 4) may be seen

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to develop from a position of ‘personal constructivism’ informed by the work of Piaget, largely focused on the ‘epistemic subject’ (§1.6.1), and Kelly’s personal construct psychology (§1.6.3). Personal constructivism has a focus on the individual learner, who is actively engaged in learning by acting on, and building up models of, his/her environment. Such a stance may seem to underplay the social elements that are commonly present in learning, especially in school learning. There are a range of different perspectives that may introduce a social element, from the simple acknowledgement that in a school setting learning is a process facilitated by others, to seeing learning as taking place within some form of community context, to understandings of knowledge that inherently locate learning on a ‘social plane’ rather than a ‘personal plane’. It will be suggested here that: 1. Some of the early writing within the RP acknowledged the social dimension, although this was not addressed in any great depth. 2. Some of the social perspectives on learning that are commonly discussed in the literature have increasingly influenced work within the RP, and inform perfectly acceptable debate within the programme. 3. Some of the more extreme notions of social constructionism would be more difficult to fit within the RP. In other words, we need to distinguish carefully between different kinds of claims for a social basis to learning, as • Some forms of social constructivism may be seen as offering suitable ‘refutable variants’ of the RP, and in these cases the positive heuristic of the programme would guide researchers to explore these perspectives. • Other notions of the social nature of human learning would indeed seem inconsistent with the hard core the RP, and the negative heuristic of the programme would guide researchers (within the RP) away from considering these perspectives as offering potentially fertile approaches to develop their research.

5.4.1

Criticisms of the RP

Coll and Taylor (2001: 219) wrote that ‘constructivism has been criticized as portraying the individual as sealed in a privately constructed world in which the social component of learning is largely ignored’. Solomon, for one, has criticized much of the work undertaken in the constructivist tradition as positing the learner as an isolated individual constructing personal knowledge in a social vacuum, without consideration of the very real influence of others on the learning process (Solomon, 1987, 1993b). She argued that, Some of the literature about pupils’ construction of meaning has tended to ignore the social influences upon them, almost as though each child were struggling in an isolated morass of mental effort. Recent research is showing that the social scene makes an essential difference to the learning situation, to how the task is perceived, and even to the tools for thought that will be used (Solomon, 1987: 63)

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Solomon has argued that Driver’s Kellyan notion of the ‘pupil as scientist’ is untenable: and she proposes ‘three troublesome questions” (1993b: 85–6) that need to be asked of the personal construction of knowledge position: 1. If children’s notions have been assembled in such a logical, almost scientific way, why do school children then have such difficulty in understanding the logical method of science and resist changing their notions in the light of new and compelling evidence? 2. If they have tested their ideas in the different circumstances of daily life why is it that they apply them so inconsistently? 3. If every child is his or her own independent scientist, how is it that within a cultural group notions are so much more similar than they are across different cultures? Solomon felt that Driver’s notion of the ‘pupil as scientist’ (Driver, 1983) was seriously flawed, and suggested that the widespread adoption of a methodological approach based on eliciting ideas from individuals underplayed the social element that was an important part of the context of school learning, The guiding plan for research in this [ethnographic] tradition is to ask children to explain their ideas and then to listen carefully to their words in the Verstehen tradition. It aims to be entirely value-free, as an anthropologist might try to be while examining the culture of an alien tribe. … Such an inquiry, however, does not easily survive a more theory-driven aim where either cognitive structure or school learning is the mainspring of the work … Despite the anthropological influence it has been extremely rare for natural groups of children to be interviewed, or for them to be recorded talking together. (Solomon, 1993a: 1–2)

Solomon drew upon ideas of the ‘life-world’ to draw distinctions between children’s typical ways of knowing based upon their social interactions from the formal nature of scientific knowledge. (This work will be considered in Chapter 6, §6.1.4.6). Solomon was not denying the notion of learning as the construction of knowledge, but emphasising the role of social processes in learning: for Solomon (1994: 15), the solitary experiences of the knowing individual ‘will not do to describe either everyday knowledge, or scientific knowledge, or the learning of school science’. This is sometimes considered to be a ‘social’ constructivist perspective, as opposed to the ‘personal’ constructivist perspective, and draws heavily on the research areas initiated by Vygotsky and his colleagues (see §1.6.2).

5.4.2

Different Flavours of Social Constructivism

In a review on the themes of individual and social learning, Salomon and Perkins (1998: 2) point out that ‘the “cognitive, acquisition-oriented” conception of individual learning’ and ‘the “situative, participatory” conception’ of social learning are sometimes discussed as if opposing interpretations of learning, but that they might more usefully be considered ‘as two levels of analysis, each of which sometimes neglects the other’. They suggest individual and social learning relate to each other in three ways (pp. 17–18):

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• Relation 1: Individual learning can be less or more socially mediated learning. • Relation 2: Individuals can participate in the learning of a collective, sometimes with what is learned distributed throughout the collective more than in the mind of any one individual. • Relation 3: Individual and social aspects of learning in both senses (Relations 1 and 2) can interact over time to strengthen one another in what might be called a ‘reciprocal spiral relationship’. Work strongly influenced by Vygostsky (§1.6.2) and his tradition is sometimes described as ‘social constructivist’, or ‘social constructionist’ (Schwandt, 2001), to contrast with the ‘personal constructivist’ focus deriving from the perspectives of Piaget and Kelly. However, there are different flavours and degrees of social constructivism. As Larochelle, Bednarz and Garrison (1998: vii) point out, constructivism ‘is an umbrella term covering theorizations which are primarily centred on either the cognitive subject; the situated subject (or social actor); or the locus of knowledge, which … has now become the group’. In particular, here I wish to distinguish one common use of social constructivism from a distinct perspective that is sometimes given the label constructionism. It is important to be aware that such labels tend to be used in different ways by different authors – Potter (1996: 15) warns that ‘the term “constructionism” is used with a number of distinct and sometimes contradictory shades of meaning across the social sciences”. In the way these terms will be used here: • Social constructivism accepts that knowledge is represented in individual minds, but emphasises the role of social processes in the individual’s coming to knowledge: although individuals develop personal knowledge systems, these are highly influenced by the culture in which they live and learn. • Constructionism is a perspective that sees knowledge as well as knowledge construction as something that exists on the interpersonal or social plane, and from this perspective notions of intra-personal knowledge are incongruous. What I here refer to as constructionism is sometimes referred to as a sociocultural perspective, taking ‘the individual’s participation in culturally organized practices and face-to-face interactions as primary explanatory constructs’, and following the principle that ‘it is inappropriate to single out qualitative differences in individual thinking apart from their sociocultural situation because differences in students’ interpretations of school tasks reflect qualitative difference in the communities in which they participate’ (Cobb, 1994: 15). Of course, science is characterised by seeking knowledge that has communal consent – knowledge that in Popper’s model (§2.2.2) exists in World 3. It is this World-3 knowledge that is ‘re-presented’ in school, college and university curricula, and is modelled in the target knowledge that provides the standard by which students’ learning will be evaluated. For a personal constructivist, ‘the initial ideas that later evolve into bodies of knowledge and disciplines have to be in individual heads’ (Glasersfeld, 1997: 2), although this does not in any way deny the role of social interactions in the development of individual thinking. Nor does a

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personal constructivist perspective (as understood here) run counter to a relational perspective (§2.5.1) that emphasises the value of seeking the perspectives of others to challenge and inform our own inevitably situated perspectives (Thayer-Bacon, 2003). Gergen considers social constructionist studies of science to have shifted to ‘ways of understanding scientific knowledge as the result of relational processes – emerging from the interchange of persons, objects, physical surrounds, and so on’ where individual scientists are not considered (as some earlier perspectives in this tradition might have implied) as ‘pawns to social forces, but full participants in a range of complex relationships out of which common understandings emerge’ (Gergen, 1999: 55). As a crude illustration of the distinction being made here between social constructivist and constructionist approaches, the personal constructivist view at the core of the RP suggests that if an individual was removed from all social contact it would still be meaningful to talk about their ideas, concept, beliefs – and to consider that the individual’s brain somehow represented a ‘store’ of personal knowledge. However, the personal constructivist does not suggest that this personal knowledge would have developed (in much the same form) in such a social vacuum. In the extreme case, any infant that somehow survived being isolated from society (and its artifacts) at birth would have been denied the linguistic and cultural tools upon which knowledge development is contingent, and their personal knowledge would be severely diminished. Indeed, in a very real sense they would surely lack a good deal of what we would normally consider typical of ‘human’ thinking and knowledge. From the perspective of the RP then, social constructivism offers perspectives on some of the contingencies of (personal) knowledge construction, whereas constructionism (when used as defined above) does not accept the ontological ‘reality’ of personal knowledge that is a key concern of the RP. From these descriptions it would seem that social constructivist work can fit well into the RP characterised earlier (§4.4), offering directions for work directed by the positive heuristic of the programme (e.g. how does knowledge construction (i.e. learning) take place?). However, the constructionist perspective would seem to be inconsistent with the hard-core assumptions of the RP (e.g. Learning science is an active process of constructing personal [sic] knowledge), and so the negative heuristic of the RP would place work in this tradition outside of the RP – although, even then, work undertaken along constructionist lines might offer concepts and notions that could inform the programme (Duschl & Hamilton, 1992) so long as they themselves are not incompatible with the hard core. As pointed out earlier in the chapter, when considering the philosophical underpinnings of constructivist research in Science Education, the constructivist RP is largely conceptualised in the (cultural) context of formal learning. Within this context there are certain taken-for-granted features (the very kinds of features that constructionist might wish to question and explain in terms of social and institutional contingencies). Generally, Science Education takes place in a context where (a) there is a set canon of knowledge that students are asked to learn; and where (b) students are evaluated individually to ascertain the extent to which they have ‘acquired’ that knowledge. Bereiter (1994: 22) suggests that schooling

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‘has traditionally concentrated on [Popper’s] World 2 – on the contents of individual students’ minds. That is where teaching strategies are focused. That is what achievement tests are intended to reveal’. From the perspective being developed in this volume it is recognised that we have to understand these two assumptions in a more nuanced way: • Scientific knowledge is developed through social processes, and is constructed through human cognition (leading to the arguments considered earlier about whether it can ever be considered to offer ‘true’ knowledge of the world). • School curricula set out curricular models that make up the target knowledge for students, and are designed to represent scientific knowledge in an appropriate manner for various group of learners. • An individual’s own knowledge will not be a copy of the target knowledge, but a personal construction that will represent that target knowledge to an extent (that varies from student to student). • Demonstration of personal knowledge that is considered to sufficiently match target knowledge ensures neither that the learner does not hold alternative conceptions of the same topic area (see §6.1.4.18), nor that the learner is committed to (‘believes’) the ideas demonstrated. Despite these complications, the whole formal education system is largely based upon accepting that target knowledge has some level of authority, and that learning involves the development of individual knowledge. Someone who did not accept the notion of the authority of curriculum models (rather than disagreeing with the validity of specific examples) or someone who did not accept personal knowledge as a meaningful construct would have difficulty working in the formal education system as it is currently organised in terms of ‘standards’ (National Research Council, 1996) or a state’s national curriculum (Ministry of Education, 1993; DfEE/QCA, 1999). This is certainly true for a teacher charged with facilitating the learning of curricular knowledge and assessing individual students according to their ability to demonstrate having internalised that knowledge. It would be quite possible for educational researchers to study Science Education without accepting these premises. However, within the RP that is the focus for the present volume, both (i) the notion of school (or college) science as in some sense an accepted body of target knowledge; and (ii) a commitment to the notion of individual learners constructing personal knowledge that can be in principle be shaped by teaching, are inherent within the hard-core assumptions (see Chapter 4). Any view that excludes the notion of personal knowledge (in some sense represented in the mind of an individual) as a viable construct is therefore considered (under the guidance of the negative heuristic) to fall outside the constructivist RP in Science Education. However, despite Solomon’s (1987: 63) criticisms of much personal constructivist writing underplaying social factors, she herself acknowledges that ‘this is not to assume that social influences rule at the expense of personal reflection: in the last analysis, what we construct is our own picture of the world and its phenomena’. Solomon’s criticism therefore can be seen as relating not to the hard core of the

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programme itself, but to the way many researchers have developed the theoretical content of the programme within the protective belt of concepts, construct, models and so forth. Her challenges (see §5.4.1) should be understood as informing appropriate discussion within the RP of how to follow the positive heuristic. The themes she raised will be discussed in the overview of progress in the field presented in Chapter 6.

5.4.3

Acknowledgement of the Social Dimension

The negative heuristic then does not in any sense exclude consideration of the social factors that are at work when an individual constructs new knowledge. Indeed, the context of formal Science Education is premised upon a notion of ‘teaching’ whereby one individual (the teacher) is assumed to be able to influence the developing knowledge of others (the learners). Rather, the focus on individuals has to acknowledge that, as Longino (1990: 221) beautifully expressed it, ‘the individual, is a nexus of interpretation coming into existence at the boundary of nature and culture’. From a constructivist perspective the individual constructs their personal knowledge by interacting with (Dewey, Thayer-Bacon), or (according to Piaget) acting upon, the environment and modifying internal models. That environment includes other people, and in a classroom context these other people (classmates as much as teachers) will be important influences. Outside of school, informal learning continues in the wider cultural context where folk knowledge is perpetuated in everyday interactions and through various media. From the perspective of the RP the social constructivist viewpoint argues for the importance of paying heed to and enquiring into this aspect of learning. Critics such as Solomon argue that the personal constructivist viewpoint has underplayed these influences. Yet Piaget, whose focus on the epistemic subject offers for many the archetype of a lone constructor of knowledge, readily acknowledged the importance of the social element of the learner’s environment (Glasersfeld, 1997). According to Howe and colleagues (Howe et al., 2007: 550), Piaget ‘saw cooperation as providing the social context where pupils would be motivated to coordinate existing ideas with alternatives’. Despite this, Piaget’s epistemic subject offers strong and influential metaphorical allusions to the person-as-individual, rather than bringing to mind the person-as-embedded-in-a-community, or the person-in-relation-toothers. Glasersfeld (§1.5.2, §5.2.6) acknowledges the social dimension within his radical constructivist perspective, The insistence on the subjectivity of the experiential world has also led some critics to the rash conclusion that radical constructivism ignores the role of social interaction in the construction of knowledge. This, too, is a misinterpretation, and a rather thoughtless one. If one begins with the assumption that all knowledge is derived from perceptual and con-

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ceptual experience, one in no way denies that ‘others’ and ‘society’ have an influence on the individual’s cognitive constructing. (Glasersfeld, 1992)

Rather, for Glasersfeld (1990: 7), ‘every individual’s abstraction of experiential items is constrained (and thus guided) by social interaction and the need of collaboration and communication with other members of the group in which he or she grows up’. However, for Glasersfeld (1997: 2), the individual knower is the focus of analysis, as ‘individuals – including social constructivists – must have some way of forming concepts and connecting relations, before they can begin to observe, analyze and meaningfully discuss social interactions’.

5.4.4

Including Social Constructivism Within the RP

Although there has been what Matthews (1992) colourfully described as ‘some skirmishing between main-stream Piagetian personal-constructivists and Vygotskian social-constructivists’, it is be argued here that work in both traditions (if not what I have labelled constructionist approaches) can be accommodated within the same RP, although having different foci of interest, Stripped to their essentials, constructivism tells us to pay close attention to the mental activities of the learner, and socioculturalism tells us to pay close attention to cultural practices in the learner’s milieu. Except for the practical difficulty of doing both at once, there is nothing incompatible in these proposals. Neither one implies rejection of the other. (Bereiter, 1994: 21)

In Driver and Easley’s early seminal paper (1978: 76) they acknowledged that ‘what is so often overlooked is the extent to which knowledge about the physical world consists of constructions about which there has to be social agreement’. In another of the papers considered here as being seminal for initiating the RP, Gilbert and Watts (1983: 87) acknowledged that ‘it is not yet agreed whether the focus of enquiry should be the individual as an isolate or the individual within a social group’. The social constructivist perspective, then, can be seen as what Glass and Johnson (1991: 38) call a ‘subprogramme’ within the wider RP, where ‘while such subprogrammes do have distinctive positive heuristics, they also utilise the larger, common positive heuristic of the “parent” (orthodox) programme’s hard core or specific metaphysics’. Any RP needs to start by abstracting out certain features for study, and although the importance of social interactions was acknowledged from the start (Driver & Easley, 1978), attention was initially largely focused elsewhere. This can be understood as an appropriate strategy when exploring such complex phenomena. For example, Fodor (1983: 1) argues that ‘since, according to faculty psychologists, the mental causation of behaviour typically involves the simultaneous activity of a variety of distinct psychological mechanisms, the best research strategy would seem to be divide and conquer: first study the intrinsic characteristics of each of the presumed faculties, then study the ways in which they interact’. E. F. Reddish,

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(2004) for example, describes a theory for thinking about teaching and learning in physics that is informed by neuroscience, and that he acknowledges is ‘focused on the individual, how the individual thinks, and how the individual’s thinking interacts with the environment’. Reddish goes on to point out that as the theory is developed it will need to be ‘interfaced and meshed with theories of social and cultural interaction’ (p. 54). The position of Driver and her co-workers (Driver, Asoko, Leach, Mortimer & Scott, 1994) developed somewhat to take greater account of such wider perspectives. Solomon’s work (e.g. Solomon, 1993b, 1987, 1992) can be seen to act as a spur to these developments, and to be closely related to the key research questions of the positive heuristic of the RP (§4.4.2): how does knowledge construction (learning) take place (e.g. to what extent is learning socially mediated?); how much commonality is there between learners’ ideas in science (e.g. to what extent does shared culture and language lead to shared understandings?); and how should constructivist teachers teach science? Social constructivist perspectives will therefore be considered to offer refutable variants within the RP, and will be considered from this perspective in Chapter 6.

5.5

The Research–Practice Interface

Another major criticism of constructivist work in Science Education is that it has not actually been able to inform pedagogy and make a real different to teaching practice, and so to school learning of science (Millar, 1989a; Harlen, 1999; Solomon, 1993a; Johnstone, 2000b). It will be argued here that it is certainly the case that the RP is a long way from offering a clear and comprehensive account of learning in science that can provide detailed and reliable guidance on the teaching of all science topics at all levels. However, it is also considered that given the complexity of the research focus (learning), this should not be considered too surprising at this stage (i.e. about three decades into the RP in Science Education). Yet, there certainly are examples of research-informed guidelines in many specific cases, even if these suggestions sometimes still often need proper ‘field-testing’ to check their value (see Chapter 7). It is also suggested here that despite the limited amount of detailed prescription deriving from the RP, the influence of constructivist research and writing has actually been widespread and substantial in influencing practice: even if the influence could sometimes be considered as insidious.

5.5.1

The Criticisms

There is a view that despite the overwhelming uptake of constructivism as something akin to a creed to many science educators (researchers, teacher educators), it

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has had a minimal effect on the actual classroom practice of most teachers. So Coll and Taylor (2001: 218) argue that ‘the wide acceptance of constructivism by the science education community does not mean that its position has been unchallenged or taken on board by science teachers’. This reflects a widespread view that a perspective that has been found useful by many researchers does not necessarily inform classroom practice. Solomon (1993a: 4), for example, hinted that the epistemological commitments informing some constructivist work make it an approach of more relevance to research than practice, i.e. that ‘the ethnographic line of research began with a simple descriptive objective in the verstehen tradition, [that] does not easily generate a guide to the daily practice of teaching’. In 1994 Solomon suggested that the ‘jury’ was still ‘out’ on the efficacy of the teaching approaches recommended by constructivist research in Science Education (p. 11). She pointed out that for a teacher to be aware of learners’ ideas is not the same as having a means of bringing about the desired changes (1994: 10), so that whilst acknowledging that the RP had produced ‘a rich source of valuable data’ she still found it difficult to understand what was meant by ‘constructivist teaching’ (p. 11). In 1999, Harlen (1999: 40) concluded that ‘there is no firm evidence as to the effectiveness of different approaches to developing pupils’ ideas within a constructivist framework’. Johnstone (2000b: 10) has argued that ‘as researchers we have solved almost none of the reported problems in chemistry teaching. … Research literature has been dominated by work on misconceptions, but little has as yet appeared about how to reverse these or to avoid them altogether’. Millar (1989a) argued that the constructivist model of learning had been (inappropriately) associated with a particular model of instruction. Millar can be seen as generally sympathetic to the constructivist programme, but does not feel that constructivism as a theory of learning implies a particular teaching approach.

5.5.2

The Research–Practice Debate

This criticism may be considered to reflect a wider concern among some science educators that research often seems divorced from practice (de Jong, 2000). There is a widespread view that academics often prioritise the undertaking of research and its publication in research journals that teachers do not access (because of time and cost issues), rather than reporting their work in more teacher-friendly language in practitioner journals that are read by classroom practitioners. As academic researchers are primarily judged in terms of research output, there is some basis for such a view, however research councils expect funded research to be effectively disseminated, and in Science Education many researchers do regularly write for practitioner journals and present at science teacher meetings. Nonetheless, it is in the nature of research that it needs to be conceptualised in ways that allow operationalisation, i.e. using well-defined technical language, and it is usually set in specific (and sometimes contrived) contexts. Accounts most

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suitable for informing teachers’ classroom behaviours may be quite different from the formal research reports that academics are expected to produce. The process of dissemination is therefore often not a trivial matter. Despite this, it will be suggested below that constructivism has strong influenced teaching practice in a range of educational contexts.

5.5.3

Matthews’ Criticisms of Constructivist Learning As Unguided Discovery

Matthews (2002: 129) has suggested that constructivism cannot usefully inform teaching, as ‘if knowledge cannot be imparted, and if knowledge must be a matter of personal construction, then how can children come to knowledge of complex conceptual schemes that have taken the best minds hundreds of years to build up?’ He asks how teachers are meant to teach ‘a body of scientific knowledge that is in large part abstract …, that is removed from experience …, that has no connection with prior conceptions …, and that is alien to common-sense, and in conflict with everyday experience, expectations, and concepts?’ and suggests that how this might be ‘taught, without teachers actually conveying something to pupils, is a moot point’. Those working in the constructivist RP in Science Education have offered a range of answers to these questions (some of which are reviewed in Chapter 6), but Matthews’s most severe criticisms do not seem to be aimed at mainstream constructivist science educators, but at advocates of some form of pure discovery learning (cf. §5.1). Matthews (2002: 130) asks: 1. Why must learners construct for themselves the ideas of potential energy, mutation, linear inertia, photosynthesis, valency, and so on? 2. Why not explain these ideas to students, and do it in such a way that they understand them? 3. How can a teacher make ‘the theoretical ideas and conventions available to pupils’ without explaining them, without illustrating them, without showing their interconnections: in brief, without teaching them to pupils? The answer to question 1 is found in the basic premise of constructivism: that ultimately learning is a process that takes place in the mind of an individual and so in that sense this is the only possibility, i.e. knowledge cannot be ‘transferred’ into the heads of learners by some kind of external process. However, that certainly does not mean that others cannot support, direct and channel the individual process of knowledge construction: that is what teaching is about, and as we saw earlier in this chapter, there is a fertile debate on the extent of the role of social processes in learning. To those working in the RP (as set out in Chapter 4), Matthews’ questions 2 and 3 would seem very odd things to ask. Matthew offers an account of how ‘most science teachers’ work,

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They try their best to explain things clearly, to make use of metaphors, to use demonstrations and practical work to flesh out abstractions, to utilise projects and discussions for involving students in the subject matter, and so on. They realize that many, if not most, things in science are beyond the experience of students and the capabilities of school laboratories to demonstrate. … Good teachers do their best in the situation, and try to point out why faith in science is warranted. They may refer to texts or studies that have better controlled for experimental conditions than is possible in school settings. They may get students to appreciate the general directions in which school laboratory results are heading. (Matthews, 2002: 130)

Elsewhere Matthews has suggested that ‘for hard [sic] constructivists, the fact that traditional teaching produces knowledge of any kind is an embarrassment’ (Matthews, 1994a: 167). Significant here is Matthew’s use of the term ‘hard’ constructivists, by which he means ‘radical’ constructivism (§5.2.7), which Matthews associates with lone, unguided construction of knowledge. The notion that a ‘constructivist’ science teacher would not, should not, or would not want to explain, illustrate, demonstrate, and to some extent suggest, argue, persuade, etc. does not derive from the constructivist RP discussed here (see §4.4). The role of the constructivist RP is certainly not to replace such tactics with something different, but rather to develop a better theoretical base to guide teachers in understanding the source of students’ learning difficulties, and so provide teachers with a more principled basis for selecting specific tactics from their repertoires in various teaching contexts. The positive heuristic of the RP seeks to inform teaching guided by such questions as how do learners’ ideas interact with teaching? The issue for the RP is how teachers can best support learners’ construction of what is considered desirable learning, by explaining, illustrating, demonstrating, etc., despite the natural tendencies of human cognition to interpret new information in terms of existing ways of understanding that may be at odds with the ideal prerequisite knowledge. Mathews’ criticisms (like those of Bowers, considered earlier, see §5.1) actually target something other than the RP in Science Education that is the subject of this volume and commonly labelled constructivist – rather the distinct view that learners should construct scientific knowledge by raw discovery methods. It will be argued here that such an approach is actually ruled out from being a suitable constructivist method of teaching by the negative heuristic of the RP.

5.5.4

Constructivist Approaches to Curriculum Development and Instruction

5.5.4.1

Discovery Learning – The Heuristic Approach

It has been suggested then that some critics seem to associate the constructivist approach, with its notion that each individual has to construct their own versions of the science (i.e. a belief about cognition), with the ‘discovery learning’ approach

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popular in earlier decades. Earlier in the chapter (§5.1.3), Bowers’s (2007) take on constructivist teaching was reported: that is, an approach which made ‘a virtue of not exposing students to knowledge in any systematic way’ (p. 98), because ‘the teacher must not impede the student’s construction of knowledge by expecting them to learn about existing knowledge’ (p. 21). Rather, according to this notion of constructivism, as Cromer (1997: 12) suggests, ‘constructivists believe that each child can learn the scientific process in a rather straightforward manner by observing patterns and making predictions’. Such a belief would seem fanciful, for as Mathews writes: many, if not most, things in science are beyond the experience of students and the capabilities of school laboratories to demonstrate. The cellular, molecular, and atomic realms are out of reach of school laboratories, as is most of the astronomical realm. It is fanciful to believe that sensory experience can, alone, be the foundation of a child’s scientific knowledge. Most of the time even things that are within reach do not work. It is a rare school experiment that is successful. (Matthews, 2002: 130)

However ‘discovery’ learning predates the constructivist movement in Science Education by a considerable period. In Britain, a discovery approach, or ‘the heuristic method’, was championed by H. E Armstrong. Jenkins reports how Armstrong’s ideas were published by the Board of Education in 1898, under the heading Heuristic Method of Teaching or the Art of Making Children Discover Things for Themselves (Jenkins, 1979). Although the approach gained popularity, Jenkins reports that ‘even as early as 1900, heurism was under attack’ (p. 43). Within a few decades it had become clear that some teachers were attempting to adopt a general teaching approach based on unguided discovery that was neither what Armstrong was advocating, nor effective. Jenkins reports that as long ago as ‘1918, the Thomson Committee severely criticised the heuristic method of teaching … [and] warned that a pupil could not “expect to rediscover in his school hours all that he may fairly be expected to know” ’ (p. 44). Jenkins (1979: 44) explains that Armstrong himself was not expecting pupils to rediscover the science in the curriculum without support. So although ‘his insistence that “the beginner not only may but must be put absolutely in the position of an original discoverer” easily led others to assume that he expected a pupil to discover everything for himself’, Armstrong himself considered such a view “the greatest nonsense” ’. Similar criticisms of discovery learning have been repeated at various points. For example, within psychology Ausubel (1961 – see §1.9.2) championed the role of verbal learning, and similarly Gagné (§1.9.1) argued that although ‘some writers have suggested that rules need to be discovered, meaning that examples of the rule should be presented and the learner left to do his own chaining, without the help of verbal statements’, there was no strong evidence to support such a view (1970: 58). He noted that ‘man is a verbal animal, and there are marvelous shortcuts in learning to be achieved by the use of language’. Similarly, from a science teaching perspective, Solomon (1980: 50) wrote that ‘unguided discovery as a format for lessons is not only emotionally demanding on both class and teacher, it also appears in practice and on reflection to be quite foreign to the whole

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ambience of class-teaching’. Interestingly, Quale’s recent argument for rethinking Science Education according to a ‘relativist epistemic approach’ consistent with radical constructivism did not reject the teaching of accepted scientific ideas, but rather suggested that science teaching be based around narratives, i.e. telling the stories of science (cf. Millar & Osborne, 1998).

5.5.4.2

A Focus on Enquiry

Despite the widespread acceptance that science teaching could not proceed by expecting students to rediscover the major insights of generations of great scientists, something of Armstrong’s heuristic method has survived in a good many science courses that offer a ‘process’ focus or ‘inquiry’ flavour. This tradition has been significant enough for Cromer (1997) to offer strong criticisms of such an approach (which he equates with constructivism). Matthews (1994b: 25) reports how ‘The US and British curricular reforms of the 1960s aimed at more than just specifying content areas or laying down topics to be taught: they were also concerned to develop scientific attitudes ands methods among students. Reformers wanted students to become scientific, not just learn science. To this end, “inquiry” or “discovery learning” was a prominent feature of the NSF [National Science Foundation] and Nuffield reforms’. Where Cromer (1997: 11) was quoted above as ‘blaming’ ‘professional science educators’ for ‘enthusiastically endors[ing] constructivism because it allows them to speak only about process (whatever that is) rather than content (of which they are ignorant)’, Matthews offers a quite different view of the promotion of inquiry approaches in the USA, where ‘the NSF scientists firmly in the saddle of curriculum reform, teachers were at best stable-hands, and education faculty rarely got as far as the stable door’ (Matthews, 1994b: 17). At the start of the 1970s, Renner and Stafford (1972) reviewed 17 different schools science ‘programs’ (i.e. widely adopted schemes) with an inquiry flavour, and even at this time this was just a selection of those available in the USA. The (UK based) Nuffield Science Teaching Project (§1.10.1) was set up in 1961, with the Nuffield Foundation asking writing teams to produce materials that ‘provide some insight into scientific thought and method’ (Ingle & Jennings, 1981: 22). In the mid-1970s, Tomlinson (1975) suggested that ‘project work’ with an enquiry flavour was undergoing a ‘revival’ in the UK. Such enquiry-based projects have also been suggested as ideal means of challenging the most able students in science classes (West, 2007).

5.5.4.3

Guided Discovery

Cromer (1997: 20) ascribes a belief in discovery learning to ignorance of science: that is, ‘many constructivists are pure empiricist because of their ignorance of the scientific process’. However, the constructivist approach explored in the RP

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in Science Education is actually anything but purely empiricist. For one thing, it acknowledges that all knowledge is built upon existing cognition (if anything, making it more a rationalist, than an empiricist view). Matthews (1994b: 146) has recognised that ‘constructivism attempts to steer a path between teacher-dominated instruction, the traditional didactic model of education, and student-led discovery learning, the progressive model of education’. For Driver (as responsible as anyone for initiating the constructivist RP in Science Education), constructivism was an approach needed to overcome the shortfalls of discovery or ‘heuristic’ learning. She gave the first chapter of her book (on the Pupil as Scientist?) the heading ‘The fallacy of induction in science teaching’, and criticized the very approach that Cromer claims is recommended by constructivist science educators, The more simplistic interpretations of the discovery approach in science suggest that we only need to give pupils the opportunity to explore events and phenomena at first hand and they will be able to induce the generalizations and principles themselves. The position suggested here is that children do make generalizations from their firsthand experiences, but these may not be the ones the teacher has in mind. Explanations do not spring clearly or uniquely from data. (Driver, 1983: 8–9)

As I have argued, for the constructivist working in science teaching, the aim of Science Education is not to encourage children to construct any conceptions of scientific phenomena that they find viable, but to guide them towards constructions that are set as target knowledge in the curriculum. Thus discovery may indeed be part of school science learning, but it needs to be carefully guided discovery. So Driver contrasted the constructivist approach with discovery learning: The constructivist view of science, on the other hand, indicates the fallacy here. If we wish children to develop an understanding of the conventional concepts and principles of science, more is required than simply providing practical experiences. The theoretical models and scientific conventions will not be ‘discovered’ by children through their practical work. They need to be presented. Guidance is then needed to help children assimilate their practical experiences into what is possibly a new way of thinking about them. (Driver, 1983: 9)

So constructivist approaches to teaching science as seen in the RP are not based on students drawing conclusions from open-ended practical work, but on social mediation, with teachers guiding the ‘discovery’ of scientific ideas by managing the construction of common knowledge in the classroom (Edwards & Mercer, 1987), using ‘scaffolding’ to channel students’ constructions (Scott, 1998) and helping the learners build up their own versions of the (theoretical) entities of science previously constructed by professional scientists (Ogborn et al., 1996). The suggestion that the constructivist RP has not strongly informed classroom science teaching ignores the research set out to ‘develop revised teaching approaches which would be informed by research on children’s thinking in science and current theoretical developments in cognition’ (Driver & Oldham, 1986: 105). A basic tenet of this approach was that the curriculum should be a programme of activities that encourage pupils to (re)construct scientific knowledge (pp. 112–116). The teacher’s role was to be a ‘facilitator’ who would provide the appropriate opportunities for the pupils to undertake the construction – including exposure to

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conflict situations and the construction and evaluation of new ideas (see §6.3). As students all have their own unique ideas (a basic assumption in the RP, see §4.4), guidance to teachers may sometimes be at the level of providing strategies that can be adapted to particular circumstances, If children’s knowledge is regarded as individually constructed and idiosyncratic … any attempt to define a generic path for learning would appear to be inconsistent with this assumption. However, the evidence is that, whilst unique understandings are certainly constructed, considerable commonality among the informal ideas which children express is frequently identifiable. … Consequently, there is the possibility of teachers adopting both a general (content-free) set of strategies as well as those necessary to manage recurring (content-specific) ideas. (Russell & Osborne, 1993: 2)

Consideration of what these strategies might be, and when ‘generic’ approaches are likely to be indicated are questions addressed within the RP, i.e. the positive heuristic of the programme (§4.4): • How should teachers teach science [in view of the contingencies that influence their learning]? • How much commonality is there between learners’ ideas in science? One of the hard-core commitments of the ‘constructivist’ RP as characterised here is that ‘it is possible to teach science more effectively if account is taken of the learner’s existing ideas’ which implies that teachers are to interact with, and so intervene in, children’s learning. Any approach that excludes such interaction (i.e. unguided discovery) does not fall under the programme’s notion of ‘teaching’, and so is excluded from consideration by the negative heuristic of the RP.

5.5.5

The Adoption of the Constructivist Agenda in Classrooms

The types of suggestions and recommendations that have emerged from the RP are discussed in more detail in Chapter 6. However, it is appropriate here, in view of the criticisms that have been raised to illustrate how the basic principles underpinning the constructivist approach have been adopted in some educational contexts

5.5.5.1

A Constructivist-informed Curriculum in New Zealand

Probably the best-known case of constructivist ideas being adopted in an official science curriculum is that of New Zealand (Bell et al., 1995). The University of Waikato in Aotearoa (the Ma¯ ori name) or New Zealand (A-NZ) was one of the first research centres for explicitly constructivist research in Science Education, particularly with the sequence of ‘Learning in Science Projects’ (§4.2.1) run over many years (Bell, 2005). Staff from the Centre for Science and Technology Education Research were heavily involved in developing a new science cur-

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riculum for A-NZ that was strongly influenced by constructivist ideas, and which was, accordingly, the subject of considerable criticism and even media attention. One newspaper reported allegations that ‘a “cell” from the Waikato University had “captured” curriculum development at the Ministry of Education’ (Saunders, 1995: 8). The curriculum document itself (Science in the New Zealand Curriculum, Ministry of Education, 1993) does not explicitly discuss constructivism as a model of learning and teaching. One of the general aims of science education, inter alia, is given as ‘to advance learning in science by … portraying science as both a process and a set of ideas which have been constructed by people to explain everyday and unfamiliar phenomena’ (Ministry of Education, 1993: 9), and one feature offered of an ‘an inclusive curriculum in science’ is (again, inter alia) that it ‘provides opportunities for girls to … examine the historical and philosophical construction of science’ (Ministry of Education, 1993:11). In referring to science as constructed, these two references in a substantive curriculum document, do adopt the metaphor of knowledge construction, but fall someway short of a radical constructivist perspective. What seems more significant is the focus on active learning, learning of process skills, group work, model building and the like rather than subject content. The curriculum document offers examples of teaching and learning contexts for meeting the curricular aims, but does not set out target knowledge in the form of detailed specification of science topics to be taught. Whilst this is certainly compatible with a constructivist approach, it is neither necessary nor sufficient to ensure teaching that is broadly constructivist. Indeed, the extent to which teachers in A–NZ have taken advantage of the flexibility provided to design schemes of work to meet the needs and interests of their own students has been questioned (Coll, 2007).

5.5.5.2

Constructivist Pedagogic Assumptions in the English Curriculum Context

An interesting contrast with the A–NZ curriculum is provided by the English National Curriculum, introduced at the start of the 1990s. Unlike the A–NZ case, the English curriculum document (DfEE/QCA, 1999) specified precise topics that were required teaching for all pupils across 4 broad age bands or ‘Key Stages’ (5–7; 7–11; 11–14; 14–16). For example, at the lower secondary level (ages 11–14) 37 different science topics were prescribed (in some detail) for all pupils (apart from a small proportion who were exempted due to extreme special needs) in English schools, regardless of ability, interests, local circumstances or any other variations. Although the curriculum document certainly made reference to wider aims of Science Education, process skills, the nature and societal significance of science and links with other areas of the curriculum, it was perceived as dominated by subject content. The curriculum was widely seem as offering too little flexibility, and too much material to be covered to allow enough scope for teaching that could motivate and engage many pupils (Osborne & Collins, 2000; HCSTC, 2002; Cerini

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et al., 2003). In particular, an explicit intention for teachers to teach about the nature of science through the prescribed content largely failed, despite attempts to make adjustments to the curriculum structure and associated assessment regime (Taber, 2008d). Recent revisions of the curriculum (QCA, 2007a, 2007b) have attempted to respond to these widespread criticisms, and specify much less content, in much less detail, in a structure that no longer clearly prioritises the learning of subject content as the basis of curriculum. However, what is of interest for present purposes is less the failings of the previous English National Curriculum for science, than the wider context of ‘guidance’ that was developed to complement the curriculum. One gloss on this process, which will be summarised here, is that the government’s response to its (and its inspection and curriculum agencies’) perceptions that teachers were failing to adopt effective pedagogies to teach the curriculum was to introduce several levels of ‘guidance’ on how to do the job better. This process was ultimately only partially successful because the main barrier to better teaching was not lack of teacher’s professional knowledge about pedagogy, but the legal requirement to cover an over-packed curriculum. The point of interest here is the nature of the government’s advice, through the issuing of a model scheme of work, a ‘framework’ for teaching and a major professional development initiative. The latter was the basis of a ‘national strategy’ that produced an extensive professional literature, in a range of formats (booklets, files, leaflets, videos, software presentations, etc.), which can only be sketchily considered here. Before considering this ‘guidance’ for teachers it is worth noting that between the introduction of the National Curriculum for pupils, and the formation of the strategies, the government toyed with an alternative form of control over teacher’s professional work, by introducing a National Curriculum for Initial Teacher Education (Department for Education and Employment, 1998). This set out how ‘training’ providers (i.e. usually universities) should prepare new teachers. A number of the points made in the document may be considered to be strongly influenced by a constructivist model of learning. So teacher candidates (‘trainees’) had to be taught that • Pupils’ own ideas about areas of science will often differ from accepted scientific ideas, and how to understand possible origins of pupils’ misconceptions, and how they can be addressed, e.g. thinking that, in a simple circuit, the current in the return wire is less than the current in the wire to the device; thinking that plants breathe in carbon dioxide and breathe out oxygen. • Some scientific ideas, e.g. an object moving at a steady speed in a straight line has no net force acting on it, are counter-intuitive in that they seem contrary to everyday experience. • Pupils’ incomplete understanding of scientific ideas sometimes prevents them from making distinctions between separate scientific ideas. • Using models, analogies and illustrations in science teaching is a powerful way to explain complex scientific principles to pupils, but that … some pupils may confuse representations with the scientific ideas they aim to explain, e.g. think-

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ing that atoms, like the models used to represent them, have hooks on them by which they join to others. • Some illustrations and examples may require a general knowledge which some pupils may not possess, e.g. pupils in urban schools may be less familiar with animal hibernation or seasonal variation (Department for Education and Employment, 1998). So here we find integrated into in an official document a view that learners come to class with existing ideas relevant to school science; that everyday experience provides resources for learning that vary between students; that students’ ideas may not match the target knowledge; and that alternative ideas may have consequences for intended learning. These ideas are clearly in line with the assumptions about learning that underpin the constructivist RP (see Chapter 4). The document goes on to require that ‘trainees must be taught that … activities must be designed to build on pupils’ previous knowledge and understanding’ (Department for Education and Employment, 1998), so the recommended approach to teaching reflects hard-core aspects of the constructivist RP in Science Education. The National Curriculum for Initial Teacher Education was replaced a few years later by new standards for qualified teacher status, but by this time similar principles were being built into documentation addressed at all teachers in English schools. The government’s Qualifications and Curriculum Agency introduced ‘model’ schemes of work for science at primary (Key Stages 1 and 2) and lower secondary (Key Stage 3) levels. These documents emphasised how students make progress by building up their knowledge across time (cf. Bruner’s spiral curriculum, §1.9.3) and again made references to the importance of learners’ ideas. So, for example, the scheme for a year 4 class (7–8 year olds) studying a topic on ‘Solids, liquids and how they can be separated’ suggests the teacher begins by ‘elicit[ing] children’s existing knowledge of materials by presenting them with a collection of solids and asking them to group these according to their own criteria, recording reasons for their choices’ and goes on to comment that ‘teachers will need to take account of what this introductory work shows about children’s knowledge and understanding of materials in their short-term planning for this unit’ (QCA, 1998: 2). Some of the units for lower secondary students make explicit reference to ‘misconceptions’ that students are likely to hold: Pupils will have met the relationship between force and movement at key stage 2 and in unit 7 K ‘Forces and their effects’, but many will wrongly associate constant force with constant speed. … Take the opportunity to challenge any pupil’s association between force and constant speed, e.g. after the ice puck has been struck, it has no force on it in the direction it travels. (QCA, 2000d: 4) A common misconception is that activity gives you energy because it makes you healthier – and so more able to do more activity. (QCA, 2000a: 1) A very common misconception is that particles themselves expand on heating. It is not obvious from the experimental results that this is incorrect and pupils will need to be given the scientific explanation, i.e. in terms of increasing separation of particles. (QCA, 2000b: 5)

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A common misconception is that plants obtain their food from the soil. It is worth establishing that this is not the case early on in the teaching sequence, and reinforcing this idea throughout the unit. (QCA, 2000c: 3)

The use of the term ‘misconceptions’ (rather than say ‘alternative conceptions’) suggests a relatively naive and atheoretical treatment (cf. 5.3.2), or – on a more generous gloss – the adoption of a ‘teacher-friendly’ approach. The nature of the advice in these cases falls short of a sophisticated pedagogy for facilitating conceptual change (cf. Chapter 6, §6.3) but again demonstrates that teachers should elicit, be aware of, and expect to need to plan teaching around, students’ ideas. In 2002 the Government’s ministry of education (the Department for Education and Skills, as it was then) introduced a major professional development initiative aimed at ‘raising standards’ at lower secondary level, called the Key Stage 3 National Strategy (and later, the Secondary National Strategy). Science, as a core curriculum subject had its own strand of the strategy. A key feature of the strategy was a ‘Framework’ for teaching the science curriculum in the 3 years of the lower secondary school (Key Stage 3 National Strategy, 2002b). This organised the teaching of the 37 topics of curriculum around five ‘key ideas’ – cells, energy, forces, interdependence, particles (Kind & Taber, 2005; Grevatt, Gilbert, & Newberry, 2007). The Framework document highlighted the significance of ‘misconceptions’, Some scientific ideas are difficult because they involve the learner in abandoning previous beliefs – for example, a belief that heavy objects fall faster than light ones. Pupils will not necessarily be convinced by a demonstration. They are likely to see what they want or expect to see – that the heaviest object lands first – or they will try hard to find fault with the test in order to hang on to their belief. Although pupils’ ideas can be challenged by physical evidence, it is often the evidence, not the idea, which they doubt. Teachers have to challenge pupils’ thinking and give them new perspectives from which to view the evidence through a range of activities and frequent reinforcement. Pupils often need to articulate the conflicts that exist in their minds. Drawing out their thinking and talking about their difficulties in abandoning their beliefs is a key role for an adult in the room, such as the teacher, a technician or a teaching assistant attached to the science department. (Key Stage 3 National Strategy, 2002b: 14–15)

Teachers were advised to be constantly checking students’ ideas and understanding of teaching, During every lesson you absorb and react to pupils’ responses, see whether they are confident or hesitant with new work, decide whether they need extension work or more help, and offer immediate support. Where you notice any difficulties, misunderstandings or misconceptions, you can adjust your lesson and address them straight away, if necessary continuing in the next lesson or two. In this way, pupils can keep up with the pace of work and do not fall behind. … Plenary sessions are also a good time to firm up short-term assessments by asking probing questions to judge how well pupils have understood new work and to check again for any misunderstanding or misconceptions. (Key Stage 3 National Strategy, 2002b: 50)

Clearly the understanding of learning presented here is one where learners’ previous ideas are significant, but where teaching concerns active interventions to shift students’ thinking towards established target knowledge. Despite the lack of

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sophistication of the treatment of conceptual change issues, the officially sanctioned view of teaching and learning science in England is clearly aligned with the RP in Science Education. The Framework was the central component of the Strategy, which was delivered by a system of regional Strategy advisers or ‘consultants’ offering courses for teachers. Some courses were meant to be attended by representatives from all school science departments (who would then be expected to pass on key ideas to colleagues through departmental sessions), and other courses were offered on an elective basis so that schools could prioritise their particular training needs. A variety of forms of supportive documentation were provided to support the training, and much of this material was made generally available through an official website (DCSF, 1997–2008). During the second year of the initiative schools were offered 6 days of training (i.e. funding to cover 6 days of staff release) in the areas: misconceptions in science; scientific enquiry; assessment in science; literacy in science; planning progression; and effective lessons (Key Stage 3 National Strategy, 2002a). So the topic of ‘misconceptions’ was seen as a key area for science teacher development. As the initiative was based on centrally designed training, delivered by local advisers, much of the training was scripted, with the advisers being provided with presentation materials, and being given instructions on which points to make, and supported by examples they might use. Whilst this might not seem the basis of effective pedagogy (and hardly models an interactive approach designed to respond to the needs of individual learners) it does provide a record of the basic content of the training sessions. So in the Misconceptions unit it was explained that ‘the term ‘misconception’ is used when referring to the commonly held beliefs that pupils hold that are at variance with the accepted scientific view’ and would ‘be used synonymously with’ ‘alternative framework’ and ‘alternative conception’ (Key Stage 3 National Strategy, 2002d: 1). It was explained that ‘misconceptions, alternative conceptions or alternative frameworks are views held by pupils (and adults) that do not fully coincide with scientific views’ and it was claimed that ‘they may be social (held by a large proportion of the population) or personal, and are developed through everyday talk’ (Key Stage 3 National Strategy, 2002d: 10). The latter point is a gross simplification (see Chapter 6) but nevertheless shows the issue was being considered important for classroom practice. A list of common ‘misconceptions’ was provided (Key Stage 3 National Strategy, 2002d: 71). Teachers attending the training were offered a list of characteristics of ‘misconceptions’: • • • • •

Have been constructed from everyday experiences May be linked to specialist language Can be personal or shared with others Explain how the world works in simple terms May be inconsistent with science taught in schools

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• Can be resistant to change • May inhibit further conceptual development (Key Stage 3 National Strategy, 2002d: 10 (Slide 1.3) ) The training (Key Stage 3 National Strategy, 2002d: 10–11) informed teachers that: • ‘Learning science is developing new ways of knowing about and understanding familiar phenomena. Pupils will need to appreciate the differences between alternative ways of knowing science and the contexts in which to use them’. • People can ‘can hold two different views of the same process at the same time’. • ‘It is important that teachers are aware of the misconceptions pupils hold’. • ‘If the difference between the accepted scientific view and the misconception is great, then pupils will have more difficulty in understanding the scientific view. Teachers will need to take this into account when planning their teaching programme’. • ‘A large proportion of pupils still hold misconceptions, despite primary science being well established, and that this is probably due to socially accepted beliefs and the way people talk to each other about scientific issues rather than poor teaching’. The training suggested that elicitation techniques should be used ‘to identify pupils’ misconceptions’, and discussed a range of suitable techniques for classroom use: focused questioning; flow charts; associated word lists; annotated drawings and posters; concept maps; concept cartoons; class discussion (Key Stage 3 National Strategy, 2002d: 21). The training also focused on the roles and nature of models in teaching and pointed out that misconceptions can be acquired during teaching, Research has shown that the choice of materials in making model cells is important and can lead to misconceptions. For instance, the use of wallpaper paste in animal cell models can contain air bubbles. These bubbles have subsequently been drawn by pupils who think that all cells contain them (vacuoles in plant cells are not randomly generated like air bubbles). It is important for teachers to discuss with pupils what each part of the model represents. (Key Stage 3 National Strategy, 2002d: 33)

Among the ‘main messages’ that teachers were expected to take away from the course (Key Stage 3 National Strategy, 2002d: 69), were: • Pupils (and many adults) frequently hold misconceptions/alternative conceptions/ alternative frameworks relating to science. These can be close to or widely different from the accepted scientific view. • Misconceptions can be resistant to change. • Teaching needs to take account of pupils’ misconceptions by: – Identifying them – Devising teaching programmes that correct the misconceptions One appendix to the training materials was a paper by Leach and Scott based on their notion of ‘learning demand’ (Leach & Scott, 2002).

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Although the Misconceptions unit was just one element of an extensive staff development initiative, its main messages were reflected where relevant in various other strategy training units and support materials. A unit on ‘progression’ in learning science emphasised that ‘we need to elicit pupils’ understanding (and misconceptions) at the start of a unit and match our teaching accordingly’; ‘the first few lessons can be organised to deal with the range of understanding elicited’; and ‘checking understanding and dealing with it at the start of a unit takes relatively little time, reduces unhelpful repetition of earlier work, thereby saves teaching time and helps maintain pupil motivation’ (Key Stage 3 National Strategy, 2002e). A unit on scientific enquiry reiterated that ‘science is often counter-intuitive’ (Key Stage 3 National Strategy, 2002f). A unit on ‘pedagogy and practice’ informed teachers that ‘good teaching results when teachers: focus and structure their teaching so that pupils are clear about what is to be learned and how, and how it fits with what they know already; actively engage pupils in their learning so that they make their own meaning from it’ (Key Stage 3 National Strategy, 2003a). Training units about teaching key topics (e.g. energy, force, particles, cells) also reiterated the general messages of the ‘misconceptions’ unit in specific contexts. So the initiative reiterated messages that can be seen as in-line with a constructivist view of teaching and learning: • Learners build up their understanding based on previous learning: ‘linking the content or concepts being explored during a lesson with examples from the world around us enables pupils to construct their new understanding within a familiar context’ (Key Stage 3 National Strategy, 2004b: 5). • Learners hold everyday meanings for technical words: ‘words with everyday meanings include: Force often used interchangeably with energy and power; will probably have everyday associations rather than the scientific concept’ (Key Stage 3 National Strategy, 2002c: 11). • Learners come to class with alternative conceptions: for example, ‘pupils will come with a range of ideas and misconceptions about energy. These will have arisen from everyday experiences and from the teaching of related ideas in Key Stage 2 [primary school]’ (Key Stage 3 National Strategy, 2003d: 7). • There are common misconceptions that may be found reflected in the thinking of a significant proportion of students: ‘there are a number of common misconceptions that pupils can hold about energy – for example, that energy is “stuff”, or that it is “used up”, or that it “makes things happen” ’ (Key Stage 3 National Strategy, 2003c: 5). • Some misconceptions may actually derive from teaching: ‘the transformation of energy teaching model may reinforce some common misconceptions, such as: heat and temperature are the same; heat is a substance that flows like a fluid, or energy generally is a kind of stuff; heat is static and occupies a particular space; food and fuel are energy rather than an energy resource and a store of energy’ (Key Stage 3 National Strategy, 2003d: 62).

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• Being aware of learners’ alternative conceptions can inform teaching: ‘an awareness of pupils’ misunderstandings and misconceptions and the appropriate use of teaching models can help overcome these’ (Key Stage 3 National Strategy, 2003c: 5). • There is value in eliciting learners’ ideas as part of teaching: ‘talking about how a particle model can explain how substances dissolve or why mass is conserved in chemical reactions can help to develop pupils’ understanding and reveal misconceptions’ (Key Stage 3 National Strategy, 2002c: 109). • There is a need to take students’ thinking into account in planning effective lessons: ‘advice about pupils’ common misconceptions about materials and particles, and how to deal with these, should be built into the department’s planning’ (Key Stage 3 National Strategy, 2003e: 92–93). • Effective teaching responds to learners’ ideas: ‘pupils have many misconceptions about digestion and that these need to be addressed in order for them to understand the process at a cellular level’ (Key Stage 3 National Strategy, 2003b: 60). This is not the place to critique this initiative in any detail. The method of facilitating teacher professional development relied upon a process of central design, mediated by courses ‘delivered’ to schools by advisers/consultants not involved in the design, and then relying upon schools to find time for the individual course members to report back and explore ideas within the science departments. Such a ‘cascade’ approach is hardly ideal, but perhaps it made the initiative financially viable. Certainly the Strategy materials generally say a lot more about the importance of responding to students’ misconceptions then they do about how this can effectively be done, and the general impression given is that challenging students’ ideas is not problematic as long as teachers are aware of the misconceptions and plan accordingly. Despite these rather major limitations, it is still the case that over a period of less than a decade basic constructivist principles underpinning the RP have become widely incorporated into the ‘model’ of teaching and learning that has been established as officially approved pedagogy. England offers only one educational context, albeit one where this author can offer an insider view (having worked in education in that context throughout the period covered by the developments outlined above). One value of the English case is that there is a genuinely National Curriculum with legal status, offering a fairly uniform curriculum context in state secondary schools – despite the rather heterogeneous mix of schools within the state system (mostly, but not all, co-educational; some denominational, mostly not; some highly selective, but most largely nonselective; variously taking students of age ranges of 11–16 or 11–18 or 13–18; schools assigned as community schools, or village colleges, or city academies, etc.; many, but not all, schools having a nominated ‘specialist’ focus on extending the curriculum – language, science, arts, technology, etc.). However, the main point of interest in considering this particular case in some detail is that over a period of a decade there has been a wealth of official guidance on teaching science issued to teachers and teacher educators, which although not

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formally labelled as such is ‘constructivist’ in the sense of being aligned with the RP in Science Education, with its focus on constructing knowledge taking into account learner’s ideas. Yet, this extensive and expense campaign of shifting teachers’ most basic understandings of teaching (cf. §4.6) towards a broadly (if fairly shallow) constructivist orientation has attracted relatively little critical comment and attention in the UK, within professional circles or more widely. This adoption of a constructivist position has certainly avoided the strong criticisms that have accompanied what has been perceived as constructivist influence on US Science Education standards (Cromer, 1997), or the constructivist-informed national curriculum in A-NZ (Matthews, 1998a). 5.5.5.3

A Qualified but Significant Influence on Practice

The lack of opposition to this development, and indeed general lack of widespread discussion, would seem to deserve some comment in view of the very different response to the A-NZ experience, and the strong criticism of ‘constructivist’ approaches in the USA (see earlier in this Chapter). It should be immediately pointed out that this is certainly not due to any general tendency to avoid debate and criticism of educational developments in England. Indeed a recent revision of the National Curriculum that has substantially reduced the prescribed subject content (QCA, 2007a, 2007b) and is aligned with an increasing focus on nature of science issues (‘how science works’) has attracted widespread debate, comment and criticism (Gilland, 2006). In the absence of any research to explore why the official adoption of ‘constructivist’ pedagogy should attract such little comment, it is possible to offer a number of potential candidates for possibly significant factors. For one thing, the English ministry has kept separate the mandatory Curriculum document, and the various ‘recommended’ guidance, so (in theory at least) no school or teacher is required to follow the guidance provided by the model scheme of work, teaching Framework or Strategy materials. It also seems likely that the guidance itself is largely welcomed by teachers in comparison with the Curriculum which has created widespread problems due to its being too extensive and inflexible. While teachers have repeatedly voiced concerns since the introduction of the National Curriculum there seems little in the general advice within the various guidance materials (which sets out to exemplify pedagogy and offers teachers flexibility to ignore any specific examples that they do not find helpful) which is objectionable. This lack of ‘objectionableness’ can itself be related to characteristics of both the educational context and the guidance. Firstly, the science teaching community in England has long been exposed to the basic ideas of constructivism, which is well established among teacher educators and was a familiar part of the professional scene during a very active burst of ‘curriculum development’ activity in the 1980s that was based upon teacher involvement (rather than government dictate). In particular, the major projects CLiSP (in secondary school) and SPACE (at primary

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level) (§4.2.1) were developed with practicing teachers, reported widely in practitioner journals and at teacher meetings, and developed materials that were widely used by teachers. Secondly, the very ‘blandness’ of the constructivist approach taken in the guidance materials (the choice of the teacher-friendly term ‘misconception’, the implication that constructivist teaching need not require major changes as long as ideas are elicited, and responses incorporated into schemes of work!) allows the recommended pedagogy to be considered as useful ‘add-ons’ to existing teaching practice, rather than a radical change of approach. Indeed, Kaymaz undertook a case study of a science teacher in an English school with a reputation as a particularly effective practitioner. Kaymaz found that although the curriculum requirements were restrictive, the teacher’s expressed beliefs and actual classroom practice generally demonstrated a ‘constructivist’ approach. However, when she was asked about constructivism, the teacher reported that she could not recall ever having come across the term (Kaymaz, 2007). Whilst it is clearly not sensible to generalise from a single case study, this finding offers an intriguing reflection of how constructivist ideas appear to have insidiously become part of expected pedagogy in England. Despite the criticisms of the limited impact of the RP on practice (§5.5.1), Osborne and Simon (1996: 112) have suggested that ‘research conducted from this perspective has had a phenomenal impact because it forced a sea-change in the perception of children as atheoretical individuals, where the function of teaching and learning is to provide children with new concepts and ideas, to one where children have theories which must be challenged and reconstructed anew’.

5.6

Constructivism in Science Education As a Degenerate RP

The situation in England does not necessarily reflect that in other educational systems, but offers an example of an education context where basic constructivist principles had shifted from the research agenda to being seen as unremarkable features of teacher thinking. In 1993, Russell and Osborne (1993: 17) suggested that ‘constructivism has already had an enormous impact on science education at all levels’, but in the following year Solomon (1994) was suggesting that the constructivist RP seemed to have lost direction, and drew attention to what she suggested might be considered as the ‘fall’ of constructivism. She suggested that constructivism, which had become seen as the most significant perspective in Science Education for several decades, had outlived its usefulness, and that perhaps it was time for the Science Education community to ‘move on’. In terms of Lakatos’s model (see Chapter 3), Solomon was suggesting that the constructivist RP could be considered as ‘degenerate’. Lakatos considered that a programme became degenerate when it was no longer empirically and theoretically progressive.

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The position taken in this volume is that the RP associated with the constructivist label (i.e. the RP set out in Chapter 4) is indeed progressive, and therefore working within the programme remains a rational choice for researchers interested in learning in science and informing science pedagogy. Lakatos’s model of progress in science sees RP as in competition, and predicts that researchers will choose to work in a programme that they consider to have the most potential, i.e. the one that is most progressive in terms of its heuristics guiding researchers to develop the empirical and theoretical content of the programme. Solomon (1994: 17) argued that constructivism was ceasing to act as a fertile stimulus to research, and that ‘if constructivism obscures other perspectives, either by its popularity or its blandness, that could be damaging’. Jenkins (2000a: 608) has suggested that ‘the attention devoted to constructivism in school science teaching may have served to narrow the professional and the research agenda within science education’. A similar view has long been held by Alex Johnstone who has publicly suggested that constructivism has been given disproportional attention in relation to its potential to inform effective science teaching. He has suggested that an information-processing perspective would be more fruitful (Johnstone, 1989, 1991). Johnstone (2000a: 35) has pointed out that ‘the International Journal of Science Education has devoted over a third of its space to work on “Alternative Frameworks” ’ and has argued that ‘this has tended to encourage an approach to research which was negative and offered few solutions to the problems exposed’.

5.6.1

Constructivism As the Basis of a Progressive RP in Science Education

The position argued here is that the RP set out in Chapter 4, the ‘constructivist’ RP in Science Education, is empirically and theoretically progressive, as (a) it has developed its protective belt of theory alongside and through studies that have built up an extensive database on aspects of learners’ scientific ideas and thinking (see Chapter 6); and (b) this progress has allowed refinements of the broad research questions initially suggested by the hard core, giving more nuanced directions for further research (see Chapter 7). Whilst progress has not been even across all aspects of the programme, this can be understood in terms of the complexity of the phenomena studied, and reflects quite understandable shifting priorities as the programme has matured. This general position is illustrated in the final two chapters, which consider first (in Chapter 6) what the RP programme has achieved to date, i.e. a consideration of how the protective belt of the programme has been constructed; and then (in Chapter 7) potentially fruitful directions for further research, i.e. how the research questions presented in Chapter 4 have been refined and elaborated by the work already undertaken within the RP.

Chapter 6

Building the Protective Belt of the Progressive Research Programme

Chapter 5 examined major areas of criticism of the tradition of work often labelled as ‘constructivism in Science Education’. Among these were suggestions that research in this tradition has offered little of use to inform teaching, and that – in effect – the constructivist ‘bandwagon’ had ceased to offer useful insights to progress the field. By considering each of the main directions of research suggested by the positive heuristic of the RP into learning in science characterised earlier in the book (Chapter 4), the present chapter offers an overview on what has been found out through several decades of scholarship. It is argued that progress has been uneven, and that there are not yet clear answers to most of the key research questions. Despite this, the body of literature that has developed offers a wide range of models and constructs, informed by diverse empirical evidence. It is argued that taken together this work provides the basis for understanding why simple answers have not often been forthcoming by highlighting the complexity of the phenomena studied (learning and teaching). Moreover, the various ‘refutable variants’ that have been proposed by those exploring the central research questions, now provide a rich set of conceptual resources for further learning in the field. Chapter 1 provided some historical background to the development of the ‘alternative conceptions’ or ‘constructivist’ perspective in science, that was set out in a series of seminal papers a quarter of a century ago (Driver & Easley, 1978; Gilbert et al., 1982; Driver & Erickson, 1983; Gilbert & Watts, 1983; Osborne & Wittrock, 1983). Chapter 4 presented the ‘hard core’ of ideas that informed the research reviewed, reported and prescribed in those papers, modelled as a Lakatosian RP (as explained in Chapter 3), showing how the hard-core assumptions provided heuristic guidance for an extensive programme of research. The ‘protective belt’ of a RP comprises the body of theory which grows up around the hard core – ‘the auxiliary hypotheses should be formed in accordance with the positive heuristic of a genuine research programme’ (Lakatos, 1970: 182) – but which is itself in flux. So, for Lakatos, it is perfectly possible for theory to change within a RP, as a ‘series of theories are usually connected by a remarkable continuity which welds them into research programmes’ (p. 132); provided that the developing theory remains true to the hard core of the programme, i.e. that ‘the successive modifications of the protective belt must be in the spirit of the heuristic’ (Lakatos & Zahar, 1976/1978: 179). K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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In a Lakatosian RP, the theory making up the protective belt of a programme is a sequence of models, ‘the ‘refutable variants’ of the research-programme’ (Lakatos, 1970: 135), that are ‘bound to be replaced during the further development of the programme’ (p. 136). That is, ‘work within a single research programme involves the expansion and modification of its protective belt by the addition and articulation of various hypotheses’ (Chalmers, 1982: 84). The present chapter offers a selective review of work in the field (considered here to fall within the RP in Science Education characterised in Chapter 4) to give an overview of progress since the implicit establishment of the RP over the period c.1978–1983. Fensham (2004) has suggested that there has been progression in what he identifies as the ‘sub-area’ of Science Education concerned with alternative conceptions and conceptual change. He has identified several phases of work in this sub-area (Fensham, 2004: 135):• • • • •

1973 – rediscovery of students’ views as an area of interest 1979 – studies of alternative conceptions 1982 – studies of conceptual change 1988 – studies of concepts and context 1990 – studies of social dimensions of conceptual change; and studies of the origins of alternative conceptions

This is of course a necessarily over-tidy simplification of the complexity of the literature, but it is certainly possible to identify such ‘fronts’ in the work within the RP. The present chapter does not offer a chronological account following Fensham. It would be possible to do this, and indeed a historical account might illuminate well the interaction between different workers and research groups, and could highlight the interplay between theoretical and empirical developments. However, to do justice to such an account would require a substantive volume by itself. Rather, the chapter is organised into three related themes that link back to the structure of the RP as set out in Chapter 4: • The ideas elicited from students • The processes of learning and the development of learners’ thinking • The task of teaching science The reader will appreciate that these issues cannot be considered in isolation from each other, and research in one area has been informed by and has built upon studies with another focus. Rather than attempt a chronological analysis, the chapter therefore follows an ordering of material that should offer a more logical structure for the reader in terms of which areas of work are most dependent upon others. Nonetheless, some repetition and cross-referencing has been necessary to offer a coherent account of the main themes. At the end of the chapter, the account will be related to the Lakatosian model. I am aware that in offering this particular reading of the field, the view offered is more synthetic than some other commentators would feel is justified. This might seem to be a rhetorical strategy for giving the appearance of a coherent RP. This is

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not the intention, but rather I recognise that my tendency to conceptualise this work in an inclusive manner – seeing work by people who may not consider their research as within the constructivist tradition as fitting in the RP; considering the social constructivist view (see §5.4) as being sufficiently compatible to personal constructivism to offer a distinct ‘refutable variant’ rather than an alternative RP – is what leads me to feel that the broad Lakatosian methodology of SRP (see Chapter 3) offers a suitable model for examining constructivism in Science Education. I suspect that the tendency to be either a ‘splitter’ or a ‘clumper’ (Lewin, 1989) reflects a cognitive style, and that some of those who would tend more to be ‘splitters’ may well take issue with my personal conceptualisation.

6.1

Students Understanding Science

One focus of the RP has been the ideas that students hold about scientific topics – both in terms of what they think, and the characteristics of their thinking (such as match to curriculum knowledge and coherence). Many terms have been used to label the outcomes of research into students’ thinking about scientific topics (§5.3.4). For the moment, the reports of students’ thinking will be discussed as ‘ideas’ (Driver et al., 1985), which is considered a fairly neutral term (Black & Lucas, 1993).

6.1.1

Challenges of Exploring Student Thinking

There are three sets of related issues which complicate the literature in this area, and which make it difficult to provide a coherent account of the state of the field that fully reflects the wide range of relevant studies (e.g. see §5.3). These issues relate to: • The nature of the phenomena studied and described, and in particular the extent to which the focus of research is student ideas and thinking or the representation of knowledge in the mind • The nature of the reports made, i.e. ‘findings’ are always necessarily the researchers’ models, based on their interpretations of data (see Fig. 4.1): however, in some cases reports are presented as if being accounts that correspond to the phenomena with minimal reconstruction by the researchers, and in other cases as abstractions that have been deliberately simplified, generalised, etc. to highlight what are considered by the researchers as key patterns, significant trends etc. • The terminology which has been adopted having little commonality, and so the same term may be used in very different ways or quite different terms used in different studies to label apparently the same or very similar phenomena

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A Rational Reconstruction of the Literature on Learners’ Ideas in Science

In offering an account of this area of work, it is important to acknowledge both (a) these challenges to a coherent reading of the literature, and (b) the likelihood that these issues have at various times impeded communication between research groups, and so retarded progress in the RP. However, it is also considered important to offer readers (and especially those looking for an introduction to this area of scholarship) a framework for making sense of the diverse literature. This is especially so when arguing that this work can be seen to make up a progressive RP: something that may not always be obvious when surveying the apparent confusions and complications across the literature. The approach in this chapter, then, is to offer a reading of the literature that reflects the author’s own thinking about the field. This will be a reconstruction, with the perspective of something like a quarter of a century of hindsight in the case of some of the research. Whilst wishing to avoid distorting other researchers’ work, inevitably assimilating their ideas and arguments into my own mental schemes I will have re-interpreted the intended meanings. From the constructivist perspective of the RP that I am championing, I do not see how it could be otherwise. Inevitably for some of the earlier work referred to here, the original authors would in any case now see their studies somewhat differently from when they were writing – as subsequent research, reading and other experiences will have deepened and developed their own thinking about their studies. (That does not necessarily imply that my own reading of their work will align with any shifts in their own thinking.) The responsibilities of the author in this matter, it is suggested, are to (1) acknowledge that in attempting to provide a coherent account, some distortion is likely (which I have done); (2) to avoid any deliberate distortions of other’s work; and (3) to offer a reconstruction that provides a useful introduction to the vast literature. Given that other readings are possible, I would hope that readers new to the literature might access some of these studies to form their own interpretations. In particular, the account here attempts to rationalise the use of terminology related to learners’ ideas, without wishing to underplay the genuine disagreements about the nature of student thinking that different choices of terms sometimes reflect.

6.1.3

What Ideas Do Learners’ Bring to Science Classes?

As suggested in previous chapters, the RP has reported on aspects of student thinking across different levels of education, a diverse range of science topics, and to some extent a wide range of educational contexts. That is, studies exploring students’ ideas have been undertaken in many countries, although in particular contexts, sometimes in only a small range of topics. Overall, however, there is

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now a vast literature on learners’ ideas. A valuable resource here is the web-based Bibliography – Students’ and Teachers’ Conceptions and Science Education compiled by Reinders Duit at Kiel University (Duit, 2007). In 1978, Driver and Easley were able to describe naturalistic studies based on clinical interviews as ‘usually small scale and scattered’ (Driver & Easley, 1978: 77). By the end of the following decade over a thousand papers were catalogued (Carmichael et al., 1990). The latest (2007) version of the Duit bibliography includes well over 7,000 entries. Jenkins (2000b: 6) has suggested that many of the studies show a bias towards traditional curriculum topics rather than ‘trans-or inter-disciplinary concepts that characterise many of the public discussions of science in the broadcast or printed media’, but even in these areas (risk, environmental issues, etc.) there are now increasing numbers of studies. It is clearly not possible to review all these studies here or indeed in any one manageable volume. A good attempt at doing this for school science in a single readable volume was Driver and colleagues’ ‘Making Sense of Secondary Science’ (Driver et al., 1994), although this is now somewhat dated. Here the focus will be on the nature of learners’ ideas rather than the specifics. However, some examples will be considered here which will be drawn upon later in the chapter. Three topics have been selected, one from each of the main science disciplines, and a brief account of some of the findings of student thinking will be reported in each. These topics have been selected partly as they reflect important topics in physics, biology and chemistry respectively, but also because they offer insights into complementary aspects of students’ thinking about science topics. The accounts are necessarily brief and intended to support points made later in the chapter rather than being comprehensive.

6.1.3.1

Force and Motion

Newton’s laws of motion offer an example of a scientific conceptual framework. Newton’s ideas about force and motion are often considered to have initiated a scientific revolution (Cohen, 1985), and ‘the three laws of motion and the law of gravitation’ are given by Lakatos as an exemplar of ‘a tenacious hard core’ of a SRP (Lakatos & Zahar, 1976/1978). Newton-1 (i.e. Newton’s first law of motion) may be stated as: A body will remain in a state of rest, or uniform linear motion, unless acted upon by a resultant external force. Indeed the rest state may be considered a special case of uniform motion when velocity is zero: the significant point is not the velocity (or lack of it), but the absence of change in velocity. Within Newton’s scheme rest and uniform motion are considered in the same way. Newton-2 may be stated: The rate of change of momentum of a body is directly proportional to the magnitude of the resultant force acting on the body, and takes place in the direction of the applied force. It follows that if the resultant force is zero then there will be no change in momentum (which is equivalent to Newton-1). The body’s mass is said to be a measure of its inertia (i.e. ‘the property of a body

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by virtue of which it tends to persist in a state of rest or uniform motion in a straight line’ (Pitt, 1977). Newton–3 concerns what is commonly termed ‘action and reaction’, and may be stated: When a body A exerts a force on a body B, then body B exerts a force on body A which is equal in magnitude, anti-parallel in direction, and which acts along the same line of action. Newton’s Law of Universal Gravitation states that such a force-pair occurs between any two masses. There has been considerable research into learners’ thinking about this topic area. Among the alternative ideas that students have been reported to hold are: • Forces are considered to be associated with individual bodies, rather than interactions between bodies (Watts, 1983; McCloskey, 1983; Viennot, 1985). • Forces are associated with an effect, and especially movement: that is movement implies a net force acting (Watts, 1982; Watts, 1983; Gilbert & Zylbersztajn, 1985; Viennot, 1985). • Stationary (rather than non-accelerating) is seen as something of a ‘natural’ state of affairs (Driver, 1983; Gilbert & Zylbersztajn, 1985). • A ball dropped by a moving person would drop vertically (McCloskey, 1983). • A horizontally launched projectile moves horizontally at first, then curves, before finally falling vertically (McCloskey, 1983). • An object with circular motion would continue to move in a curved path (McCloskey, 1983; Linder et al., 2007). • The larger of two interacting bodies will exert a greater force on the smaller (Watts & Zylbersztajn, 1981; Driver, 1983). • A range of different meanings have been identified as associated with the scientific term ‘force’ (Watts, 1983), although only a small number may be very common (diSessa et al., 2004).

6.1.3.2

Plant Nutrition

The area of plant nutrition has also been widely studied (Wood-Robinson, 1991). This was, for example, one of the topics included in the Children’s Learning in Science Project (§4.2.1), which looked at secondary level students’ understandings of the topic (Bell & Brook, 1984). Among the ideas elicited from students, it was found that for many students plants obtained their ‘food’ directly from the environment, e.g. from the soil. Students who learn about photosynthesis will readily accept that this can only take place during daylight, and may see photosynthesis and respiration as alternative means for a plant to get energy – photosynthesis during the day, and respiration during the night when there is no light available. Students who had learnt about photosynthesis and apparently understood the process have been found to nonetheless explain that most of the material in a tree had got there by being taken in through the root systems. Cañal offers a summary of common conceptions about plants that are found among primary age students (Cañal, 1999: 365):

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1. Plant nutrition is the process through which plants feed themselves. 2. Plants are nourished by the substances that they take from the earth through their roots: water and mineral substances. 3. The substances that plants absorb from the earth form raw sap, which moves through the stalk and which allows the plant to grow and carry out its other vital functions. 4. Sunlight is indispensable for the health of green plants, their strength and good colour. Without light, they become weak and may end up dying. 5. Plants breathe like animals, taking in and expelling air. If they do not do so continuously they asphyxiate and die, like people. That is, pupils tends to appreciate that plants need gaseous exchange and light but tend to model their understanding of plant nutrition on their familiarity with human/ animal nutrition, where material has to be absorbed in condensed states to provide material for growth and other functions.

6.1.3.3

Atomic Structure and Chemical Bonding

Much of chemistry is explained in terms of models at the ‘submicroscopic’ level, i.e. in terms of atoms, molecules, ions, electrons and so forth. Particle models are often introduced early in secondary science, and used initially to explain the properties of the principle states of matter (solid, liquid, gas) before discriminations are made between atoms, molecules and ions. However, later in secondary school a basic model of atomic structure is used to explain the elements and the periodic table, and (by considering models of chemical bonding) the structure and properties of different substances. At higher educational levels, the sophistication of the models used increases, e.g. from modelling atomic structure in terms of shells of electrons, to models involving electronic orbitals. A wide range of student ideas at odds with scientific thinking have been identified in a range of studies undertaken in various contexts (Wightman et al., 1986; Lijnse et al., 1990; Johnston & Driver, 1991; Griffiths & Preston, 1992; Harrison & Treagust, 1996, 2000; Johnson, 1998a, 1998b; Taber, 1998a, 2001b, 2003c; Adbo & Taber, 2008; García Franco & Taber, 2008). These ideas include: • The atoms/molecules of a material share material properties such as shape, colour, conductivity, malleability etc. • The particles (atoms/molecules etc.) in a material change (e.g. melt, expand) in the same ways as the material. • The particles (atoms/molecules etc.) in a material are embedded in the material. • The particles (atoms/molecules etc.) in a material have air between them. • Everything is made from atoms. • Atoms are indivisible and the smallest particles possible. • Atoms want to fill their shells, and reactions occur so that atoms can do this. • Atoms will spontaneously eject electrons to have full electron shells. • Covalent bonds form by atoms sharing electrons to fill their shells.

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• Ionic bonds form by an atom with an extra electron donating it to one with insufficient electrons so that they can both have full shells. • Electrons move around the atom in trajectories called orbitals. These very brief sketches of what studies have discovered about student thinking in just three topic areas offer a flavour of the nature and range of student ideas that the RP has uncovered. Understanding the nature and significance of such ideas continues to be a main theme for the programme.

6.1.4

What Is the Nature of the Ideas That Learners Bring to Science Classes?

Reddish (2004: 4) has discussed the need to develop what he terms ‘a mesoscopic thermodynamics of thinking – that provides a useful ontology for constructing mechanisms’. As discussed in Chapter 5 (§5.3), one area of criticism of the constructivist RP has been that the description of learners’ ideas and thinking in literature has been confused and includes a wide range of distinct terms which seem to often be meant to refer to the same or overlapping entities; and more tellingly that the characteristics assigned to the reported ‘conceptions’ and ‘frameworks’ were insufficiently supported in the literature. It was argued in Chapter 5 that this was an important area of criticism, but should not be seen less as a fault in the RP per se, but rather as part of the discussion that was proper business within the RP. In this part of the chapter, some key aspects of that debate will be explored. diSessa, Gillespie and Esterly (2004: 845) have suggested that ‘among the fault lines in conceptual change research, one of the most contentious and probably among the most consequential concerns the nature of uninstructed knowledge’. The key discussions about learners’ ideas relate to the extent to which the ideas elicited from students are: • Stable over time • Strongly committed to • Theory-like, in terms of – Comprising of networks of related propositions – Being coherent and self-consistent – Being applied across a range of contexts – Being explicitly applied This is a critical issue for the RP, as (a) the justification of the RP rests on the claimed significance of learners’ ideas; (b) the hard core of the programme includes an assumption that teaching can be informed by knowledge of learners’ ideas (§4.4), so the positive heuristic motivates studies into this research focus; (c), as will be seen in the pages that follow, different researchers have made very different and inconsistent claims about the nature of students’ ideas, so that part of being a progressive RP requires this issue to be addressed (i) empirically by collecting data

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to test out various claims; and (ii) theoretically by developing within the ‘protective belt’ models to explain and predict the findings of empirical studies. In the pages that follow some of the models of aspects of learners’ thinking, the ‘refutable variants’, proposed within the RP will be reviewed. In reading through this section it is worth noting how straightforward but mutually inconsistent claims come to be subsumed within a more complex picture that can accommodate diverse research findings.

6.1.4.1

Learners Demonstrate Alternative Conceptions in Scientific Topics

One of the terms commonly used to describe learners’ ideas in science is ‘conception’. Gilbert and Watts (1983: 69) proposed that ‘conception’ ‘be used to focus on the personalised theorising and hypothesising of individuals’. ‘Conception’ has been defined as ‘that type or level of cognitive process which is characterised by the thinking of qualities, aspects, and relations of objects, at which therefore comparison, generalisation, abstraction, and reasoning become possible, of which language is the great instrument, and the product the concept – normally represented by a word’ (Drever & Wallerstein, 1964: 47). The term ‘concept’ is widely used in the cognitive sciences (although again the nature of ‘concepts’ is subject to debate, cf. §1.2), and the elicitation of conceptions implies that in some sense students have available relevant concepts (although not necessarily matching scientific versions). A conception may be understood as a notion that can be represented by a proposition, such as ‘moving objects possess momentum’, ‘a shark is a big fish’ or ‘learners have alternative conceptions about science’. An alternative conception is a conception that is inconsistent with the science represented in the curriculum, such as ‘moving objects use up their impetus’, ‘a whale is a big fish’. (Note, in practice the terms alternative conception and alternative framework have often been used as if synonymous, but here framework will be reserved for a somewhat different meaning.) The term ‘conception’ would seem to be a fairly neutral one, implying little more than that learners offer verbal statements demonstrating explicit conceptualisation. Such conceptions could be of a variety of forms, such as: • • • • • • • •

Movement of a body implies a net force acting The stationary state is a ‘natural’ state that does not need to be explained Plants have leaves Plants grow by taking material from the soil Mushrooms are plants Atoms with full shells are always stable There are two types of chemical bond Polar bonds are a type of covalent bond

Such conceptions then can relate to beliefs or conjectures about the way the world is, the properties of certain classes of entity which exist in the world, why

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certain things happen, how parts relate to wholes, how to group entities in the world, etc. That students demonstrate such conceptions is widely acknowledged (even if the term ‘conception’ is not always used, and the significance of students’ conceptions is sometimes disputed) and so it will be taken here as common ground for the RP. In particular, ideas elicited from students that do not match scientific knowledge (or the curricula models in the science curriculum) have been labelled as ‘preconceptions’, ‘misconceptions’ or ‘alternative conceptions’. Driver and Easley (1978) wrote the first of the papers identified earlier as being seminal for the RP. Their paper began with an extract from two 14-year-old pupils discussing thermal expansion, and referring to the molecules expanding, and to the ‘heat molecules’. Driver and Easley asked about the status of such statements: whether they were ‘misconceptions, errors, partial understandings or misunderstandings’ (p. 61)? They considered Ausubel’s term ‘preconceptions’ could be considered to exclude explicit theoretical notions, and they felt the term ‘misconception’ implied a misunderstanding of formally taught material, and so excluded notions developed outside of a teaching context. The general term used here then for an idea elicited from students in the RP will be conception, and in particular alternative conception where the elicited idea is inconsistent with scientific and/or curriculum models.

6.1.4.2

Alternative Conceptions May Sometimes Be Tenacious and So Not Be Extinguished by Teaching

Ausubel (1968: 336) had claimed that (what he termed) preconceptions could be ‘amazingly tenacious and resistant to extinction’, which he related to his characterisation of such conceptions, suggesting this could be because: • The influence of such factors as primacy and frequency. • They are typically anchored to highly stable, related, and antecedent preconceptions of a more inclusive nature. • They are inherently more stable (e.g. more general; less qualified; expressive of a positive rather than inverse relationship; predicated on a single rather than multiple causality or on dichotomous rather than continuous variability). • Resistance to the acceptance of new ideas contrary to prevailing beliefs seems to be characteristic of human learning. Early papers within the RP characterised some of the ideas elicited from students as stable and sometimes tenacious aspects of student thinking (Gilbert & Watts, 1983). It was of course this feature of learners’ ideas that had justified their study within the RP, for as Driver, Guesne and Tiberghien (1985: 3) pointed out, ‘it is often noticed that even after being taught, students have not modified their ideas in spite of attempts by a teacher to challenge them by offering counter-evidence’. Of course, those researchers who argue that learners’ conceptions are ‘stable’ do not consider them to derive from immutable knowledge structures, or there would be little purpose in advising teachers how to bring about conceptual change.

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However, research suggests that some alternative conceptions seem to be largely unaffected by teaching which directly contradicts the learners’ conceptions and presents inconsistent ideas to be learnt. Driver (1983: 38) reported that ‘even when pupils appear to have understood an idea or principle, they revert to alternative frameworks for their intuitions when faced with slightly novel tasks’. Hammer (1996: 99) has summarised the notion of (alternative) conceptions that: • Are strongly held, stable cognitive structures • Differ from expert conceptions • Affect in a fundamental sense how students understand natural phenomena and scientific explanations • Must be overcome, avoided, or eliminated for students to achieve expert understanding Smith and Anderson (1984) report a case study of a US fifth-grade class undertaking a unit of work on plant growth and photosynthesis, and discuss how the teachers’ attempts to follow the course guide were sometimes compromised by the pupils’ existing conceptions, The students’ ideas that water and fertilizer are food for plants had surfaced several times in discussions of the experiment in which students attempt to germinate various seed parts… Given these ideas of what plants’ food is, they frequently stated that plants get food from the soil. On these occasions, Ms. Howe tried to lead them to the conclusion that plants do not get food from the soil, a point emphasized in the teacher’s guide. However, because their underlying conceptions of food as materials plants take in remained unchanged, her efforts were difficult for the students to understand. Ms. Howe repeatedly cited the growth of seeds in the germination systems (which contain no soil) as evidence that plants do not need soil or fertilizer to grow. She developed the idea that fertilizer makes plants healthier, but is not necessary for growth. While this idea was understandable to the students, from their point of view this did not necessarily imply that fertilizer is not food. (Regarding humans, for example, an argument like Ms. Howe’s could be made about broccoli; broccoli is good for people, but they can get along fine without it.) (Smith & Anderson, 1984: 690)

One of the issues for the RP has been the contrary claims about the nature of learners’ ideas, so that despite many reports that learner’s ideas are often stable and tenacious, other commentators (as will be shown below) claim that learner’s ideas are often transient if not ephemeral. One key feature of the debate concerns the methodology, whereby (cross-sectional) comparisons of different groups may only strictly allow group comparison, and no strict inferences about the degree of stability of individual thinking (Arzi, 1988: 41). For this, longitudinal studies of individual learners are needed (see Chapter 7). I have reported a case study of a student known as Annie who held an unusual alternative conception through most of her 2-year college (age 16–18) chemistry course (Taber, 1995b). Annie interpreted the charge symbols used to indicate ions (+, −, 2 +, etc.) to mean a deviation from a full shell or octet configuration. For Annie, Na+and Ca+ +, for example, would indicate the atoms with their ‘extra’ electrons in their outer shells, whilst Cl− indicated that a chlorine atom was an electron short of an octet. Despite being interviewed at several points in her course, it only became clear that this was how Annie understood the notation near the end of her course. Annie had managed to reinterpret the various teaching over the 2 years in terms of her own

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meanings for the symbols without her, her classmates, or her teachers, spotting this. Such an example is of particular interest, as her conception persisted without any apparent reinforcement through shared use with other students.

6.1.4.3

Conceptions Elicited from Learners May Sometimes Be Constructed During the Elicitation Process

Although some alternative conceptions elicited from learners (in research, or during classroom teaching) may reflect stable and long-standing knowledge representations, this is clearly not always the case. That learners are demonstrating conceptions shows they are operating with concepts. This leaves open the question of the extent to which elicited conceptions reflect novel conceptualisation in situ, or the activation of conceptual knowledge already represented in memory. It follows from this that the researcher cannot assume that learners are strongly committed to the conceptions that they report thinking. This was recognised by Piaget (1929/1973: 21), who referred to young children ‘romancing’ answers to questions, when they did not have a ready response available: ‘when the child, without further reflection, replies to the questions by inventing an answer in which he does not really believe, or in which he believes merely by force of saying it’. Claxton (1993: 45) suggests that we may readily interpret an idea elicited from a student as reflecting some ‘sturdy’ feature of thinking when it ‘need be no more that the ephemeral reflection of a purpose-built and tentative attempt to cope with the social and intellectual demands of the present moment’. (It will be suggested below that this can be explained in terms of ‘facets’ of knowledge being formed by the mapping of an existing knowledge structure called a ‘p-prim’ onto a novel question or topic.) This is certainly not to suggest that all conceptions elicited from learners are created in the context of the research process, rather than being reports of existing features of conceptual structures represented in memory. An overview of the literature strongly indicates that it is not helpful to see these possibilities as exclusive alternatives (i.e. either research informants are forming new conceptions as they respond to research probes, or they are simply reporting conceptions that are already represented in memory), as neither extreme view can do justice to the findings reported. Rather, the real issues for the RP are to what extent, and when, do elicited conceptions reflect concepts being formed in the process of research elicitation rather than existing conceptual resources being drawn upon from memory.

6.1.4.4

The Relationship Between Thinking and Knowledge Structures

One of the complications identified above is the distinction between the ideas that a learner experiences when thinking (i.e. during cognitive processing) – and so

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which may be inferred by researchers from learners’ behaviour (e.g. answering a question) – and the underlying brain structures that facilitate the individual’s thinking. This distinction is itself based on assumptions about the nature of key phenomena. The model assumed here is that learners’ thoughts are transient, and reflect aspects of (a) underlying cognitive apparatus; (b) knowledge somehow represented physically in the brain (see §6.2.1.1); and (c) current immediate perceptual information (e.g. about a particular question, worded in a particular way, asked by a familiar teacher, or maybe a mysterious researcher, with a certain tone of voice, etc.). As Claxton (1993: 45) points out, research exploring learners’ ideas only ever reveals ‘their mobilization and application of [their] knowledge in a situation that embodies an unprecedented question, and in which a unique nexus of opportunities, priorities, abilities, constraints and personal history is present’. There are several challenges here then for researchers. There are issues relating to the means by which a researcher can effectively interpret and model the ideas expressed by the informant. Then there are issues relating to the extent to which the process being indirectly inferred reflects stable features of underlying mental structure – which is often the intended focus. Phillips (1987: 139) has suggested that some of those who report research in this area are not very clear in distinguishing the precise nature of the findings they report (i.e. the ontological status of the phenomena reported), and clearly this situation is not helped by uncertainty about how knowledge might be represented in the brain (see §6.2.1.1). These complications make it difficult to separate out debate about the nature of the ideas elicited from learners and the best ways of representing and modelling student thinking about scientific topics and underlying aspects of conceptual structures (as represented in memory). There is a danger of confusing four related, but distinct questions • What is the nature of student thinking about science topics? • How can we best model student thinking about science? • What is the nature of the knowledge structures represented in memory that support student thinking about science topics? • How can we best model aspects of these conceptual structures

6.1.4.5

Elicitation of Conceptions May Involve Verbalising Tacit Knowledge

One of the terms used by researchers to refer to some of the ideas elicited from learners early in the RP was ‘intuitive theories’. Driver and Easley (1978: 62) dismissed the term ‘preconception’ as a descriptor for the conceptions elicited from learners as they felt this did not fit what had been termed ‘intuitive theories’. Pope and Denicolo (1986: 154), for example, described how work within the Personal Construction of Knowledge group (§4.1.6), had been ‘concerned with the investigation of intuitive theories held by pupils, students and teachers about a range of

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topics, e.g. scientific concepts such as energy, the nature of learning and teaching, the role of metaphor in explanation’. Clearly the term ‘intuitive theory’ suggests knowledge elements that are part of an individual’s intuitions about the world, and that may be considered as theoretical. It is probably useful to consider these two features separately. Whether learners’ conceptions reflect theoretical knowledge, in the sense that scientific knowledge is theoretical (i.e. theoretical knowledge would normally be expected to have certain properties, such as being coherent, based on principles that can be made explicit, and having well-defined and usually broad ranges of application), will be considered below. To suggest that conceptions elicited from young children and school pupils, for example, derive from intuitive knowledge is to imply that this is knowledge that is in some sense ‘tacit’ (Polanyi, 1962), and is normally applied without explicit rationalisation and/or verbalisation. Kelly, in his Personal Construct Theory (§1.6.3) recognised that individuals commonly operate with knowledge elements (e.g. behave in making discriminations on the basis of knowledge somehow encoded in the brain) that are tacit. His elicitation technique of ‘triads’, basically asking informants to select the ‘odd one out’ from three presented elements (Fransella & Bannister, 1977; Taber, 1994a), was devised as a means of identifying those discriminations that individuals might make using constructs of which they were not explicitly aware. Such intuitions could be ‘instinctive’ in the sense that many living things show instinctive behaviour – adult birds ‘know’ how to feed their young, fish ‘know’ how to swim, etc. (Whether the representations within the nervous system that enable such behaviour by non-human animals are best considered a form of ‘knowledge’ is a moot point.) However, intuitive knowledge does not have to be innate: learning can lead to the development of intuitions. diSessa (1993: 175), whose model of phenomenological primitives and ‘knowledge-in-pieces’ will be explored later in the chapter (§6.2.2.3), takes this view, and suggests that enquiries into student thinking suggest that much knowledge is represented in inarticulate forms: ‘empirical results … indicate complex, conflicting, and unreliable strands of reasoning in which students may be guided by aspects of the circumstances that they cannot articulate or check’. This is seen as the source of some alternative conceptions. For example, earlier in the chapter it was suggested that many students develop conceptions about force and motion such as associating movement with a net force. However, it could well be that this association is usually intuitive and largely applied in physical activity (catching, throwing, batting, ducking, etc.). In a research context, an individual may be presented with various pictures cards representing different situations and asked if there is any force present (i.e. Interview-about-Instances, see Chapter 7, §7.3.3.1). In this context, the respondent will verbalise their intuitions, and report them in terms of ‘force’ and ‘movement’ even if the knowledge was not previously represented in his form. Once an idea is verbalised it may well become memorised in this form, and so become available explicit knowledge, and so recur in similar formulations on subsequent questioning, even though not previously represented in that form before the initial questioning. Whilst such ‘gut’ knowledge

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may not fit into the canonical formal scientific conceptual frameworks, it may offer a basis for mental simulations which allow individuals to predict physical outcomes in scenarios set under familiar conditions, e.g. where gravity and friction operate as in common everyday experience (Georgiou, 2005).

6.1.4.6

Elicited Student Conceptions Often Reflect Life-world Thinking

Commentators such as Solomon and Claxton felt that students’ informal knowledge is changing all the time. Solomon (1992) discussed Pine’s doctoral research into young children’s ideas in a range of science topics, which suggested children’s notions changed over time as well as being multifaceted and dependent upon context. She also pointed out how research into various topics had demonstrated how children seemed to quite readily move between applying different ideas, even in a single interview. Claxton (1993) also argued that student thinking about a topic often seemed to reflect a wide set of distinct ideas that are applied locally, according to the perceived context. In discussing children’s informal ideas in science, Solomon has drawn upon the notion of the ‘life-world’, a term used to describe the world of our immediate experience (Laughlin, 1994) – that is, the world as subjectively experienced in Popper’s World 2 (§2.2.2), and which acts as the ‘reality’ that is modelled in Glasersfeld’s radical constructivism (§5.2.6). Solomon (1993b) has suggested that one should distinguish between what she labels ‘the natural attitude’ and ‘symbolic universes of knowledge’. She highlights four important distinctions between scientific thinking, and everyday ‘life-world’ thinking, pointing out that (Solomon, 1993b: 92–93): • Whereas ‘the aim of debate [in science] is to sharpen differences and to confirm or refute rival opinions’, in the life-world ‘social exchanges try to achieve a mutual understanding and agreement’. • Although ‘concept words are unambiguously defined for exact use’ in science, in the life-world ‘words used have multiple meanings which are … negotiated socially’. • Whereas in science ‘concept meanings are symbolic and abstracted from any particular situation’, in the life-world ‘meanings are dependent on the cultural group and on the physical or affective context’. • Although science aspires to and claims ‘a tight logical network of concepts and theories’, life-world knowledge tolerates ‘apparent contradictions’. Evidence of learners applying the ‘natural attitude’ is evident in the loose way that learners use technical words that have life-world currency such as energy and force (Watts & Gilbert, 1983). Although science teachers might model scientific ways of thinking to classes, Solomon (1993b) pointed out that the life-world knowledge system ‘is well socialized by daily use with familiar people’. From this perspective, children would be

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expected to enter school already socialised into the ‘natural attitude’, and to only later learn about alternative scientific knowledge systems as a specialised way of thinking met in the formal curriculum. Aikenhead (1996, 2006) has compared the transition students make when entering the science classroom as ‘cultural bordercrossing’ (whilst acknowledging that the extent to which such ‘borders’ are crossed will vary considerably among different cultural groups). Arguably, other school subjects also teach about symbolic universes of knowledge that share characteristics with science – that knowledge represented in a school curriculum is in effect ‘World 3’ knowledge. Nonetheless, it is seen as an alternative specialist way of thinking that has to be acquired during schooling. Driver had recognised that most schoolchildren do not instinctively think like scientists (thus her book –The Pupil as Scientist? (Driver, 1983) – questioning the value of unguided discovery learning), but rather than the scientific attitude has to be acquired. Biologist Lewis Wolpert (1992) has also written about the ‘unnatural’ nature of scientific thinking. For Solomon, ‘children’s science’ is less an untutored alternative to school science, than something that has persistence and social value, as – for children and most adults – it is the theories of formal science that are fragile, and have low social value. If the learner has to be able to converse with peers and parents in out-of-school contexts, it way well be more appropriate if life-world knowledge is called upon in such contexts, as this is how effective communication will occur. As Driver and her colleagues commented, Becoming socialized into the discourse practices of the scientific community does not entail, however, abandoning commonsense reasoning. Human beings take part in multiple parallel communities of discourse, each with its specific practices and purposes. There is considerable interest in the science education community at present in the process of conceptual change. Learning science is being characterized in some quarters as promoting conceptual change from students’ informal ideas to those of the scientific community … We see a problem in this characterization in that we would not expect students necessarily to abandon their commonsense ideas as a result of science instruction. As argued earlier, students still have such ideas available to them for communication within appropriate social contexts. (Driver et al., 1994: 8–9)

Solomon’s distinction between the ‘natural attitude’ and ‘symbolic universes’ offers some insight into different modes of thinking employed by schoolchildren and should not be surprising when developing ‘scientific thinking’ is commonly seen as an aim of Science Education, and learning about the ‘nature of science’ is increasing seen as important as learning about specific science topics. 6.1.4.7

Folk Mechanics, Folk Biology and Folk Psychology

In at least three areas there are commonly recognised alternative bodies of knowledge that have common currency in the social world, sometimes labelled as ‘folk’ knowledge or ‘folk science’: • Folk biology • Folk mechanics • Folk psychology

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The first of these areas is folk biology, where people have extensive informal knowledge of animals and plants that may be considered as sources of food, danger, medicine, etc. This forms part of the Traditional Ecological Knowledge of many societies (see §5.1.5). Some of this knowledge is at odds with formal scientific models of the world. As one example from the West Indies, George and Glasgow (1988: 115) note that ‘it would seem that the whole aura of pregnancy and everything connected with it, are regarded as harbingers of ‘plenty’, of productivity. Should a pregnant woman plant a pumpkin vine or walk over one, it will ‘bear well’. Planting the umbilical cord under a coconut tree ensures its productivity’. A second area is folk mechanics, which is considered the source of common alternative conceptions relating to force and motion (see §6.1.3.1). As Perkins and Simmons (1998: 318) point out, students’ ‘naive theories’ about dynamics ‘reflect straightforward and often pragmatically useful generalizations about the way the everyday world behaves’, whereas ‘the straight-line motion at a constant velocity of Newton’s first law rarely is seen in ordinary circumstances’. Indeed one of the most common ‘species’ of alternative conception is that linking force to velocity (rather than acceleration), so that where the canonical physics formalism has a force causing a change in velocity, the common everyday notion is that a force is needed to maintain a steady speed. From the perspective of formal science, an object at rest is ontologically similar to one moving with constant velocity (it has constant velocity of zero), but there is an important difference between that situation of constant (zero or non-zero) velocity and an object accelerating: the latter requiring a net force acting. Yet from the everyday ‘life-world’ perspective, the salient distinction between stationary and moving objects tends to seem more significant (and in practical terms often is). This revisits comments earlier about the implication of labelling learners’ informal ideas as ‘alternative’ (§5.3.4), and to most people it is the scientific perspective that is a specialised alternative to the more practical ways of thinking. Physicists begin their analysis with an idealised case of an object that is not influenced by gravity or frictional forces. Real-life situations met by most people seldom approximate to this, and a dynamics based on the assumption that objects soon stop moving once we stop applying a force, unless they are falling in which case no further force needs to be applied, works much of the time. Where folk biology is an explicit system of knowledge, communicated intergenerationally as Bowers (2007) discusses, folk physics may well be supported by implicit, intuitive knowledge that derives from each individual’s physical and visceral experience of moving about, and moving objects in, a limited range of types of physical environment (i.e. in air at or near the surface of the earth; in water at or near the surface of the earth). It remains an interesting question why some learners seem to develop intuitive physics that is more at odds with formal physics than others (Taber, 2004; Brock, 2006). The third area is folk psychology, which we have already met (§4.6). The transfer model of teaching was considered to be of this nature. Young children develop a theory of mind, that others have minds much as themselves, and this allows the development of empathy, appreciation of deception, etc. People acquire the ‘natural attitude’ through the way minds are discussed in everyday life (Claxton, 2005) – we

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hold things in our minds (so it is – metaphorically at least – a container with contents), but sometimes things ‘slip’ our minds (perhaps the container is leaky?), and sometimes we consider people are ‘out of their minds’ (a way of talking that suggests that ‘our’ minds can be separate from ‘us’?) The notion that we can take information from our own minds and put it in (actually, copy it to) someone else’s, fits into this common-sense understanding of the world. Interestingly it is not normally considered that there is a ‘folk chemistry’ to accompany folk biology and folk physics, as it is not usually thought that chemistry maps onto a domain of everyday cognitive activity that has been important for a significant period of human evolution (Mithen, 1998). Much of the theoretical content of academic chemistry relates to particle (e.g. molecular) models that are not part of the common life-world discourse. It would also seem that a formal concept such as oxidation is sufficiently distinct from life-world phenomena (such as burning and souring) to avoid some of the complications that occur when students are taught Newtonian dynamics and are asked to consider apparently familiar concepts such as speed and force as having different relationships in physics from those usually taken for granted. However, the most basic chemical notion of substance is readily confused with the everyday concept of materials, so that it is not intuitive that steam and ice are forms of the same substance, nor that juice freshly squeezed from an orange should not be considered ‘pure’. (When sociologist Pierre Bourdieu wanted to argue that issues of gender and class were ‘inseparable’ he offered the comparison of how the yellowness of a lemon was inseparable from its acidity (Dumais, 2002), an analogy that a chemist would feel undermined his point as the compounds giving rise to the colour of lemon can readily be separated from those mainly responsible for its acidity. Whether Bourdieu was aware of this, he clearly assumed his readership would not consider the colour and sourness in the same way as reductionist scientists.) It is also of interest here that common ideas of structural chemistry, which are widely taught and used in the subject, are considered so distinct from the current canonical models from quantum theory, that they are known as a ‘folk molecular theory’ (FMT). According to Sánchez Gómez and Martín (2003: 132), FMT provides ‘a simple visual model of molecular structure, independent of … quantum mechanics’ and comprises ‘an informal [sic] set of structural ideas and semi-empirical rules’ that nonetheless ‘is the theoretical model used for presenting the foundations of molecular structure in every introductory text’. That many scientists find these ‘alternative’ conceptions to be useful reinforces the point made in Chapter 5 that the labelling of learners’ ideas as alternative should only be taken to mean not matching whatever is set out as the target knowledge in the curriculum (i.e. relevant to what is currently authorised as knowledge), and should neither be seen as suggesting some kind of absolute categorisation, nor ideas that are inherently of less worth than the canonical versions.

6.1.4.8

Learners’ Conceptions Modelled As ‘Minitheories’

Solomon then argues that thinking in the life-world is characterised by the ‘natural attitude’: that is to categorise experience loosely, to typify, and to absorb knowledge

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into fragmented meaning structures. Claxton (1993) has made very similar points to Solomon, in proposing a model of students’ thinking about science topics in terms of what he calls ‘minitheories’. Claxton, like Solomon, suggests that children’s thinking is characteristically quite different from the ‘supertheoretical’ thinking that science aspires to. In particular he characterises the ‘minitheories’ of youngsters as piecemeal, contextualised and fragmented, The ideas that young people have picked up about the world seem to have a number of fairly obvious characteristics. First, they are piecemeal. Instead of the one big supertheory that the research scientist aspires to, in which many seemingly disparate phenomena can be brought under the same abstract, explanatory umbrella, the everyday ‘theories’ of young people are fragmentary and local. Many ‘minitheories’ are developed in response to particular experiences, predicaments or needs, that work well enough on their home ground, but whose limits of applicability – what Kelly (1955) called a theory’s ‘range of convenience’ – may be rather circumscribed. (Claxton, 1993: 46–47)

Whereas scientific theories (or in Claxton’s characterisation, ‘supertheories’) are generalised abstract entities that have been decontextualised, and so may be applied across a wide range of contexts, Claxton characterises minitheories as ‘packages’ with five aspects (‘SPADE’): ‘the Situations to which it applies, together with the Predictions, Attitudes, Descriptions and Experiences that it produces’ (pp. 47–48). As particular minitheories are tied to a limited set of associated contexts (‘situations’) ‘young people in particular can display wild inconsistencies when they (frequently for no apparent reason) tip over from one minitheory to another’ (p. 47). In other words, questions about – what are seen by a science teacher or researcher as – the same concept, may trigger the learner to activate different minitheories because of contextual cues that are secondary or irrelevant from the scientific perspective. This is an important point in terms of the methodology of the RP, when considering whether learners have stable patterns of thinking. There are several possible interpretations of apparently inconsistent responses elicited from informants (a point to be returned to below), and one possibility is that what seems to be inconsistent appears so because the researcher and informants ‘carve up the world at different joints’. As diSessa comments, ‘the range of phenomena covered by the intuitive sense of mechanism is not obviously that of any scientific theory’ (diSessa, 1993: 125). For example: there is nothing intrinsically contradictory in the statements that • ‘Fish live in the sea’ and • ‘Some fish have legs’ for someone who classed all sea animals as fish, and describes a cephalopod’s tentacles as ‘legs’. It would certainly seem feasible that in some cases researchers may have failed to fully appreciate learners’ personal meanings for terms; and so misidentified what are actually coherent responses as representing a contradictory set of ideas. The discrepancy in these cases is less a matter of consistency in the individual’s thinking, and more about the limitations of a common basis for communication.

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For, as Viennot (1985) has pointed out, the very things that make an individual’s thinking ‘alternative’ make it difficult to comprehend, and describe, as the learner may use different terminology, and his or her alternative notions do not necessarily match the concepts of science through a ‘one-to-one correspondence’. diSessa, Gillespie and Esterly (2004: 852) suggest that researchers can easily adopt an assumption that ‘the range of contexts covered by intuitive physics more or less coincides with—or sits within—that of professional physics’ whereas ‘intuitive elements might have wide[r] scope’. (The issue of suitable methodology for research into learners’ thinking is considered in Chapter 7.)

6.1.4.9

Categorising Minitheories

Claxton (1993: 50) suggests it is useful as an ‘approximation’ to consider school students’ minitheories to fall into three clusters, that he labels as ‘lay science’, ‘school science’ and ‘gut science’. According to Claxton, ‘lay science’ derives from, and is used in, informal social interactions. Lay science, has been acquired through informal, but mediated sources such as family, friends and the media, and commonly comprises a store of ‘amazing facts’ that can be traded and discussed with others as a means of exploring or establishing friendships. … What is important about lay science is that it gives you practical advice about when to plant the radishes, or how to load your camera; and that it gives you intrinsically interesting things to talk about. (Claxton, 1993: 52–53)

It was suggested above that some conceptions elicited from learners will be of the form of verbalisation of knowledge that was previously tacit, and it is this kind of knowledge that Claxton refers to as ‘gut science’. Gut science is ‘acquired through experience and is expressed in unreflective, unpremeditated action’ (Claxton, 1993: 52). Claxton argues that ‘what is important about “‘gut science” is that it works: It stops you getting burnt and falling over’, and so as long as it works, it is not important ‘how piecemeal or situation-specific the minitheories are, or how well you are able to articulate them’ (pp. 52–53). This reflects notions of (what I refer to as personal) knowledge in the pragmatic philosophy of Dewey (§1.5.1) and instrumentalist constructivism of Glasersfeld (§5.2.6). So, for example, in the case of an individual’s understanding of dynamics (such as notions about moving objects requiring a force to keep them in motion), the collection of minitheories constituting ‘gut dynamics’ tend to be unarticulated and not necessarily conscious. Rather they are shown in a person’s spontaneous reactions and intuitive judgements and tested against ‘does it work?’ and ‘is it useful?’ ‘Gut dynamics’ provides the individual with the ability to interact physically with the world…Examples of gut dynamics for many people would include their experience that heavy things fall fastest, things need a push to get them going, you have to keep pushing to keep things moving, and rubbing causes things to heat up and wear out. (Claxton, 1993: 51)

Just as Solomon characterised life-world knowledge as distinct from scientific knowledge, Claxton emphasised how ‘gut science’ and ‘lay science’ had different characteristics from ‘school science’ as ‘in neither of these domains are the

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“school science” demands – for rationality, logic, coherence, rigour, precision and explanation in terms of a limited set of agreed, technical concepts – of much importance’ (p. 52). Claxton nonetheless referred to children’s ‘school science’ as another cluster of minitheories, and indeed also describes a fourth cluster of minitheories, that he labels as ‘scientist’s science’ of ‘which both school children and school teachers are largely ignorant’ (p. 50).

6.1.4.10

Minitheories As Personal Knowledge; Curriculum Science As Objective Knowledge

In characterising ‘school science’ and indeed ‘scientists’ science’ as clusters of minitheories, Claxton seems to imply that there is continuity in the form of an individual’s knowledge – it is comprised of minitheories rather than ‘supertheories’ – regardless of ‘cluster’. Claxton (1993: 47) refers to George Kelly’s (§1.6.3) notion of a construct’s ‘range of convenience’, which for many minitheories ‘may be rather circumscribed’. Claxton (2008) points out that all theories are developed in terms of a specific focus, and have a limited range of application once applied beyond the initial focus. Although Claxton (1993: 55) describes ‘school science’ as a cluster of minitheories like ‘lay science’ and ‘gut science’, he also refers to how ‘school science tries to create a coherent, integrated conceptual structure’. So here his analysis reflects Solomon’s contrast between the ‘natural attitude’ and ‘symbolic universes of knowledge’ presented above. Both Solomon and Claxton then characterise children’s science-related knowledge as fragmentary, whilst acknowledging that school science aspires to a coherent and integrated body of knowledge. Popper’s notion of ‘World 3’ (§2.2.2), the world of objective knowledge, may be useful here. The structure of scientific knowledge (in World 3) is typically abstract, highly formalised, and based upon general principles that are integrated (as far as possible) into coherent knowledge structures. School science, as Claxton acknowledges, aspires to these qualities. The curricular models of science (Gilbert et al., 1982) – the representations of target knowledge in formal school curricula (Kind & Taber, 2005) – also belong in ‘Popper’s Third World’, and will comprise of simplified representations of scientific knowledge. Personal knowledge, however, will typically not match up to the formal World 3 knowledge, and indeed as both Claxton and Solomon point out, the more piecemeal and contextualised nature is usually appropriate for many purposes. Yet success in school science (and even more so in professional science) certainly requires some degree of mastery of more formalised knowledge structures, and therefore that the individual can develop representations of scientific knowledge that allow ‘scientific thinking’, such as using tightly defined concepts, and applying abstract formalised principles across broad ranges of specific contexts. Both Claxton and Solomon suggest that such knowledge may only be adaptive in specialised contexts (school work and exams, professional scientific work, but not in everyday conversation), and research suggests that the acquisition of ‘scientific’ knowledge occurs without substituting life-world knowledge.

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This raises the issue of the very nature of a science curriculum – i.e. the argument that if what is taught in school is of little use to most students outside the classroom, then a more ‘humanistic’ Science Education should be developed which better addresses the way most learners will engage with science in their lives (Aikenhead, 2006). This is a central issue for discussion in Science Education (and beyond, among the major stake holders), but in a sense it is orthogonal to the concerns of the research programme into learning in science discussed here. This is not to say that it is excluded by the negative heuristic in the sense that say unguided discovery learning or social views of learning which are inconsistent with notion of personal knowledge are excluded (because they contradict hard-core assumptions of the RP). Rather, the RP concerns the nature of learning curriculum science and how teaching might better facilitate this learning. The programme can certainly offer insights into why certain types of target knowledge are more or less readily learnt, and so the feasibility of including certain subject knowledge in school and college courses; but the RP does not in itself concern decisions about what is worth teaching and learning. So although this is a very important issue, it is one on which the RP itself is neutral. Although it is not excluded by the negative heuristic, researchers will not be directed to study it by the positive heuristic (§4.4.2). The RP can include those enquiring into science learning to improve the effectiveness of teaching established school and college science content, as well as those who would argue that traditional courses should be replaced by a curriculum more relevant and accessible to the majority of students. In either case, once priorities for learning are set, it is important to know how the best support and facilitate that learning.

6.1.4.11

The Elicitation of Alternative Conceptions Is Context-Dependent

One of the outcomes of children’s science interacting with formal instruction (§4.1.2) identified by Gilbert, Osborne and Fensham (1982) was the ‘two outcomes perspective’ where pupils learn presented theories and explanations, and can use them in class and during school tests, but revert to their existing ideas in everyday conversation and problem-solving. A learner may effectively demonstrate mastery of the curriculum (scientific) version of a concept, and apply it in the context of classroom and examination questions, but choose to answer questions in an ‘everyday’ setting according to an alternative set of ideas. Vygotsky (1934/1986: 245) pointed out that word meaning is tied to the context of use, so in effect learners may simultaneously hold several different meanings for the ‘same’ word. Studies have shown that learners are more likely to apply scientific principles if questions are set as formal exercises with obviously ‘scientific contexts’, but they tended to revert to using their alternative conceptions in novel – and particularly ‘everyday’ – contexts (Viennot, 1979, 1985; Driver, 1983; Dumbrill & Birley, 1987; Bliss et al., 1988). The tendency to pay heed to ‘irrelevant’ contextual factors in questions can decrease with age, but even University students can change their reasoning in (scientifically) similar questions due to perceived contextual cues (Palmer, 1997).

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For example, Viennot (2001: 66) discusses the frequency of errors made by students due to their associating force with velocity (§6.1.3.1), and suggests that these are less likely when the question is presented ‘in analytic’ form, and more likely when the motion is ‘salient’ (the question is contextualised in terms of the movement of an object that can readily be imagined); or when the data given are obviously inconsistent with the premises of the alternative conception – e.g. if the question informs the student that the force acting on an object is zero, but the object velocity is non-zero. From extensive work on physics learning, particularly with undergraduate students, diSessa (1993: 108) reported that ‘students may be capable of solving a problem posed in explicitly quantitative terms, yet they may think very differently when asked for a qualitative analysis of the same problem’. From their case study of high school student Carl’s learning pathway in atomic physics (see §6.2.2.14), Petri and Niedderer (1998: p. 1084) suggest that ‘the stronger a conception is represented, the less it depends on a special context’, citing how ‘the prior conception of a planetary atom seems to be very strong; in many (new) contexts it is the first to be used by Carl … it is used spontaneously in many different contexts’. Mestre and colleagues (Mestre et al., 2004) suggest that becoming an expert in a knowledge domain includes learning about the range of application of concepts across contexts, something lacked by novices. They report studies asking students to discuss various problems, e.g. viewing animations showing balls rolling along two different paths with the same end points (so the balls started at the same heights, ended at the same heights, and travelled the same overall distance). They concluded that ‘context plays a major role in both students’ predictions and in the type of reasoning they bring to bear to explain their predictions’ (p. 390).

6.1.4.12

Learners May Represent Knowledge in Separate ‘Domains’

Although Solomon was concerned to characterise much of students’ thinking as reflecting the ‘natural attitude’, and so represented in memory in fragmentary fashion, she acknowledged that through formal instruction learners could also develop new knowledge structures, which, significantly, they kept separate from their lifeworld knowledge. That is, ‘when students learn the new formalism of scientific thought they store it in a different compartment from that of the familiar life-world thought of daily discourse’ (Solomon, 1993b: 96). Considering the effect of contextualising questions on the answers elicited from students, Solomon (1993b: 95) reports that ‘data suggest that the two kinds of knowledge – the one well socialized and illogical, the other specialized, logical, and less often used – may be grouped separately in the memory’ and that ‘the amalgamation of knowledge from the two domains was comparatively rare’. Although life-world knowledge may initially be elicited, once knowledge in the school science domain is activated, considerable recall may be initiated, so that ‘a single cue may switch thought into the domain of science knowledge, and a whole network of meanings, theories and concepts are recollected and furnished with examples

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which show real understanding’ (p. 95). This phenomenon clearly has implications for methodology when exploring students’ ideas (methodology is discussed in Chapter 7). Claxton (1993: 55) suggests that this separation is important for effective learning of school science, especially where common labels are used in both domains as ‘although many of the key terms are familiar (work, force, speed, compound, solution, etc.) they are now given new, counter-intuitive meanings that are easily lost or confused if they are not stored and used in a separate domain’. Indeed, Claxton argues that when learning school science, it is unhelpful for life-world knowledge to be brought to mind as he considers that the two systems will interfere as ‘children who activate gut and lay science in a science lesson are in danger of flooding their minds with myths, usages and associations that are actually inappropriate and distracting’ (p. 55). He argues that ‘if children are to learn school science there is no reason why they should not learn it alongside their pre-existing knowledge, and good reason why they should keep the two domains distinct’ (Claxton, 1986: pp. 125–126). Coll and Taylor (2001: 219) have argued that constructivism ‘contains an assumption that human cognition depends on domain-free, general-purpose processing by the brain. However, this assumption is inconsistent with studies of children’s early learning that suggests cognition is modular in nature’. Coll and Taylor base their claim on the ideas of P.S.C. Matthews. Matthews (2000) claims that constructivist theories of learning are based on an implicit assumption that human cognition depends upon domain-free, general-purpose processing. Matthews argues that studies suggesting aspects of innateness, domain specificity and modularity of cognition undermine constructivist models of learning, and that more direct teaching approaches (such as rote learning) may be more effective. This perspective might be considered to have some merit if it could be shown that formal conceptual structures can only be acquired by verbal learning and cannot, as diSessa (1993) suggests, be built from more implicit knowledge elements. However, if modulation and domain-specificity were to be this restrictive it is hard to understand how formally learned concepts could ever become meaningful beyond pure symbols and rules for relating them, nor how the abstract concepts of science were ever developed in the first place. Again the term ‘constructivism’, which has so many associations, proves a distraction in this context. If Coll and Taylor’s criticism applied to the RP explored here then it would suggest that research exploring the possibility and potential consequences of knowledge domains would be excluded by the negative heuristic. This is an important consideration, because it in turn would suggest that if progress in understanding learning in science is to be facilitated by studies exploring the notion of compartmentalised knowledge then a RP that excludes such possibilities could cease to make progress, and become degenerate. However there is no hard-core commitment in the RP set out in Chapter 4 which requires cognition to occur without reference to modules or domains. Rather the hard core of the RP gives rise to general questions asking how learning takes place, and how knowledge may be represented in individual’s brains. Therefore, the positive heuristic of the programme invites researchers to consider and explore possibilities such

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as modularisation, and allows the development of models based on this approach within the protective belt of the programme’s theoretical content.

6.1.4.13

Student Representation of Scientific Knowledge May Itself Be Compartmentalised

Solomon’s reference to the domain of scientific knowledge suggests that unlike the ‘localised’ nature of informal knowledge, scientific knowledge comprises a domain of coherent and interlinked ideas. This is indeed how formal (World 3) scientific knowledge is understood, and this links to commonly espoused scientific values (Laudan, 1984). Scientific knowledge is expected to be largely coherent, and well integrated, and to have something of a hierarchical nature so that a great many ‘facts’ can be accommodated within a much more limited number of models and theories that themselves can be shown to derive from a small set of fundamental laws or principles. In practice, school knowledge seems to be somewhat compartmentalised according to the disciplinary boundaries represented in the curriculum – a form of contextualisation of learning that seems tied to how school subjects are demarcated. It has been reported that students who can successfully use mathematical techniques in mathematics lessons may be unable to apply the same procedures in a science lesson (Gabel & Bunce, 1994: 319). This could be explained in terms of the limitations of working memory (see §6.2.1.3), if the need to coordinate contextual information with the mathematics may overload cognitive processing abilities (Tsaparlis, 1994). However, it is less clear that this is a feasible explanation for when, for example, students studying both physics and chemistry seem unable to draw upon their physics knowledge to apply in chemistry lessons; and may indeed seem affronted at the suggestion that this could be helpful in learning the chemistry (Taber, 1998b). A difficulty that is met in the models proposed by Solomon and Claxton (though for different reasons) is how learners’ (and especially more advanced learners’) representations of formally learnt scientific knowledge should be understood. In Solomon’s model, students are able to keep separate their formally learnt school science knowledge from their informal ideas developed in the life-world. If in doing this they are able to represent school knowledge to reflect the ‘symbolic universe of knowledge’ then this aspect of their knowledge system should reflect scientific thinking: being coherent, well integrated, theoretical (subsuming phenomena to explanatory schemes, etc.). Yet this raises the question of how formal schooling enables learners to acquire knowledge structures so different from those acquired outside of schooling (especially when Solomon characterises group work in school science as more likely to be structured by the norms of everyday social conversation). It should certainly be an aim of Science Education to help students develop knowledge structures that better reflect the formal structure of scientific knowledge (i.e. in Popper’s World 3), but Solomon’s notion of operating in two distinct, mutually impenetrable domains is not helpful in seeing how such transitions are possible.

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Student Learning About Science May Be Represented in Well-Integrated and Coherent Knowledge Structures

However, Claxton’s model of school science being stored in clusters of minitheories that have a similar nature to the gut science and lay science minitheories presents a complementary problem, that of not acknowledging how learners do over time come to build coherent and integrated knowledge structures. Vygotsky (1934/1986) recognised the significance of interlinking in conceptual structures the best part of a century ago. For scientific (i.e. academic, or formal) concepts, the ‘structures’ made up a system (p. 205), and the meaning of the concept depended on its relationship to other concepts in the system. One published case study of a college level (senior high school) student, known as Alice, studying chemistry and physics offers ‘an account of one student’s scientific thinking, showing both how she applied fundamental ideas widely, and also where conceptual integration was lacking’ (Taber, 2008e). I found that ‘Alice used key ideas of force, energy, and particles widely in her explanations’. The case study reported that some alternative conceptions were found, and a number of examples where potential links between different concepts or topics that might have been desired at this level of study had not been made. So, compared with the formal target knowledge in the curriculum, Alice’s personal knowledge demonstrated flaws and omissions in her conceptual structures at the point in time she was interviewed. However, despite not presenting as a ‘perfect’ learner in this sense, it was clear that Alice’s learning of school and college science was largely coherent and organised, and was certainly much too well integrated to be accurately modelled as a cluster of minitheories. More work is needed exploring student knowledge structures and coherence across topics to give a better understanding of what is typical of learners of different ages. It is hardly surprising that the personal knowledge of schoolchildren and college students lacks the levels of integration and coherence of formal World 3 scientific knowledge. However, it also clear that for a student like Alice, her knowledge is far from a set of local, highly context-dependent and incoherent minitheories. Until more work is done mapping out learners’ ideas across a wide range of topics at various stages of education, however, it is difficult to know whether Alice should be considered as exceptional, or perhaps quite typical of students at her stage of science learning.

6.1.4.15

Alternative Conceptions Do Not Always Derive from the Life-world Domain

Solomon’s arguments about the nature of life-world knowledge certainly need to be taken seriously, and must be considered when investigating topics such as force or plant nutrition which feature in everyday discourse. Her model of compartmentalisation of knowledge between life-world and the symbolic universe of formal science has considerable explanatory power in considering the origins and context-dependency of the application of learners’ ideas in some topics, especially

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those where there is common folk knowledge with significant social currency. However, this would certainly seem not to offer a full basis for understanding the range of alternative conceptions that are widely reported – for example, life-world thinking does not explain the many alternative conceptions in chemistry. So Bodner offers an excellent example of a student being strongly committed to an ‘alternative conception’ that cannot be readily explained by ideas having currency in the life-world, On a recent hour exam. we asked students to calculate the N-O bond order in the NO3− ion. The answer key read: 1 1/3. One of our graduate students was furious, arguing that the only possible values for bond order are integers (0, 1, 2, 3) or half-integers (1.5, 2.5, etc.) because ‘everyone knows’ that the bond order is equal to the difference between the number of electrons in bonding and antibonding molecular orbitals divided by two. No amount of argument, from any source, would convince this student that his model was naive, that it was developed from discussions of diatomic molecules, and that it does not always hold for polyatomic molecules. (Bodner, 1986: 876)

It seems highly unlikely that even in the social world of a graduate student, notions of bonding and antibonding molecular orbitals form the basis of folk knowledge in the sense implied by the life-world model. Alternative conceptions may have different origins in different science disciplines, and these types of alternative connections have been labelled as ‘pedagogic’ in origin as they seem to be based upon taught ideas (Taber, 2001d). It is these kinds of ‘misunderstandings’ within the context of what is clearly instructed learning that have traditionally been referred to as ‘misconceptions’; however, this does not explain how they arise. Whereas a student’s ideas about force and motion can clearly originate in their life-world experiences, their notions about ‘quanticles’, particles such as molecules and atoms that behave very differently to familiar particles because of the significance of quantum effects at their scale, cannot be based on direct experience. That is not to say that learners will not apply their intuitions about the world to chemistry, they clearly will (Taber, 2008a) – for example, the alternative conception that an electron is attracted to the nucleus of an atom more than the nucleus is attracted to the electron is likely to derive from a common intuition that bigger sources can have greater effects (cf. diSessa’s p-prims, see §6.2.2.6). However, it also seems likely that many of these examples relate to learners drawing upon ideas that are directly taught, if through notions only intended as figures of speech, or limited teaching models. Statements reflecting common alternative conceptions about chemical reactions occurring to allow atoms to fill their shells can certainly be found in many school textbooks. Part of the problem here might well be that what teachers intended as metaphor is taken literally, as when talk of atoms ‘needing’ more electrons or ‘wanting’ to share electrons is adopted uncritically (Taber & Watts, 1996), and that learners may not have the epistemological sophistication to appreciate the nature of models (e.g. Grosslight et al., 1991). With metaphor being at the base [sic] of so much of human language and cognition (Lakoff & Johnson, 1980a, 1980b), and with the products of science being largely models and representations (Carr, 1984; Frigg & Hartmann, 2006), teachers may not readily keep track of those taken-for-granted features of

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their talk that may need unpacking for their students. One example of this is what Hans-Jürgen Schmidt refers to as ‘the label as a hidden persuader’. Schmidt (1991) discusses how students commonly assume that a process they meet in chemistry called neutralisation will, necessarily, produce a neutral product. As the introductory examples they meet (usually strong acids reacting with strong bases) do indeed give neutral products, it may only be some years after meeting the concept that this (by then, well-established) conception is found inadequate. In my own work, I found that when college-level students are asked to draw the structure of metals at the submicroscopic level, they may include a vast excess of conduction (delocalised, ‘free’) electrons in relation to the atomic cores (cations) shown (Taber, 2003b). This seems to be linked to the common verbal metaphor (which is used as a teaching model) of a metal containing atomic cores in a ‘sea’ of electrons. Such examples do, however, warn against dichotomising student knowledge and seeing Solomon’s two domains as intrinsically limited to representing very different types of knowledge structures. Nor does Bodner’s example fit well with Claxton’s notion of school science minitheories, as in this case a heuristic rule is not being associated with a limited context, but rather being applied beyond its range of convenience.

6.1.4.16

Learners’ Alternative Conceptions May Derive from Personal Conceptual Frameworks

This suggests that at least some school science learning facilitates the construction of new knowledge representations that: 1. May be contrary to target knowledge, yet 2. May reflect the characteristics of objective (World 3) scientific knowledge – that is being abstract and formalised, decontextualised, coherent and well integrated That is, not all of the alternative conceptions elicited from learners will take the form of life-world knowledge. The positive heuristic of the RP (see §4.4) makes it an imperative to explore the degree to which learners’ science knowledge can be characterised as taking on these more desirable (from a curriculum perspective) characteristics. In 1989, Driver (1989: 483) referred to ‘the extent to which children’s conceptions are genuinely “theory-like”, that is having a coherent internal structure and being used consistently in different contexts’ as an ‘open question’ within the RP. Solomon’s model suggests that knowledge acquired through science teaching might be theory-like – being stored in a specific domain of memory – whereas knowledge acquired socially (in the ‘life-world’) will reflect the ‘natural attitude’. Yet if learners are capable of representing knowledge as coherent integrated structures, rather than only in minitheories, it might be expected that to the extent that learning in the life-world and formal education share cognitive mechanisms, in principle learners could develop informal conceptual knowledge of this type (see Fig. 6.1).

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Fig. 6.1 Representing knowledge in two domains

scientific knowledge domain

C

S representation

contextualised knowledge fragments

S, C

formalised frameworks of knowledge

ACF? life-world knowledge

Claxton (C) and Solomon (S) both argue that formal science knowledge is stored separately in memory from informal ideas about science. Claxton emphasises how knowledge representation in both domains can be characterised in terms of local ‘minitheories’, where Solomon acknowledges that representation of formally learnt science can take on features of the theoretical knowledge structures of science. Others (e.g. Driver, Gilbert & Watts) have argued that some of the alternative conceptions exhibited by students may also reflect theoretical scientific knowledge, drawing upon alternative personal conceptual frameworks represented in memory (ACF). This possibility – that students’ alternative conceptions may sometimes be drawing upon representations of abstract (decontextualised) and coherent knowledge structures – has been suggested since the beginning of the RP. Driver and Easley (1978: 62) proposed the term ‘alternative frameworks’ for ‘the situation in which pupils have developed autonomous frameworks for conceptualising their experience of the physical world’. Although the terms ‘alternative frameworks’ and ‘alternative conceptions’ have not always been distinguished in the literature (and so some knowledge claims that students hold ‘alternative frameworks’ in the literature do not go beyond demonstrating alternative conceptions that could well derive from something like a minitheory), it is also clear that some reports do support interpretations of student thinking drawing upon more extensive theory-like conceptual representations. So according to Driver (1983: 7), the conceptions elicited from students may be ‘more than an idiosyncratic response to a particular task, they may be general notions applied to a range of situations’. In these cases it seems appropriate to refer to learners having represented in memory personal conceptual frameworks. Where these are (completely or partially) contrary to the target knowledge of curriculum science – those cases where ‘the accepted theory may be counter-intuitive

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with pupils own beliefs and expectations differing in significant ways from those to be taught’ (p. 3) – they would be considered as ‘alternative frameworks’ (in the alternative frameworks1 meaning discussed in Chapter 5, §5.3.4.1). This notion of conceptual ‘frameworks’ may be considered to relate to the common psychological term schema, where ‘if the patterns [of association between elements] are tightly organized, so that activation of one element almost always activates the others, we may treat the pattern as a schema’ so that ‘it can serve as a single unit in working memory’ (Reddish, 2004: 23). The links in a conceptual framework would not be as ‘tight’, but the associations would be strong enough that accessing one part of a framework would cue ready recall of other elements.

6.1.4.17

An Alternative Generalised Conceptual Framework from Chemistry Education

It seems reasonable to conjecture that more extensive theory-like knowledge representations are more likely to be found in studies with older, more mature learners, and perhaps especially with those who have demonstrated success in studying school science. Some of the alternative conceptions related to chemical bonding that were used as examples near the start of this chapter derived from an interview-based study undertaken in an English Further Education college (Taber, 1998a). The informants were ‘Advanced Level’ students, typically 16–19 year olds, who had been successful in their school-leaving examinations, including science, and who had chosen to enrol in chemistry in post-compulsory education. Advanced level, or ‘A level’, is the most-common qualification taken when applying for University entrance. (In England, this level of education is often referred to as ‘sixth form’, and can occur in secondary schools, sixth-form colleges specialising in this age range, or – as in the present case – in further education colleges that offer diverse academic, vocational and professional education across a wide range of educational levels to school leavers and adults.) In this particular study a number of common alternative conceptions were reported, some apparently held by all of the students interviewed, and others only elicited from some of the informants. In offering an overview of the main findings from across the sample, the results were described as a (generalised) alternative conceptual framework (see Fig. 6.2). The framework is generalised in the sense of being a representation of commonalities in students’ comments, but is still alternative in the terminology of the RP as it is an alternative conceptual structure to the target knowledge set out in the curriculum. I acknowledged that ‘it is not claimed that the framework precisely makes up part of the cognitive structure of any specific individual chemistry student. Rather, the framework is a model constructed by the author to represent related aspects of learners’ thinking that were elicited during empirical research’ (Taber, 1998a: 600). However, individual informants did offer conceptions that matched up to large

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the basic chemical entities

own their

electrons retu

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are

spontaneously undergo

atoms want

held together by

are

to be

just forces

can be

?

ld

be

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metallic solvation forces

covalent is like

br on eak fo s u rm p in g

arranged in

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is

held together by

lattice

can be

can be

ionic maintained by

gives

stable

occu rs achie to ve

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s an me ing v ha

are

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the

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full outer electron shells usually

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Fig. 6.2 A generalised alternative conceptual framework for chemical bonding (From Taber, 2000c)

parts of the generalised framework. The framework shows how different conceptions link together into a relatively coherent account of a topic area, as well as indicating how a key ‘misconception’ (i.e. the alternative conception that chemical processes occur to allow atoms to fill their shells) can lead to a network of conceptions considerably at odds with the target curriculum knowledge. It should be noted that the conceptual framework is presented in terms of general concepts such as ‘atoms’, ‘metals’, etc. rather than in terms of more specifics (hydrogen atoms, copper, etc.), as student informants applied these general ideas across contexts when asked about a range of examples. The reporting of conceptual frameworks of this nature is significant because it shows that students can have extensive, theory-like, personal conceptual frameworks that are ‘alternative’ to curriculum science and occur in the domain of scientific knowledge. Such notions about the behaviour of electrons and the properties of chemical structures are unlikely to derive directly from physical intuitions about the world, nor from folk-knowledge that is part of the everyday discourse of the life-world.

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Building the Protective Belt of the Progressive Research Programme

Learners May Exhibit Manifold Conceptions for the ‘Same’ Concept

In view of what has already been discussed, it should not be surprising that researchers have commonly reported that individual informants may offer several apparently contradictory conceptions of ‘the same’ phenomenon or scientific concept. Three possible sources of such manifold conceptions have already been indicated: • A methodological explanation: consistent knowledge appears contradictory because of the idiosyncratic language of the informant (so that key technical terms do not have their consensus meanings). • An ontological explanation in terms of the nature of students’ knowledge systems – that considers knowledge to be typically contextualised minitheories, so that what is the ‘same’ concept from a scientific point of view is multifaceted and context-dependent in terms of the learner’s thinking. • An ontological explanation in terms of the nature of students’ knowledge systems – that considers two ways of understanding and thinking about the world operating in distinct domains (largely encapsulated in memory) so that responses are drawn from different knowledge systems depending upon the perceived context of the inquiry. The latter two possibilities are not exclusive, as the second account can be taken as applying to one of the two domains in the final option. This is caricatured in Fig. 6.3. Consider a question asking why we get hot when we exercise. Solomon’s two

‘hot’ in everyday life?

in school science?

exercise George Clooney

thermometer temperature

heat topic states

transfer

that new rock band air

conduction convection radiation

beverage

stolen money

energy

summer holiday kettle

film

internal energy

changes

sweaty

dinner oven

room molecules etc.

bath

heater boiler

etc.

Fig. 6.3 Caricature of understanding ‘hot’ in terms of two distinct domains, for which knowledge is represented separately and with different characteristics

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domains model suggests this will either be perceived as a life-world question or as a school science question. In the former case it is likely to activate a local contextualised minitheory (in Claxton’s terminology) which includes a notion of heat linked to exercising. However, if perceived as a question requiring school science knowledge, the same question will activate knowledge in a different domain, where more abstract ideas are better interlinked, and are applied across a wide range of contexts. The case for learners’ manifold alternative conceptions being stable does not require knowledge to be presented as conceptual structures that satisfy the criteria applied to public science (e.g. in terms of logical coherence). Driver, Guesne and Tiberghien (1985: 3–4) emphasised the distinction, when they commented that ‘although students’ notions may be persistent, as we have already argued, this does not mean the student has a completely coherent model of the phenomena presented. The students’ interpretations and conceptions are often contradictory, but none the less stable’. We have also seen that Claxton considers (e.g. scientist’s) science knowledge to also be formed of a cluster of minitheories, and Driver and others have characterised some alternative conceptions as deriving from personal conceptual frameworks. This would suggest that the distinction in the characterisation of knowledge representation in the two domains should not be considered absolute, and that Fig. 6.3 indicates no more than a tendency for knowledge to be more abstract, integrated and generalised in one domain, and more context-tied and fragmentary in the other.

6.1.4.19

Learners’ Manifold Conceptions May Derive from Complex Personal Conceptual Frameworks

Pope and Denicolo explored the relationship between the comments made by individual learners in interview studies, and the general models constructed by researchers to represent the range of ideas elicited from a sample. In Gilbert and Watts’s (983: 69) approach to exploring learners’ ideas early in the RP they developed an analytical scheme for moving from the utterances elicited from individual informants to ‘generalised non-individual descriptions … as short summary descriptions … thematic interpretations of data, stylised, mild caricatures of the responses made by students’. Such an approach clearly loses some of the detail and authenticity of case studies that can offer in-depth accounts of an individual’s thinking (see the discussion of methodology in Chapter 7). However, Gilbert and Watts recognised that the ideas of individual learners were unique, so research that offered accounts of sufficient generality to inform teaching required generalised models. The outcomes of such research were sets of alternative ways of understanding such concepts as force, energy, gravity, etc. that collectively reflected the different ideas that were elicited from samples of learners. So, for example, Watts (1983) identified eight distinct generalised conceptual frameworks (‘alternative frameworks3’, in terms of the discussion in Chapter 5) as ways of thinking about force among his informants. These eight generalised conceptual frameworks derived

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from analysis of the responses of twelve school pupils of different ages, suggesting that the findings were likely not ‘saturated’ – and so increasing the sample size might well have uncovered additional conceptual frameworks (see Taber, 2007a: 79–80 for a discussion of this case). More significant for present concerns, there was no one-to-one correspondence between the informants’ comments and particular generalised frameworks, as was readily acknowledged, Firstly, it is far from clear how representative of an individual’s thinking a particular [generalised] framework is. Indeed, given the manner in which such frameworks are obtained from interview (and other) data, it may well be that an individual’s conceptions make use of several frameworks. (Gilbert & Watts, 1983: 86)

Pope and Denicolo (1986: 158) labelled this situation ‘where, within one utterance or short speech act, more than one of [the proposed] frameworks was projected’ as ‘multiple frameworks’. Pope and Denicolo noted that although it was possible to artificially ‘disaggregate’ a learner’s statements into smaller parts that could individually be fitted to the different generalised frameworks, such a process was not an authentic representation of utterances that seemed to genuinely encompass several categories that the analyst considers distinct (p. 159). Pope and Denicolo pointed out how any single generalised framework could often not do justice to the complexity of a student’s thinking, but this would not negate the claims for such generalised frameworks where the elicited conceptions are drawing upon knowledge represented in terms of something like Claxton’s minitheories, each cued (sometimes sequentially in a single utterance) by different contextual associations made to the researcher’s questions. If this is the case, then although the generalised frameworks do not correspond to the responses of individual informants, they may well – to a good approximation, and they are meant to be thematic abstractions – correspond to the range of minitheories available among the different students. However, Pope and Denicolo raised the different possibility that students’ ideas were drawing upon more complex knowledge structures and that a model of student thinking in terms of a set of discrete generalised frameworks fails to reflect the nuances of individual thinking. They suggested that ‘the existence of these “multiple frameworks” begs the question what is the operative intuitive theory held by the pupil? – Is it several component intuitive theories or is it the system of necessary interrelationships which is the intuitive theory?’ (p. 158). Drawing upon the ideas of George Kelly (§1.6.3), Pope and Denicolo argued that research should not focus on ‘framework-spotting’, but rather on exploring the complexity of individuals’ thinking, When Kelly (1955) discussed his organisation corollary he suggested that knowing that an individual possessed a particular construct was not of as much interest as knowing how (s)he organised a group of constructs into a coherent pattern. We suggest that those interested in intuitive theories need to go beyond classification of discrete utterances of ‘frameworks’ towards a full description of inter-related facets of explanations. (Pope & Denicolo, 1986: 58–59)

The positive heuristic of the RP seeks to develop models that can inform teaching, and in practical terms generalised conceptual frameworks may be more useful to

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teachers than fine-grained accounts of individual knowledge structures. However, the latter are important to researchers who wish to detail learning processes, and how they interact with teaching – issues also motivated by the positive heuristic (and which ultimately also have potential to inform practice).

6.1.4.20

Learners’ Manifold Conceptions May Reflect Multiple Personal Conceptual Frameworks

It is also possible to imagine that an individual holds more than one well-established and coherent set of ideas about a topic, with no strong reasons to commit to one alternative, i.e. that a students’ ‘manifold conceptions’ actually derive from several alternative personal conceptual frameworks (rather than distinct minitheories each having a restricted range of application). My study of A level students’ developing understanding of chemical bonding offered an example of the more complex interrelationships of facets that Pope and Denicolo (1986) called for. I found that one of the student informants, known as Tajinder, used three complementary explanatory principles throughout his 2-year course to explain chemical bonding (Taber, 2000d). So if Tajinder was asked why a bond was formed he was likely to respond in three different ways, which may be paraphrased: so that atoms could obtain full shells; to give a lower energy level; because of the attractions between charged particles (Taber, 2000d: 404). The first of these options is a central feature of the generalised alternative conceptual framework shown in Fig. 6.2. The other two principles derived from his college-based learning, although in considering them as distinct bases for explanations the ‘minimum energy explanatory principle’ is (like the ‘full shells explanatory principle’ or ‘octet rule explanatory principle’) teleological, and only the ‘Coulombic forces explanatory principle’ offers a mechanism for the processes Tajinder was explaining. The significance of this research is not that Tajinder offered several different rationales for explaining chemical bonding and related processes, but rather that (a) these principles were all used over an extended period; (b) the principles did not derive from localised ‘minitheoretical’ knowledge, but rather each was elicited in a wide range of specific contexts as the basis for explaining different examples; and, moreover, (c) Tajinder was prepared (at least in some cases) to apply these different principles to the same contexts. The case study of Tajinder (Taber, 2000d, 2001c, 2003a) offers evidence that an individual learner can over an extended period be shown to simultaneously hold distinct explanatory frameworks that are widely applicable, have overlapping ranges of application (or convenience) and are actually acknowledged as alternative ways of thinking about the same topic. Another example can be found in a study by Petri and Niedderer (1998), which traced a German gymnasium (high school) student’s learning pathway as he studied atomic physics (see §6.2.2.14). At the end of the teaching sequence Carl’s ‘final cognitive element “atom” following teaching is displayed as an association of three

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parallel conceptions including his initial planetary model, a state-electron model and an electron-cloud model’ (p. 1075).

6.1.4.21

Coexisting Knowledge Structures Can Be Stable, Contradictory, and Have Overlapping Ranges of Application

Tajinder, then held several different conceptions for why chemical bonding occurred; each of which was applied in the ‘school science’ domain; and each of which was held as a general principle that could be widely applied. It is important here to distinguish stability from consistency. This distinction is recognised in Kelly’s Personal Construct Theory (§1.6.3) in terms of his ‘fragmentation corollary’ (Kelly, 1963: 83), i.e. that ‘a person may successively employ a variety of construction subsystems which are inferentially incompatible with each other’. From this perspective, an individual could have a stable construct system, yet still give the impression of flitting from one notion to another. It is quite possible for an individual to answer a question drawing upon a stable knowledge structure represented in memory without necessarily being completely committed to it (in the sense of ‘believing’ it to be so). Indeed, the kind of constructivism advocated by Glasersfeld (§5.2.6) does not require individuals to believe their models of the world, but rather, like instrumentalists in science, simply to have good reasons to commit to a model as being sufficiently well fitted to experience to be considered viable and useful in certain circumstances. In Tajinder’s case, he was (at least by the end of the study) aware that he held alternative conceptions that he was selecting from, which he recognised appeared inconsistent alternatives (as he did not link his Coulombic forces principle to his minimal energy principle as a physicist would). He came to see these alternatives as different narratives, each of which had some merit, from which he could select to explain particular examples of chemical behaviour (Taber, 2000d). In effect he came to see the different principles as generally applicable models with different strengths. Whilst this was not an entirely appropriate way of thinking about this particular set of principles in the context of the target knowledge taught in his course, it demonstrated a quite sophisticated approach to thinking about the nature of scientific knowledge. Tajinder was a student working at quite high (university entrance) level who had previously been successful in school science. Case studies cannot be widely generalised, and Tajinder is unlikely to be typical of most school-age students. Research into children’s ideas about the nature of science suggests that although they do adopt many of the models they meet in school science, they often do not have the metacognitive awareness to conceptualise their thinking in this way, i.e. using models as thinking tools (Duveen et al., 1993; Driver et al., 1996). Petri and Niedderer’s study of Carl (a case study dealing with a student of similar maturity to Tajinder, see §6.2.2.14) and his learning pathway in atomic physics, reported that during his course Carl developed a complex knowledge structure with several interlinked models of the atom. However, even at the end of his work on the topic,

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his original conception, ‘the prior conception of a planetary atom seems to be very strong’ (p. 1084).

6.1.4.22

Modelling Complex Knowledge Structures As Possible Partial Models

When students’ thinking draws upon such complex representations of knowledge in cognitive structure it becomes a challenge to model. Reddish (2004: 24) has conceptualised different views about the nature of students’ knowledge structures ‘as the model theory and the modular theory’ characterised ‘along the axes of robustness (how broadly the knowledge is activated in a variety of situations), degree of compilation (the extent to which complex knowledge can be applied in working memory), and level of integration (how much diverse knowledge is tied together)’. If even a sophisticated scholar such as Thayer-Bacon can acknowledge that her knowledge resembles a patchwork quilt work-in-progress, drawing upon contributions from a broad community deriving from different standpoints, and never a finished product (§3.3.3); then it perhaps should not be surprising that students’ knowledge structures may be manifold, inconsistent, sometimes incoherent, and reflecting the pluralism of sources they derive from (physical intuition, school, family, peers, mass media etc.). Certainly schoolchildren and college students may have personal knowledge that fails to meet the standards expected of formal World 3 knowledge (§2.2.2), and certainly this may in part be linked to their status as students (immature, still passing through their formal education, etc.). However, the characteristics of their ‘knowledge-quilts’ may have less to do with youth as such, and may simply reflect the nature of human ‘personal’ knowledge compared to formal scientific knowledge. Whilst this may seem to echo Claxton’s (1993) suggestion that all personal knowledge is in the form of something like minitheories, this need not be the case. Much personal knowledge may well be like this, but humans can become experts (Nickerson, 1985), where knowledge relating to the area of expertise is more highly and coherently structured. This consideration suggests that scientist’s science should be seen as something more than a set of minitheories, and that learners’ science may often be moving significantly towards that of the expert. A learner’s knowledge will demonstrate some manifold aspects, incomplete integration, and so forth, but may well show much more structure than a collection of loosely associated ideas with narrow ranges of application. Reddish (2004) describes an approach to exploring teaching and learning that posits ‘associations’ and ‘controls’ as key concepts. A model within this approach would ‘identify resources, their associational patterns and their context dependence’, where the associational patterns ‘identify which resources go together’. The controls ‘identify the environments and cues that activate particular associational patterns’ (p. 54). Another approach to modelling the complexity of knowledge structures has been described by Camacho and Cazares (1998). They set out to devise an approach that allows researchers ‘to construct models or schemes that indicate the existence of hierarchies among the intuitive ideas and how they guide the predictions,

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explanations, and interpretations given by the students confronting different physical explanations’ (p. 16). The aims of such models would be to (p. 16): • Include an elementary set of inferential forms; that is, there would be associate schemes of reasoning construction used by students in their answers to specific physical problems • Establish hierarchies and classes among intuitive ideas, relationships, and phenomenological descriptions, meaning that we would be able to identify conceptions that in the students’ mind act as regulators or constrictors of their own interpretations and inferences • Distinguish between types of conceptions or intuitive ideas; for example, if these refer only to phenomenological descriptions or to the establishment of functional relationships among variables • Specify the physical context; that is, the application range should be identified Camacho and Cazares’s approach is called ‘possible partial models’ (p. 17) and includes two types of element they call ‘constrictor concepts’ (‘conceptions the students have as a basis for interpretation of certain physical phenomena and that are used to make inferences’; ‘believed to be true by students and thus constitute a kind of axiomatic framework’; ‘knowledge that students elaborate as abstract representations’) and ‘rules of correspondence’ (‘the students’ ideas that define specific relationships between variables or phenomenological conditions and variables’; ‘conceptual constructions in which explicit relations among phenomenological variables are established, or in which particular conditions that students attribute to physical processes are specified’). Camacho and Cazares explain that the term ‘partial possible model’ refers to how the models are ‘mainly framed within students’ empirical schemes’ and ‘provide us with a scheme of interpretation based on: (a) an inferential reconstruction starting from students’ conceptions; and (b) the possibility to build a scheme of interpretations that the students have on physical phenomena’ (p. 18). This type of approach seems well suited to modelling the complex and often apparently contradictory nature of students’ thinking in science, Possible partial models allow us to represent several of student representations related to the same physical phenomenon at the same time, and also to identify which type of intuitive ideas or relationships among them are determining that interpretation. Possible partial models also allow determination of how contradictions can appear without modifying the students’ basic ideas or constrictor conceptions; for this purpose, it is sufficient to produce a different rule of correspondence and then contradictions are possible. (Camacho & Cazares, 1998: 25–26)

6.1.5

Explaining Diverging Views of the Nature of Learners’ Ideas

Researchers who have explored student thinking in depth have still come to very different views about the nature of the ideas that students demonstrate in contexts

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such as research interviews and classroom dialogue. It seems reasonable to assume that work published in respected peer-reviewed journals and academic books should generally be considered competent, so it is not appropriate to simply dismiss one side of this debate as wrong. Yet, competent researchers may be understood to come to opposing conclusions to the extent that the phenomena being studies are complex enough to offer viable answers to a range of apparently incompatible research questions. In other words, we might expect this situation if ‘students’ ideas’ cannot simply be characterised as theory-like or not; as labile or stable, as extensive or local, etc. Rather, learners’ ideas may potentially vary along a range of dimensions, depending on age, familiarity with topic, context of question asked, etc. This diverse set of findings in the literature suggests that our default assumption should be that learners’ ideas will show diversity along a range of dimensions, and that our research question ‘what is the nature of these ideas that learners’ bring to science classes?’ from the positive heuristic of the RP (§4.4) needs to be asked with this in mind (Taber, 2006a, 2006b). As Sjøberg explains, the status of the ideas that children express may indeed differ from one type of phenomenon to another, and this is an empirical question that may be clarified by research. In some areas, one may find that the expressed ideas are very loose, often ad hoc, and even invented in the interview setting. Piaget himself wrote about these challenges in the 1920s. For other types of phenomena, children’s explanations are more deeply rooted, well integrated, and systematically used to understand a wide class of experiences. In this case, they may be very resistant to change, and sometimes one should think twice before embarking on such a project. (Sjøberg, forthcoming: 7)

6.1.6

How Much Commonality Is There Between Learners’ Ideas in Science?

With many of the issues explored so far in this chapter, learners’ ideas in science cannot be readily characterised at one pole of a dimension (such as stable–labile; or specific–general; isolated–integrated) and this is also found in terms of the idiosyncratic–universal dimension. It was clear from early in the RP that some of the alternative conceptions elicited in research seemed to recur widely in populations. Driver (1989: 483) noted how ‘the conceptions originally documented through indepth investigations in specific domains … have been identified in a wide range of replication studies suggesting that there may be some commonality in the models that students construct to interpret the natural world’. However, as Pope and Denicolo (1986) warn (see §6.1.4.19), judgements about the commonality of ideas elicited from students depends to some extent on the methodological approaches taken to identify them. When data collection techniques explore the thinking of individuals in depth, and analytical approaches prioritise modelling individual conceptual structures, then the unique nature of each person’s knowledge structures become clear. When data collection techniques focus on collecting data from large samples (at the necessary cost of limited detail) and analytical approaches

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are focused on identifying categories of response, then findings inevitably reflect commonalities rather than differences (Taber, 2007a). This complicates any overview, but it is clear that some alternative conceptions elicited from individuals are relatively idiosyncratic, whilst others reflect aspects of the thinking of many learners (although as components of knowledge structures that may in detail differ considerably among those demonstrating the conception). Given the biological similarity of all humans, and the commonalities of their physical and cultural environments, and the importance of social interactions in learning, strong similarities between the conceptions elicited from different learners are to be expected. Conversely, given the unique set of specific contingencies that has channelled the learning of each individual, the elicitation of apparently idiosyncratic conceptions seems equally unsurprising.

6.1.6.1

Common Alternative Conceptions

The conception that a force is required to maintain motion offers an archetypical example of a ‘common’ alternative conception (see §6.1.3.1). It has been suggested that the vast majority of learners display untutored thinking along these lines (Watts & Zylbersztajn, 1981), and as we have seen above, such conceptions tend to be tenacious and continue to be applied in familiar contexts despite formal teaching of the canonical physics formalism. This way of thinking about force and motion has also been compared to Aristotle’s ideas (Gilbert & Zylbersztajn, 1985), showing that this conception, although ‘alternative’ now, was an accepted way of thinking before Galileo and Newton. It is of course important to recognise that Aristotle’s ideas were well developed, but were based on an assumption than motion is impeded (Toulmin & Goodfield, 1962/1999) which matches the examples of motion that children experience in developing their intuitive notions. This perhaps reinforces the point that the use of the term ‘alternative conception’ in the RP is meant to be a marker showing a discrepancy with officially sanctioned target knowledge, and is not intended to necessarily imply an evaluation of the worth of the idea. As suggested above (§6.1.4.5, §6.1.4.7), in this particular case, the common life-world way of thinking about force and motion is more directly applicable in most everyday contexts than the idealised formalism of physics. Steinberg, Brown and Clement (1990) have argued that some of the common learning difficulties (i.e. difficulties accepting and adopting the physics formalism set out as target knowledge) found among contemporary students when studying Newtonian mechanics reflect conceptual difficulties that significantly impeded Newton himself when developing this ideas. So Newton had to overcome an impetus-like notion of force, and a belief in centrifugal force to produce his laws of motion and gravitation, just as so many students ever since when being taught about his theories. The research on student understanding of chemical bonding and related topics discussed earlier in the chapter identified a number of alternative conceptions that were common across different student informants (in the sample from within a single college setting). I used some of these as the basis of survey items to explore the degree to which they resonated with other learners. Surveys are used

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to demonstrate patterns in populations based on sampling, but only offer reliable estimates of frequencies within populations when a sample is carefully designed (Taber, 2007a). In educational studies, especially those not supported with high levels of funding, less rigorous sampling procedures are commonly used which cannot allow inferences about the likely ‘error’ in estimating a population frequency from results. Nonetheless, such methods can offer useful indications when samples are used that are not considered likely to be especially atypical of wider populations, and particularly where diverse samples offer similar results. As one example, atoms are electrically neutral entities, and the ionisation of an atom is a process that requires work to be done to separate the negatively charged electron from the positive residue of an atom. In chemical contexts ions may be formed from neutral atoms (although neutral atoms seldom feature in chemical reactions under familiar conditions, Taber, 2003c), as the ionisation process may be just one aspect of a more complex systematic change that is exothermic overall. However, when college (high school) students are taught about ionisation in chemistry, they are taught about the relative magnitudes of the energy required to ionise different atoms, and expected to explain patterns in and comparison of ionisation energies. Despite the topic of ionisation energies being based around a schema of energy being applied to remove electrons from atoms, interview studies found that students still commonly thought that atoms would spontaneously ionise to form more stable ions that had octet or full-shell configurations. The ion would only actually be more stable than its ‘parent’ atom when considered as a component of larger systems such as ionic lattices, whereas students commonly see the ion and electron as more stable than the atom even when the question context is clearly an isolated atomic system (Taber, 2008f). Statements based upon student comments in interviews were used as items in various paper-and-pencil instruments that could be administered to groups of students. A statement that a sodium cation (Na+) was more stable than the atom (Na) was selected as correct by the majority of students in each of a number of modest samples (24/29; 17/19; 24/28; 27/33) in a series of related studies on student’s perceptions of chemical stability (Taber, 2000a, 2008f). In a study of student thinking about ionisation energies almost four-fifths of a sample (264/333) agreed that ‘the atom would be more stable if it ‘lost’ an electron’ (Taber, 2003d). These studies were conducted in the UK. However, in a subsequent cross-national study of (some college, some undergraduate) students, a compound statement (in a two-tier multiple choice format) that ‘the Na(g) atom is a less stable system than the Na +(g) and a free electron’ because ‘the Na + (g) has a stable octet configuration’ was selected by at least twofifths of the sample in each of six different countries: China: 69%; New Zealand: 49%; Spain: 40%; UK: 51%; USA: 63%; Singapore: 64% (Tan et al., 2007).

6.1.6.2

Idiosyncratic Alternative Conceptions

As suggested above, the finer-grained the investigation of a learner’s thinking that is undertaken, the more it is possible to detail the range of application of concepts, the nuance of meanings, and the nature and strength of their connections

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to other concepts. In principle, given a detailed enough investigation, it should be possible to show that any learner’s conception of force, chemical bonding, plant nutrition, etc. has unique aspects, even if only in terms of its relatively peripheral characteristics. However, it is also clear that there are many examples of individual students demonstrating quite idiosyncratic conceptions that are not just nuanced variations on common theses. Earlier in this chapter, the example of Annie who held a ‘deviation’ conception of ionic charge system was reported (Taber, 1995b). Annie managed to develop a scheme for interpreting teaching according to her alternative formalism. So, for example, Annie was able to balance equations using her ‘deviation’ conception of charges, but seeking full shells rather than neutrality. Her formula for aluminium sulphate was (Al3+)4(SO42−)2. For Annie, the four aluminium atoms provided three surplus electrons each. Four of these twelve electrons went to cancel the deficit of two electrons on each sulphate group, leaving eight electrons, which made a full shell! It is interesting that Annie, in common with many other learners studying chemistry at this level had developed an alternative conceptual framework based upon the idea of atoms needing full shells (see §6.1.4.17), but including an alternative conception that was idiosyncratic and required her to make sense of much of her teaching in quite different ways to her classmates.

6.1.6.3

Variations on a Theme

One further example may be useful in illustrating several of the points made in this section about the complexity of student knowledge structures (and so the methodological difficulties of exploring them). This will concern the use of a simple survey to explore the extent to which secondary age learners who had studied the topic of ionic bonding had either learnt features of the canonical science model, or had adopted an alternative conceptual framework. Butts and Smith (1987) had identified ionic bonding as a topic that high school students considered difficult, and reported that in interviews their informants commonly volunteered ideas at odds with the scientific model. In my own interview study I elicited similar ideas (Taber, 1994b). These ideas made up part of the (‘generalised’) alternative conceptual framework describing students’ thinking about bonding discussed earlier (see Fig. 6.2). However the particular ideas relating to the ionic bond appeared to make a coherent conceptual framework of their own (which might be considered subsumed within the framework shown in Fig. 6.2). The ‘molecular’ framework is a generalised alternative conceptual framework in the sense discussed in Chapter 5 (§5.3.5), i.e. different students demonstrate aspects of the framework to different degrees. It is alternative in that it can be compared to the scientific model of ionic bonding represented in the curriculum. This is shown in Fig. 6.4. The gist of the alternative framework is that ionic bonding occurs when a metal atom donates its electron to a non-metal atom so that both can fill their shells, and so

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Students Understanding Science label

molecular framework

status

alternative framework

261 electrostatic framework curricular science

role of molecules

ion-pairs are implied to act as molecules of an ionic substance

ionic structures do not contain molecules - there are no discrete ion-pairs in the lattice

focus

the electron transfer event through which ions may be formed

the force between adjacent oppositely charged ions in the lattice

valency conjecture

atomic electronic configuration the number of bonds formed determines the number of ionic bonds depends on the coordination formed. (e.g.: a sodium atom can only number, not the valency or ionic donate one electron, so it can only charge (e.g.: the coordination is 6:6 form an ionic bond to one chlorine in NaCl) atom.)

history conjecture

bonds are only formed between atoms electrostatic forces depend on that donate / accept electrons. (e.g.: in charge magnitudes and separations, sodium chloride a chloride ion is not prior configurations of the bonded to the specific sodium ion that system (e.g.: in sodium chloride a donated an electron to that particular chloride ion is bonded to six anion, and vice versa.) neighbouring sodium ions)

‘just forces’ conjecture

ions interact with the counter ions a chemical bond is just the result of around them, but for those not electrostatic forces-ionic bonds are ionically bonded these interactions are nothing more than this (e.g. the just forces. (e.g.: in sodium chloride, a forces between a chloride ion and chloride ion is bonded to one sodium each of the neighbouring sodium ion, and attracted to a further five ions are equal.) sodium ions, but just by forces-not bonds.)

Fig. 6.4 Comparing two conceptual frameworks (From Taber, 1997)

the bond is between the atoms that have been involved in this transfer. These atoms form a unit within the structure similar to a covalent molecule, and these pseudomolecules are themselves bound to each other by ‘just forces’ rather than proper chemical bonds. The discrepancies between this model and the scientific model may seem to be of little importance to most learners, just concerning notions of how conjectured quanticles (atoms and ions) interact at a scale that students can never directly experience. However, the value of submicroscopic models in chemistry is to explain molar scale phenomena, and the alternative conceptual framework falls short. The structural integrity of salts, their hardness and high melting temperatures, are explained by the continuous lattice of strong bonds – whereas the molecular framework would predict soft, easily melted substances. Similarly, salts dissolve as discrete ions, which leads to the important electrolytic properties of their solutions – yet students commonly assume that dissolving in ionic material leads to neutral pseudo-molecules (e.g. ion pairs) being the main solute species. Examples such as these are important in exploring student thinking in science, for the molecular framework clearly does not directly derive from life-world

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experience: it is not part of folk knowledge that salts are molecular, and nothing in students’ direct experience of ionic compounds (e.g. using salt in cooking) is likely to lead to developing intuitive theories about the nature of its chemical bonding. As suggested above, such ideas cannot be explained by assigning alternative conceptions to a different domain that is distinct from where scientific models learnt in school are represented. This does not refute the idea of knowledge domains, but shows that any tendency to conceptualise life-world and academic school knowledge separately is not sufficient to explain all the alternative conceptions students demonstrate. The survey based upon the two frameworks consisted of a simple figure representing a slice through a NaCl lattice and a set of statements that students were asked to rate as ‘true’ or ‘false’ (and a ‘do not know’ option was available as well). The final version of the instrument was used to collect data from eight institutions in England from a total of 370 students who had studied the topic at school-leaving level, including 129 that had undertaken further study of the topic at university entrance level. Among the findings (Taber, 1997), a majority of students in the sample agreed with items stating: • • • • •

The sodium and chloride ions could only form one ionic bond each. The ionic bond was when electron transfer took place to give full outer shells. The bond was formed because electron transfer had occurred. Molecules of sodium chloride were shown in the diagram. Each molecule of sodium chloride contains one sodium ion and one chloride ion.

Aspects of the alternative framework seemed perfectly acceptable to most of the students despite being at odds with the target knowledge in the curriculum. However, the patterns of results also showed that (a) statements based on the electrostatic framework were often also seen as correct by a majority of respondents, even when they contradicted the popular alternative statements; and (b) there was considerable variation in the level of support for different items based on a particular framework, and this applied even when items were based on the same aspect of the framework. As there was very little use of the ‘do not know’ option, these patterns of responses do not seem to reflect a lack of motivation to complete the survey, but rather would seem to show that many individual students demonstrate inconsistency in judging which responses they agree with. The interpretation favoured was that at least some of these students had developed multiple frameworks for thinking about ionic bonding, interpreting some teaching in terms of a molecular way of thinking, but also acquiring something of the (inconsistent, from that perspective) curriculum model. In these cases, where a statement matched understanding from one or other framework it would likely be rated as correct even if this was contradictory to responses on other items. This section has suggested that a wide range of ‘refutable variants’ of the RP (minitheories, life-world knowledge, folk science, manifold conceptions and

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multiple frameworks, etc.) have been adopted to interpret and explain different aspects of student thinking in science elicited in research. That such a variety of views and constructs have been proposed suggests that a student’s knowledge structure is too complex to be understood within any one simple model, and what is needed is an approach that can subsume the range of notions that have been applied in the field into one overarching theory. Such a theory would need to offer something more than just a wide enough set of categories to be able to accommodate all possible empirical findings, but rather needs to be empirically progressive by suggesting principles for predicting the particular characteristics of students’ ideas that will be elicited in various research contexts (Taber, 2008a). Clearly such a theory would be informed by an understanding of the learning processes by which students develop their ideas. This is the aspect of the RP which is considered next.

6.2

Students Learning Science

Learning can be understood as a change in the individual’s behavioural repertoire that results from experience (as opposed to ‘development’ which is seen ‘unfolding’ under genetic control – the distinction is not absolute of course). Behaviour of interest in formal science learning contexts is often (though not always) verbal. So, for example, learning might allow an individual to have the potential to explain why a whale is not considered a fish, when this was not available before the learning took place. A student may also interpret teaching to learn that plants photosynthesise only during the day and respire only at night, so what is learnt about science is not necessarily well matched to target knowledge (even when learnt in science lessons, as we discovered when considering the molecular framework for ionic bonding).

6.2.1

Levels of Analysis of Learning

Reddish (2004: 4) refers to triangulating information about learning from different disciplines, variously concerning ‘three levels: neuroscience, cognitive science and the phenomenological observational science of human behavior’. In cognitive psychology an information processing perspective on cognition often considers three different ‘levels’ (Dawson, 1998), ‘computational’ (considering the information processing ‘problem’ being ‘solved’ by the system), ‘algorithmic’ (concerning the method of processing the information) and ‘implementational’ (the physical properties of the system). The RP in Science Education has not been strongly concerned with the implementational level (however, see the next subsection), but is more concerned with both the types of information that can be represented in mind, and in what ways it is processed in learning science (the computational level), and – to the extent that it can inform teaching – understanding the cognitive

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apparatus available to learners, and how this impacts upon cognitive processes (the algorithmic level).

6.2.1.1

Neuroscience and Science Education

Learning is considered to be due to changes in the brain at the level of neuronal connections, and the ease with which particular synapses are activated. A certain amount is known about how learning occurs at this level (Goswami, 2008), but there is still a considerable explanatory gap between models of neuronal changes and observed changes in behaviour from which such learning is inferred. The generative learning model of Osborne and Wittrock (1983) offered an early attempt to build Science Education theory that adopted latest thinking from cognitive science (§4.1.4), and Alex Johnstone (1989) has championed such an approach. However, it is only more recently that it has begun to seem feasible for science educators to move beyond information processing models to draw upon work in neuroscience itself (Roth, 1998, 2000; Lawson, 2003).

6.2.1.2

Models of the Cognitive Apparatus Involved in Learning

Although ideas about the ‘implementational level’ of cognition are only in recent years beginning to inform research into learning and teaching in science, ideas relating to the algorithmic level have been useful in thinking about the cognitive processes involved in learning. Some of the ideas about learning discussed below make use of notions relating to system elements that can be considered to have specific roles in cognitive processes, even where it has not been possible to identify specific neurological structures that can embody the conjectured apparatus (e.g. the abstract knowledge structures labelled ‘p-prims’ would need to be encoded in specific neural circuits). A key concept in learning is that of ‘memory’, that cognitive ‘organ’ that is able to represent facts, ideas, episodes, etc. in some form of long-term store. It is common human experience that we can ‘learn’ things, that we are able to put out of conscious awareness, but then access later as memories so that we can again be consciously aware of (what seems to be) the original information or experiences. Bruner (1964/1977) describes three levels of representing the world: the enactive level (through action), the iconic level (through mental imagery) and the symbolic level (through the manipulation of symbols). Studies into (normal) memory function have led to some basic information that can inform teaching and learning (Baddeley, 1990). A key distinction is between two types of memory, a very limited capacity and short-term form of memory which enables us to keep ‘things in mind’, but which only maintains information as long as it is currently being used, and a long-term memory that has effectively infinite capacity, and seems capable of retaining representations that allow reactivation of material as long as the brain remains intact and functioning (Baddeley, 1990).

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6.2.1.3

265

Working Memory, Processing Information and Problem-Solving

The work of Miller (1968) has been particularly influential, as he summarised the findings from a series of studies of perception in terms of a general limitation to human processing ability. This became known in terms of the ‘magic’ number 7±2, which represented the number of independent items that could be juggled at any one time in ‘working memory’ (compared with the effectively limitless capacity of long-term memory). Working memory as one of the conjectured components of the cognitive system itself comprised of an executive unit supported by a ‘visiospatial’ sketch pad (for images) and a phonological loop (for sounds). Working memory was considered to act as a buffer between perception and long-term memory, and so its limited capacity could be considered to be a bottleneck in the cognitive system. Although seemingly a severe restriction on human cognition, it has been argued that it may have been selected for, as it protects long-term memory from becoming too labile (Sweller, 2007). A key finding about working memory capacity is how it is relative to how the learner ‘chunks’ information: that is what is conceived as an independent item of information. A commonly reported example is of Chess experts who show exceptional ability to recall the positions of chess pieces, as long as they are arranged in actual game positions (Mayer, 1992). When the pieces are arranged randomly on the board, the chess experts lose their advantage, as they no longer see the pieces in familiar patterns (cf. §1.7.2). More directly relevant to Science Education is a study that replicated the principle in the context of electrical circuits. Egan and Schwartz (1979: 149) reported how skilled technicians could recall briefly seen circuit diagrams more accurately than novices, but lost the advantage when the circuit symbols were arranged randomly – suggesting that the degree to which they chunked material was progressively related to the length of experience working in the domain.

6.2.1.4

Long–term Memory

Storage into long-term memory is not usually instant (the exception being highly charged events that produce a sudden flood of adrenalin into the bloodstream) and so information has to be stored in some form of temporary buffer until it is transferred into long-term memory. A distinction is often made between different types of memories, such as episodic memories (of particular life events) compared with semantic memories (of conceptual information, such as a statement of Newton’s third law, the atomic number of carbon, or the difference between the functions of xylem and phloem). Not all information seems to be transferred to long-term store, and the intermediate buffer seems to be of a different form to long-term memory. The buffer seems to store information in some form of active electrical circuits, which may

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be disrupted by a traumatic event (e.g. a heavy blow to the head causing loss of consciousness), whereas the long-term storage appears to be based on ‘permanent’ changes in synaptic connections that are not susceptible to such interruptions. The analogy with a computer which loses information ‘in memory’ (RAM) but not that coded into a physical substrate such as a magnetic disk (ROM), when power is interrupted, is very enticing – albeit reflecting the influential, but limiting, personas-machine metaphor. Memory studies have explored the extent to which people are able to learn new information (although often based on nonsense syllables or other not especially meaningful material) and have led to advice about the way the proportion of material remembered tends to dip in the middle of learning sessions. Studies of longterm memory suggest that once something is encoded it is likely to be potentially available indefinitely, but that access to the original information depends upon activating the appropriate representation, and that is by no means always readily achieved. Access to represented information is increased when the information represented is highly integrated, as (it is conjectured) this provides alternative access routes to the target ‘memory’.

6.2.1.5

Consolidation of Learning

Accessing a memory is not a passive process as it effectively strengthens the future activation of the same representation, and allows new links to be formed with whatever other materials is processed in connection with the memory. This ‘strengthens’ memories, but as the network of representations is changed it can also modify the ‘memory’ that is activated when the representation is accessed. Azri (1988: 19) lists a number of studies detecting learning beyond instruction, i.e. studies in which the delayed outcomes were better than the immediate ones: • Eleven days after training of primary schoolchildren in classification • After a 6-week retention interval with secondary students on conservation of volume • After a 6-week retention interval with secondary students on concept learning in ecology • Three months after instruction of the space concept in primary school • Four months after a tertiary course on qualitative chemical analysis Azri argues that such effects can be explained using Ausubel’s (§1.9.2) learning theory, as ‘when a student is exposed to new materials which are related to antecedent learning, and if the student indeed relates the new materials to her or his prior knowledge, then the interaction between new and prior knowledge during the assimilation process mobilizes previously learned concepts in the student’s cognitive structure, thus increasing their availability for future use’ (p. 43). This is the basis of the very common advice that teachers should revisit new ideas regularly to support consolidation of ideas in memory – to allow the learner to build up extensive sets of connections between represented information.

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In the study of chemistry, increasingly abstract models of the atom are introduced. Students are often taught a model based on a nuclear atom with ‘shells’ of electrons in their introductory chemistry classes, which is then complemented by a model where electrons occupy orbitals in more advanced classes. One of the findings from an interview study I carried out with UK Advanced-level students was that in some cases students would be able to give acceptable expositions of orbital ideas when asked about them, yet those same students seemed unable to apply the same ideas in their explanations (Taber, 2005b). So a student referred to as Kabul ‘knew’ that molecular orbitals (MO) are considered to be formed from atomic orbitals (AO), and so that once MO are formed the AO from which they are considered to be constructed are no longer present. (Such language suggests an ontological reality to orbitals that is questionable, but seems necessary for talking about the concepts when introducing them to students.) Despite being apparently quite clear about this, Kabul was also adamant that these AO were still present in the molecules. This did not seem to be some philosophical point, but rather even after accepting that his answers were inconsistent and agreeing that it was not the case that AO were present, he would repeat the claim in the context of further examples. This type of fragmentation in knowledge structure was conjectured to relate to the timescale for consolidation of new learning, Kabul could provide all the relevant knowledge when scaffolded … through specific direct questioning, but was not yet able to spontaneously construct chains of explanation in this concept area. … It could be hypothesized that these fragmentation learning impediments occur in such ‘within-topic’ contexts when the students had not integrated aspects of recent learning, i.e. that the new ideas are present in cognitive structure, but not yet consolidated. … It is conjectured here that recently acquired knowledge – though accessible in response to direct questioning – may not always be available in a form suitable to act as the foundations for new learning, not having yet been fully integrated into conceptual schemes. From this perspective the new learning is present, but ‘fragile’, whereas prior learning has to be well established (‘robust’) before it can effectively support new learning. (Taber, 2005b: 111)

6.2.1.6

Confabulation and ‘False’ Memories

Indeed, research suggests that when we remember things it is common for the brain to only be able to access a portion of the information it needs to present a complete memory of the target, and that the brain tends to fill-in the details to present consciousness with a coherent ‘memory’. That is, memories are reconstructed based on representations accessed, and we are not usually aware which parts have been confabulated and which parts are based directly on accessed representations. (Further, if the confabulated memory seems to ‘work’ when we use it, it is likely to then become represented in memory, and what was a ‘false memory’ may be genuinely accessed from memory in future.) In one study pupils were shown, and appeared to accept, that their predictions about the relative brightness of lamps in circuits were wrong. About three months later the researcher found pupils restating their initial (scientifically incorrect, alternative) notions, but now citing the demonstration they

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had seen as supporting their ideas (Gauld, 1989). Their memories of the evidence had been modified to fit their existing understanding, rather than the other way round.

6.2.1.7

Forgetting Science

Whilst there are many studies that show students cannot recall what teachers think they have been taught, there are as yet few studies in Science Education specifically looking at forgetting. Tajinder, a student who was introduced earlier (§6.1.4.20), and whom I interviewed throughout his 2-year college chemistry course, was invited back for a follow-up interview several years later (after university study of a sciencerelated course with minimal chemistry content). Tajinder readily remembered many of the ideas he had learnt when he had studied chemistry. However, where Tajinder’s thinking had shown a clear trend during his studies of chemistry (shifting slowly away from reliance on alternative conceptions he had developed during school science), when he was re-interviewed he reverted to basing many of his explanations upon the alternative conceptions that had dominated his answers near the start of his college chemistry course (Taber, 2003a). Tajinder seemed to have forgotten much of the college learning that was inconsistent with the alternative conceptions he had acquired in school science. This is one case, and whether Tajinder might have shown an accelerated recapitulation of his earlier shifting thinking had there been the opportunity for a sequence of delayed interviews is not known. This would seem to be one area where further research would be illuminating.

6.2.2

How Does Knowledge Construction Take Place in Learning Science?

6.2.2.1

The Piagetian Model

Piaget’s research (§1.6.1) focused on cognitive development rather than conceptual development – so where his studies collected data about children’s conceptions this was in service of exploring the development of the broader logico-mathematical schemes that under-girded thinking, rather than being concerned with developing understanding of specific topic areas (§1.10.4). However, his ideas have been highly influential in considering how learning occurs in science. A key aspect of Piaget’s work is that he saw development as an iterative process, with existing structures providing the substrate for directing action upon the world that provided the feedback to develop new levels of structure. Key terms that Piaget introduced were assimilation, disequilibration, accommodation and equilibration. Assimilation can be considered as the incorporation of new ‘information’ within an existing mental scheme; disequilibration as the disruption of an existing scheme by the addition of new material; and accommodation as the modification of the scheme

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to fit the new information and so lead back to equilibration. For Piaget, assimilation and accommodation were sequential parts of the same overall process, rather than alternatives.

6.2.2.2

The Generative Learning Model

Very early in the RP, Osborne and Wittrock (1983, 1985) attempted to link constructivist principles with an information processing perspective on cognition, and proposed the ‘generative’ learning model (§4.1.7). Osborne and Wittrock argued that where the generative model differed from some other constructivist perspectives on learning was in the way it did not consider cognition primarily in terms of interpreting new information in terms of (stable) existing conceptions or schemata, but rather of building new knowledge structures by the very process of ‘generating links between different aspects of existing knowledge, different aspects of the incoming stimuli’ (p. 68).

6.2.2.3

Intuitive Mechanisms for Learning – Knowledge in Pieces

Any model of development or learning which relies on existing structures to be in place has to explain where the initial level of structure originates. Such a model therefore assumes some level of innate structure produced under genetic instruction to initiate the process. On this view the human brain necessarily has learning potential in the form of either innate knowledge (as per Socrates, see §1.5), or at least apparatus that offers some kinds of bias to start the learning spiral. The question of what might be considered innate in human cognition is a very old and still a live one (Elman et al., 1998). The question of at what point an innate structural feature is considered to code for knowledge rather than predispose learning in particular directions would also seem to be a matter of debate. One model that has been developed, especially in the context of physics learning, is that of ‘phenomenological primitives’, or p-prims. This model has developed from the work of Andrea diSessa (1993: 105) who set out to ‘understand the intuitive sense of mechanism that accounts for commonsense predictions, expectations, explanations, and judgments of plausibility concerning mechanically causal situations and to understand how those intuitive ideas contribute to and develop into school physics’. diSessa organised his programme around a series of questions (pp. 105–111): • • • • •

What are the elements of knowledge? How do they arise? What level and kind of systematicity exists? How does the system as a whole evolve? What can be said about the underlying cognitive mechanisms that are responsible for the normal operation of the system and its evolution?

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The view that diSessa developed was called ‘knowledge in pieces’, an approach that he claimed ‘assumes only a few very simple cognitive mechanisms, although the resulting knowledge system is conjectured to be large and complex’ (p. 111). In following his programme of research, diSessa has developed a detailed model (at the algorithmic level) for how the brain forms relatively naive knowledge representations by abstracting common patterns from individual experience (e.g. perceptual data) that he labels as phenomenological primitives, or p-prims. Although the brain is primed to develop abstracted knowledge elements at this level, in diSessa’s theory ‘it is an individual’s extended experience with the physical world that determines what particular p-prims exist’ (p. 119). This is a level of cognition above raw perceptual data, but not yet approaching formal theoretical knowledge, where ‘the intuitive sense of mechanism involves many simple elements whose origins are relatively unproblematic, as minimal abstractions of common events’ (p. 105). This leads to a system that, according to diSessa, ‘is only weakly organized’ and so ‘is subject to a number of constraints’. These include limited power to justify decisions and (due to the lack of a meta-level of organisation or a hierarchical structure) the ‘inability to resolve conflicts on the basis of knowledge within the system’ (p. 105). diSessa claims that despite the ‘weak organization’, it is possible to identify ‘some broadly characteristic traits’. Among these he includes ‘a prominent causal schematization in terms of agents, patients, and interventions’ that he refers to as a ‘causal syntax’ (p. 105). The ‘naive sense of mechanism’ that diSessa describes ties in well with the characteristics that Claxton (in his minitheories) and Solomon (in her ‘natural attitude’) associated with many of the alternative conceptions elicited in research into children’s ideas in science (§6.1.4.6, §6.1.4.8), the naively developed sense of mechanism does not come close to the expert’s in depth and systematicity. Instead, it is both less focused and less integrated. Although physics-naive people make important distinctions between superficial phenomenology and deeper mechanisms, these distinctions are very unlike those made by experts. For experts, phenomenology must uniformly be reducible, via an analysis of circumstances, to a few core theoretical ideas. This is not the case in the naive sense of mechanism (diSessa, 1993: 108).

6.2.2.4

A Common Core to Students’ Alternative Conceptions in Science?

The ‘causal syntax’ described by diSessa (1993: 105), a scheme involving ‘agents, patients, and interventions’, has been identified as a possible ‘common core’ to learners conceptions in a broad range of science topics: ‘such widely different areas as temperature and heat, electricity, optics and mechanics’ (Andersson, 1986: 155). Andersson labelled this core ‘the experiential gestalt of causation’ (p. 155), an idea proposed independently of diSessa by Lakoff and Johnson, Causation is an experiential gestalt which starts to be constructed at a very early age. The infant pulls his covers or his parents’ hair, shakes a rattle, takes a stick and pushes away a toy, throws his feeding bottle. Common to these and many other actions is that there is an

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agent which directly, with its own body, or indirectly, with the help of an instrument, affects an object, or, as Lakoff and Johnson prefer to say, a patient. (Andersson, 1986: 156)

Lakoff and Johnson (1980b: 205) see experiential gestalts as a stage in the abstraction of experience. They distinguish four levels in this process (p. 205): • Experience or occurrence in the world • Experiential gestalt – defined as ‘(a) a structure within a person’s experience that identifies that experience as being of a certain kind; or (b) a structure in terms of which a person understands some external occurrence and that identifies that occurrence as being of a certain kind’ • Concept (or generalized experiential gestalt) – defined as: ‘a mental structure that characterizes a category of personal experiences or occurrences in the external world’ • Representation of a concept (or generalized experiential gestalt) – defined as ‘a mathematical object which is a model of a concept (or generalized experiential gestalt)’ Concepts are formed ‘within the experience of people’, whereas representations of concepts are models constructed by researchers (Lakoff & Johnson, 1980b: 205). As we saw in Chapter 5, failure to make this discrimination leads researchers’ claims to be ambiguous and open to criticism. Lakoff and Johnson (1980a: 478) used the term gestalt to refer to the first level of abstraction in their scheme as although experiential gestalts might be ‘decomposable into other elements’ they were ‘yet basic and irreducible in terms of grounding our conceptual system’. Lakoff and Johnson argue that ‘prototypical causation is the direct application of a force resulting in motion or other physical change’, as ‘at the heart of causation is its most fundamental case: the manipulation of objects by force, the volitional use of bodily force to change something physically by direct contact in one’s immediate environment’. As ‘conscious volitional human agency acting via direct physical force’ is ‘at the center [sic] of our concept of causation’ (Lakoff & Johnson, 1999: 177), it provides the template for understanding causes generally. This ‘prototype’ would then be used in a metaphorical sense to explain other types of causality (the causes of wars, for example). Lakoff and Johnson (1980a: 479) suggested twelve ‘common features of what we may call a “prototypical” or “paradigmatic” case of direct causation’: 1. 2. 3. 4. 5. 6. 7.

The agent has as a goal some change of state in the patient. The change of state is physical. The agent has a ‘plan’ for carrying out this goal. The plan requires the agent’s use of a motor program. The agent is in control of that motor program. The agent is primarily responsible for carrying out the plan. The agent is the energy source (i.e. the agent is directing his energies toward the patient) and the patient is the energy goal (i.e. the change in the patient is due to an external source of energy).

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8. The agent touches the patient either with his body or with an instrument (i.e. the change in the patient is due to an external source of energy). 9. The agent successfully carries out the plan. 10. The change in the patient is perceptible. 11. The agent monitors the change in the patient through sensory perception. 12. There is a single specific agent and a single specific patient. According to Andersson (1986: 169), the experiential gestalt of causation provides an explanation for the very common alternative conception that a moving object must be subject to a force (§6.1.3.1), as ‘the idea of motion with no force whatsoever goes absolutely against the experiential gestalt of causation, that successful organizer of so much experience’.

6.2.2.5

Explaining Anthropomorphism and Animism in Learners’ Thinking

If Lakoff and Johnson’s characterisation of the basis for understanding causality is correct, it can also offer insight into some of the alternative conceptions from chemistry discussed near the start of the chapter, i.e. the way students commonly think about chemical processes in terms, for example, of atoms actively donating or accepting or sharing electrons to obtain full shells. Taber and Watts (1996) discuss how even quite advanced students use anthropomorphic ways of explaining the behaviour of atoms which are discussed as if consciously acting to fulfill their desires and needs. Such language was at one level recognised by students as only being a way of talking, yet – at the same time – appeared to be considered to offer a viable and productive way of explaining the chemistry. This fits well with Lakoff and Johnson’s view that once a common-core gestalt for causality is established it will act as prototype to be applied by metaphor even in cases where there was not a perfect mapping from the prototype. diSessa (1993) recognises that such a prototype is likely to be applied beyond its most appropriate range of application (or in Kelly’s terms, range of convenience), but suggests that overall the extension of this sense of mechanism is adaptive. He argues that ‘agency is a crucial attribute in the development of many aspects of cognition’ and that ‘it is likely that developing some sense of personal agency is one of the first important learning tasks for babies’. So although ‘various forms of overextension may be seen as anthropomorphic or animistic mistakes’, diSessa thought this tendency to overextend reflected how ‘agency is a good model for many physical regularities’ (p. 151).

6.2.2.6

Characteristics of p-prims

diSessa (1993: 111) describes phenomenological primitives, or p-prims, as ‘hypothetical knowledge structures’, that ‘often originate as minimal abstractions of

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common phenomena’ (p. 114) and which are ‘rather small knowledge structures, typically involving configurations of only a few parts, that act largely by being recognized in a physical system or in the system’s behavior or hypothesized behavior’ (p. 111). Some p-prims ‘serve important roles in explaining physical phenomena’ so that they seem ‘self-explanatory’, i.e. ‘the intuitive equivalent of physical laws; they may [be used to] explain other phenomena, but they are not themselves explained within the knowledge system’ (p. 112). diSessa explains the choice of name for this level of knowledge structure, They are phenomenological in the sense that they often originate in nearly superficial interpretations of experienced reality. They are also phenomenological in the sense that, once established, p-prims constitute a rich vocabulary through which people remember and interpret their experience. They are ready schemata in terms of which one sees and explains the world. … P-prims are often self-explanatory and are used as if they needed no justification. But also, primitive is meant to imply that these objects are primitive elements of cognitive mechanism-nearly minimal memory elements, evoked as a whole, and they are perhaps as atomic and isolated a mental structure as one can find. (diSessa, 1993: 112)

In seeing p-prims as irreducible, diSessa reflects Lakoff and Johnson’s (1980a: 478) view that experiential gestalts ‘though decomposable into other elements, are yet basic and irreducible in terms of grounding our conceptual system’. diSessa (1993: 122) saw p-prims as occupying ‘mid-levels’ of the cognitive systems, between ‘the lowest, possibly “hard-wired” and data-driven sensory elements’ and ‘the world of ideas, or named concepts and categories’. (Again this reflects Lakoff and Johnson’s model where concepts were seen as generalised from gestalts.) diSessa and his colleagues suggest that p-prims can be characterised “as subconceptual entities, below the conceptual (word) level, perhaps close to the level of senses of individual words, such as various senses of balance, equilibration, and so on’ (diSessa et al., 2004). In diSessa’s model, activation of the cognitive system moves through levels, so the lower level elements activate p-prims, which in turn activate concepts. This is represented in Fig. 6.5, where ‘at the top are relatively conscious ideas and concepts that involve and are cued by lower level elements, down to sensory schemata’ (diSessa, 1993: 112). The figure is merely schematic, and does not show how it is likely, according to diSessa that ‘p-prims will be used in clusters or in combination with other kinds of reasoning’ (p. 118). diSessa (1993: 114) characterises the ‘naive’ state of the cognitive system of the learner as relatively unstructured, having patterns of activation that are poorly integrated and offer alternative activation paths that are not subject to clear prioritisation, so that ‘cuing and reliability are only established in small neighbourhoods within the network [and] there may be no central and dominate elements. There may even be no sense-of-mechanism-based way to decide which of two p-prims actually should apply in a case of conflict’. This description of the system fits well with the types of knowledge systems that Claxton and Solomon characterised as supporting the informal ideas commonly elicited from school-age learners. diSessa has identified a ‘set of physical p-prims’ that is ‘rather large and loosely coupled’ (p. 115) – he suggests that ‘intuitive physics largely (but not exclusively) [derives from] hundreds or thousands of

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Concepts (some embedded in conceptual frameworks) activation

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p-prims

activation hard-wired units

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Fig. 6.5 The role of p-prims as intermediate level knowledge elements in cognitive structure

self-explanatory schemata, typically abstracted from common situations’ (diSessa et al., 2004). He argues that the nature of the abstraction process in the development of a naive knowledge system will sometimes omit features without which knowledge elements will not always be used appropriately so that ‘the accidental failure or systematic inability to encode presumptions and prerequisites should be expected to typify low-reliability subsystems’ as ‘an expectation or deduction may be valid only by virtue of situation specifics that might not be encoded’. Similar to Claxton’s comments about minitheories (§6.1.4.10), diSessa (1993: 116) argues that ‘many misconceptions come simply from using an element outside its range of legitimate applicability’. diSessa distinguishes the predictions someone might make ‘on the basis of a p-prim’ from the p-prim itself (p. 119). His characterisation of p-prims is particularly relevant to ‘intuitive theories’ or ‘gut science’ as they tend to be ‘inarticulate’ lacking ‘explicit propositional form’ so that ‘conscious access to their application is very limited, mostly localized in satisfaction or dissatisfaction with a current state of understanding’ (p. 119). This model can be compared with Karmiloff-Smith’s model of cognitive development (§1.8.3), which sees the successive redescription of representations within the cognitive system making knowledge increasingly available to consciousness, as more explicit and so flexible representations. Although Karmiloff-Smith’s model and diSessa’s ideas do not contain elements at precisely the same levels and with perfectly matching characteristics, their general schemes seem to have much in common.

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Reddish (2004: 55) has taken up a notion of ‘facets’ of knowledge (due to Minstrell), which are seen as specific notions produced by the mapping of p-prims in particular contexts: ‘I identify phenomenological primitives as fundamental resources and refine the idea slightly to separate them into abstract reasoning primitives (of which there are few) that can be mapped into facets describing specific phenomena (of which there are many)’. So for example, a statement that it is warmer in summer because the Earth moves nearer the Sun, might be seen as a facet of knowledge produced by mapping a general p-prim pattern that (we might verbally describe in terms of) nearer-is-stronger onto the context of seasonal variations in temperature. Such a facet could be constructed in an interview context (cf. §6.1.4.3) when an interviewer asks about this phenomenon if the informant has no existing explanation represented in memory, but perceives the question in terms of that existing p-prim.

6.2.2.7

How Is Rote Learning Possible?

diSessa’s scheme seems to imply that all physics (and by extension, science) learning builds upon tacit abstracted intuitions such p-prims, but this seems to ignore the possibility of students learning their science ‘by heart’ (i.e. by rote learning). For example, it is common experience among teachers that students, who can reproduce laws, principles, equations, etc. may have very little understanding of them, and so be unable to apply them. Vygotsky (1934/1986: 5) focused on word-meaning as a useful unit for analysis (believing this to be the ‘unit of verbal thought that is further unanalysable and yet retains the properties of the whole’). He pointed out that a word represents a generalisation (p. 6). Fodor (1972: 86) has suggested that Vygotsky’s central thesis was that word meanings evolve as the child develops. As Polanyi (1962: 82) expressed it, ‘to speak is to contrive signs, to observe their fitness, and to interpret their alternative relations’. For Vygotsky (1934/1986: 107), words were tools of thought, and were the essential tools for higher-level thinking (Vygotsky, 1934/1986: 251; Newman & Holzman, 1993: 132), so that ‘real’ concepts were not possible without them (Vygotsky, 1934/1986: 107). He saw language as the medium in which teaching takes place, and from which the learner constructs a way of thinking (Edwards & Mercer, 1987). Vygotsky (1934/1986, 1978) recognised the social context in which learning and development take place and saw word-meaning as the unit of the social interchange that was itself central to development of higher cognitive functions. Vygotsky (1934/1986: 83) considered thought and speech to have different origins, but that the acquisition of words through speech provided the tools for conceptual thinking to develop. In Karmiloff-Smith’s (1996: 23) model, she acknowledges the possibility that ‘some knowledge learned directly in linguistic form is immediately stored at level E3’ (i.e. the most explicit level), but that it can be stored in this form ‘but not yet be linked to similar knowledge stored in other representational formats’. She argues

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that, ‘often linguistic knowledge (e.g. a mathematical principle governing subtraction) does not constrain nonlinguistic knowledge (e.g. an algorithm used for actually doing subtraction) until both have been redescribed into a similar format so that inter-representational constraints can operate’. So, in terms of diSessa’s model developed from physics learning studies, this would mean that conceptual knowledge can be represented in verbal form, without being associated with (and so activated by) appropriate p-prims, and so not related to the individual’s intuitions about physical mechanism. Bruner who had described three levels of representing the world (the enactive level; the iconic level; and the symbolic level – see §6.2.1.2) suggested that teaching that starts with the symbolic level will lead to rote learning. Such representations would need to be linked to suitable p-prims (directly, or perhaps indirectly through links at the conceptual level) before they could play a meaningful part in understanding physics. Such a process seems reminiscent of Vygotsky’s notion of how conceptual development requires the learner to interrelate their ‘scientific’ (‘academic’) and ‘spontaneous’ concepts (§1.6.2). Like Piaget, Vygotsky (1978: 56) saw ‘internalisation’ as a process whereby an originally external operation becomes ‘reconstructed’ within the mind of the individual, and he emphasised that teachers could lead pupils to higher levels of conceptual understanding than they would otherwise achieve. The child becomes conscious of his spontaneous concepts relatively late; the ability to define them in words, to operate with them at will, appears long after he has acquired the concepts. He has the concept (i.e., knows the object to which the concept refers), but is not conscious of his own act of thought. The development of a scientific concept, on the other hand, usually begins with its verbal definition and its use in nonspontaneous operations – with working on the concept itself. It starts life in the child’s mind at the level that his spontaneous concepts reach only later. (Vygotsky, 1934/1986: 192)

Vygotsky believed that conceptual development involved a process of convergence as the concrete becomes abstracted, and the abstract is made concrete (p. 193). Over time spontaneous concepts would acquire a formal structure and be open to conscious use, and formal scientific concepts would evolve connections with real experience (p. 194) – indeed scientific concepts provide the frameworks within which a learner could become aware of his tacit spontaneous concepts (Crain, 1992: 213).

6.2.2.8

The Role of p-prims in Learning

According to diSessa, an individual’s repertoire of p-prims provides resources for building up conceptual knowledge. He argues that an expert’s knowledge structure is based on ‘reused intuitive knowledge’, whereas alternative conceptions can derive from ‘hitches’ in the building process (1993: 190). In diSessa’s scheme, the repertoire of p-prims may be enlarged during this process, so that ‘some entirely new p-prims are generated as the learner’s descriptive apparatus changes to focus on different features and configurations in the physical world’ (pp. 114–115), but existing p-prims do not in themselves change. Rather, as knowledge representation

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at the conceptual level develops, the pattern of activation of concepts by p-prims becomes ‘tuned’. This clearly requires a feedback process – akin to the assimilation-disequilibration-accommodation-equilibration process in Piaget’s model; the adjusting of an individual’s model of the world to give better fit in Glasersfeld’s radical constructivism; or ‘the dynamic balance of organism and environment, which manifests itself both in specific changes in the environment and specific changes in the patterns of action of the organism’ in Dewey’s transactional realism (Biesta & Burbules, 2003). During this process, ‘the priority of some p-prims becomes greatly enhanced or reduced, and contexts of activation may migrate, expand, or contract’ (diSessa, 1993: 114). diSessa (1993: 112) describes how the cognitive system can evolve in response to formal teaching (which provides the feedback that can modify the system towards ‘expertise’ in science), so that ‘learning should provide that p-prims are activated in appropriate circumstances, and, in turn, they should help activate other elements according to the contexts they specify’. In this process ‘the rather large but relatively unstructured collection of p-prims present in naive individuals gets tuned toward use in instructed physics’ (p. 114). What diSessa seems as a ‘more drastic’ change, is something he refers to as ‘distributed encoding’, whereby the individuals’ learn to justify their thinking in terms of the formally learnt knowledge structures (at the level of concepts) instead of their self-evident p-prims, which ‘come to serve weaker roles, as heuristic cues to more formal knowledge structures, or … do their work only in contexts that are much more particular than the range of application of the general or universal laws’ (diSessa, 1993: 115). diSessa’s model of learning, then is one of systemic change, One starts with a very shallow explanatory system: many p-prims serving as essentially primitive explanations for various phenomena. Gradually, p-prims cluster and become organized as distributed encodings … instead of a very broad and shallow explanatory system, whatever p-prims are still used must defer to or become part of the complex but few subsystems that are the encoding of the physical laws themselves. (diSessa, 1993: 142–143)

6.2.2.9

Conceptual Resources for Learning

diSessa (1993: 108) argued that learning physics could be seen as a process of reorganisation of existing resources. In particular he claims that it should be seen as a process of building the ‘gradient’ between ‘the naively developed sense of mechanism’ and an expert’s phenomenology that ‘must uniformly be reducible, via an analysis of circumstances, to a few core theoretical ideas’ by ‘reorganizing and prioritizing existing phenomenology’; i.e. that ‘the development of scientific knowledge about the physical world is possible only through reorganized intuitive knowledge’. diSessa’s ‘knowledge-in-pieces’ approach is consistent with the constructivist premise at the core of the RP (§4.4), i.e. that learning is a process of individuals constructing knowledge by building up new knowledge upon the foundations of existing

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knowledge. Models such as diSessa’s, based on his work in physics education (and Karmiloff-Smith’s model deriving from general studies of development and learning), assume that learning complex conceptual material is achieved by a form of iterative process, starting with elements working at an intuitive subconscious level close to perception, and working towards increasingly more abstract representations. From this perspective individuals come to class with a range of knowledge elements represented in cognitive structure, many in the form of relatively tacit p-prims, and these provide the resources available for constructing new knowledge. Hammer gives an example of how one of the p-prims proposed by diSessa can give rise to a specific conception in response to a question or problem context (cf. Reddish’s notion of applying p-prim to produce knowledge ‘facets’). The example shows that p-prims themselves cannot be considered ‘correct’ or ‘wrong’ but just general patterns that can be used to generate various conceptions that may or may not match scientific models. The example also illustrates how a conception elicited from a student may be generated through the very process of answering a question, and need not have been previously explicitly represented in cognitive structure (cf. 6.1.4), How students respond to a question depends on which p-prims are activated. For example, the question of why it is hotter in the summer may activate for them a p-prim connecting proximity and intensity: Closer means stronger. This p-prim is an abstraction by which one may understand a range of phenomena: Candles are hotter and brighter the closer you get to them; music is louder the closer you are to the speaker; the smell of garlic is more intense the closer you bring it to your nose. It may be through the activation of closer means stronger that students generate the idea that the earth is closer to the sun in the summer. That most people would have this primitive in their knowledge system, and that it has a high probability of being cued in the seasons question, is an alternative explanation for why many students give such a response. (Hammer, 1996: 102)

Although diSessa’s work can be seen as following the positive heuristic of the RP, the ‘knowledge-in-pieces’ approach does not necessarily adopt the language or categories of alternative conceptions and alternative frameworks that are commonly used in Science Education. So diSessa and colleagues have suggested that as well as concepts (which determine set membership – is this a bird?), individuals develop what they call coordination classes, which are ‘systematically connected ways of getting information from the world’ (diSessa & Sherin, 1998: 1171). The work of a coordination class involves a ‘readout strategy’ which is ‘a set of resources that translate sensory information into meaningful and processable terms’ and a ‘causal net’ which is ‘the set of relevant inferences about the relevant information and their context-dependent associations’ (Reddish, 2004: 28). However, the notion of p-prims underpinning higher structures can be adopted by those who use the more common (in Science Education) terms such as alternative conceptions. Ault, Novak and Gowin (1984) studied learners’ notions of the ‘molecule’ concept using a method for interpreting and representing data collected through clinical interviews (p. 441). As they investigated the same individuals on two occasions (in second grade, and then in seventh grade) they were able to draw some conclusions about the development of conceptual understanding. They found

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that it was better for a young pupil to have a variety of alternative conceptions than few conceptions at all, as understanding evolved more rapidly from a rich conceptualisation. If a pupil in an early grade held a range of idiosyncratic meanings these would tend to persist, but still provided a better structure for conceptual development, than a poor range of notions (pp. 459–460). In particular, they found that it was not important if the learner’s initial ideas were incorrect from a scientific viewpoint, as long as there was ‘rich conceptualisation’ on which to build, What matters most in the improvement of understanding is not simply the accuracy of conceptualisation, but the richness; not the sequence of acquiring new meanings, but the concerted effort to reconcile new with old; not the characterization of children’s understanding chronologically, but the teaching of concepts by someone who takes time to find out how children modify meanings conveyed, how they apply concepts to make sense of events, and how they arrive at the claims they make. (Ault et al., 1984: 460)

The question of whether students’ knowledge structures are better understood as coordination classes or alternative frameworks, or whether these concepts should be seen as complementary with different ranges of application with the RP – being more useful in different types of research context – can be seen as the kind of issue that is motivated by the positive heuristic, and so is part of proper debate within the programme.

6.2.2.10

Ontological Classification of New Concepts

Micheline Chi has developed an alternative model, which is similar to diSessa’s in many respects (Chi & Slotta, 1993), but which has some specific differences. In particular, Chi and her co-workers ‘believe that there is more structure in intuitive knowledge than diSessa has suggested and propose a theory of ontological categories as an alternative to his theory of knowledge fragments’ (p. 249). Chi and colleagues ‘fundamentally disagree’ that intuitive knowledge is ‘fragmented, meaning that there is minimal underlying coherence’, but rather whilst recognising ‘the internally variable and context-sensitive reasoning displayed by physics novices in solving qualitative physics problems’, they ‘propose a theory of ontological categories that affords a certain level of coherence to intuitive knowledge’ (Chi & Slotta, 1993: 250–251). Chi and her colleagues have argued that an important aspect of the learning of new science concepts is how they are understood in terms of the learner’s basic ontological classification of the world. That is, people understand the components of their world as falling under certain basic types or categories, and in particular as being ‘matter’ or ‘events’. By contrast, many concepts taught in physics belong under a different basic category, called ‘processes’, and more specifically a subcategory ‘acausal interactions’ (Chi, Slotta, & de Leeuw, 1994), or ‘constraintbased’ interactions, ‘about which physics novices have little knowledge but to which the veridical physics concepts belong’ (Chi & Slotta, 1993: 256). The lack of availability of the appropriate category can have long-term consequences on learning,

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Because learning is primarily the assimilation of new knowledge into existing knowledge structures, this implies that physics concepts are preferentially encoded into the MATTER ontological category. Doing so prohibits the accurate understanding of physics concepts, which veridically should be assimilated into the PROCESS category and Acausal Interaction subcategory. (Chi & Slotta, 1993: 256)

Chi and her colleagues refer to the ‘incompatibility hypothesis’, i.e. that initial learning of a concept as part of the wrong ‘ontological tree’ leads to an understanding that is inconsistent with the scientific models. They predict that the most tenacious alternative conceptions will result from these cases where a student assigns a concept to an ontological classification very different from that given to the concept within science. The argument runs that when the student first meets a concept (e.g. in the science class) it is located within one of the ontological trees of concepts available, being classified ‘according to its perceived ontological attributes’ (Slotta et al., 1995: 376). However, often the initial classification will not match the ontology of science, and so some adjustment would be needed (for the students’ knowledge to fit the target knowledge). Chi and colleagues argue that the difficulty of making such an adjustment depends upon the degree of misfit, and that if the initial classification is on completely the wrong ‘trees’ (perhaps seeing electricity as a substance) such adjustment may be highly problematic. This model offers predictive power as ascertaining the degree of match between the ontological classifications made by the student and those appropriate according to canonical knowledge ‘provides an account of why certain concepts are more resistant to instruction than others’ (Slotta et al., 1995: 377). According to Chi’s model, many alternative conceptions about such phenomena as heat, electrical current, light, momentum, etc., may be explained in terms of what Chi refers to as ‘a mismatch between the intrinsic and the psychological ontology’ (Chi, 1992: 133). Chi and her colleagues argue that whereas conceptual change within an ontological tree may be more or less difficult, conceptual change across different trees does not occur. Rather, another version of the concept has to develop independently – thus perhaps explaining why the original notions should be retained when the scientific alternatives have been acquired (cf. students applying different versions of the ‘same’ concept when questions in everyday or school-science contexts, see §6.1.4.11). As with diSessa’s ideas, Chi offers a model that can be seen as motivated by the positive heuristic of the RP (the nature of learners’ knowledge structures, and how learning of science occurs, cf. §4.4) falling within the protective belt of theory to be discussed and tested within the programme.

6.2.2.11

Learning and Conceptual Change

Learning has been defined by Petri and Niedderer (1998: 1075) as ‘a change in a cognitive system’s stable elements’. Such change may be usefully considered to be of two types (Posner et al., 1982; Novak, 1985; Duschl et al., 1992; Vosniadou, 1992, 1994; Duit et al., 1998). Probably much learning is actually intermediate in nature (Strike & Posner, 1985: 216), but these two classes of change, akin to

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accretion of knowledge and conceptual revolution, suffice to stand for the spectrum of conceptual changes learners undergo. Different workers have chosen to give various labels to these two categories, so for example, Ault, Novak and Gowin (1984: 460) refer to progressive differentiation and integrative reconciliation. One category concerns incremental changes that may be seen as adding new elements to, or new connections between, existing knowledge elements already represented in cognitive structure. This type of change fits well with constructivism notions of using prior learning to support the building of new knowledge. A trivial example might be for a student to learn there is a type of bird called an albatross, and add this knowledge to existing knowledge of birds. Another example might concern a student who has learnt to model atoms of elements in terms of nuclei surrounded by one, two or three shells of orbiting electrons, and who is told that some atoms have a fourth shell of electrons. More problematic are those categories of learning which seem to require changes in existing knowledge – changes in perspective that fundamentally alter the perceived relationship between different concepts held in cognitive structure, and suggest that some form of major reorganisation is required (Novak, 1985). A trivial example might be a student who is taught that a bat is not a bird (or a spider is not an insect or a whale not a fish). Ault, Novak and Gowin (1984: 459) found that sometimes ‘acquisition of a key concept causes a significant shift at a number of levels in the organisation of conceptual understanding’. An example might be the student who ‘knows’ that pushes are required to maintain motion (§6.1.3.1), but is being taught that in the absence of any force an object in motion will continue moving indefinitely. If the prior learning is a well-established belief based upon extensive experience then it might be expected that it will not be readily changed. As was suggested earlier in the chapter, many alternative conceptions may prove to be tenacious (§6.1.4.2). So students often resist the suggestion that an atom could have 18 electrons in its third shell, despite the atom being a hypothetical entity that they have no direct experience of, it not having common currency in the social interactions of the ‘life-world’ and only being met in the context of school science. Yet when students commonly build an explanatory framework around the desirability of ‘octet’ atomic structures (§6.1.4.17), they develop strong commitments to a belief that apart from the innermost shell, all electron shells are full at eight electrons. The types of conceptual change indicated in such cases requires something other than addition (or ‘accretion’) of new knowledge to existing structures. The two types of learning event have sometimes been labelled with the Piagetian terms assimilation and accommodation (Posner et al., 1982; Rowell & Dawson, 1985; Dykstra et al., 1992; Pintrich et al., 1993) – that is, ‘incorporation of new objects and experiences into existing schemas’ and ‘modification of schemas as a result of new experiences’ (Beard, 1969: ix) respectively (although in Piaget’s model assimilation and accommodation are seen as distinct aspects of the same overall process). The term ‘conceptual change’ is sometimes reserved for the later type of learning events. When it is accepted that much learning seems to require some degree of modification of existing knowledge structures beyond simple

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additions, those changes that seem to require major reorganisation of existing knowledge may be termed as ‘radical’ conceptual change.

6.2.2.12

Chi’s Model of Conceptual Change and the Differential Status of Alternative Conceptions

As described above, Chi sees conceptual change as ‘when a concept is reassigned from one category to another’, and so makes this distinction in terms of ‘the ontological status of the initial and scientific conceptions’ so that ‘if the two conceptions are ontologically compatible, conceptual change is easy. If the two conceptions are ontologically distinct, learning is difficult’ (Chi et al., 1994: 27). Consequently she has suggested that there are ‘two kinds of conceptual change: one within an ontological category, and one across ontological categories’ (Chi, 1992: 178). Chi and colleagues suggest that this explains why the Science Education literature contains opposing views about the ease with which learners’ ideas may be evolved towards target knowledge (see §6.1.4). Where ‘the students’ naive conceptions and the scientific conceptions share the same ontological class’ then learning the science concepts ‘require no major conceptual change for deep understanding’ (Chi et al., 1994: 39). Chi suggests that although students may present alternative conceptions in these cases, these conceptions would not tend to be major barriers to science learning. However, when the concepts to be learned are ontologically ‘incompatible’ with the learner’s existing conceptions, it is then that these alternative conceptions will have the characteristics of major barriers to the intended learning: being ‘robust’; ‘consistent’ over time and situations; ‘persistent’ across different ages and schooling levels; ‘homogeneous’ among different students; ‘recapitulated’ across historical periods; and ‘systematic’ in terms of whether the alternative conceptions seem to be drawn from a coherent ‘theory’ or appear fragmented (Chi et al., 1994: 35–36). One strength of Chi’s model then is that it can explain the wide variation in the characterisation of students’ alternative conceptions described earlier in this chapter (§6.1.4) in terms that can be tested (as the degree of ontological match between scientific concepts and learners’ alternative conceptions is open to empirical investigation). Chi also claims that one implication of her ‘incompatibility hypothesis’ is that where the student’s initial conception and the scientific concept being taught are ontologically inconsistent ‘a learner must alternate between these two conceptual categories in trying to understand them’ (Chi et al., 1994: 34–35), which reflects the reports of students simultaneously demonstrating manifold conceptions in a topic. Whilst Chi and colleagues have used their ideas to explain why students commonly have difficulties in developing scientific understandings of concepts such as heat and light, because they have notions based on such concepts describing material entities, it is possible to consider other ‘alternative conceptions’ and learning difficulties as less extreme cases of developing ontological trees at odds with

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canonical science (Taber, 2008c). As one example, some of the learning difficulties in understanding basic chemical models of structure and bonding reflect an ontology of the submicroscopic components of the world (‘quanticles’) where the atom is considered the fundamental unit, with everything else conceptualised as parts of, or a combination of, atoms (Taber, 2001a). Although such a view might seem to be based on the way the topic is often treated in introductory science texts (Taber, 2003c), it can act as a significant barrier to appreciating the scientific models that students are expected to learn. Another example would be learning about electron spin at college level (Taber, 2005b), where I have suggested that when learning about properties of electrons students tend to assign ‘spin’ (something that in everyday life depends upon the state of movement of an object) as a contingent property like energy, rather than an inherent property such as charge (Taber, 2008c). To adopt Chi’s tree metaphor, whereas the examples she has suggested are most problematic concerning assignments to the completely wrong tree, we might see the ‘atomic ontology’ as an error of identifying which of a set of dividing branches are nearest the trunk, and the example of electron spin as assigning the property to the wrong twig.

6.2.2.13

Developing More Extensive Knowledge Structures

The ‘knowledge-in-pieces’ perspective (see §6.2.2.3) is in tune with constructivist principles, in considering that new learning draws upon existing conceptual resources. diSessa (1993: 109) characterises ‘intuitive physics’ as ‘an expression of an underlying sense of mechanism that occasionally exhibits relatively uniform results but on the whole lacks important systematicities of theoretical science’, and suggests that this being so ‘it does not need to be replaced so much as developed and refined’. Smith and colleagues (Smith et al., 1993: 124) ask how this transformation of cognitive structures can occur, and suggest that it is ‘a major task for a constructivist theory of learning is to present a psychologically plausible resolution’. They go to argue that this ‘depends on identifying a range of cognitive resources that can support the bootstrapping of more advanced cognitive structures’. This notion of ‘cognitive resources’ as ‘any feature of the learner’s present cognitive state that can serve as significant input to the process of conceptual growth’, is an inclusive one which could encompass different levels of Karmiloff-Smith’s model (§1.8.3) for example (and see Fig. 6.5). However, not all of these resources are ‘accessible’ to the learner for deliberate conscious reflection (Fodor, 1983). This leads to a model of cognition and learning with various components operating, only some of which are within conscious awareness, such as in Fig. 6.6. The ‘bootstrapping’ aspect of the knowledge construction process is supported by the positive feedback possible as representations are read from long-term memory, processed in conjunction with new ‘input’ in working memory leading to new linkages that can potentially themselves be represented in long-term memory. Such notions of building up more complex structures from more ‘primitive’ units can also be extended to understanding something of the phenomena of

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Building the Protective Belt of the Progressive Research Programme behaviour (e.g. utterances) accessing of stored resources for application and restructuring

conceptual resources (components of conceptual structure stored in memory - i.e. represented in cognitive structure)

positive feedback cycle

problem solving etc.

storage (representation) of new concepts, new conceptions, and new complexes of prevoiusly established resources

development of intuition?

explicit (conscious) thinking

input interpreted (pattern recognition)

tacit (subconscious) thinking

perception sensory input (e.g. from researcher’s questions)

Fig. 6.6 A model of learning involving diverse conceptual resources. (From Taber, 2008e: 1038)

multiple frameworks (see §6.1.4.20). For example, Fig. 6.7 offers a highly schematic representation of how the subject knowledge of one student we have already met developed during his college chemistry course. Initially he had a limited range of relevant concepts available to explaining bonding phenomena, which he used to build up two frameworks for applying in chemistry (signified O and E – standing for the octet rule and electrostatic frameworks). Over time he acquired new concepts, and built a new framework (M – minimum energy framework), and the balance in the use of the different frameworks changed as their overall coherence and range of application changed. Of course, such a model begs the question of to what extent the ‘same’ concept can be embedded in several different frameworks.

6.2.2.14

Conceptual Trajectories and Intermediate Conceptions

The possibility of learning proceeding through gradual modifications of conceptual knowledge offers the possibility of student ideas changing by degrees and approaching scientific models little by little. Driver argued that this was observed, and so that learners could demonstrate ‘intermediate notions’ or ‘intermediate conceptions’ (Driver, 1989: 483; Driver et al., 1994: 81), so that progression may follow conceptual trajectories, defined as ‘a sequence of conceptualizations which portray significant steps in the way knowledge within the domain is represented’ (Driver et al., 1994: 85). The intermediate notions, although not ‘correct from a scientific point of view’, nonetheless can be recognised to ‘reflect progress in

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Fig. 6.7 Conceptual resources contributing to different conceptual frameworks (Modified from Taber, 1999)

children’s understanding’ (Driver, 1989: 483) when considered against the target knowledge set out in the curriculum. Examples of such ‘learning pathways’ are now available in the literature (Scott, 1992). So, for example, Petri and Niedderer (1998: 1086) have reported the changing understanding of the model of the atom for a high school student known as Carl, whose ‘learning pathway illustrates a sequence of one prior conception

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and three newly developed intermediate conceptions of the atom, which are the results of his own cognitive construction process’. Petri and Niedderer identified four distinct conceptions of the atom demonstrated by Carl during their study: the planetary model; the probability orbit model; the state-electron model; and the electron cloud model. Petri and Niedderer report that after the teaching sequence, Carl’s demonstrated ‘an association of different conceptions of different strengths and status’ (p. 1084). The probability orbit model did not seem to feature in Carl’s thinking at that point, but appears to have acted more as an intermediate conception in developing his state-electron and electron cloud models. Stavridou and Solomonidou (1998) undertook a cross-sectional study of French secondary students’ conceptions of chemical reactions. They reported that ‘before any chemical instruction pupils used common-sense semantic categories (natural categories) for their comprehension and organization’, but that ‘there is progressive formation of new semantic categories’ and ‘there is a gradual abandonment of the initial common-sense semantic categories, in favour of more scientific ones’. (pp. 212–214). Stavridou and Solomonidou (p. 215) commented that, • A significant step towards pupils’ conceptual evolution and reorganization was marked by the use of ‘intermediate’ semantic categories, such as ‘change due to’, ‘no change’,‘change of’. • The pupils who used these semantic categories had not developed the concept of chemical reaction, but they had begun to comprehend the various phenomena as ‘changes’. • Intermediate semantic categories are progressively abandoned and replaced by scientific ones. Although conceptual trajectories are here being inferred from cross-sectional data (comparing groups of students at different school levels), rather than followed in individual learners, it again seems there is evidence for the importance of intermediate conceptions which can act as ‘stepping stones’ between naive and formal scientific conceptions. 6.2.2.15

‘Radical’ Conceptual Change

Modelling and understanding how the more radical type of conceptual change might occur has been more puzzling (cf. Chi’s comments earlier, i.e. that conceptual change across different trees does not occur). Richard White (1994: 199) described this type of change (which he called ‘conceptional’ change) as ‘a much more complex matter, less open to commonsense notions of teaching and learning, and not yet supported by theory or evolved practice’. 6.2.2.16

Bringing About Change by Persuasion

Piaget (§1.6.1) had discussed how the individual’s mental schemes have to be adjusted to accommodate experiences that do not fit expectations and lead to

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a disequilibration, and Dewey (§1.5.1) considered personal knowledge to be constantly evolving through transaction in the environment. In psychology, the construct cognitive dissonance describes ‘a condition that is said to arise when an individual’s action is not in accord with his belief’ (Guilford, 1967: 219). This is considered an uncomfortable experience, and so people will tend to modify their behaviour and/or beliefs to minimise the dissonance. In a similar way, creating a cognitive conflict, where a student’s existing conceptual schemes are insufficient to make sense of phenomena, has been used as the basis for teaching approaches designed to bring about conceptual change (Duit, 1991). Strike and Posner (1985: 211, see also Posner et al., 1982) have suggested that learning should be considered ‘a rational enterprise’, where rationality is concerned with the conditions that should lead someone to change his or her mind. These conditions involve judging how well competing conceptions match empirical evidence, can explain experience, meet metaphysical assumptions about the form explanations should take, and are consistent with other knowledge. Strike and Posner suggest four conditions that must be satisfied before accommodation will occur. Firstly, the learner must have reason to be dissatisfied with existing conceptual schemes. They point out that accommodation is unlikely if existing frameworks can be made to work with minor adjustments. Secondly, the learner must have ‘minimal’ understanding of the new conceptions, so that its potential for explanation may be explored. They suggest that this involves being able to relate the new conceptions to some existing part of cognitive structure, and to familiar examples from experience (cf. Ausubel’s notion of ‘meaningful learning’, see §1.9.2). Their third criterion was that the new scheme should seem a plausible alternative because it can be seen to explain the apparent discrepancies in the present scheme, and it meets metaphysical expectations. Finally, the new conceptions should seem to be ‘fruitful’, in the sense of suggesting the possibility of wider explanatory scope. If we apply this model to learning about evolution by natural selection, we can see immediately why those holding beliefs based upon a conviction that God created the world by an act of special creation are unlikely to be persuaded, even if (a ‘big if’ as we shall see) they fully understand and make sense of natural selection. For those who accept as a matter of faith that the Earth was created much as is, and with the species alive today in place, there may be no dissatisfaction with their existing ideas (even if ‘creationist’ attempts to interpret scientific evidence in line with their views way well seem forced and implausible to those who do not share their commitments). For those who have not been taught to treat religious creation myths (i.e. not just a ‘story’, but one that conveys some deep truth about humanity/nature, but through symbolic and metaphorical language) as literal accounts or who have come to doubt their plausibility, the next step is to develop a minimal understanding of the alternative [sic] scientific model. Unfortunately, natural selection although an elegant idea is not as simple as experts (biologists, science teachers) may suppose (Taber, 2008g). I would suggest that to have a minimal understanding of how natural selection can lead to the origin of species, a learner would have to coordinate the following ideas:

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• That individuals in a species have a similar genetic code • That the genetic code varies within a population • That offspring have a set of genes more similar to their parents than of most of their co-specifics • That reproductive mechanisms not only give myriad permutations but allow copying errors which introduce novel genes that may sometimes still be able to code for a viable and fertile adult • That the genetic code influences a wide variety of physical characteristics that give the individual its particular features (height, colouring, size of appendix, etc.) • That organisms generally have many offspring, most of which do not survive to reproduce themselves • That the characteristics of individuals in relation to their particular environment influence their chances of leaving their own offspring • That different species have significantly different genetic codes (i.e. differences between individuals from different species tend to be significantly greater than differences between individuals who are members of the same species) • That breeding populations may become separated into different groups by geographical barriers (seas, mountain ranges, deserts) • That genetic changes drift independently in the separated populations • So that in time the two groups come to represent separate species unable to interbreed even if brought back together Given that understanding of the scientific narrative of the origin of species relies on taking onboard and coordinating so much, it might be suggested that a learner needs to be strongly motivated to undertake the conceptual work involved: something clearly not likely to be the case for many of those who are perfectly happy with the accounts given in Scripture.

6.2.2.17

Affective Aspects of Changing Minds

Although Posner and colleagues’ model of the rational basis for conceptual change has been influential, it has also been criticized as assuming learning is primarily a process determined by cold logic, whereas humans are influenced by a range of factors beyond the rationale claims of alternative models. In our example of natural selection, we saw earlier that in traditional ecological knowledge systems (§5.1.5) creation myths may provide a narrative that is indicative of a relational view of the place of humans as part of nature, and may be integrated with practical knowledge of survival value. Whilst the same argument may not apply so strongly in the case of those living in ‘modern’ industrially developed societies, nonetheless faith-based views may well be strongly linked with a sense of personal and cultural identity, and strongly reinforced on an everyday basis in the family and/or peer group. As Solomon (1987: 67) has pointed out, ‘continual reaffirmation of social notions makes them very durable and resistant

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to change’. Simply confronting student beliefs with a rational reconstruction of scientific evidence is hardly likely to be sufficient to lead to conceptual epiphanies in these cases. Claxton (1986: 127) has gone further than acknowledging an affective aspect of conceptual change, to challenge the very premise that ‘learning is promoted by conflict’ (through simply showing students the error of their ways to produce dissatisfaction, before building up an intelligible, plausible alternative which can be rationally shown to be more fruitful), which he characterises as a ‘Piagetian proposal that has been rather uncritically taken up by the researchers on children’s scientific ideas’. He argues that likely reactions to having one’s ideas directly challenged can be ‘defensive entrenchment, and a denial or evasion of the learning opportunity’, as ‘children generally learn from discovering alternative ways of achieving a successful performance rather than from attempts to rectify error, failure or conflict’ (p. 127) so that ‘conflict may be neither sufficient, nor necessary, nor even helpful’ (p. 128).

6.2.2.18

Contextual Factors Influencing Learning

In the previous section (§6.1.4) it was seen that ideas elicited from learners have been found to be context-bound. However, as Edwards and Mercer (1987) point out, context is largely a mental phenomena that is not available to other people (pp. 65–66). It is something that is ‘problematical’ (pp. 160–161). Nonetheless, Solomon’s distinction between life-world knowledge and symbolic universes of knowledge may be illuminated by the notion of situated cognition, a perspective that people have different ‘ways of seeing’ that are appropriate in different contexts (Driver, 1989: 486). This is a topic that has been reviewed by Hennessy (1993), who reports that both experts and lay people apply thinking that is honed in a particular problem-context (p. 29). According to this view, the reversion to children’s science (or life-world knowledge, or lay science) outside of formal learning contexts would be expected as specialist knowledge – such as formal scientific knowledge – is not considered relevant to everyday life, and does not tend to be activated in the absence of the – perceived – appropriate context (p. 24). Hennessy’s review supports Solomon’s emphasis on the difference in origins of life-world and symbolic universes of knowledge: the former having developed through solving problems in real-life contexts (Hennessy, 1993: 30), whereas the latter would need to be ‘reconstructed’ and re-contextualised before it could be used in everyday life situations (p. 26). Indeed Hennessy describes schooling as ‘a unique culture, a specialised practice with its own conventions, organisation and concerns, which are in fact of little value to society outside’ (p. 2). According to the situated cognition perspective the apparent ‘partial, incoherent or internally inconsistent’ nature of many alternative frameworks is to be expected as ‘pieces of knowledge or models are being drawn upon flexibly and according to their appropriateness and usefulness in a specific practical context’ (pp. 6–7, c.f. Claxton’s ideas, see §6.1.4.8).

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Social Factors in Learning science

One important set of factors that the initial Posner and colleagues’ (Posner et al., 1982) model of conceptual change did not take into account was the social context of learning. In Solomon’s work she distinguished learning in the life-world, from formal learning in science. However, she also acknowledged that learning in science is not primarily an isolated activity, but takes place in a social context. For practicing scientists, this context is a professional community of practice, who will in general share values, aims, and understandings of the science (cf §3.2.4). In a school or college class, the community of practice will be that established by the teacher with the learners – who generally are still being inducted into that learning. According to Solomon, the form of interaction naturally adopted by students in group work will not match the nature of analytical debate in science. Solomon argues that ‘the process by which children construct notions for explaining the meaning of events in their daily life is more social than personal’ (Solomon, 1993b: 86). She points out that in the ‘life-world’ ‘it is taken for granted that others see things very much as we do’, and we ‘expect to be able to understand each other and to share meanings’ (p. 86). Solomon bases her argument on episodes from classroom discussion – collected during her own research – where she commonly observed an ‘unstated pressure’ to resolve any disagreements (p. 88), so that during a process of discussion contradictory opinions were often supported by the same children, with various assertions being put forward until some suggestion receives ‘social recognition’. According to Solomon ‘familiarity wins the day’ and unresolved disagreements were ignored (p. 88) because in the life-world ‘the essential criterion is no longer the internal logic of the explanation but that it should be recognised and shared with others’. Operating in the social context ‘relies on agreement with others’ and ‘makes no pretences to produce abstract over-arching theories’ (Solomon, 1987: 67). As Solomon points out, this is not how scientific debate is meant to occur and the purpose of discourse is therefore different in the two domains, so that even a term such as ‘explanation’ takes on a different meaning – as ‘only in science … does “to explain” mean to fit the event into a metaphorical scenario’ (Solomon, 1992: 107). Another key point in Solomon’s position is that the purpose of communication in science is to ‘sharpen differences’ rather than to ‘try to achieve a mutual understanding’ (Solomon, 1993b: 92). Her point is that in professional scientific discourse debate takes on a dialectic nature, that correspondents seek to take contrary views to test out positions. In normal social chat the purpose is quite different – to achieve a consensus, and preserve social cohesion. According to Solomon, scientific knowledge is by its very nature less likely to be the domain of knowledge called upon by most people in most circumstances. Her argument is that whereas ‘life-world knowledge is “learnt” through social reaffirmation in everyday situations, the more esoteric knowledge of science is the product of school learning – a later, secondary process of socialization’ (p. 112). In the sciencelearning context, students have to be explicitly introduced to the form of discourse expected, and the nature of argumentation (Newton et al., 1999).

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Whilst Solomon’s focus on social aspects of science learning has emphasised the differences between learning in the life-world and in formal classes, others have drawn upon Vygotsky’s ideas about how social interaction, largely through language, supports learning in a particular cultural context so that individuals learn to develop the mental resources for entering into the discourse(s) of their own cultures. As Leach and Scott (2002: 120) explain, a core feature of Vygotsky’s perspective was how ‘higher mental functioning in the individual derives from social life’ so that ‘language and other semiotic mechanisms (such as mathematical symbols, diagrams, gesture, stance) provide the means for ideas to be talked through and communicated on the social or intermental plane and, following the process of internalisation, language and other semiotic modes provide the tools for individual thinking’.

6.2.2.20

Radical Conceptual Change As a Fresh Start

According to Chi (1992: 179), radical conceptual change that requires concepts to be shifted into different major ontological categories is not feasible due to the ‘incompatibility hypothesis’: that ‘conceptual change that requires crossing ontological categories is nearly impossible to accomplish, in both physical as well as psychological terms’. Rather, Chi’s perspective is that radical conceptual change is a process of new concepts being acquired, and developed over long periods of time. Indeed, she suggests that ‘it may be inappropriate to think of conceptual change across ontological categories as a change at all. It may be more proper to think of this kind of radical change as the development or acquisition of new conceptions, with the initial conceptions remaining more or less intact’ (pp. 133–134). Chi accepted that concepts could be shifted to different branches within ontological trees (i.e. within the main divisions within an ontological hierarchy of concepts), but that when a new concept to be learnt belonged to a different major category (e.g. learning about ‘heat’ in physics being a process, when currently ‘heat’ is understood as a kind of substance), then ‘such concepts on distinct trees may be better developed independently, so that there is really no shifting per se, although the resulting outcome represents a shift’. As the ‘new’ version of the concept may take time to reach a level where it can be cogently applied, there may be little evidence for the changes until a critical stage is reached: ‘new conceptions on an ontologically distinct tree can be developed gradually, and yet the final outcome of the development (the shift) may appear to occur abruptly’ (p. 134). Such a ‘catastrophic’ change (in the sense of reaching a critical point in a complex system) had been considered by Gilbert and Watts (1983) as a possible model of conceptual change in their contribution to what has been identified here as the seminal corpus of the RP (§4.1). If much of the conceptual work underpinning such a shift occurs below the level of conscious awareness, then the change of mind may take the character of a gestalt-shift to the learner as well as to an observing teacher or researcher.

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Thagard’s Model of Explanatory Coherence

One model of conceptual change that is of particular interest in this context derives from the work of Paul Thagard (1992). Thagard’s main concern was to model conceptual change (and especially revolutionary conceptual change) in the history of science, to ‘understand the structure and growth of scientific knowledge’ (p. 3), and to model how scientists came to change their minds. Although school and college learners were not the focus of his project, he recognised that his approach may be useful in this context as well. Thagard’s (1992) work has produced a model based on similar principles to Strike and Posner, using the criterion of ‘explanatory coherence’ to determine when conceptual change would be expected. His particular computer-based model assumes knowledge is arranged hierarchically (somewhat similar to Chi’s ontological trees). Thagard models cognitive structure in the form of a network of concepts (‘mental structures representing what words represent’) connected by propositions (‘mental structures representing what sentences represent’, p. 21), with the concepts making up the nodes of the network (p. 30). The networks are primarily structured via kind-hierarchies and part-hierarchies’. In such a model conceptual change is easily represented as adding or removing nodes and links (p. 32), although these changes may be more or less severe depending at what level in hierarchy the change is made (p. 34). Like Novak, and Strike and Posner, Thagard distinguishes two types of conceptual change. He considers adding or substituting a single concept or rule as relatively trivial, whereas ‘revolutionary’ changes which involve the overthrow of whole systems of concepts are more difficult to understand (p. 6). Thagard sees the personal construction of models of alternative scientific theories as a step in a rational process of paradigm-shifts. The scientist (or by extension young learner) holds one theory, but gradually builds up an understanding of, and familiarity, with an alternative. If the alternative comes to be seen as having greater explanatory coherence then it will become the preferred theory with which to operate in that domain. Thagard describes how a scientist exposed to an alternative theory to the one held will construct a model of the theory ‘in the background’ to compare with his or her original (p. 60). For example, when chemists learnt enough about the oxygen theory to believe it had greater explanatory coherence than the phlogiston theory, they changed to the new theory. For this to happen they had to be instructed in the new theory (perhaps in Kuhn’s terms, to be inducted or socialised into the new paradigm), but also had to have time to construct and explore, or read about and reflect on, the arguments in favour of the two alternative theories: ‘setting up the requisite nodes and links, was not enough: people had to use the new system enough to appreciate its power’ (p. 59). Thagard considers this to be a process that may take years. Priestley’s rejection of the oxygen theory may be considered rational if it is understood that as the ‘preeminent phlogiston theorist’ he had over many years developed the most elaborate and coherent conceptual scheme based around the phlogiston concept and therefore his exploration of the oxygen concept was not enough to appreciate that it had greater potential (pp. 59–60).

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Thagard suggests similar processes may be operating in children, and conjectures that when they learn enough about an aspect of curriculum science to ‘consciously or unconsciously’ appreciate it has greater explanatory coherence than their existing ideas then they will switch to using the taught version (p. 258). Thagard’s analysis of historical case studies suggests a range of criteria are used to determine ‘the explanatory coherence of a hypothesis’ (p. 63), and that alternative explanations ‘compete’ on such dimensions as, • • • •

How much does the hypothesis explain? Are its explanations economical? Is the hypothesis similar to ones that explain similar phenomena? Is there an explanation of why the hypothesis might be true?

The first of these criteria – ‘the explanatory breadth of the new theory’ – seemed to be the most important factor (p. 248). However (as with Priestley), greater familiarity with the existing theory and its potential applications may act as a barrier. An important aspect of Thagard’s model is his acknowledgement that during major conceptual change ‘the new conceptual system does not arise by piecemeal modification of the old one’ but ‘rather, the new one must be built up largely on its own, and its replacement of the old is the result of a global judgment of explanatory coherence’ (p. 60). Thagard’s model thus explains the epistemology of conceptual revolutions in terms of the construction of representations of alternative theories in a conceptual network. This model of conceptual change offers a rationale for expecting individuals to hold alternative conceptual frameworks for the same phenomena or topic areas (see §6.1.4.20). As his case studies concern professional scientists, we should expect this will not be limited (in the case of learners) to an alternative to a naive ‘life-world’ understanding being constructed in the domain of school learning of scientific knowledge. Rather, Thagard’s model offers an interpretation for how learners may exhibit alternative ways of understanding the same topic from within the domain of formal taught knowledge. This is of course needed if students are to be able to develop, for example, an orbital model of electronic structure of the atom, without dismantling or abandoning an electron-shell-based model that retains utility in some contexts. One outcome of Thagard’s research is to show that coming to see a new conceptual framework as having greater explanatory coherence than an existing conceptual framework may be an extended process, so in the case of scientific revolutions, the process could take decades of working in a field. Whilst these cases may be extreme (involving the overthrow of scientific ideas that have themselves been considered adequate by the scientific community for long periods), it does suggest that teaching for conceptual change in science cannot be seen as something that fits in a lesson or short sequence of lessons. Chi (1992) came to the same conclusion, that because radical conceptual change ‘requires extensive learning about the new domain’ it would take extensive periods of learning (Chi suggests ‘thousands of hours’), before new conceptions, due to their ‘abundance, coherence and strength’ would be able to ‘overtake the existing conceptions’. The choice of the term ‘overtake’ implied that the new conceptions

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did not replace the older ones in the sense of erasing or overwriting them, but rather that ‘the new conceptions are accessed more frequently than the old conceptions, which may still exist and remain intact’ (p. 180). As in Thagard’s model, Chi’s analysis suggests that ‘new conceptions on an ontologically distinct tree can be developed gradually, and yet the final outcome of the development (the shift) may appear to occur abruptly’ (p. 134). 6.2.2.22

Epistemological Profiles

The assumption of a sudden shift seems to assume that it is possible to compare two alternative conceptual frameworks in some absolute sense, but this can only refer at best to the degree of internal coherence of a framework. In practice such a framework is used to consider, and make sense of, evidence, and to solve problems. Judgement of the most appropriate framework to apply to particular data is therefore likely to vary depending upon the data. Earlier we saw an example of this in the case of student Tajinder’s switching between three apparently inconsistent explanatory principles to make sense of chemical processes (see §6.1.4.20). This seems a more extreme case of how in different contexts (e.g. social versus academic) a statement such as ‘exercise gives me energy’ might be judged very differently. The French schoolteacher-cum-philosopher Bachelard suggested that during the progress of science, a series of increasingly sophisticated epistemological perspectives have guided the understanding of science concepts, but that each individual scientist’s own development passes through the same phases, The evolution of differing epistemologies is another established fact: the theory of energy entirely altered its character at the beginning of the [twentieth] century. Regardless of what the particular problem is, the direction of epistemological evolution is clear and constant: the evolution of a particular piece of knowledge moves towards rational coherence. (Bachelard, 1940/1968: 17)

This recapitulation process meant that even sophisticated scientists would effectively hold a series of distinct versions of concepts, a ‘plurality of meanings attached to one and the same concept’ (Bachelard, 1940/1968: 21), each of which would be available to the cognitive system and used in difference contexts. Bachelard considered that the less advanced versions could act as ‘epistemological obstacles’ to developing science, and so ‘that the healthiest philosophies, like Newtonian and Kantian rationalism can, under certain circumstances, become an obstacle to the progress of culture’ (Bachelard, 1940/1968: 37). This clearly has parallels in the role played by students’ alternative conceptions in complicating the learning of curriculum science, something Bachelard would have observed in his own early career teaching physics and chemistry (Souque, 1988). Bachelard (1940/1968: 43) argued that ‘an epistemological profile bears the marks of the obstacles which a culture has had to surmount. The earliest obstacles, those which are met during the first stages of culture, pave the way for some very clear pedagogical efforts’. On Bachelard’s model, the system of perspectives is understood as an ‘epistemological profile’, which can be represented as a kind of bar-chart indicating the relative frequency of use of the different versions of a concept. Mortimer (1995:

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267) has adopted the notion of a ‘conceptual profile’ to reflect how learners can ‘use different ways of thinking in different domains and that a new concept does not necessarily replace previous and alternative ideas’. From this perspective ‘learning science is to change a conceptual profile and become conscious of the different zones of the profile, which includes commonsense and scientific ideas’. Using this approach, it is possible to represent graphically (if schematically, this is not intended to be a quantitative representation), the changing way that the student Tajinder (see earlier in the chapter, §6.1.4.20) discussed chemical bonding over the 2 years of his college course. This is represented in Fig. 6.8 where it is shown that at the start of his course Tajinder was already applying electrical principles in some of the explanations he gave in interviews, but was mostly conceptualising chemical bonding in terms of atoms striving to fill their electron shells and achieve A profile model of development in understanding of chemical bonding during an A level course octet framework minimum energy electrostatics quantum / orbital typical conceptual profile for bonding at the start of the A level course

example conceptual profile for bonding for a successful student at the end of the A level course

target conceptual profile for bonding at the end of the A level course

Fig. 6.8 An example of a shifting conceptual profile during learning (From Taber, 1999)

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‘octets’ of electrons (cf. Fig. 6.7). Tajinder developed two strands to his ways of explaining chemical bonding, both based on taught ideas. His minimum energy explanatory principle developed as a discrete basis of explanation (rather than being linked to electrical interactions), and new ideas about orbitals and orbital overlap were acquired. There was also a shift in the extent to which he (increasingly) applied electrostatic ideas and (decreasingly) used notions of atoms trying to fill their shells (i.e. to acquire ‘octet’ configurations). A potential weakness of such a form of representation when transferred from Bachelard’s original context (broad epistemological commitments) to looking at evolving knowledge systems in particular topics is that it may imply completely discrete ways of thinking that are in practice related in a more complex system. In Tajinder’s case, he did view his three main explanatory principles as offering alternative narratives for making sense of chemistry, but in Petri and Niedderer’s (1998: 1086) study of a high school student’s learning pathway in atomic physics (see §6.2.2.14), the final (i.e. after teaching) state of Carl’s conceptual representation of ‘atom’ is described an association of ‘three different co-existing conceptions which he revealed during interview and tasks with different “strength” and “status” ’.

6.2.2.23

Learners’ Epistemologies and Metacognition

The discussion of manifold conceptions, repertoires of conceptual resources, and conceptual profiles suggests that one important factor in conceptual change in science learning will be the learners’ own awareness of their knowledge structures, and beliefs about the nature of their personal knowledge – the theme of Watts and Pope’s (1982) exploration of the notion of the student as a Lakatosian scientist (§4.3). This was recognised by Osborne and Wittrock (1985: 70), in their ‘generative learning’ model (§4.1.7), ‘with its emphasis on the control that the learner has of his or her own learning’. Any constructivist approach would seem to need to share this ‘importance of the learner accepting responsibility for his or her own learning, and … understanding that learning science is something only the learner can do’ (p. 70). Hammer and Elby (2000: 4) refer to three ways of thinking about knowledge, as ‘propagated stuff … a kind of stuff that can be passed from a source to a recipient’ (cf. §4.6); ‘as free creation’ originating in ‘the child’s mind, where it arises spontaneously’; ‘as fabricated stuff … inferred or developed from other knowledge’. They suggest that a framework for thinking about learners’ epistemologies will include ideas about the status and forms that knowledge may take, and the activities it can be used in. A learner who feels that their science knowledge is factual and true, and who believes that a moving object must be subject to a force, or that there are two types of chemical bonds, or that plants only respire in the dark, will find it difficult to find motivation to explore contrary ideas. To use Tajinder as an example once more, by the end of his college course he was able to offer three alternative explanations for the same phenomena, and consider these as narratives that could each offer useful insights (Taber, 2000d). Despite this he had been critical of how his schoolteachers

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had emphasised models that he was asked to learn for examinations, but which he was later during his college course expected to progress beyond in his thinking. Hammer and Elby (2003: 57) suggest that research relating to learning in introductory physics ‘shows that students learn more successfully when they understand physics knowledge as a coherent system of ideas, the formalism as a means for expressing and working with those ideas, and the task of learning as a matter of reconstructing and refining one’s current understanding’. Although research suggests students may commonly take very different views, Hammer and Elby argue that ‘the more successful learners do not necessarily have coherent, committed, articulate epistemologies’, rather that learners should be understood to have available ‘fine-grained epistemological resources, analogous to diSessa’s … phenomenological primitives’ (p. 55), and their success should ‘be understood instead as reflecting the activation of productive resources in the context of the [science] course’ (p. 57). From this perspective, teachers should consider that learners will have ‘productive epistemological resources they naturally invoke in other contexts’ that can act as ‘epistemological anchors’ (Hammer & Elby, 2000: 5). Whilst there is increasing attention to learners’ epistemological commitments, this topic is currently less well researched than the nature of learners’ ideas about science topics themselves. 6.2.2.24

The Conceptual Ecology Metaphor

Taking these various considerations into account suggests that there is a wide range of factors that will influence whether (or to what extent) conceptual change is likely to occur in a particular case. There is good reason to agree with Hammer (1996: 122) when he argues that ‘research, moreover, provides strong theoretical and empirical reasons to believe that an adequate theory of knowledge, reasoning, and learning must include a range of cognitive and affective structures and processes in a complex ecology’. The term conceptual ecology has been adopted by some researchers to reflect the idea that there are parallels between the way organisms compete and evolve (or become extinct) in the natural world, and the way conceptions are developed, adopted and modified or fall into disuse in the mental life of individuals. Mariana Hewson (1985: 153) discussed Toulmin’s notion of ‘conceptual ecology’ where concept formation is interpreted according to ‘the varied mental sets of individuals which are a function of their intellectual and physical environment’. This idea – that in order to understand why an idea comes to prominence or not, and how it is adapted, by an individual, we have to understand that idea in the context of its ‘mental environment’ – is also used by Strike and Posner (1985: 219) who suggest that ‘understanding entails finding a niche within a conceptual ecology’. 6.2.2.25

Components of a Conceptual Ecology

Clearly one important feature of a learner’s conceptual ecology for a particular concept area is their understanding of other related ideas (i.e. those the learners would

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perceive as related), within what has been termed the students’ cognitive structure. The extent to which a particular conception is consistent with other ideas and the degree to which it is integrated with those ideas will influence such matters as: • How readily the idea is accessed • How feasible it seems • How readily it can be modified Strike and Posner (1985: 216–217) list the following as features of such a conceptual ecology: • • • • • • • • •

Anomalies Analogies and metaphors Exemplars and images Past experience Explanatory ideals General views about the character of knowledge Metaphysical beliefs about science Metaphysical concepts of science Knowledge in other fields and competing conceptions

A key theme of this volume has been that learning is contingent: that the constructivist perspective should be seen as the basis of a RP that (a) recognises how knowledge is constructed in terms of the psychological/biological nature of the cognitive apparatus we have available, and which (b) informs teachers about the various contingencies which limit, facilitate or channel that construction process. The RP has amassed – both from empirical studies within Science Education, and adoption of ideas from the wider ‘domain of enquiry’ (§1.4) – a diverse set of constructs to describe and characterise aspects of students’ thinking, and an impressive list of contingent factors that science teachers are being asked to take into account when supporting student learning, that is, when teaching science.

6.3

Teachers Teaching Science

The constructivist RP is centrally concerned with informing the teaching of science, i.e. the hard-core commitment that it is possible to teach science more effectively if account is taken of the learner’s existing ideas (§4.4). As discussed in Chapter 5, some critics had suggested that there was something of an inconsistency in constructivist rhetoric from science educators claiming that learners’ ideas should be investigated and given significance, when Science Education is charged with teaching students scientific knowledge which has a specified form and is not open to negotiation by learners. It was argued there (§5.2) that informing teachers about learners’ ideas, and about the importance of finding out about the thinking of their own students, was based upon the pedagogic significance of those ideas, and not because learners’ alternative conceptions should be celebrated for their own sake.

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The brief review of the aspects of the RP concerning learners’ ideas (§6.1) and how science may be learnt (§6.2), in the previous sections of this chapter, provides the basis for a somewhat more nuanced perspective. For one thing, the work of Bachelard and Thagard reminds us that although the ideal of knowledge in Popper’s World 3, the formal knowledge structures of consensus science, may allow limited room for ambivalence in the formal theoretical structure of the subject, the personal knowledge of even the most accomplished scientists fails to meet such ideals (cf. Claxton’s notion of scientists’ minitheories), and indeed key scientific breakthroughs may rely upon the manifold and apparently redundant nature of cognitive systems. Secondly, although some perspectives on learners’ ideas focus on either informal knowledge being compartmentalised away from school learning; or tenacious alternative conceptions that need to be actively challenged; other approaches consider the teacher’s role in a more positive, ‘constructive’ light: that of identifying which of the manifold conceptual and cognitive resources available can best be used for constructing target knowledge in various teaching situations (Smith et al., 1993). Of course, one of the key challenges in developing constructivist pedagogy is how these different perspectives suggest rather different ways forward: to help students to see formal science knowledge as something very different from lifeworld knowledge; to show learners how their conceptions cannot be right and are less useful than ‘scientific’ alternatives; or to show learners how their intuitions and informal knowledge can be moulded into new scientifically acceptable knowledge.

6.3.1

Teaching Within the Domain Boundary

A minority view deriving from the RP is that research informs pedagogy by highlighting the distinct characteristics of informal (life-world) and scientific knowledge, and so showing how teachers should seek to avoid engaging with learners’ informal knowledge when teaching science. So Claxton (1993: 55) argues that ‘School science tries to create a coherent, integrated conceptual structure, and it is a mistake to site it on top of the fragmented and shifting quicksand of everyday experience and discourse’. To some extent, Chi’s model leads to similar conclusions when she argues that ‘it is not possible to refine or develop intuitive knowledge to the point that it becomes the veridical physics knowledge; entities on separate ontological trees cannot be merged, because they cannot inherit each other’s attributes’ (Chi & Slotta, 1993: 256). She believes that for those cases where the learner’s existing ontology assigns a concept to the completely wrong ontological tree (e.g. heat classed as matter), ‘intuitive knowledge may need to be ignored, in the sense that veridical conceptions must be taught afresh in a way that allows them to be embedded in the correct ontological category, while initial conceptions are allowed to die away or are reserved for use only in everyday contexts’ (p. 259).

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However, this perspective seems very much in the minority. For example, Russell and Osborne argue strongly that the science teacher should be seeking to ensure that pupils do link new teaching with their everyday life so that they will not see science learning as specialised knowledge only of relevance to the classroom, It seems to be at least relevant, and quite probably critical, to consider the sources of ideas when considering how or why those ideas might change. Ideas have origins; they have sources. They are confirmed to the satisfaction of the believer by evidence of some kind. Evidence may vary in kind, in power and in its frequency of occurrence and replicability. And even if evidence presented to the child seems ‘plausible, intelligible and fruitful’ … it is unlikely that everyday experiences will be analysed from this framework if they are decontextualised in the move to the classroom. Science teaching should endeavour to concern itself with everyday and ordinary phenomena, using familiar rather than specialised materials. (Russell & Osborne, 1993: 14)

Even Solomon (1987: 79), whose proposes that students hold life-world and scientific knowledge separately, argues that ‘pupils are strongly social beings for whom the teaching of a rigidly insulated science which makes no contact with the everyday context is simply not an option’.

6.3.2

Finding Out Where the Learners Are

Most ‘constructivist’ approaches, however, consider it very important to elicit the learners’ ideas as part of the teaching process – to inform the teacher, and often to make those ideas explicit for the learners as well. This can be seen as following Ausubel’s (1968: vi) advice, quoted in Chapter 1, to ascertain ‘what the learner already knows’ and ‘teach accordingly’. Brock (2007) argues that teachers should differentiate teaching according to students’ conceptions in a class. Scott, Asoko and Driver (1992: 318) argued that ‘the fundamental principle underlying [constructivist approaches] is one which stresses the importance of acknowledging the learner’s existing ideas and understandings in any teaching/leaning event’. Indeed Russell and Osborne (1993: 13) go as far as to claim that ‘if a constructivist approach to pedagogy is to have any practical possibility of being implemented, it must provide a set of elicitation techniques that serve as classroom tools to explore the nature of children’s thinking’. They suggest a range of elicitation activities: • • • • •

Teachers’ open-ended questioning Children’s drawings as expressions of their thinking and ideas Class diaries or logbooks Sorting activities Concept mapping

At primary level, asking pupils to draw out their ideas ‘was a particularly successful technique because it enabled ideas to be expressed which might have been difficult for children to articulate verbally’ (1993: 10). Where research has shown that students commonly present what can be considered substantially the same alternative conceptions, guidance available for

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teachers often highlights the likelihood of students holding such ideas (e.g. see the discussion of the curriculum guidance in the UK context in Chapter 5, §5.5.5.2). There are readily available diagnostic tools for many topics where students have been shown to have common alternative conceptions and learning difficulties. For example, a widely used concept inventory relating to student understanding of the force concept is available (Savinainen & Scott, 2002a, 2002b). Treagust (1988) has described the process of developing tools suitable for research or classroom elicitation of alternative conceptions, and a range of classroom probes are available in chemistry topics (Taber, 2002a). Solomon (1994: 10) has criticized constructivist teaching approaches on the basis that individual learners may have no stable alternative frameworks for a topic, yet the classroom activities intended as elicitation provide just the social context where the construction of alternatives to science will take place. Whilst Solomon’s concern should be acknowledged, the work of Ault, Novak and Gowin (1984, reported above, §6.2.2.9) suggesting that the acquisition of a complex scientific concept seemed to be more likely where the learner had been able to produce a range of relevant ideas at an early stage, and that it was not important if the learner’s initial ideas were incorrect from a scientific viewpoint, as long as there was ‘rich conceptualisation’ on which to build, is reassuring. Further research confirming this finding in other contexts and particularly working with older learners would be valuable here. Readily available probes are useful in helping teachers identify the occurrence of common alternative conceptions, likely to be represented in most classes. However, as we have seen above (§6.1.4), individual learners may develop quite idiosyncratic notions that teachers cannot be forewarned of, and which may be quite significant for the individual’s further learning. In these cases ‘prevention’ is difficult as the problems cannot be planned for, and a strategy of ‘diagnosis’ and ‘cure’ is needed (Taber, 2002b). It has been suggested that teachers need to act as ‘learning doctors’ looking to diagnose the ‘bugs’ in the learning system (Taber, 2005a). This approach requires teachers to be sensitive to student comments and answers that may offer ‘signs’ and ‘symptoms’ of alternative thinking. A tool that has been recommended as an aid to diagnosing the nature and source of student’s alternative conceptions or other learning dificulties (and so a starting point for planning a response) is the typology of learning impediments (Taber, 2001d). The term ‘impediments’ has negative connotations, but refers to the different ways that there can be a mismatch between the intended meaning of teaching and the results of a student’s making sense of it in terms of existing conceptual resources. The tool is in effect an attempt to support the shift in teacher thinking from working with an intuitive transfer model of teaching (§4.6), that offers little guidance on how to respond to ‘transfer failures’, to teaching that considers how to manage the highly contingent nature of student learning. In its latest version (Taber, 2006c), this sets out a number of categories of learning impediment, seen as the potential origins of the alternative conceptions students may demonstrate (see Fig. 6.9). The model is based on the basic constructivist premise that the desired learning requires making appropriate connections between new information and prior

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Fig. 6.9 Categories of learning impediment in the typology of learning blocks

Learning blocks: NULL LEARNING IMPEDIMENTS Deficiency learning impediments Fragmentation learning impediments

SUBSTANTIVE LEARNING IMPEDIMENTS Grounded learning impediments 'intuitive' social/'life-world', folk beliefs previous teaching Associative learning impediment linguistic cues inappropriate analogies nature of models

knowledge, and so teaching goes ‘wrong’ when the intended connections are not made, or when inappropriate connections are made – the latter point emphasised in Osborne and Wittrock’s (1985: 69–70) generative learning model, where ‘pupils have no difficulty generating links from sensory input to existing ideas’ but ‘links generated are not always to the ideas which teachers anticipate; frequently they are to existing ideas which would be considered quite irrelevant by the teacher’. The main division in the model is between situations where (a) no meaningful learning occurs (a null learning impediment) because the student either lacks the necessary prerequisite knowledge, or fails to recognise its relevance to the teaching or (b) where there is meaningful learning, but this differs from what is intended (a substantive learning impediment). In the latter case the new learning can either derive from existing alternative conceptions of the topic (grounded learning impediments) – which can be based on intuitive theories (‘gut science’), or from social sources (‘folk science’) – or from deficiencies in previous teaching; or by drawing upon other existing cognitive resources in ways that are unhelpful for the present learning (associative learning impediments). The latter includes drawing inappropriate conclusions from (i) linguistic cues, such as Schmidt’s (1991) example of students assuming neutralisation necessarily leads to a neutral product or assuming that electron ‘spin’ should be understood in the everyday sense (Taber, 2005b); or (ii) the student making an unhelpful comparison with a topic perceived as analogous; or (iii) failing to appreciate the nature and limitations of models, and so applying a model beyond its limits of application. A number of these features can be found in this 1974 description of Ausubel’s ideas by West and Fensham, A learner may not have in his cognitive structure the relevant subsumers for a given piece of new learning, and yet may not learn in the way described above as rote learning. Again the existence of the relevant subsumers does not per se guarantee that they will be called into play to produce meaningful learning. In either case there is a chance that the learner will, in fact, embark on a process of subsuming the new learning but using concepts from his prior knowledge that are not relevant. Ausubel … has recently agreed with one of us

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that a likely outcome would be misconceptions about the new learning. The carry over by learners into a new learning area of earlier, important but irrelevant concepts is a familiar experience to teachers of science. In particular, models that were useful in achieving learning at some stage are often retained and used by learners in situations for which they are quite inappropriate. (West & Fensham, 1974: 70)

There is nothing original then in the components of the Learning Doctors model beyond its form, which is intended to be of heuristic value in the classroom. The model simply outlines the main areas where the contingent nature of learning can lead to teaching of science (or other) concepts being ineffective. The categories represent thinking from a wide range of work on the RP, as discussed earlier in the chapter. The model is intended to offer a teacher-friendly overview of much research, and so offer a balance between simplicity and intelligibility on the one hand, and yet basic construct validity on the other. Versions of the model have been presented in initial and in-service teacher development contexts, and anecdotally it has been found useful by teachers (Taber, 2005a). However, as of yet, there has been no formal evaluation of its use in classrooms. If teachers are to move beyond being informed about learners’ common alternative conceptions by teaching guidance and application of pre-designed elicitation probes, to engage with learners’ difficulties on an individual basis, it seems this area of developing teachers’ diagnostic skills deserves more attention.

6.3.3

Using Knowledge of Students’ Conceptual Resources to Inform the Teacher

The CLiS project (§4.2.1) was devised to ‘develop revised teaching approaches which would be informed by research on children’s thinking in science and current theoretical developments in cognition’ (Driver & Oldham, 1986: 105). These approaches would involve both devising learning materials to take account of students’ prior ideas, and developing ways of working that encourage students – both individually and collectively – to engage in learning actively (p. 108). A basic tenet of this approach was that the curriculum should be a programme of activities which encourages pupils to (re)construct scientific knowledge (p. 112–6). The teacher’s role was to be a ‘facilitator’ who would provide the appropriate opportunities for the pupils to undertake the construction (p. 116). The constructivist model proposed included elicitation of ideas, and the restructuring of ideas – including exposure to conflict situations and construction and evaluation of new ideas (p. 119). The CLiSP model has five (somewhat overlapping) stages (Driver & Oldham, 1986): • Orientation: ‘designed to give pupils the opportunity to develop a sense of purpose and motivation for learning the topic’ (p. 116) • Elicitation: ‘when pupils make their ideas explicit, hence bringing them to conscious awareness … achieved by a variety of activities such as group discussion,

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designing posters, or writing, and may involve the presence of physical phenomena designed to focus thinking’ (p. 118) • Restructuring: discussion of different viewpoints (including the scientific model) to facilitate ‘the challenging of particular perspectives’ followed by ‘the evaluation of alternative ideas … against experience, either experimentally or by thinking through their implications’ (p. 118) • Application: ‘pupils are given the opportunity to use their developed ideas in a variety of situations, both familiar and novel’ to consolidate and reinforce learning (p. 118) • Review: ‘pupils are invited to reflect back on how their ideas have changed by drawing comparisons between their thinking now and at the start of the unit’ (p. 118) The use of notions such as teacher-as-facilitator, and curriculum-as-activities may seem to reflect the type of constructivist approach condemned by Bowers (see §5.1), however the ‘restructuring’ envisaged in the CLiSP model means moving student thinking towards scientific models, so curriculum as a programme of activities is not meant to imply a curriculum without established target knowledge, but rather one that includes pre-designed (and tested) activities designed to help students restructure their thinking towards specific predetermined conceptual learning goals. The application stage involves students testing out, and so appreciating the nature and value, of their new conceptions. One of the most teacher-friendly notions (or refutable variants) to derive from the RP is that of the ‘learning demand’ (Leach & Scott, 2002), which originates from the Leeds based Centre where CLiSP was located, and is based on teachers analysing the difference between students’ current knowledge states, and the target knowledge set out in the curriculum. This is intended to “bring into sharper focus the intellectual challenges facing learners as they address a particular aspect of school science” (p. 126). By definition, ‘learning demand’ is a tool that acknowledges established curricular models of scientific knowledge as the aim of teaching. One possible approach informed by the learning demand is to plan teaching using the notion of ‘intermediate conceptions’ (§6.2.2.14) along a ‘conceptual trajectory’ towards the target knowledge (Driver, 1989). For example, an approach labelled as ‘reflective discourse’ involves acknowledging “students’ comments respectfully, as expressing legitimate steps along a journey that likely will involve many changes in their thinking” (van Zee & Minstrell, 1997: 209). In the SPACE project (§4.2.1), primary age students’ ideas were elicited and treated as “valued expressions which could be accepted temporarily” before “teachers moved children to an intervention phase in which those ideas were more explicitly treated as conditional upon supporting evidence” (Russell & Osborne, 1993: 5). The typology of learning blocks, considered above, is intended to offer teachers heuristic guidance on what action needs to be taken when they diagnose particular types of learning impediments. The teacher’s most appropriate course of action depends upon the nature of the particular ‘learning bug’ (see Fig. 6.10).

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NULL lack of prior knowledge? failure to make sense?

presentation

deficiency make good

or missing the connection?

fragmentation

connect

grounded

correct

or

understand differently?

inappopriate prior learning/belief? or inappopriate connection?

associative

dissociate

SUBSTANTIVE Fig. 6.10 Applying the typology of learning blocks

6.3.4

Making Existing Thinking Explicit to Allow Exploration and Challenge

When comparing constructivist teaching approaches with more traditional expositions of new material, White (1994: 119) suggests that traditional ‘current classroom practice concentrates on providing explanations that learners will find intelligible and plausible, but overlooks two further conditions for conceptional change, of creating dissatisfaction with existing beliefs and convincing learners that the new notion is fruitful’. Garnett, Garnett and Hackling (1995: 71) reviewed instructional strategies based on constructivist principles and identified a number of common elements: • The provision of opportunities for students to make their conceptions explicit • Encouraging the restructuring of learners’ conceptions through a range of strategies such as discussion, exchanging ideas, demonstrations or experience with conflict situations • Allowing students to apply these new conceptions to experience their fruitfulness Rowell and Dawson (1985) suggest that once learners’ basic ideas about a topic are elicited, they should be used to build the appropriate curriculum science model (scaffolded by the teacher). Then, when the learners have constructed the new model they are given the opportunity to practice applying it. Then (once it is familiar, and considered their own construction) the class is asked to compare the

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new model with specific existing conceptions, and again the teacher structures the discussion to bring out the advantages of the curriculum science idea. This seems straightforward as a general strategy, but the findings discussed earlier in the chapter indicate that executing such an approach is unlikely to always be simple. A key aspect of such constructivist teaching is its high level of interactivity, both between teacher and students, and among students. Trumper (1993: 141) refers to how, from a constructivist perspective, curriculum ‘may be seen usefully as a process in which students are actively involved in constructing a view of the world closer to the scientists’ view’ with teachers looking to ‘develop ways which incorporate [students’] viewpoints within a learning-teaching dialogue’. Minstrell’s ‘reflective discourse’ ‘involves vigorous interactions among students and teachers’, characterised by (van Zee & Minstrell, 1997: 209–10) • • • • • • •

Acknowledging students’ comments respectfully Questions being asked by students as well as teachers Students elaborating their reasoning Exploration of ‘how do we know?’/‘why do we believe?’ The teacher ‘reflecting’ students’ thinking back for further consideration Avoidance of evaluation of the correctness of students’ responses Students being encouraged to claim the authority to judge answers

Such approaches put high priority on students developing metacognitive and independent learning skills that encourage them to take increasing responsibility for their own learning (Garnett et al., 1995), and so take an active part in the structuring and restructuring of their ideas. Bell and Gilbert (1996: 10–11) describe a constructivist view of learning that incorporates encouraging students to think about both their existing ideas and new scientific ideas they meet; supporting learners in answering the questions they have; and helping students reflect upon their own learning, both in terms of content and the actual learning process. From a constructivist perspective (in terms of much of the research into the nature of learners’ thinking, and the models of learning science considered earlier in the chapter) it is important that learners can make sense of and see the value of scientific notions, not just attempt to learn them by rote on the teacher’s authority. Osborne and Wittrock (1985: 70) suggest that pupils should be encouraged to ‘(i) to attempt to generate multiple links between sensory input and existing knowledge, and (ii) to construct meaning, and to critically evaluate this meaning against other aspects of existing ideas and meanings which could be constructed from other sensory input available’. In the primary SPACE project (§4.2.1), the intervention phase was described as ‘helping children to develop their ideas’ rather than ‘developing children’s ideas’ (Russell & Osborne, 1993: 7). SPACE used an approach of ‘providing experiences which would engage children and encourage them to reflect on their own understanding’ (p. 4). Russell and Osborne describe how ‘to remain within a constructivist orientation, children would need to explore evidence which might support or challenge their existing assumptions’ so ‘the strategy was not to confront, but to take interest in children’s ideas and pursue their implications’ (p. 5).

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This constructivist approach was distinguished from more traditional ‘guided discovery’ approaches as ‘the enterprise of seeking new evidence was stimulated and guided by the teacher, but remained within the ownership of the child’, recognising ‘children’s need to engage with evidence relevant to their personal theories’ (p. 5). The acceptance of ideas within the class were not, according to Russell and Osborne, determined by the match with target knowledge, but rather were ‘conditional on supporting evidence’ and ‘subjected to scrutiny and validation, often using class discussion’ (p. 5). The CLiSP project, directed by Ros Driver, published a number of case studies of learning in classrooms informed by the model of curriculum development outlined above (Brook et al., 1986; Wightman et al., 1986; Johnston & Driver, 1991). Bodner and colleagues (Bodner et al., 2001: 7) summarised Driver’s characterisation of constructivist teachers: • They question students’ answers, whether they are right or wrong, to make sure that the same words are being used to describe the same phenomena. • They insist that students explain the answers they give. They don’t allow students to use words or equations without explaining them. • They encourage students to reflect on their answers, which is an essential part of the learning process. Adey (1997: 59–60) has argued that ‘even under what might be considered as optimal conditions’ in the work of the CLiSP project, ‘where an enormous effort is made to engage students in discussions about their own conceptualisations, then to devise critical tests, and to confront preconceptions with evidence, there seems to be no more evidence that higher level concepts are permanently developed than in conventional classrooms’. However, there seems little basis for any reliable ‘objective’ evaluation, as case studies do not offer suitable evidence for making such comparisons. (Although in more recent years various controlled studies have appeared comparing ‘constructivist’ and ‘non-constructivist’ classrooms, these usually suffer from inherent design problems – see Chapter 7 for a consideration of research methodology.) diSessa (1993: 120) suggests that in view of the extent of refinement of naive scientific understanding needed, ‘that critical experiments and refined observational techniques are, by themselves, extremely unlikely to do the job that needs to be done’. This suggests that the teacher’s role goes beyond identifying learning demand, and setting up activities to promote cognitive conflict (§6.2.2.16) with existing thinking. The dissatisfaction is induced by presenting evidence that does not match students’ expectations and so leads to ‘cognitive conflict’ – or ‘disequilibrium’, ‘cognitive dissonance’, ‘cognitive tension’ or ‘conceptual conflict’ (Nussbaum & Novick, 1982; Strike & Posner, 1985; Driver & Oldham, 1986: 117; Gilbert & Pope, 1986). Adey (1999: 7) argues that the teacher’s role in such situations it to maintain the cognitive conflict through close questioning, as students ‘will tend to settle for the minimum solution that will meet the immediate demands of the problem in question’. However, where approaches rely upon demonstrating to students that their existing ideas are deficient in explaining phenomena, there is also the possibility

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that conceptual change may come at a cost: so Reddish (2004: 49) asks ‘can we retain the conceptual gains produced by the best cognitive conflict methods without doing damage to the students’ epistemological framing?’ Further, Chi and Slotta (1993: 259) argue that in some cases, where the new concept is (ontologically) incompatible with the prior conceptions, ‘we do not believe that the methods of replacement proposed in the literature, such as confrontation and challenges, will result in the acquisition or invention of this new ontology’.

6.3.5

Making the Unfamiliar Familiar

From a constructivist perspective, new meaningful learning is built upon existing conceptual resources, so the teacher has the task of ‘making the unfamiliar familiar’ (Taber, 2002b) by providing links between the new and what is already known. (As opposed to the educational researcher who, to avoid failing to appreciate the idiosyncratic nature of learners’ ideas, has to learn to make the familiar unfamiliar.) Glasersfeld expresses this process in terms that reflect the knowledge-in-pieces perspective of diSessa, Hammer and their colleagues (§6.2.2.9). Glasersfeld (1992) argues that ‘in order to become operative in a student’s thinking, a new conception must be related to others that are already in the student’s repertoire’ and that the most straightforward and effective way of doing this is ‘when the new structure is built out of elements with which the students are familiar’. He argues that students must be shown that • There are elements in their experience that can be related differently from the way they habitually relate them. • The new way provides advantages in a sphere of living and thinking that reaches far beyond passing exams and getting good grades. Glasersfeld points out that the conditions for the everyday mechanisms by which an individual’s meanings are tuned to fit those of others around them, or what Bruner calls ‘constant transactional calibration’ (Bruner, 1987: 87), and that are generally effective in respect of physical objects and situations (e.g. apples, birds, bus stops, queues, dancing); do not commonly occur for more abstract notions (inflation, intermolecular bonding, photosynthesis) where ‘it is far more difficult to achieve this social adequation, because the occasions where conceptual discrepancies might come to the surface are few and far between. Hence, in order to teach abstract notions, it is indispensable for the instructor to generate experiential situations for the students to make the necessary abstractions’ (Glasersfeld, 1992). Chi has suggested that student’s informal conceptualisation of the world is unlikely to spontaneously produce a suitable ontological category that fits the physicist’s understanding of concepts such as electrical current and heat. Chi and Slotta (1993: 256) therefore argue that ‘to learn physics concepts of this nature requires that the Acausal Interaction category be developed (i.e., instantiated) in the mind of the physics novice so that the concepts can be correctly categorized’.

6.3

Teachers Teaching Science

6.3.6

309

Learning by Analogy

This presents a challenge to the science teacher, but one approach to making ideas that are unfamiliar because they are distant from everyday experience more familiar, is to find ways to exploit analogies with what students can directly experience – for example, using what have been described as ‘bridging analogies’ and ‘anchoring conceptions’ (Clement et al., 1899). Analogical learning appears to be a common mechanism in human learning, starting from a young age (Goswami, 2008). Analogical learning has been well described in Science Education, e.g. (Harrison & Coll, 2008), and recommended as a powerful approach. Tyson, Venville, Harrison and Treagust (1997: 397) report that ‘Venville and Treagust (1996) utilized four different perspectives of conceptual change to analyze different classroom teaching situations in which analogies were used to teach biology concepts [and] found that each of the perspectives of conceptual change had explanatory value and contributed a different theoretical perspective to interpreting the role that analogies played in each of the classroom situations’. There are also clearly dangers of using analogical learning, as the learner may transfer inappropriate as well as appropriate features of the analogue to the target. For example, it is common to describe the atom (an unfamiliar concept) as being like a tiny solar system, but there are many ways in which the analogy breaks down (Taber, 2001e). However, where the analogy is used as the basis of a discussion which considers both positive (both have central bodies with most of the system’s mass, etc.) and negative (the orbiting bodies in a solar system are not identical, etc.) aspects of the analogy, then the approach can be a powerful basis for exploring new concepts. Chi’s model places particular significance on the major ontological classification of concepts, so it is not surprising that she warns that analogies which compare the target concept with an ontologically inconsistent analogue will be unhelpful, For example, the danger in using the analogy of flowing water to instruct about electrical current is that students will continue to assimilate newly taught information about electrical current into the ontological class of MATTER. If students assimilated new information about electrical current into the Liquid subcategory … the concept might also inherit properties such as ‘has volume’, ‘occupies space’, and other ontological attributes of the MATTER category. This explains why misconceptions about electrical current often include statements such as ‘It can be stored in the battery’ or ‘It can be used up’. (Chi & Slotta, 1993: 256)

6.3.7

Scaffolding the Building of Shared Knowledge

Solomon would argue that as scientific knowledge is ‘harshly uncompromising’, the teacher’s role is to direct the pupils to ‘make the imaginative but agreed pictures of consensual science their very own’ (1995: 16–17) through questions ‘designed to elicit the right answer’ (1992: 132). Edwards and Mercer (1987: 46) point out that

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questions are components of ‘the discursive weaponry’ that teachers use to direct classroom discussion towards the intended ‘common knowledge’. They describe education as ‘essentially a process of cognitive socialization through language’ whereby classroom discourse is used for ‘introducing pupils into the conceptual world of the teacher and, through her, of the educational community’ (p. 157). Part of the teacher’s role is to assist pupils to take up as their own the desired vocabulary, and the selected descriptions and explanations that will form the ‘basis of joint understanding’ (p. 151). Vygotsky (§1.6.2) introduced the term ‘the zone of proximal development’ (ZPD) or ‘zone of next development’ to describe the sphere of activity where a learner could solve problems with the teacher’s guidance, or in collaboration with peers, but not independently (Vygotsky, 1934/1986: 187, 1978: 86). It is within the ZPD that control of cognitive functions is transferred from the interpersonal plane to become truly intrapersonal (Newman & Holzman, 1993), so that what the learner can achieve within the ZPD, with assistance, is what he or she will next be able to achieve unaided (Crain, 1992). Wood, Bruner and colleagues popularised the term ‘scaffolding’ (Wood, 1988: 80) for the way an adult can ‘lend’ consciousness (Bruner, 1986: 74) to the child during the learning process, i.e. ‘a form of adult assistance that enables a child or novice to solve a problem, carry out a task or achieve a goal which would be beyond his unassisted efforts … a process whereby the adult controlled those elements of the task that were initially beyond the learner’s capacity, thus allowing the learner to complete those that were within existing capabilities’ (Daniels, 2001: 107). Writers such as Edwards and Mercer, and Hennessy, have put emphasis on the role of the teacher in providing the structure – in a Vygotskyan sense, that is ‘through a series of processes such as modelling, coaching, scaffolding, fading, articulation’ (Hennessy, 1993: 11) – to encourage the desired construction of knowledge. Leach and Scott (2002) have described an approach to designing teaching based upon social-constructivist principles. They suggest that teaching should follow three main ‘stages’, although these are not be seen as strictly sequential: 1. Staging the scientific story 2. Supporting student internalisation 3. Handing-over responsibility to the students Staging the scientific story involves ‘a performance (involving various teaching activities) led by the teacher, in which the scientific story is gradually developed during the sequence of lessons’ so that ‘the scientific point of view is made available on the social plane of the classroom’ (p. 122). Supporting student internalisation (a Vygotskyan term) is the process by which students are helped to make personal sense of the scientific story that has been ‘made available’ in their ZPD. Leach and Scott see ‘the continuous monitoring of students’ understandings and responding to those understandings, in terms of how they relate to the intended scientific point of view’ as central to this process, and would include ‘planned opportunities for monitoring student understandings (through, for example, whole class questioning and discussion, small group activities, or individual writing activities)’ (p. 123), and teaching responses ‘developing student understandings (by,

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for example, sharing particular points in class, challenging particular points in class, offering comments on student written exercises, discussing issues with individual students where time allows)’ (pp. 123–124). The third aspect of the Leach and Scott model, the handing-over of responsibility ‘involves providing opportunities for students to “try out” and practice the new ideas for themselves, to make the new ideas “their own” …first …with the support and guidance of the teacher’ (p. 124). Following the principles of scaffolding, increased responsibility is transferred to the learners ‘in recognition of their increased capability for unassisted performance’ (p. 124).

6.3.8

Teaching As Developing a Community of Practice in the Classroom

One of the strong messages that has underpinned much of the work reported earlier in this chapter, is that learning science is not just about learning more (or different) information, but is about developing new epistemological approaches to knowledge, and knowledge construction and ‘validation’: approaches that require students to develop metacognition about their own knowledge and learning. Hennessy (1993: 12) uses the notion of cognitive apprenticeship to suggest the teacher’s role is in ‘providing help in developing an appropriate notation and conceptual framework for a new or complex domain and allowing the learner to explore that domain extensively, then gradually withdrawing support’. Through this process the learner will develop ‘tacit strategic knowledge’, both cognitive and metacognitive. This will include strategies for exploring new domains of knowledge, and for ‘reconfiguring’ knowledge in a topic area (p. 20). Driver, Asoko, Leach, Mortimer and Scott (1994: 4) have similarly suggested that the teacher’s role not only includes providing physical experiences and encouraging reflection, but giving learners access to what they have called the ‘symbolic realities’ or ‘cultural tools’ of science. This notion of constructivist teaching, influenced by social constructivism, involves, ‘young people entering into a different way of thinking about and explaining the natural world; becoming socialized to a greater or lesser extent into the practices of the scientific community with its particular purposes, ways of seeing and ways of supporting its knowledge claims’ (p. 5). It is when such perspectives on science teaching are adopted that it becomes meaningful to start referring to teaching groups in such terms as ‘communities of practice’ (cf. 5.3.3).

6.3.9

Consolidating New Learning

The research into learners’ scientific thinking suggests that it is often contextualised (§6.1.4.11), and that informal ideas may readily reassert themselves as time passes after formal classroom learning. It is clear that new conceptual schemes may be hard

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won, and are only likely to be readily accessed and recalled if they are regularly activated and applied. It has also been suggested that recent learning may need consolidation before it is robust enough to support further learning for which it acts as prerequisite knowledge (Taber, 2005b). Ravitz, Becker and Wong (2000: 3) comment that ‘Constructivist-Compatible Instruction is based on a theory of learning that suggests that understanding arises only through prolonged engagement of the learner in relating new ideas and explanations to the learner’s own prior beliefs’. This makes sense from a Vygotskian perspective which suggests that ‘learning science should involve the gradual integration of personal experience and knowledge into the complex systems of models and theories, and the ways of thinking, that scientists use to explain natural phenomena … children need time to get used to and accept new ideas and other ways of understanding phenomena … and … time to move back and forth between everyday concepts and scientific concepts’ (Howe, 1996: 47–48). Similarly, from his studies on scientists’ developing thinking, Thagard (1992: 59) points out that it takes time and mental effort to explore the new ideas. This exploration may include debate with peers, and reflection on the discussion. Chi (1992: 180) also suggests that ‘because it requires extensive learning about the new domain, radical conceptual change cannot be some minute event that one can capture in the laboratory during a few sessions of work. Rather, it can probably come about only after extensive learning about the new domain or ontology of concepts’. Further, she suggests that if the new conception is to overtake (so ‘that the new conceptions are accessed more frequently than the old conceptions, which may still exist and remain intact’) the prior conceptions by Thagardian mechanisms of explanatory coherence (see §6.2.2.21), then ‘only after thousands of hours of learning these new conceptions could their mere abundance, coherence and strength potentially appear to overtake the existing conceptions’.

6.3.10

Claims for Constructivist Teaching

Robin Millar (1989a: 589) has pointed out that conceiving the construction of knowledge as an intrapersonal process does not automatically preclude particular teaching approaches. If the construction of knowledge is a mental process within an individual’s mind (as assumed in the hard core of the RP, even if not accepted by some constructionists, see §5.4), then a traditional method such as ‘chalk and talk’ (i.e. teacher exposition of ideas, with summary points to be noted highlighted for learners), might on occasion provide a suitable impetus to conceptual change as ‘the process of eliciting, clarification and construction of new ideas takes place internally, within the learner’s own head … independent of the form of instruction’. This reflects Ausubel’s (1961) view that meaningful learning in adolescent learners does not rely on ‘discovery’ methods (cf. §5.5.4), and that verbal reception learning can be an efficient way of meaningfully learning subject content. Millar (1989a: 592) points out that all learning involves the learner in reconstructing

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knowledge internally, and concludes that ‘science should be taught in whatever way is most likely to engage the active involvement of learners’ (p. 589). Although Millar suggests that some of the activities recommended for facilitating conceptual change could be substituted by more direct teaching approaches, he acknowledged that ‘the classroom activities suggested by the constructivists for eliciting, clarifying and reconstructing ideas become immensely valuable for the teacher who is monitoring and managing this reconstruction process’ (p. 592). Of course, variety of learning activities may be advisable regardless of a constructivist pedagogy, and including some elements of personal choice may be motivating for many students (Taber, 2007b) as well as potentially supporting constructivist approaches (e.g. offering a range of examples when allowing students to apply new concepts so they can select contexts of personal interest and familiarity making the new ideas more personally relevant). Despite the disagreements about what ‘constructivist’ teaching should involve, and the demands of monitoring and responding to learners’ ongoing conceptual shifts in the classroom, there are plenty of studies which suggest constructivist Science Education can be effective. Yager (1995) suggests that when constructivistbased approaches were compared with more traditional (‘text-book based’) teaching approaches in Iowa, there were a range of positive outcomes: • • • • • • •

More science concepts were learnt. Better science process skills were acquired. Students were increasingly able to apply concepts and principles. More science creativity skills were developed. More positive attitudes to science were acquired. There was a greater understanding of the nature of science. Students’ perceptions about causes in science were more accurate.

Indeed, according to Yager, ‘many of the most perplexing problems of science education are resolved when teachers use constructivist procedures’ (p. 57). Bearing in mind that designing such studies to give meaningful comparisons is difficult, and both novelty and expectation effects may come into play (see §7.6), it could well be that the role of prior knowledge is so significant for new learning, and the active and reflective involvement in learning so important to significant conceptual change, that even imperfect attempts at constructivist teaching often offer better learning outcomes than careful but tradition exposition that pays minimum attention to the learners’ own ideas and role in the construction process.

6.3.11

Constructivist Teacher Education?

In Chapter 4 (§4.6), the transfer model of teaching was considered. It was suggested that this should not be considered as a formal theory although because of the way it is linked to metaphorical messages in language it may often be a tacit and taken-for-granted way of thinking about teaching. Taking these considerations

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together, it would seem that we can consider the transfer model of learning as an element of folk psychology that makes up a common alternative conception of the learning process. Nonetheless, to the extent that the model is based upon generalisation of common experience, and it is not underwritten by any strong theoretical underpinning (i.e. mechanisms of cognition) it can be considered a useful conceptual resource as a starting point for a constructivist theory of learning. That is, given the transfer model our experience is that transfer seems to sometimes be substantially successful, sometimes partially successful, and sometimes unsuccessful. To explain this, we need to explore the mechanisms by which ‘transfer’ sometimes works, so that we can identify limitations in the system, and inform teaching accordingly. Constructivist thinking need not be incompatible with such an approach. Teachers have tended to apply the transfer model as if an implicit theory, and making the model explicit and bringing their attention to failures could be a first stage in developing their understanding of learning processes. In other words, we should recognise that teacher learning is constrained and channelled by the same kinds of contingencies that come into play with any learners. For example, Osborne and Simon (1996: 135) have reported how ‘based on a constructivist model of teaching’, research into ‘the deficiencies in primary teachers’ knowledge of science’ has informed ‘the extensive development of teacher education materials to help primary teachers improve their understanding’. Bell and Gilbert (1996: 58) argue for a view of ‘teacher development as learning by teachers [that] needs to take into account the existing knowledge, experiences, opinions and values of the teachers. This will include their prior knowledge of teaching and learning, and the nature and status of knowledge. It will also take into account their ways of learning’. Teaching teachers this way can be seen as an excellent example of teaching by example (Taber, 2009).

6.4

To What Extent Has the RP Addressed the Issues Set Out in the Positive Heuristic?

In Chapter 4, the constructivist RP into learning science was characterised in terms of its hard-core assumptions, and a set of general questions that informed a positive heuristic for building the protective belt of the programme. This chapter has offered a necessarily truncated sketch of the research and scholarship in the field (and informing the field) that can be considered to have addressed these key issues. This current state of the field will now be summarised in terms of the questions I have identified as directing the positive heuristic.

6.4.1

What Ideas Do Learners’ Bring to Science Classes?

There seems little argument even among those who criticize the constructivist RP that a great deal is now known about the ideas that learners bring to class. For most

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To What Extent Has the RP Addressed the Issues Set Out in the Positive Heuristic?

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science topics that feature strongly in school science curriculum, there are studies that report the common conceptions that students express. Research covers the full school-age range, and there are many studies exploring the ideas of college and university students as well. It also seems widely accepted that it is useful for teachers to be aware of these findings so that they can plan their teaching in the light of the common ideas and ways of thinking that students demonstrate. This is usually accepted even by those who feel the ‘constructivist’ programme is built upon a confused philosophical base (see §5.2).

6.4.2

What Is the Nature of These Ideas?

There is much less agreement on the precise nature of the ideas elicited from learners, especially in terms of how such conceptions might relate to underlying representations with the brain. A range of theoretical positions have been developed (i.e. refutable variants within the RP) in line with a diverse set of empirical claims. Given this situation, I retain the common term ‘alternative conception’ as a generic label for the ideas elicited from learners that are at odds with the target knowledge representing canonical science in the curriculum, without implying that this term indicates ideas of a homogeneous and uniform character. It has been claimed that reported conceptions derive from stable and tenacious beliefs that will interfere with teaching; and that they may be part of extensive and theory-like conceptual frameworks. It has also been claimed that many alternative conceptions reported are active constructions developed in situ and facilitated by the elicitation process, and that children’s thinking is characterised by poorly articulated and often tacit ideas with limited ranges of application, often bound to particular contexts, and not well integrated into coherent schemes. This apparently confused position requires some comment. One point that should always be borne in mind is that the type of research outcomes possible depend upon the methodology used: which is in turn chosen according to the way researchers conceptualise their work (Taber, 2007a). However, it could be argued that the normal mechanisms of the scientific community tend over time to overcome such inherent bias as it becomes clear that certain types of phenomena are best investigated and explained in certain ways. Yet in the constructivist RP there has not been a move to a consensus view that alternative conceptions are best specifically understood one way or another. Rather, what the diverse findings offered by different researchers appear to suggest is that the phenomena studied are far too complex for simple answers such as ‘alternative conceptions are tenacious’, ‘are integrated into conceptual frameworks’, ‘are stable over time’, etc. Instead, it is only sensible to explore such issues in relation to specific cases – which hopefully can in time become understood as members of classes of cases – and so to seek to find general patterns in the different conditions that apply when learners’ ideas tend to

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have specific characteristics. That is, teaching can be informed by identifying the circumstances when (for example) learners’ ideas are most likely to offer significant impediments to learning the prescribed target knowledge, so that teachers can be provided with a range of strategies to select from in different circumstances. As the focus of the RP extends over the full age range for formal scientific education, it is to be expected that attempts to characterise students’ scientific thinking should not lead to a unitary model of student conceptions, their origins and their significance for teaching. It should not be surprising that the nature of conceptions elicited from primary-age children is typically different from many of the conceptions elicited from college-level students with records of high interest in science and regular success in formal assessments of their science knowledge. This chapter has explored the models (refutable variants) of Claxton and Solomon. These were found to make useful contributions to the RP (even if offered from a perspective somewhat critical of the ‘alternative conceptions movement’, see Chapter 5). Claxton’s characterisation of minitheories does not seem to do justice to the knowledge structures inferred from research with some students, and in my own view underplays the difference between the conceptual structures of young children and professional scientists (compared, for example, with diSessa’s approach). Although a wide range of views can be supported by the literature, my own work with students mostly in the 11–19 age range suggests a great variety in the nature of the ideas offered when their science knowledge is probed. So, for example, some alternative conceptions reflect relatively isolated and local islands of thought; others are found to be components of conceptual frameworks that may have wide ranges of application. Solomon’s model comparing two distinct domains of knowledge is helpful here, but again is limited as it in effect compares the ‘natural’ (organic, shifting, context-bound) organisation of life-world knowledge with the formal organisation of disciplinary knowledge – and the individual learner’s personal representations of formal curriculum knowledge is not well described by either of Solomon’s categories – ‘border-crossing’ occurs to a varying degree in classes around the world (Aikenhead, 2006). In my view Claxton and Solomon’s models do not fit all of the empirical evidence, but they usefully offer insights into parts of the story. So, whilst there is evidence of context-bound elicitation of either life-world or school science knowledge in some research, it is clear that such domains cannot be completely encapsulated, students can forge links, and are likely to represent their academic learning within curriculum-relative boundaries, that may include separating out learning from the ‘different’ sciences. This raises new questions for the RP: To what extent do students separate out, for example, physics and chemistry knowledge, because of limitations of their cognition, or because of deficiencies in our teaching about the connections, or perhaps because it is a strategy that they find is usually most successful given the common modes of assessment of school science?

6.4

To What Extent Has the RP Addressed the Issues Set Out in the Positive Heuristic?

6.4.3

317

How Much Commonality Is There Between Learners’ Ideas in Science?

Again, it seems clear from the literature that there is not a simple answer to the question of whether learners tend to develop similar ideas: rather learners’ thinking in science has much commonality in some key topics, yet individual learners offer unique conceptions that may sometimes be especially important for their own future learning. We know some of the topics where there are very common alternative conceptions, and these commonalities offer considerable insights into the development of those ideas. The archetypical case is students’ intuitive thinking about force and motion – where most learners develop similar intuitive ideas about moving objects necessarily being subject to force – and both the significance for learning and the likely origins are thought to be well understood. The importance of early experience in the physical environment explains why similar conceptions should be found among (physiologically similar) people living (in physically similar environments) all over the world. It is less clear why some other conceptions should be found to be common in different contexts. So if alternative notions about the behaviour of atoms are found to be common in completely different educational and cultural contexts, then this raises interesting questions about universal biases in the human cognitive system or commonalities in the way the subject is taught – or both. Certainly exploring how such ideas develop in different cultural and linguistic contexts offers a useful way of starting to tease apart the factors that lead to such notions becoming popular (see Chapter 7).

6.4.4

How Is Knowledge Represented in the Brain?

The difficulties for science educators in knowing what knowledge is actually ‘stored’ in learners’ brains has been explored in various parts of the book. The knowing subject at best knows what she or he is conscious of at any moment, and can only describe this imperfectly. We can only draw inferences about the extent to which activated knowledge is remembered, reconstituted or even romanced – even in terms of our own thinking. If human recollections are typically only partially remembered, and then filled in with what seems feasible, then any sharp distinction between ‘learning’ science to remember it, and being able to produce educated guesses, dissolves into a question of degree. This is something that has perhaps not been considered in enough depth: for surely it has consequences for how we teach, and how we assess, and what we understand by our assessments? Yet, the folk psychology we generally share leads us to talk about memories, and remembering and forgetting in much more comfortable ways as if these were clear-cut processes. Perhaps the ‘alternative conceptions’ common among the teaching and research communities act as epistemological impediments to our research in this regard?

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What Are the Most Appropriate Models and Representations?

Notwithstanding these reservations about our usual way of talking and thinking about learning and remembering, the apparent stability of many of the ideas expressed by learners suggests (given the severe limitations of working memory) that these are often based on activating knowledge representations held in longterm memory. Many ‘alternative conceptions’ reported in the literature can be considered to be abstractions of stable features of learners’ cognitive structures. Moreover, in some cases, these conceptions are found to show stable links with other knowledge elements activated in student thinking, suggesting that knowledge representations are structured in long-term memory in terms of coherent conceptual structures (as Vygotsky suggested was inevitable). In these cases, where extensive and stable linkages between concepts can be demonstrated, modelling aspects of student cognition in terms of ‘alternative conceptual frameworks’ seems justified. Some of these knowledge structures appear to involve breadth of application, logical coherence, and to be based upon quite abstract general principles. Such alternative conceptual frameworks may reasonably be considered as ‘theory-like’. It is also clear that many ideas elicited from students appear to derive from stable knowledge elements which are less explicit to the individual, and which may appear to be tenacious, but which are largely applied tacitly and without deliberate application of abstract principles. These ideas may well derive from elements such as diSessa’s p-prims. The term ‘intuitive theories’ has been used in the literature, but it is questionable whether these intuitions should be labelled as theoretical except in a metaphorical sense. Models of students’ cognitive systems that will prove most useful in extending research into learners’ understanding of science are likely to include ‘conceptual resources’ at different grain sizes (including, but not only including, extensive conceptual structures), accessed at various levels of consciousness, and organised into domains with various levels of permeability. Effective models will allow for multiple overlapping conceptual structures, so presumably include either redundancy of representation, or a form of structuring that allows the same elements to, at different times, comprise components of different activated structures. The challenge for the RP will be to develop models which are capable of explaining all the existing empirical content of the research area (which seems to require a multi-level, diversely populated cognitive system), but which are still able to offer useful falsifiable predictions to allow empirical testing.

6.4.6

How Does Knowledge Construction (i.e. Learning) Take Place?

The basic constructivist premise offers a general principle of building up new knowledge from existing resources, and highlights the active role of the learner.

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There is plenty of research illustrating how intended learning can be distorted or prevented by students’ existing cognitive states. Piaget offered an extensive theory of cognitive development, based on a constructivist perspective, but the detail of his work has been widely challenged, and his main concern was not with the development of specific conceptual schemes. Within the field of Science Education itself, the transitions in student thinking and knowledge representation over extended periods of time remain largely unexplored. Two main sources of knowledge are widely acknowledged. The brain appears to have evolved as a processing apparatus, capable of different levels of abstraction and representation, which allows perceptual data to form the basis of generalisations. This has ultimately allowed the formation of concepts that can be consciously accessed and manipulated in some kind of internal mental ‘language’. We develop networks of conceptual knowledge that can become increasingly coherent and well integrated over time, but much of this takes place away from conscious awareness. We do not yet have a very good indication of the extent to which there are inherent limits (and how these vary for different learners, under different conditions, and with different types of subject matter) on learning of conceptual material due to the timescale needed for representing and consolidating knowledge structures in memory. As much science learning tends to be bootstrapped on earlier learning, this is an important topic, especially if the notion that new learning needs time to become ‘robust’ enough to act as foundations for further learning has general validity. We have also evolved over many generations certain biases and propensities which tend to channel our thinking in certain ways, which the principles of natural selection suggest should mostly be adaptive to have been perpetuated, at least in the environments where that selection took place (i.e. somewhat different from school classrooms and college lecture halls). Secondly, humans have evolved public languages which can be used for intramind communication, and which allow one individual to express his or her concepts, and other individuals to form their own internal representations of those concepts. A full understanding of concepts initially acquired this way requires more than simply hearing or seeing them expressed in the symbolic language, but undoubtedly such communication allows considerable shortcuts compared with each individual having to form concepts entirely by the processes of increasingly abstract re-representations of their direct experiences of phenomena. Such communication certainly increases the extent to which different individuals come to have similar conceptions. As most formal education involves learning through such communicative processes, it would be valuable to understand how this works in much more detail.

6.4.7

How Do Learners’ Ideas Interact with Teaching?

The different logical possibilities for how students’ existing ideas might influence further learning were established early in the RP. There is plenty of empirical research showing that these various options are all found to some extent in practice (even if complete replacement of previous ideas is understood in terms of the use of ideas and

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not overwriting and preventing potential access to them). Various models of cognitive structure and cognition offer useful approaches to understanding how these different options may come about, and – in principle – provide the basis for testable notions relating to the circumstances when different outcomes are likely. The ideas of Chi and Thagard suggest that sometimes considerable work on familiarisation with, and understanding of, a new way of thinking about a topic may be needed before it is likely to provide a generally accessed and applied conceptual framework. One strength of Chi’s model, in terms of maintaining a progressive RP, is that it offers a clear basis for predictions about which alternative conceptions are likely to be open to modification through restructuring and where conceptual change is unlikely to be profitably approached in such a way, and a new starting point is needed. Models of this sort would also seem to imply that where modification is possible the new conceptual structure (presumably achieved by the gradual retuning of the different connection strengths between various conceptual elements represented in cognitive structure) will in effect replace previous ways of conceptualising a topic, whereas the kind of radical ontological change highlighted by Chi would provide an alternative that comes to be accessed more readily and in a broader range of contexts – but where it will in principle be possible to trigger the learners to access and apply the initial conceptual structure by suitable contextual cues. In these ‘radical’ cases, something like Solomon’s demarcation of knowledge into life-world and school science domains may well seem to operate, but such a division will be less apparent where less radical conceptual change follows a gradual restructuring process. It is also possible to link this model with diSessa’s ideas. Where modification of conceptual structures may be seen as changing connection strengths in networks that are built upon a particular set of p-prims (or similar elements), Chi’s major ontological change would require starting from building new higher level abstractions from a different set of p-prims, based on completely different physical intuitions. A difference between Chi’s model and diSessa’s approach would seem to be that whereas Chi assumes the basic ontological categories, diSessa’s model offers a more flexible account, and therefore would seem to predict finer graduations in the extent to which conceptual change needs to be radical. It will be clear that much of this is speculative, but whilst it is premature to suggest that we have reliable models of conceptual change in Science Education, there are now well-established theoretical models that have sufficient predictive power to guide further research. In particular, studies that are primarily based in psychology or cognitive science offer models that are elaborated well enough to be taken as the basis for developing empirical studies in Science Education.

6.4.8

How Should ‘Constructivist’ Teachers Teach Science?

If the constructivist RP has achieved little else, it has undoubtedly made it much less acceptable for science teachers to base their teaching on the ‘folk-psychology’

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model of teaching as transferring knowledge from teacher to student. Notions of ‘teaching for understanding’, ‘pre-requisite knowledge’, ‘diagnostic assessment’, ‘active learning’, ‘assessment for learning’, ‘reflective learning’ and so forth are not specific to Science Education. However, the availability of constructivism as a generally accepted theoretical standpoint in Science (as in Mathematics) Education has allowed a common set of principles to be shared among science teachers. Recognising that learners have alternative conceptions (or ‘misconceptions’) and that these influence learning is now part of craft-knowledge, and so science teachers in many parts of the world are expected to elicit and take account of learners’ ideas. Arguably, even if the current state of the RP does not always offer clear guidance on when to respond in particular ways, the expectations that teachers will monitor and work with learner’s developing ideas is a desirable one. The norm in many countries is now that teachers expect to acknowledge learners’ ideas; do not expect it to necessarily be straightforward to teach the curriculum models that are at odds with learners’ thinking; recognise that they cannot automatically blame failures to learn on unwilling or intellectually ‘weak’ students; and appreciate that teaching has to involve students actively engaging in exploring and building up new knowledge rather than just receiving it. It may be argued that the folk-psychology model of teaching and learning was always untenable, and that good classroom teachers have always (if through practice rather than training) come to understanding teaching science as more than just providing accurate, clear and logical expositions. However research suggests that in the absence of a suitable theoretical model of learning, many teachers have in the past planned their work around the need to transfer specified material as efficiently as possible into learner’s heads. A theoretical perspective such as constructivism, even if only adopted as a general account, gives teachers the ability to justify decisions that are likely to promote effective learning (seemingly often something teachers are required to do when education is evaluated in terms of set ‘standards’, high-status testing, school league tables and the like), but would have seemed inefficient (or even counter-productive) from the basis of the transfer model of teaching. From a transfer perspective, time spent exploring the strengths and weaknesses of different ideas should surely be better used to focus on the ‘right’ answers? That is not to say that the RP has not offered much more than this. There is a wealth of research offering the teacher insights in to the nature of learning difficulties in particular topics, and many studies demonstrating the effectiveness (or otherwise) of specific approaches used to teach particular concepts in various educational contexts. The weakness of the current state of knowledge is that it offers a good deal of potential to advise teachers, but that much of this is: • Very specific knowledge (that is useful for those teaching the same topic to similar groups of learners in similar contexts), but which may be too specific for teachers to see how it may be adapted to other teaching situations • Specific suggestions for teaching particular topics that derives from research into learners’ ideas and learning problems, but which needs to be properly fieldtested to see if it does lead to better learning outcomes

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• More general advice about approaches to take in teaching, but which may not be clearly applicable in the classroom by the teacher without more detailed technical knowledge of the theoretical models from which it derives There is much useful advice for teachers in the literature produced by the RP, and there are very useful accounts suitable for teachers, that set out constructivist approaches and principles (e.g. Mintzes et al., 1998; Fensham et al., 1994; Bell & Gilbert, 1996). However, despite references to constructivism as a kind of paradigm in Science Education, the RP (with its formal origins within Science Education dating from c.1978, see §4.3) is still quite immature, as the treatment earlier in this chapter has shown. There are many useful concepts and conjectures to make up a productive protective belt around the constructivist hard core. However, contradictory refutable variants can each attract strong empirical support, suggesting that a conceptual framework that does justice to the complexity of student learning in science will (like science learning itself) be a nuanced construction drawing upon a range of different conceptual resources. The challenge to the RP is to build a synthesis from apparently inconsistent perspectives that actually specifies enough detail to allow refutable predictions that can be tested and move the programme forward: rather than an extensive theoretical edifice that can explain virtually any empirical findings about student responses to the teaching they experience. It is possible to separate out weak and strong approaches to ‘constructivist’ science teaching. The ‘weak’ approach would see learners’ ideas as deviations from the prerequisite knowledge that is part of a well-designed instruction sequence. From this perspective the teacher needs to: • • • •

Be aware of where learners may have alternative ideas Know about the range of alternative ideas in the relevant student population Have techniques to diagnose or audit the relevant prior knowledge in a class Have instructional approaches that can challenge learners ideas

This approach would be based on ‘correcting’ bugs in students’ prior learning so that the designed instructional sequence can be implemented. A ‘stronger’ approach would suggest that learners’ ideas cannot be readily overturned, and substituted by the desired conceptual building blocks. This view would suggest that the teacher may need to have a flexible instruction plan, and find ways to view learners’ existing ideas as the available conceptual resources for building towards target knowledge. As Glasersfeld (1983: 66–67) suggested, ‘if, then, we come to see knowledge and competence as products of the individual’s conceptual organization of the individual’s experience, the teacher’s role will no longer be to dispense “truth”, but rather to help and guide the student in the conceptual organization of certain areas of experience’. There is no reason to assume that one or other approach is necessary always ‘the’ correct one: it may be that teachers need a repertoire of teaching approaches: a weak approach being more straightforward when indicated, but supplemented by stronger approaches when these are needed. White (1998: 62) argued a decade ago that ‘it may be that information processing and constructivism have yet to be condensed to a set of propositions that teachers can use not only in curriculum and lesson planning decisions but also in the

6.4

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rapid sequence of actions they take in classrooms’, and this would still seem to be a fair assessment. There is much work to do before science teaching can be considered to be guided by a clear theoretical basis that provides teachers with the tools for constructivist teaching (which support ongoing and specific decision-making in planning and teaching) that can be reliably applied across subject matter and student group. This might lead to the type of constructivist position envisaged by Russell and Osborne (1993: 17), which they characterised as ‘to see the learning process as organic, dependent on the individual’s biography, the teacher drawing on a wide and diverse range of strategies to meet the student’s needs’.

6.4.9

A Progressive Research Programme

In the Lakatosian model, a RP remains progressive by changing, with new refutable variants developed through the research indicated by the positive heuristic. This chapter indicates that, whilst some of the initial research questions remain largely unanswered, the research that has been undertaken has moved the positive heuristic forward: we now have more nuanced and better conceptualised research questions about science learning than could have be proposed by Gilbert and Swift when they characterised the RP in 1985. In Chapter 5 (§5.4.1) it was reported that Joan Solomon (1993b: 85–6), arguably the strongest critic of the constructivist approach working on aspects of students thinking and learning about science, posed three questions that she saw as challenges to constructivism in Science Education. I would suggest that from the current state of knowledge in the field, none of these questions would be seen as doing more than informing the positive heuristic. Firstly, schoolchildren have difficulty in understanding the logical method of science, and resist changing their notions in the light of new and compelling evidence, because although they behave somewhat like scientists (attempting to create models to make sense of their experience) they are not trained scientists, but follow intuitive approaches that have evolved to provide mental models of adaptive advantage in our ancestors, rather than suitable for publication in peerreviewed research journals. Secondly, children may often seem to apply their ideas inconsistently, because they are much more context-bound than those of science, and not informed by the scientific ‘value’ of seeking the more generalisable abstract notions. Presumably, such contextually bound notions have often served humans well in practical contexts. Finally, even if each individual has somewhat unique experiences on which to base their models of the world, nonetheless, we would expect cultural group notions to be so much more similar than they are across different cultures, both because experiences are likely to be more similar within rather than across cultures, and because the experiences from which individuals construct understandings are as likely to be social and cultural as to be based on direct experience of the ‘natural’ world. Given what we know now of the contingencies that influence science learning, it is difficult to see why Solomon’s questions should be seen as challenging the RP. In 1994 Solomon suggested that ‘constructivism’, which had been seen as the most significant perspective and indeed the dominant paradigm in Science

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Education for several decades, had outlived its usefulness, and that perhaps it was time for the Science Education community to ‘move on’. Solomon’s paper presented a strong case that constructivism was ceasing to act as a fertile stimulus to research, and worse, that ‘if constructivism obscures other perspectives, either by its popularity or its blandness, that could be damaging’ (p. 17). My own reading of the literature discussed in this chapter is that the basic premises set out as the hard core of the constructivist RP by about 1983 remain as tenets underpinning much research in the field. Over the past two and a half decades, there has been a great of theorising and empirical work that can be seen as responses to the positive heuristic of that programme (§4.4.2). Because of the nature of the complex phenomena being studied it is possible to see this as resulting in a vastly increase literature base, that has failed to produce definite answers to the key questions set out by the RP. To borrow a phrase from Evelyn Fox Keller, this ‘merely confirms the existence of forms of order more complex than we have, at least thus far, been able to account for’ (Keller, 1986/1996: 171). There is then some truth in Solomon’s evaluation of constructivism, but Lakatos (1973/1978) recommended leniency for new RP, suggesting it may take decades for them to become fully progressive. My own view is that even in the fledging RP into learning in science we have seen much progress, and that the increased empirical base has constrained the acceptable theoretical approaches which are, therefore, having to be refined to remain acceptable. We have perhaps seen this most clearly in the way that an apparent opposition between personal and social constructivist perspectives has largely given way to a form of constructivism where most workers assume the existence of personal knowledge but acknowledge the high significance of social processes in determining its evolution. I would also suggest that whilst models to explain student thinking such as Claxton’s minitheories and Solomon’s domains do not explain everything we want to understand, as they are inconsistent with some of the empirical evidence, they have been useful refutable variants that include common features that any acceptable model to explain the nature of students’ ideas in science must have – just as such a model needs to explain the presence of widely applied, coherent and well integrated alternative conceptual frameworks that Claxton and Solomon’s models exclude. Whether a more coherent, better coordinated, RP might have achieved more, quicker, is a moot point. However, comparing the state of the protective belt now with that set out in 1978–1983 suggests that the constructivist RP into learning science has been empirically and theoretically progressive. Lakatosian RP are capable of evolving, and as Solomon (2000: 285) herself has acknowledged in reflecting on her earlier comments on the demise of constructivism in science education, ‘when an educational perspective is no longer new it is far more susceptible to change than to extinction’. Perhaps the ‘constructivist’ label has been outgrown to some extent, and even become a distraction because of its various associations (perhaps even an associative learning impediment, §6.3.2). However, the positive heuristic of the RP that was established at the beginning still offers guidance on moving the programme forward, and the progress so far has allowed some of the initial research questions to be refined considerably.

Chapter 7

The Positive Heuristic: Directions for Progressing the Field

This final chapter shifts the focus from an account of the nature of the (‘constructivist’) research programme (RP) into the contingencies of learning science, and the body of published research that can be identified as engaging with the positive heuristic of the RP, to a consideration of the priorities for further research. Chapter 6 offered an overview of the progress that had been made in responding to the key concerns of the RP, showing that this progress had been uneven. That account suggests that even where lines of research have to date made little progress towards offering reliable knowledge to inform teaching, the work that has been undertaken has been useful in demonstrating the complexity of the issues, and so better highlighting methodological difficulties and indicating the level of sophistication needed of models that will be widely applicable to science learning in widely diverging contexts. This chapter considers the layers of context that make up any learning environment, and considers how research within the RP needs to be directed to make further significant contributions to the field. In other words, this chapter considers how to interpret the positive heuristic of the RP, in view of what we have learnt so far, in order to continue to progress Science Education. The main conclusion drawn from the previous chapter is that since the adumbration of the RP characterised in Chapter 4 (§4.4), there has been a good deal of work which can be understood to have been directed by (or at least having aims consistent with) the RP. As a result of this body of work, the empirical content of Science Education has increased considerable. There has clearly also been a good deal of theorising, with new ideas introduced, sometimes borrowed from other academic areas, and that there has been considerable interplay between theory and data collected. Despite this, it is clear that three decades of somewhat fragmentary research has not been sufficient to offer definitive accounts of the complex nature of learners’ cognition and developing conceptual frameworks in science, There are a number of constructs in the field of physics, for example, that have remained stable for decades and are in essence unanimously accepted. Electricians, scientists, and lay people quite commonly apply metals conduct electricity as scientific fact; physicists and solid-state engineers treat Coulomb’s law as an established truth, and in almost all situations, it has served them well to do so. In contrast, there is not sufficient basis of experience, theoretical coherence, or consensus to justify teachers’ faithful adherence to either a misconceptions or a p-prims account of student knowledge. (Hammer, 1996: 122)

K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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Whilst there are few ideas that are as well characterised and universally accepted as might be desired in the natural sciences, there are commonly used ideas that are widely felt to be of some explanatory and/or heuristic value – what we might consider in Lakatos’s (1970) terms as ‘refutable variants’ of the RP (§3.6). To this extent, I would maintain that the RP can be considered to have been both empirically and theoretically progressive. When considering the positive heuristic deriving from ‘the seminal corpus’ (i.e. Driver & Easley, 1978; Gilbert et al., 1982; Driver & Erickson, 1983; Gilbert & Watts, 1983; Osborne & Wittrock, 1983, see §4.1), it seems clear from Chapter 6 that progress has been uneven, although that chapter also argued that this was both understandable and indeed to be expected. As Lakatos (1973/1978: 6) warned, ‘one must treat budding programmes leniently: programmes may take decades before they get off the ground and become empirically progressive’. In this chapter, I set out a view of the key directions for further research in the Programme. It will be clear that at a general level these recommendations echo suggestions made at the very start of the Programme, and indeed this is the ‘certain continuity’ that Lakatos (1970: 132) thought characteristic of any RP, as ‘in the positive heuristic of a powerful programme there is, right at the start, a general outline of how to build the protective belts’ (p. 175). However, this does not mean there has been no progress. Rather, we are now in a position to refocus on some of the questions that were perhaps too challenging at the start of the RP, as we now have available both a considerable empirical database and a refined and expanded toolbox of conceptual tools (within the ‘protective belt’) to support and hone the next stages of the research. According to Lakatos, in a RP the basic commitments and general outline of the programme are established at the beginning. A progressive RP maintains its hard core, and increases its empirical and theoretical content whilst developing the research directions initially indicated by its heuristic – a situation that can certainly be seen to apply here. It is also clear that some of these directions could be seen as responses to the criticisms of constructivist research discussed in Chapter 5, reiterating a view that at least some of that criticism is best seen as part of healthy debate within a RP rather than as criticisms of the overall programme itself. The themes raised in this chapter should not come as a surprise in view of what has gone before in the book. The main recommendations are that in order to continue progressing our understanding of learning in science so as to inform science pedagogy, we need more research to: • Study individual learners in depth, but • In parallel need to test out the generalisability of apparently significant findings from individual cases • Investigate learning over extended time periods • Contextualise science learning within conceptual ecologies • Investigate learning within specific teaching contexts • Investigate learning processes within student groups • Find ways to relate specific features of educational contexts to learning outcomes

7.1

7.1

What We Know Now

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What We Know Now

These foci derive from a consideration of the current status of our knowledge. We know that learners do often arrive in classes with a range of existing ideas that can influence further learning in most if not all science topics. We also know that the nature and status of these ideas has been contended, and it has been strongly argued here that – assuming most researchers reporting results are reasonably competent – this would suggest that the potential significance of such ideas for future learning varies considerably. We know that learning is a complex mental process that is potentially influenced by a wide range of factors (linguistic, social, motivational, student expectations about the nature of learning and subject knowledge, etc.) as well as the students’ existing ideas and the teachers’ instructional approach and presentation of subject material. We also know that learners can be highly individual, but sometimes demonstrate strong commonalities. Given all this, it is clear that we are enquiring into very complex phenomena. Some of the critics of constructivism in Science Education have felt that it was largely an activity based on collecting accounts of learners’ ideas (§5.3) – thus the term the ‘alternative conceptions movement’. There has been a view that the early stages of the RP focused too heavily on the ‘natural history’ of learners’ ideas (§5.3.1) – akin to ‘butterfly collecting’ or ‘stamp collecting’ – rather than on more theoretically driven, model building activities. For example, Smith, diSessa and Roschelle (1993: 123) argue that ‘much less emphasis was given to modeling the learning of successful students in those domains, to characterize how misconceptions (and the cognitive structures that embed them) evolve, or to describing the nature of instruction that successfully promotes such learning’. Chapter 6 suggested that although there has now been some significant and important work along such lines, it is areas such as these that continue to suggest research questions and problems that will allow us to move the programme forward. As Driver (1989: 484) noted, although ‘studies of students’ conceptions present us with discrete snapshots in the continual construction and reconstruction of students’ knowledge [that] provide valuable insights that can inform curriculum planning and the possible sequencing of ideas for teaching purposes’; something more is needed to ‘provide information on the dynamics of change, information that is necessary as a basis for designing approaches to teaching’. Perhaps by conceptualising the constructivist RP as less about learners’ ideas per se, and more about understanding the contingencies of science learning, it becomes clearer that the programme has considerable theoretical content, has a good deal of important work still to do, and has much potential to inform science teaching. This seems clear from the literature sketched in Chapter 6, which shows that the research following the positive heuristic established around the period 1978–1983 was always about much more than collecting and cataloguing conceptions. The ‘constructivist’ tag has been a very apt one, but prone to distort the work of the RP, either by those who see it as merely about finding out what students think before being taught, or those who associate various

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philosophical or pedagogic stances which whilst often also labelled constructivist, are not part of this programme’s hard core. The work of exploring the ideas students bring to class cannot be considered to be closed, but certainly there is an extensive literature, and this can no longer be seen as the main focus for moving forward the RP. However, there still will be opportunities for useful work where there are ‘gaps’ in existing knowledge – for example, in response to Jenkins’ (2000b: 6) criticism that whereas research has ‘been directed principally at children’s understanding of such concepts as mass, acceleration, chemical change, gravity and evolution that form the staple of classical and school science’, there has been limited research on student thinking about ‘trans-or inter-disciplinary concepts that characterise many of the public discussions of science in the broadcast or printed media, e.g., biodiversity, threshold limit value, various measures of environmental or personal risk’. Similarly, research into students’ understandings of the nature of science is far less extensive than that directed to understanding of the products (i.e. theories, models) of science (Taber, forthcoming).

7.2

The Continuing Challenge for the RP

The unique nature of individual learners, and classes, suggests that they are best studied by methods that can offer detailed accounts of particular cases. Yet the imperative to inform teachers, who are too busy to read research in detail, and who typically plan and teach a number of large groups of students each week, suggests that generalisation, where possible, is to be highly valued. There is clearly a tension here. The complexity of learning would suggest that ‘clinical’ approaches that study individuals isolated from uncontrolled variables are needed. Yet taken to the extreme (and such studies have been common in psychology – learning nonsense syllables, etc.), such work can only tell us about learning in a very abnormal context. Most school and college science learning takes place in class sessions, and involves considerable interaction with teachers and (as the social constructivists rightly remind us) other students. The many variables that can influence this learning in the chaotic classroom context are the very things that can in principle be manipulated by teachers to improve teaching. Another obvious tension is at work here.

7.2.1

Post-positivist Approaches to Research: Fitness for Purpose

A researcher’s ontological beliefs about the nature of the phenomena being studied, and epistemological commitments to the kind of knowledge which it is possible to hold about the phenomena, should always guide their development of specific

7.2

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research questions, and the methodology adopted to design studies (Taber, 2007a). A view of educational research which sees enquiry as dichotomised between (a) positivist approaches (controlled experiments to test hypotheses) that can reveal general truths and (b) interpretivist (‘constructivist’) studies that look to construct personal meanings from exploration of individual cases, would suggest that these tensions would exclude a comprehensive understanding of learning from being the subject of a single coherent programme of research. As discussed in Chapter 2, this is a common view taken of educational research. However, Chapter 2 also argued that although the controlled experiments of physical science can seldom be applied in education, a post-positivist view of science suggests that ‘scientific’ research in education need not adhere to a narrow view of how objective knowledge claims are derived. A post-positivist view of science admits a range of research approaches (NRC, 2002) including those that acknowledge the researcher’s inevitable role in constructing findings that necessarily entail a ‘subjective’ element. As Furnham (1992: 61) has argued ‘research methodology not only reflects certain epistemological positions taken by the researchers but it can also, and frequently does, shape both the questions one can ask and the answers emerging’. He suggests that whilst ‘small scale, cross-sectional, rightwrong answer studies on small unrepresentative populations do not provide much theoretical advancement’, ‘equally, unless in-depth interview or simulation studies are driven by theory, their rich findings fall on stony ground’. It is considered here that it is inevitable, and not necessarily undesirable, that epistemological positions influence research in this way: but that this is only a weakness when such influences are not made explicit (to researchers themselves, as much as their readers), and when particular positions become default positions rather than alternatives that inform complementary research approaches. A report of a particular study should offer readers a clear justification for the methodology used, which should reflect the research questions asked – that in turn derive from a clear conceptualisation of the field. Questions of the form ‘what is going on here’, ‘what does the student make of this’ will be approached differently form those which ask ‘do most students think this way’ or ‘is it better if the teacher does this rather than that’? However, from the context of seeing research in terms of RP rather than individual studies, methodological pluralism is appropriate. Exploratory questions (‘what is going on here?’, ‘what does the student make of this?’) are often needed to start building models to offer operationally defined concepts that can be tested in more controlled ways (‘do most students think this way?’ or ‘is it better if the teacher does this rather than that?’). The starting point is to develop interpretations of the complex phenomena ground in empirical evidence that lead to conjectures that are worth testing out (Taber, 2000a). Within a RP, individual methods are selected because of their ‘fitness for purpose’ for a particular research question that arises at a particular stage of the research. Given this general principle, I have no qualms about offering research priorities that require a range of research approaches. Progressing the PR will require coordination between these different modes of enquiry.

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Complexity: The Need to Study Individual Learners in Depth

A key feature of human learning, certainly school- or college-based learning, is that it is a complex set of processes. This can be seen clearly in the research that has been reported in Chapter 6. The conceptual structures that learners develop through their (informal and formal) learning are also very complex. In Chapter 6, the notion of a conceptual ecology was introduced (§6.2.2.24) which reflected how the constructivist notion of learning being influenced by prior knowledge went well beyond just current understanding of a particular concept. However, it is also clear that the individual’s conceptual ecology is just part of a nested system of environmental contingencies which influence the learning process. Learning takes place in some form of social context (perhaps alone, but more often in a group setting: sometimes in a formal lecture hall; sometimes a small group of friends in a ‘progressive’ classroom; sometimes a family group watching a documentary or visiting a museum; sometimes as legitimate peripheral participation in textile work or agriculture, etc.), where the nature of the setting and the interactions with others channel learning. The social setting is part of a wider culture with its artifacts, linguistic codes, and various tools to mediate communication and learning. The culture is embedded within the natural environment where humans (whether they prefer to celebrate or ignore it) are interdependent with the rest of the living word. Finally, the various natural environments in which cultures are located are all constrained by the physical environment with its fixed chemical and physical properties. Each of these ‘levels’ of environment has been argued to influence learning at various points in the book, and a full consideration of the ‘learning environment’ needs to pay attention to the full system (see Fig. 7.1).

7.3.1

Exploring Cognitive Structure

There is much scope to look to develop lines of work such as those of researchers such as Chi (1992) and Howe (1998) who argue that further research should be focused on exploring learners’ cognitive structures, for example, that ‘one should develop methods to assess directly the structure and coherence of the knowledge base that generated naive explanations on an individual basis’ (Chi, 1992: 157–158). The very different characterisations of the nature of learners’ ideas in science (§6.1.4) would seem to be telling us something significant about either our research or those ideas themselves. As discussed in Chapter 3 (§3.3), a research finding relies upon an extended chain of logic, and it is always possible to sidestep research findings that seem to refute our ideas by transferring breakdown from the conclusions themselves to an earlier link in the logical chain: that is, ‘data are evidence for a hypothesis only in light of background assumptions’ (Longino, 1990). Refutation

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Fig. 7.1 Learning takes place in a multi-layered environment

may be considered to refer to the theory of instrumentation – the methodology by which a study set up the chain of inference. That commentators have had widely different views about the nature of learners’ ideas in science could lead us to question the competence of some of those researchers, or the appropriateness of their methods for eliciting children’s ideas. However, it is also possible, as argued in Chapter 6 (§6.4.2), to interpret the differences found by various researchers as telling us something significant about learners’ ideas – that is, that they vary along a range of dimensions. This is certainly what my own research has suggested. Students’ ideas are not always consistent, theory-like, highly structured, committed, having manifold nature, etc.: but they certainly can be all of these things. Here one of the central phenomena studied in the RP offers considerable complexity. Of course, some methodological approaches do not enable us to collect the forms of data necessary to characterise learners’ thinking along such dimensions. For example, simple questionnaires and diagnostic probes offer indications of the frequency with which groups of learners find certain ideas feasible: but without testing out whether such judgements are long-lasting, or strongly committed too, or exist alongside other apparently contradictory ideas, for example. As we have seen earlier in the book, such distinctions are not of purely esoteric interest. Elicited alternative conceptions may be considered as serious impediments to intended learning that should be challenged, as irrelevancies best ignored, or as potential resources for constructing target knowledge. Unless we are able to find

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ways to identify when particular ideas are best treated in these different ways, the identification of learners’ ideas (whether by researchers, or as part of classroom practice) has limited value for pedagogy. It is strongly argued here, therefore, that we need to understand learners’ ideas in detail. Only in-depth studies that offer us the chance to characterise learners’ ideas in terms of their status within students’ conceptual structures offer the possibility for making linkage between different classes of idea and the most appropriate educational responses. For example, As Maloney and Siegler (1993: 294) suggest in relation to physics knowledge, research needs to explore ‘both what concepts the student knows and the conditions under which the student thinks each concept applicable’. Techniques capable of characterising learners’ ideas – of testing out their qualities, range of application, stability, unitary of other nature, etc. – will reveal some (but not all) elicited ideas as romanced, isolated and transient. However, approaches that merely count incidences of different students offering an idea are not capable of indicating the likely status and significance of those ideas for the individual students’ future learning.

7.3.2

Techniques for Exploring Student Thinking and Cognitive Structure

In-depth studies imply spending time with learners exploring their thinking. As Pope and Denicolo (1986: 154) suggested, ‘the very choice of intuitive theories as a focus of investigation represents an epistemological stance consistent with the qualitative-interpretative approach’. Osborne and Wittrock (1985: 80) commented on their own constructivist approach that ‘the depth of analysis of children’s idea and learning required to test the generative learning model in specific situations is likely to require in-depth interview analysis’. In-depth interview techniques are certainly suitable, but there are a range of other potentially valuable approaches. Techniques such as concept-mapping and word-association can also be useful, especially when used as starting points for interviews.

7.3.2.1

Children’s Drawings

Drawings can be used to elicit students’ ideas, especially where ideas may be tacit or difficult to verbalise. This may be especially useful when working with younger learners. As Russell and Osborne (1993: 10) noted ‘the act of articulating an idea in this form causes the child to focus on and explicate the concept here as previously their thinking may have been semi-intuitive and lacking an articulated form’. The ‘draw-a-scientist’ technique has been used to elicit children’s perceptions of working scientists (e.g. Newton & Newton, 1988), or the types of scientists they might aspire to be (Alsop, 2007). However, the technique has also been used to elicit students’ mental models, e.g. asking college students (studying for university

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entrance level examinations) to draw metallic structures at the submicroscopic level revealed alternative conceptions (Taber, 2003b).

7.3.2.2

Modelling

Whether drawing is seen as ‘artistic’ or ‘technical’, it certainly offers an alternative creative outlet to verbal means of elicitation (writing, speech). Students can also represent their ideas in other forms of models (Grevatt et al., 2007) – such as building physical models of cells to show the structure of typical plants and animal cells (Key Stage 3 National Strategy, 2004a), or at a more sophisticated level, e.g. such as of the nephron to show its function (Hicks, 2005). As well as physical models, students can develop their own analogies for abstract notions such as electrical current (Taber et al., 2006). Students can also be asked to illustrate their ideas though dance and drama. Sizmur and Ashby (1997) give an example of a class creating a dance sequence representing the movement of cosmic bodies, something that recognises that normal communication of ideas is not purely verbal (Kress et al., 2001). Dorian (2007) describes various role plays and simulations he observed in secondary science classes, and discusses how group work to devise drama activities can allow students to model (and teachers to assess) their understanding of science concepts.

7.3.2.3

Concept-mapping?

Another elicitation technique that has been widely used (Al-Kunifed & Wandersee, 1990) is that of concept maps. This technique was, according to Joseph Novak (2004: 5), introduced as ‘a better way to represent children’s conceptual understandings and to be able to observe explicit changes in the concept and propositional structures that construct those meanings’, but as Novak acknowledges, ‘has now become a powerful knowledge representation tool useful not only in education but in virtually every sector of human activity’. Wandersee (1990: 926) refers to concept-mapping as being the ‘cartography of cognition’, arguing that ‘if knowing is making a mental map of the concepts one has learned and if people think with concepts, then the better one’s map, the better one can think’. Whilst useful in formal research, concept-mapping techniques can be useful teaching and learning tools in Science Education (Taber, 2002b); and so when used as classrom elicitation techniques (§6.3.2), have the advantage of being something that encourages reflection upon learning, and that many students recognise as useful for crystallising, evaluating and monitoring their own learning (Taber, 1994c).

7.3.2.4

Grid Technique

George Kelly, who was a strong influence on some key workers in the field (§4.1.6), developed a method called Construct Repertory Test as a means of eliciting the

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constructs that an individual used to structure their world (Fransella & Bannister, 1977). The original version of the approach involved identifying significant others for the individual, and then presenting cards representing various triads of those people. The individual was asked to identify possible ‘odd-ones-out’ and to try and explain the basis of the discrimination. The use of presenting three ‘elements’ (triads) for a comparison was a key part of Kelly’s (1963: 122) technique, as ‘the minimum context for a construct is three things. We cannot express a construct, either explicitly or implicitly, without involving at least two things which have a likeness and one which is, by the same token, different’. Repertory grid technique was developed so that once constructs were elicited, they then could be used to judge each of the elements, and so indications of how the constructs were related could be constructed – to give ‘a map of the construct system of an individual’ (Fransella & Bannister, 1977: 3). Fransella and Bannister (1977: 117) suggest that it may be an appropriate technique for studies of conceptual development: that is, that research ‘on children’s acquisition of constructs to do with the physical world might be richly elaborated using the grid as a way of exploring how these constructs fitted into the more total construct system of the child’. The approach has been used in Science Education, e.g. with the cards representing chemical structures such as molecules, ions, etc. (Taber, 1994a). Osborne and Wittrock (1985: 63) have argued that the repertory grid technique is ‘not easily accepted by science teachers’ as ‘teachers of physical science in particular are suspicious of research which requires complex statistical analyses to make sense of the data’. However, the original Construct Repertory Test can be used to elicit constructs (e.g. to increase the validity of interview questions) without following the full Repertory Grid procedure. Jon Ogborn and his co-workers used a similar grid-based approach, ‘with the nine scientific concepts across the top and a list of features whether or not it possessed each feature’ to explore correlations among the perceived features of nine science concepts within a four-dimensional ‘ontological space’ (Mariani & Ogborn, 1991: 73).

7.3.2.5

Combining Techniques

Any single approach to exploring cognitive structure will have limitations, but the use of a battery of approaches allows a form of ‘triangulation’ (Eybe & Schmidt, 2001). Such an approach may be useful in overcoming the limitations of individual techniques. So although in-depth interviewing is rightly recognised as a very powerful technique, it is inevitably a somewhat subjective technique in that the interviewees’ answers are interpreted by the interviewer (§2.6.2), and responded to according to that interpretation. As Kvale (1996: 14) suggests, ‘the qualitative research interview is a construction site for knowledge. An interview is literally an inter view, an inter-change of views between two persons conversing about a theme of mutual interest’. Combining interviews with approaches that are more ‘objective’ can draw upon the strengths of interactivity (the ability to explore and check the interviewee’s

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comments, see below), but moderated by the adoption of less probing, but also less suggestive, approaches. So, for example, Repertory Test techniques can be used as the starting points for interviews (Taber & Student, 2003). Champagne, Gunstone and Klopfer (1985: 178) describe how they combined the findings from different ‘group-administered probes (word-association, free sort and tree construction tasks)’. They report that ‘proximity matrices have been produced from responses to each of the three tests and scaling methods applied to these matrices to produce representatives of cognitive structure’.

7.3.3

The Development of Interview Methodology

The use of interviews as a basic approach to exploring children’s thinking was common in Piagetian studies. Although Piaget (1932/1977: 8) saw his work as ‘naturalistic’, rather than experimental, he recognised that pure observation was limiting, and suggested that naturalistic observations of his daughters had been informed by his interview studies. He explained that, over several years he had ‘been engaged in taking down the spontaneous remarks made by my two little girls … the meaning … of many of their chance remarks, would have almost completely eluded me if I had not in the past questioned hundreds of children personally on the same subjects’. Interviewing had the advantage that ‘it makes evident what observation left to itself can only surmise’. Piaget’s interviews went beyond asking children what they already believed and thought. So, for example, in his studies of ‘moral’ thinking, Piaget was interested in understanding how children understood rules to originate (e.g. whether they were absolute, or based on an authority that should be respected, or open to being modified by mutual agreement of those concerned). Recognising that direct questioning was unlikely to offer a reliable means of ascertaining this, Piaget developed means to indirectly probe the youngsters. He devised a two-stage approach where ‘during the first part, it is sufficient to ask the children (we questioned about 20 boys ranging from 4 to 12–13) how one plays marbles. …Then comes the second part. …You begin by asking the child if he could invent a new rule’ (Piaget, 1932/1977: 20–21). Piaget developed his approach of using clinical interviews such that ‘each child’s thought patterns are traced by a series of questions, each being dependent upon the previous response given by the child’ (Brown, 1977: 89). Piaget (1929/1973: 19) recognised that his approach had shifted from a naturalistic stance to a more interventionist one, and considered that clinical interviews offered the best qualities of ethnographic and experimental approaches, by being able to ‘unite what is expedient in the methods of test and of direct observation, while avoiding their respective disadvantages’. This best-of-both-worlds approach was: • ‘experimental in the sense that the practitioner sets himself a problem, makes hypotheses, adapts the conditions to them and finally controls each hypothesis by testing it against the reactions he stimulates in conversation’.

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• ‘dependent on direct observation, in the sense that the good practitioner lets himself be led, though always in control, and takes account of the whole mental context, instead of being the victim of “systematic error” as so often happens to the pure experimenter’. In-depth interviews explore the range of application of ideas, and the consistency of their application, by probing various examples and contexts, inviting informants to offer extended answers, and by the interviewer attempting to reflect back and explore the learners’ own language and invite them to enter into an extended conversation. A range of general question forms are useful in such interviews, e.g. • • • • • • •

Why do you think that? Have you always thought that? Does that always apply? Do you think your friends think about it this way; (why not?) How do you think your teacher/scientists know that? Do you think people have always thought that? (Why not?) Do you think aliens from another galaxy would have come to the same view?

Other useful probes can include • If you had to explain this to a younger sibling/cousin/pupil… • Another student I was talking to told me [something different to what you have said]; have you any idea why they might have suggested that? Although an advantage of these types of interviews is that they have flexibility not possible in a rigid survey-type schedule, they can be designed so that they offer ‘coverage’ of a range of potentially relevant points, even when these are not volunteered by the informant without leading the interview (e.g. ‘hierarchical focusing’, Tomlinson, 1989). This work is quite skilled, and requires careful preparation and practice. As Piaget pointed out, The good experimenter must, in fact, unite two often incompatible qualities: he must know how to observe, that is to say, to let the child talk freely, without ever checking [stopping] or side-tracking his utterance; and at the same time he must constantly be alert for something definitive, at every moment he must have some working hypothesis, some theory, true or false, which he is seeking to check. (Piaget, 1929/1973: 20)

7.3.3.1

Interviewing About Instances/Events

Early in the RP, techniques were developed to include focal material to support interviewing. Interviewing-about-instances (I.A.I.) used a set of cards with diagrams, that might, or might not, be considered as examples of a focal concept (e.g. ‘force’), so that ‘in outline, the I.A.I. technique consists of tape-recorded dyadic discussions between the researcher and a student, using a deck of cards and focusing on the applications of a single word’ (Gilbert et al., 1985: 12). Swift, Watts and Pope (1983: 23) suggested that the use of pictures as foci ‘may overcome … reliance on

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verbal formulation’. A related approach, using props such as apparatus or materials in place of diagrams, was known as ‘Interviews about Events’ (Osborne, 1980).

7.3.4

Analytical Approaches

Data collection is an important part of the research process, but the quality of the data collected can only be fully utilised if the analysis of data can do it justice. Richard White (1985: 51–22) has commented on how ‘interview techniques promise to give us great insights into how people store and recall knowledge and use it in thinking [but] they provide so much information, however, that there is a danger of drowning in a sea of uninterpretable data’. The analysis of complex qualitative data is challenging, and usually requires iterative processes that can model the key features and structure of extensive (usually) verbal material: approaches such as Johnson and Gott’s ‘neutral ground’ (Johnson & Gott, 1996); Petri & Niedderer’s ‘iterative hermeneutic interpretation procedure’ (Petri & Niedderer, 1998), or approaches developed from grounded theory (Taber, 2000a). Whilst grounded theory approaches attempt to develop categories and concepts to describe data that are based on in vivo coding (i.e. developing codes from data, rather than applying a predetermined analytical framework), the range of theoretical tools and models developed in the RP under the influence of the positive heuristic (see Chapter 6) offers a choice of theoretical perspectives that can be used to interrogate interview data. Given the complexity of the phenomena studied, a degree of analytical pluralism – drawing upon a range of analytical schemes – may well offer a better overview of data than analysis based on a single scheme (Taber, 2008c). This point links back to the difference between exploratory and confirmatory research highlighted in Chapter 2: studies designed to test a particular hypothesis will use a specific predetermined analytical framework, where more exploratory studies may be strengthened by the application of complementary approaches. As one example, interview data on student understanding of the orbital model of atoms and molecules was analysed by a battery of three complementary approaches considered as three ‘lenses’ – student understanding of the nature of the models used; the typology of learning impediments (§6.3.2); and Chi’s notion of conceptual change across ontological categories (§6.2.2) – to focus on different features of the data in order to offer possible explanations for student learning difficulties (Taber, 2008c).

7.4

Generalisability: The Value of the Methodological Pendulum

The need to study individual learners in depth, as recommended above, is complemented by the need to have indications of commonalities in student thinking. Clearly the methodologies that allow in-depth study of individuals do not allow

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large-scale studies (as the resource costs are too high). Yet, an in-depth account of a learner offers limited value in informing teaching except for the teachers of that individual. The RP is built on both an assumption that learning is idiosyncratic, and an expectation that there will be sufficient commonalities to inform practice (§4.4). Sometimes the commonality may be in terms of alternative conceptions or conceptual frameworks that reflect the thinking of high proportions of learners – and these may be readily summarised to inform teaching, and can lead to enquiries into the best ways of responding to those specific ideas to move on the thinking of most students. Yet, in view of the complexity of learning and thinking, it seems clear that such direct application of research into students’ ideas to inform specific instructional approaches is likely to be the exception. However, as we better characterise students’ scientific thinking (and its development, and its interactions with teaching, etc., see below), we can hope to find higher-level commonalities – patterns in types of thinking and the evolution of scientific understanding, that inform more general pedagogic approaches in science teaching. That is, rather than cataloging ‘best teaching approaches’ on a topic-by-topic basis, the RP should lead to models which offer a repertoire of teaching approaches linked to sets of characteristics that can guide the teacher when teaching a particular topic or concept area, to a particular age group in a particular educational context. The research that would support this would need to be focused on specifics, but with a view to finding principles that, if unlikely to be ‘laws’, would certainly support the theoretical development of general teaching guidance. Such a possibility brings us full circle from Chapter 1 in some sense. In part, the constructivist programme developed from dissatisfaction with the Piagetian programme and its focus on general cognitive structures (§1.10.3). The constructivist programme moved away from the cognitive approach to a focus on concepts (§1.10.4). However, as this book has made clear, the RP that has developed has shown how the conceptual and the cognitive are inevitably linked in thinking and learning (§6.2.2). Ultimately, a full account of learning in science will offer a synthesis of considerations at both levels. Many science educators were dissatisfied with the highly general structures offered by Piaget in his stage model as a basis for exploring science learning, but whether starting from concepts or cognition, a programme that aims to explain learning well enough to inform teaching will need to coordinate understanding of conceptual structures with awareness of how they are built and applied through cognition (e.g. see Figure 6.6). Generalising from individual findings will need survey-based approaches. Surveying the frequency with which learners offer or select statements reflecting specific alternative conceptions is already common. Such surveys compromise the detail and subtlety of learners’ ideas for insight into their commonality. So, for example, instruments to diagnose alternative conceptions can offer frequencies of students choosing options, but even when the two-tier approach is used, where a factual answer and a rationale have to be selected (Treagust, 1988), these do not demonstrate the actual reasons behind students’ choices – and these may sometimes relate to contextual cues in response options rather than the scientific content itself (e.g. Griffard & Wandersee, 2001). Rather, such studies complement those

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using in-depth approaches that sacrifice any information on the generalisability of findings for a more detailed resolution of the models developed. Methods that are able to ‘survey’ for more subtle features of student thinking that may be initially identified through in-depth approaches will present more of a challenge. Nonetheless, the programme as a whole needs the iterative power of the ‘methodological pendulum’, with in-depth studies characterising the nature of complex phenomena, and survey approaches showing which features of our findings are most common (and so potentially the most fruitful targets for further in-depth studies).

7.4.1

Individual Differences – And Facilitating Expert Thinking

However, whilst generalisable results are often of utility, the RP has always encompassed a tension between the focus on the individual – that ‘nexus of interpretation coming into existence at the boundary of nature and culture’ (Longino, 1990: 221) – and on what is common across learners. Studies of individuals can of course not only provide detailed models not available from more superficial enquiry, but can also allow comparisons to be made between individuals. This has potential value in a number of ways. As different individuals experience different learning difficulties, and different ways of coming to understand scientific ideas, it is useful to inform teachers about these. It may also be valuable to make comparisons between more and less successful learners (in terms of school science achievement), as this offers useful insights into why some individuals have more success in acquiring school science. No doubt there are factors here that are beyond the teacher’s control, but there may well be some aspects, which are potentially amenable to informing pedagogy by helping learners acquire the most productive learning habits. Whether or not less successful learners would do better if they were helped to become more like successful learners, and whether indeed such changes are feasible, are research questions that deserve exploring.

7.5

Learning As a Process: The Need to Study Change

The principle that learning will be influenced (constrained, channelled) by existing conceptual structure justified the enormous research effort into uncovering learners’ ideas in science. However, finding the best ways for teachers to respond to learners’ ideas depends upon not only knowing what learners presently think, but how their ideas tend to develop (and, as discussed below, how they interact with teaching). This requires research that has a temporal component, i.e. exploring student thinking over time.

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This was acknowledged in the seminal papers that set out the RP. Gilbert and Watts (1983: 87) recognised the need for ‘a careful interpretation of successive re-enquiries into the frameworks of a particular word used by an individual over an extended period of time, e.g., several years’. Similarly, Driver and Erickson (1983: 54) acknowledged that the timescale over which substantial learning could be expected to occur would be long-term, i.e. months and years, and so recognised the need for ‘longitudinal studies of students’ scientific conceptualisations both during and after formal schooling [which] would make a useful contribution to our understanding of conceptual change’. Smith and colleagues (1993: 148) argue that ‘the central task of a constructivist theory of learning is to establish, at a fine grain of detail, how novice knowledge systems evolve into expert ones’, something that requires ‘an analytical shift from single units of knowledge to systems of knowledge with numerous elements and complex substructure that may gradually change, in bits and pieces in different ways’. As Chapter 6 has demonstrated, directed by the positive heuristic of the RP, researchers generally did tend to move on from studies of what students have learnt to studies of learning and conceptual change. Yet diSessa and colleagues (2004: 844) have argued that the diversity of studies, ‘spread somewhat thin across a wide-ranging set of domains (e.g., the shape of the earth, the effects of forces, the meaning of “alive,” the distinction between heat and temperature) and across a wide range of ages, from preschool to university students’ and the various methodological approaches to data collection, ‘clinical interviews, performance in physical or computer-implemented setups, and answers to paper-and-pencil questions’ and analysis, has limited overall progress: ‘for lack of common ground, it is possible that different results are more the result of asking different questions, in different ways, of different subjects. Indeed, there is precious little argument, let alone convincing data, that conceptual change is a homogeneous phenomenon’. The RP has available such refutable variants as ‘conceptual trajectories’ and ‘learning pathways’, with their root metaphors of learning as a journey, but – despite a sprinkling of informative studies (§6.2.2) – many student learning journeys remain as weakly illuminated as when Russell and Osborne (1993: 14) observed that ‘science education at present bears many similarities to walking through a moonlit forest – there are many obstacles and little light to be guided by. Better descriptions of the journeys undertaken by children through this dimly lit landscape will help us to provide more accurate and effective guidance to teachers and their students’.

7.5.1

The Timescale of Learning

If the timescale over which substantial learning could be expected to occur was indeed months and years (Driver & Erickson, 1983: 54), then – as Gilbert and Watts (1983: 87; cf. Bell, 1995) had suggested – there was a need for ‘successive reinquiries’ into the frameworks used by individuals over several years. By looking at individual learners in depth, and over extended time periods, the RP moves

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well beyond the ‘butterfly collecting’ stage of listing alternative conceptions. So Chi (1992: 180) suggested that ‘because it requires extensive learning about the new domain, radical conceptual change cannot be some minute event that one can capture in the laboratory during a few sessions of work’. Where a plurality of concepts is held in cognitive structure (§6.1.4.18) it is possible to use such manifold conceptual schemes to explore conceptual development. Where alternative conceptions are considered to naturally coexist as part of a mental toolkit (Taber, 1995a), then it is possible to study conceptual development in terms of the changing extent to which the alternatives are selected over time as the learner develops both the conceptual frameworks themselves, and judgements about the contexts in which they are best applied (see §6.2.2.23). Such analyses will again require in-depth case studies of individual learners.

7.5.2

Two Approaches to Studying Change in Learners’ Ideas

There are two common approaches to exploring how learners’ ideas develop over time. The cross-sectional approach samples learners of different ages or at different educational stages to compare sub-samples (Driver et al., 1994). The longitudinal approach involves data collection from the same individuals over extended periods of time. Such studies require long-term commitment, but are increasingly being represented in the Science Education literature (e.g. Ault et al., 1984; Hewson & Hennessey, 1992; Schwedes & Schmidt, 1992; Scott, 1992; Taber, 1995b, 2001c; Petri & Niedderer, 1998; Tytler, 1998; Harrison & Treagust, 2000).

7.5.3

The Nature of Cross-sectional Studies

Cross-sectional studies have the advantage of allowing a limited period of data collection, and so that the study may be completed more quickly. They suffer from the obvious disadvantage of representing the different ages or stages by different individuals, so that ‘inferences on changes within individuals are drawn from crosssectional data, although such data inform only on differences between groups’ (Arzi, 1988: 35). This means that they depend upon identifying samples that can be considered comparable. For example, a sample of school pupils and a sample of university students are unlikely to be directly comparable in a study considering how maturation or educational experience influences students’ ideas in a topic, as University students tend to be a self-selecting and competitively selected subgroup of former school pupils. (So, for example, both educational aspirations and ability to perform in formal examinations would be likely to be complicating factors in comparing the two groups.) Even where a comparison is made between different year groups in the same school, it is possible that there may be other factors that

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reduce the comparability of the groups: for example, a change in admissions policy or catchment area, or a modification of the curriculum experienced at lower grade levels. Arzi (1988: 35) has commented that ‘the major problem is cohort effects which preclude full comparability of different cross-sectional cohorts’ pointing out that some published reports ‘provide insufficient information on the extent to which their cohorts are comparable, or ignore this issue altogether’. A second related issue concerns sample size. For any differences identified between subsamples to be considered to reflect the different age/grade level, there has to be a sufficient sample size to allow the significance of such differences to be tested statistically. This type of approach is therefore only suitable for certain types of studies. The numbers involved make this approach less suitable for in-depth studies, as clearly the more informants involved, the less resource is available to collect data from each. So in-depth interviewing, as discussed above, is unlikely to be feasible. Survey approaches may use more structured interviews, but are more often carried out by written instruments. The use of statistical comparisons also depends upon characterising learners’ ideas according to objective categories (Taber, 2007a). Where in-depth studies look to model the complexity of student thinking, crosssectional comparisons need to be able to characterise student responses in ways that allow classification, and tallying-up to give frequency counts that can be fed into statistical tests.

7.5.4

The Nature of Longitudinal Studies

Longitudinal studies follow the same individuals over time. It is therefore possible to consider studying more nuanced changes in learners’ ideas, as in-depth methodology may be applied to build sophisticated models of students’ conceptual structures at different points in time. However, diSessa and Sherin (1998: 1170) have commented that ‘it is remarkable how much study of conceptual change has been simply description of before and after states, without watching in any detail how concepts work and develop, fitting such observations into theoretical patterns’. There are now some studies that take a more fine-grained approach (e.g. Petri & Niedderer, 1998; Harrison & Treagust, 2000; Taber, 2001c), and which begin to reflect studies of microgenetic change where (Opfer & Siegler, 2004): • Observations span the period during which rapid change in the particular competence occurs. • The density of observations within this period is high, relative to the rate of change of the phenomenon. • Observations are subjected to intensive trial-by-trial analysis, with the goal of inferring the processes that give rise to the change. This provides the potential to study actual changes in learners (Arzi, 1988), rather than average differences between groups, and does not (unlike cross-sectional

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studies) limit considerations to gross features that can be readily characterised to allow ease of identification and statistical testing. Longitudinal studies offer the obvious advantage of not needing large samples and statistics, as changes can be observed rather than being inferred from differences between separate groups of individuals. However, longitudinal studies also have their costs and limitations. The obvious one is that data collection may need to take place over periods of years (something not encouraged by the pressures on researchers to produce results and publications quickly). A complication here is the possibility of dropout. There is always the potential for informants to decide to leave studies – something particularly likely in in-depth studies where data-collection sessions may be long, intense and even potentially disheartening (Taber, 2002c). Students being followed may change their attitude to taking part in a project as they get older (perhaps becoming more concerned about peer-group perceptions, for example) or may move away from an area, change schools, etc. Although large samples with matched grouping are not needed for comparisons (as actual changes in the thinking of individuals can be followed), there is also a question of the extent to which small numbers of informants may be in some way representative of the wider population from which they are drawn (many of whom may decline involvement in such research). Within an individual idiographic study, this is not an issue, as the focus is on the inherent value of the individual case. However, within the wider context of the RP, as suggested above, the value of studying individual cases is to find patterns that may be common enough to inform pedagogy. Thus, the argument above about the use of the ‘methodological pendulum’ in an iterative process to test out the generality of findings from idiographic studies.

7.5.4.1

The Effects of Our Observations

Another key issue that arises with such longitudinal studies is the influence of the research itself. Bell (1995: p. 353) points out that if interviewing is undertaken to explore students’ thinking, then it is not appropriate for the interviewer to ‘teach’, as ‘the interview is a teaching situation only in that we are listening to the student; it is not an opportunity to guide students by careful questioning to the “right answer” ’. Despite such admonishments, learning is influenced by experiences, and any experience that causes a student to think about and reflect upon their learning will influence it. This is particularly the case when sequences of questions are used to probe away at a learner’s understanding: the typical nature of semi-structured interviews. Even though a researcher may consider themselves to be learning (about the students’ thinking) rather than teaching, such sequences of questions often have a very similar character to the approaches to questioning teachers’ use when developing common understanding in a class (Edwards & Mercer, 1987). That is, such questioning may be akin to the Platonic teaching method (§1.5), and guide the learner to constructing new knowledge (Mercer, 1995).

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This suggests that even though longitudinal studies may be needed to identify actual changes in students’ thinking, they may also direct the path of such changes away from the course they would have otherwise taken: for example, acting to ‘accelerate’ learning (Taber, 2002c). This does not negate their value as studies of learning, but may make them atypical of the rate and character of learning of students in classes not experiencing such intense and individualized questioning.

7.5.4.2

Analysing the Data

It was suggested above that interrogating interview data requires careful analytical techniques, and that in some circumstances a form of ‘analytical pluralism’ may be called for (Taber, 2008c). Tyson, Venville, Harrison and Treagust (1997: 399) have discussed the different perspectives from which conceptual change can be considered, and have argued for the needs for a ‘multidimensional framework’ with distinct ‘lenses’, • The ontological lens of the multidimensional framework of conceptual change examines the way a student perceives the nature of the thing being studied; that is, the student looking ‘out’ at the world. • The epistemological lens examines how the student perceives her or his own knowledge about the thing being studied; that is, the student is looking ‘in’ at their own knowledge. • The social/affective lens examines the social/affective conditions necessary for conceptual change to occur. Tyson and colleagues comment that most studies only consider one of these aspects, and so offer only a partial account of conceptual change.

7.5.5

Complementarity

Again, there is something of an indeterminacy principle at work here: if we observe the thinking of different individuals at different times, then we are more likely to find typicality among our sample (both because of the influence of the probing, and because learners prepared to be investigated closely over time may be in a minority) but can have no direct knowledge of conceptual trajectories – whereas if we follow individuals over time to ensure that we are actually tracking changes in thinking, we can never know the extent to which our own investigations have influenced those changes. The analogy with quantum mechanics is not to be taken too seriously, but we do have a parallel situation in terms of the effects of our observations. The choice of what to observe (cf. position/momentum) determines methodology that excludes us from either knowledge of individual changes or from knowledge of thinking that was not influenced by earlier observations.

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Teaching As Facilitation of Learning

345

Whilst student thinking certainly exists in some form before our questioning, the use of specific probes and questions will surely sometimes lead somewhat diffuse and unfocused student thinking in particular directions. It would be pushing the analogy too far to see this as being like the collapse of a quantum state, but another scientific metaphor may be appropriate: our questioning can certainly lead to a ‘crystallisation’ of student thinking that may not have happened, or at least not at that point in time, or perhaps not quite in that form, without our input. As Smith and colleagues (1993: 154) have recommended, what is needed is not only (a) ‘research that focuses on the evolution of expert understandings in specific conceptual domains and builds on and explains the existing empirical record of students’ conceptions … detailed descriptions of the evolution of knowledge systems over much longer durations than has been typical of recent detailed studies’ that can lead to ‘explicit theoretical frameworks of knowledge systems’ but also (b) ‘studies that evaluate the generality of those models’.

7.5.6

The Conceptual Ecology: The Need to Study Learning in Its Mental Context

One of the strongest arguments for studying learners’ ideas in depth is the complexity of the learning process. Even restricting consideration (for the moment, see below) to what might be termed the ‘internal’ context of learning with an individual’s mind (the central region of Fig. 7.1) involves a very complex system. In Chapter 6 (§6.2.2.24), the notion of the conceptual ecology was introduced. This model, based on the analogy between conceptual change and natural selection, suggests that the development of a concept within an individual’s mind is influenced by a wide range of factors, relating to both features of cognitive structure and various meta-conceptual issues (such as ontological and epistemological commitments and metacognitive stances). Studies of learning that explore how learners’ ideas develop should therefore seek to describe the conceptual ecology within which a particular concept exists and evolves. This by itself, of course, still ignores the wider social and cultural contexts, and beyond (cf. Fig. 7.1).

7.6

Teaching As Facilitation of Learning: The Need to Study Learning in Classroom Contexts

The rationale for the RP within education is to inform pedagogy, and thus the central importance of the general research question: ‘how do learners’ ideas interact with teaching?’ (§4.4). Driver and Erickson (1983: 50) argued that ‘naturalistic classroom studies are necessary and important in determining the nature of the interactions between student frameworks and various types of instructional

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practices and in identifying some of the constraints which must be considered in designing more formal instructional techniques and models’. As was suggested in Chapter 6, most research into learners’ ideas has explored individuals in relative isolation. However, if a key interest is to find out how teaching influences learning, then studies are needed which are able to characterise the teaching context alongside learning. That is, to include the second most central region of the learning environment shown in Fig. 7.1. Such studies are necessarily more demanding, as they require suitable methodologies to collect data about the classroom (or other teaching–learning context) alongside investigation of the learners’ thinking. Ultimately the aim is to link changes in conceptual structure to features of the instructional context. This is clearly a difficult task given that learning processes are influenced by such a wide range of factors. What is clear is that it is seldom going to be possible to characterise teaching in terms of simple variables that directly lead to specific changes in student understanding and thinking. Again, progress probably depends upon the coordination of in-depth studies that offer ‘thick-descriptions’ of both teaching context and conceptual change to provide models of how teaching influences learning on an individual scale, and correlational studies that attempt to test out the statistical associations between teaching approaches and learning outcomes on the larger scale. As suggested above, one type of the study offers us the resolution to conjecture important causal relationships between teaching and learning, but on an individual scale: the other approach can test out the generality of relationships without offering the same forms of insight into mechanisms. Progress in developing our understanding requires both the model building and testing stages.

7.6.1

Communities of Practice: The Need to Study Learning in Its Social Context

Teaching can be a 1:1 process, but in formal science education (certainly below postgraduate level), most teaching and learning takes place in groups. This adds further complexity, as the individual learner’s thinking is not only influenced by the teacher’s words and actions, but by the way these are received, interpreted, and responded to within the class. The amount of student-student interaction encouraged in class varies considerably. At one time ‘good’ teaching was often considered to mean the students listened to the teacher, only spoke when invited, and that interstudent discussion was to be eliminated or minimalised: a form of instruction that makes good sense from the perspective of the transfer model of teaching and learning (§4.6), where the transmitter should be transmitting and the receiver receiving only from the authorised transmitter. Science was perhaps one of the earlier academic subjects to invite interaction, if this was often limited to the pragmatic needs of carrying out practical work in groups. Yet even in a classroom where discussion between students might be excluded there is still potential for learners to talk about their work outside of the class – for example, asking each other for help with homework. In this way one student’s take on a topic would influence another.

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Natural Experiments: The Need to Compare Across Educational Contexts

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Modern classrooms, at least in many educational contexts, are no longer modelled on the basis that it is the expert who should do all the talking, and the learners who should only listen. Considering learning as a process of active construction of knowledge fits better with learning based on activities that give students opportunities to explore and develop their ideas. Discussion and group work often feature, with ‘working together’ more likely to be seen as a prerequisite for an effective classroom rather than a sign of lax discipline and/or failing students. In this perspective there needs to be some shift in the ‘unit of analysis’ of learning. Some constructionists (§5.4.2) would consider that knowledge is created and exists interpersonally, and so the group becomes the appropriate focus of attention. The position taken earlier in the book was that the perspective that it is only sensible to talk of knowledge and knowledge construction on the social plane is excluded by the negative heuristic of the RP that treats personal knowing as a hard-core commitment. However, even when a personal constructivist view is privileged, it is clear that classroom interactions about subject matter will be part of the ‘input’ influencing learning, and that this includes the learner’s interactions both with the teacher and with other students.

7.7

Natural Experiments: The Need to Compare Across Educational Contexts

We have seen that the RP is concerned to identify and untangle the different influences that collectively channel student thinking in science so as to inform pedagogy. It is suggested in this volume that the current state of our knowledge suggests we now need a strong focus on in-depth explorations, over time, that can illuminate individual cases (students, classes) to build models, which can be tested by more ‘experimental’ or survey approaches. Yet it is also clear that the complexity of the subject matter of our research makes controlled experiments very difficult (on both practical and ethical grounds). Whilst it is certainly feasible to set up studies that attempt to test out teaching approaches and innovations, whilst controlling for potential complicating factors as far as is possible, this is always going to be challenging (see the discussion in Chapter 2). The basis of controlled experiments is to make comparisons ceteris paribus, and of course in educational contexts, all else is seldom even close to being equal. Furthermore, our enquiries change the very things that we are enquiring into. For example, any ‘experiment’ that uses an approach that is atypical in a particular educational context is likely to arouse students’ interest because of its novelty value. Gains made under experimental conditions may not be maintained once the approach becomes familiar. There is also the opposite problem if the approach requires learners to behave in ways that are uncomfortable either because of lack of skills and experience, or because the approach does not fit their expectations of how students are meant to behave in classrooms (e.g. keeping quiet and still during lessons). Attempts to run controlled experiments also raise the possibility of expectancy effects, where if the teacher expects a novel approach to be effective

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this communicates (even if totally unintentionally) expectations to which students are likely to respond (Rosenthal & Jacobson, 1970). In medical studies, techniques are developed for double-blind trials, but it is not so easy to change teaching without teachers and students spotting whether they are in the ‘treatment’ group or not. Given the problems of such approaches, there is much to be learnt in principle by comparing across contexts that already exist and may offer useful clues. In particular, contexts with different educational traditions and expectations. Wandersee, Mintzes & Novak (1994: 186) note that whereas ‘studies that compare populations across advanced Western countries seem to find few differences of statistical significance … studies that search for [sic] differences in substantially divergent cultures often find an “overlay” of traditional views that are quite distinct from explanations offered by contemporary science’. This suggests there is considerable potential for learning from the ‘natural experiments’ of different educational contexts – that is, taking into account the cultural level of environment in Fig. 7.1. Mueller and Bentley (2007), in arguing for plurality in Science Education, have compared science classrooms to the ‘decorated landscapes’ that zoos sometimes use to make animal enclosures have something of the character of the creature’s natural environment. These decorated landscapes are poor facsimiles for the natural habitat, and the school or college science laboratory is itself only a representation of the context in which science is carried out, and of course like the prescribed curriculum, represents a particular image of science (cf. Millar, 1989b). Mueller and Bentley suggest that these decorated landscapes reflect something of the wider values of a society, and that, for example, the focus on ‘high-stakes testing’ in some educational contexts (the USA and the UK would be examples) offers an experience of learning about science very much coloured by that emphasis. However, studies that seek to elicit student thinking on a topic and at an age that has previously been well described, but in a novel educational context, do not automatically make a significant new contribution (Taber, 2008b). They may be judged as purely replication studies, unless they report significant new examples of student thinking (e.g. Cakici, 2005), or survey conceptions as part of a more ambitious study, such as being the initial phase of an intervention project (e.g. Chiu, 2007). From the perspective of the RP, such studies are only considered significant if they are directed towards progressing the programme by offering something that is theoretically or empirically novel. So, for researchers wishing to describe students’ thinking about topics in a particular local population, there is a good chance that the results may well appear to journal editors and referees as just ‘more of the same’ unless findings can be linked to specified aspects of the educational context in ways that offer more general significance. Researchers interested in students’ ideas in science should explore the extent to which findings reported in the literature can be ‘replicated’ among learners in different educational contexts, but in ways that further the RP. Populations need to be characterised in terms of certain relevant factors that allow them to be compared with other populations with different characteristics. Such an approach can never ‘control’ for all possibly relevant variables, but it could – nonetheless – offer comparisons that may suggest very useful insights.

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Natural Experiments: The Need to Compare Across Educational Contexts

7.7.1

349

Surveying Populations in Diverse Educational Contexts

We would expect similarities and differences in different educational contexts, in features such as the frequencies of alternative conceptions elicited from learners, to reflect the relative significance of such contextual variables as, inter alia, contingent factors in the development of those conceptions. If similar frequencies of common alternative conceptions are found in different contexts, then it may be that the conceptions tend to develop regardless of these contextual factors (language, cultural beliefs, educational practices) or that although cultural factors play a significant role, the two educational contexts are substantially similar in terms of the particular significant contextual factors at work. Where very different frequencies of conceptions are found among ‘comparable’ populations in different contexts (e.g. students of the same age, having been exposed to teaching that seems to be directed to similar target knowledge) then there would seem to be a prima facie case for considering contextual factors as a significant influence, and so for looking to identify likely ‘causes’ for the different outcomes in the different educational contexts. However, it is not possible for such comparisons to offer more than interesting possibilities as the lack of ‘controls’ can lead to conclusions that are ‘false positives’ or ‘false negatives’ (as Table 7.1 suggests). Comparisons between different educational contexts provide a particular challenge for those attempting to build explanations for the patterns in student thinking and learning because the data that can be collected in any particular comparison is always likely to clearly underdetermine any particular conclusions because of the wide range of potentially relevant variables that could be at work. However, as was discussed in Chapter 2, the available facts always underdetermine scientific conclusions, and in practice data are always interpreted in terms of theoretical considerations. For a RP to remain progressive there needs to be interplay between new theoretical developments and empirical work. Isolated comparisons between educational contexts can only offer limited insights, but when interpreted in terms of Table 7.1 Conditions for expecting different frequencies of common conceptions among students in distinct populations Educational context not a Educational context significant factor in evolution significant in evolution of of particular conception particular conception Two educational contexts similar in terms of potentially relevant contextual factors Two educational contexts dissimilar in terms of potentially relevant contextual factors

Incidence of conception likely to be similar among populations studying in the different contexts Incidence of conception likely to be similar among populations studying in the different contexts

Incidence of conception likely to be similar among populations studying in the different contexts Incidence of conception likely to be different among populations studying in the different contexts

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current theory (variants within the protective belt of theory in the programme) they can contribute to developing models, which in turn can indicate potentially useful comparisons for future studies to test out predictions. So one study can only highlight some difference in student learning and suggest (in the light of existing theoretical notions) which features of the difference in context seem likely to be significant factors in producing the observed differences. This in itself is still quite speculative, but allows researchers to predict other useful comparisons where the same effect should, and should not, be found. This then offers guidance on the most promising directions for further research. This reflects the post-positivist notion of how science progresses that was discussed in the early chapters of the book. Cross-cultural studies that use common methodology to explore student thinking (rather than focusing on attainment or attitudes to science – see Guo, 2007), in different contexts (e.g. Shipstone et al., 1988; Tan et al., 2007), and which find similar frequencies of common alternative conceptions across a range of contexts (e.g. different cultural groups, different languages of instruction, different school systems) begin to suggest that the development of these conceptions may be strongly influenced by factors outside of teaching approaches – that is, in the aspects of the learning environment represented by the outermost two regions in Fig. 7.1. This only follows, of course (cf. Table 7.1), to the extent that the educational contexts where we find similarities in thinking are significantly divergent in terms of cultural norms, language of instruction, teaching models used, curriculum sequencing, teaching approaches, etc. As always, researchers never know for sure which factors are significant, and which may be ignored, as this is what the research is intended to find out. However, building and testing models from those insights such studies offer, can at least allow us to iteratively make progress in terms of the empirical and theoretical content of our programme (i.e. we develop more sophisticated models that are supported by an increasing body of empirical evidence). Studies that find features of student thinking that seem to be significantly more common in specific contexts offer hints (conjectures for later testing) at how cultural, linguistic or institutional factors may influence the development of scientific thinking (e.g. Cokelez et al., 2008). All of this information, however tentative, may be useful in building up an understanding of how science is learnt that can inform teaching. Studies that are able to identify specific institutional features relating to the curriculum models used, the sequencing of instruction (within science, and in terms of other school subjects and age-related development), common teaching models and analogies, etc. may lead to more specific hypotheses that can be more directly tested (see below). However, differences between populations can only be considered significant where surveys are based upon (Taber, 2008b): • Methodology that is comparable • Sampling methods that can be considered to give representative findings These are not trivial concerns. For example, Kuiper (1994) failed to replicate Watts’ (1983) reported student alternative conceptions for force when surveying populations from cultural contexts different from that where Watts undertook his original

7.8

Bringing It All Together: A Progressive Methodological Pendulum?

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research. However, the methodology used in the two studies was (in a case where Kuhn’s term seems a fair description) incommensurable, so that very little can be read into the ‘lack of replication’ of the original findings (see §5.3.5, and Taber, 2007a for a more detailed consideration of this example). Even when attempts are made to carefully replicate the original methods, there may be complications. For example, if research instruments have to be translated into a local language, there is immediately a problem as translation inevitably modifies meaning and emphasis to some extent.

7.7.2

Sampling a Population

A study that explicitly discusses a sample implies there is some particular (defined) population being sampled, so we would expect any such study to offer a clear account of what is meant by the population being sampled in that study. Research that replicates previous studies in distinct populations can only make significant original contributions to the field, when research reports offer a clear description of the population being studied. If such surveys are to contribute to a developing understanding of how features of educational context influence student thinking then researchers must be able to clearly define the population sampled; provide ‘thick description’ (Geertz, 1973) of the educational context in which the population studies; and provide assurance that the sampling methods used if not technically rigorous are at least suitably robust. Descriptions of survey samples limited to very general information about student ages and geographical location will be inadequate to support the production of original knowledge that can be considered to make significant contributions to the RP.

7.8

Bringing It All Together: A Progressive Methodological Pendulum?

The themes running through this chapter have highlighted the limitations as well as the strengths of the different approaches that research in this field can take. However, it has also been suggested that whilst individual studies inevitably have weaknesses, the RP can still move forward by a suitable coordination of different approaches. So longitudinal and cross-sectional studies have complementary strengths when exploring changes in student thinking. Surveys have limited resolution and are only useful once clear operational definitions are available to guide design of closed response categories. Yet in-depth studies suitable for offering thick-description lack generalisation. However, coordination of the two approaches can allow progress to be made in developing detailed models that have been tested within defined populations of learners. Individual researchers or groups may be more comfortable and

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competent in particular approaches, but by valuing and learning from other workers taking complementary approaches it is possible to collectively progress our RP. So it seems clear that there will be some degree of iterative work needed to move the state of knowledge about learning in science on. For example, decisions about which aspects of an educational context are salient and worth reporting, and so how to demarcate what is to be considered an identifiable population for these purposes are necessarily underdetermined. To design effective studies, we need to be able to take into account the very things the studies are meant to be finding out. Initially a good deal of informed guesswork may be needed. However, over time, the indications from studies designed to best meet these criteria should offer increasingly sophisticated guidance on how to operationalise these requirements. These different approaches might traditionally be considered quite incommensurable (drawing upon interpretative and ‘positivist’ paradigms (§2.6), and on ‘action research’ approaches). However, within a post-positivist model of scientific research in education (§2.5.3) these different approaches can collectively contribute to the same overall RP. The ontological status of what is studied may vary between studies, and so also the kind of knowledge possible from the different methodologies that are applied. Thick-description of individuals allows different kind of knowledge about learners’ ideas and thinking from frequency counts representative of defined populations of learners. What is important within an educational RP is not that these matters need to be consistent across studies, but that researchers are clear about the kind of entities studied in particular studies, and the types of knowledge possible from the methodology utilised. In this way researchers avoid the ‘either/or’ mentality (§2.6) that can lead them to dismiss other types of work as invalid, but instead appreciate the strengths and limitations of work undertaken in a different methodological tradition to their own – and so understand how to interpret it to inform their own work. Those reporting research can support this process by being explicit about the status and nature of their knowledge claims – something that has not always been the case in the past (§5.3).

7.8.1

Testing Out Pedagogic Approaches

Whilst survey approaches can indicate how common or isolated gross features of student thinking identified from in-depth studies may be, and ‘natural experiments’ can offer insights into potential factors that are particularly significant for aspects of learning, these approaches can only inform pedagogy by looking for patterns and correlations. This leads to hypotheses about how to most effectively teach science. In the physical sciences such hypotheses would be tested by controlled experiments, but we have seen how such control is seldom available in educational research. Despite this restraint, it is clear that before pedagogic advice is widely disseminated, or introduced into formal aspects of teacher education or into official

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guidance issued to teachers by governments or educational authorities, ideas deriving from research need to be tested in realistic teaching contexts. Driver and Erickson (1983: 54) called for ‘more classroom intervention studies … guided by perspectives on learning that take account of the learner’s ideas while studying the effectiveness of various strategies aimed at promoting conceptual change’. Whilst controlled experiments are generally an unrealistic ideal, it is still possible to test out new approaches in realistic contexts, e.g. in curriculum projects (Driver & Oldham, 1986), ‘lesson-study’ (Allen et al., 2004) or ‘design experiments’ (Brown, 1992). These approaches will themselves be informed by more naturalistic studies, and may be evaluated as in-depth case studies. Approaches that show promise may then be worth scaling-up for wider implementation, potentially to be evaluated as quasi-experiments comparing learning outcomes across ‘treatment’ and ‘control’ conditions, having demonstrated that what they potentially offer justifies investment in trying to overcome the problems of ‘fair testing’ in educational contexts. Overall, then, studies that can contribute to the RP vary along two particularly important dimensions (see Fig. 7.2). Studies may be highly naturalistic, such as case studies of individual learners or classes that set out to describe and understand rather than change (and bearing in mind that the observer inevitably has some effect on the research site), or surveys that look to identify the frequency that students exhibit particular features. The focus here shifts from the individual learner or group or class or lesson, to samples that can represent much more general, specified, populations. Other studies may involve deliberate intervention, with teaching approaches introduced that would not have been adopted without the research frame. Again these studies may vary considerably in terms of scale, from one teacher trying out an idea in a single lesson, which is documented in some depth, up to (ultimately) the evaluation of the implementation of a new approach across an entire national educational system.

Fig. 7.2 Dimensions of research studies: Degree of intervention; scale

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in-depth studies of individual learners offer 'thick description' and insights into - the complexity of learners' ideas (stability of ideas, manifold conceptions, commitment to ideas etc) -conceptual change

complement & inform

may not be representative of 'typical' learners

surveys of well-defined populations, in well-documented contexts offer posibility of comparisons between contexts, and so insights into the influence of cultural, linguistic and institutional factors underdetermined: may not be able to identify the most salient factors responsible for any differences

offer testable hypotheses for effective teaching

studies that test innovative instructional approaches, teaching materials, curriculum sequencing and pacing, teaching models, etc. always tied to specific contexts, and suffer from expectancy effects. may be scaled up for large-scale trialling and implementation where indicated

Fig. 7.3 Different strands of research contributing to an overall research programme

What should be clear from the discussion of the RP here, is that these different studies should not be seen as a hierarchy, but rather as complementary approaches that are most useful at different stages of developing an understanding of pedagogy (§7.4). There is clearly a flow from naturalistic to more experimental work, just as there is in the tendency to scale-up on the basis of the most interesting findings from small-scale studies. However, a key message that arises from considering all that has gone before in this book is that progress within the PR will surely need the careful coordination of a range of different types of empirical study.

7.8.2

Interdisciplinary Research: Drawing upon Insights from Cognate Areas

Some of the work discussed in Chapter 6 was not undertaken by mainstream Science Education researchers, and might be considered to be out of place in an account of an educational RP. However, as Duschl & Hamilton (1992: 7) have pointed out (§1.4), Science Education can be considered to be part of a wider

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Constructivism, Contingency and the Progressive Research Programme

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domain of inquiry that ‘seeks to understand the dynamics of the growth of scientific knowledge’. The Lakatosian analysis, identifying the hard core and positive heuristic of the RP, provides a sound basis for judging whether different strands of research, perhaps seeming to be based on very different fundamental assumptions, fit within the RP. Studies consistent with the hard core (whether explicitly adopting them or not) and offering enquiries aligned with the positive heuristic, seem ‘fair game’ for including in any account of the programme. (I direct readers who do not approve of this liberty to the postscript). A number of commentators have suggested that students’ alternative conceptions sometimes reflect historical episodes in science, and studies into the history of science may offer one useful source of ideas and insights (Steinberg et al., 1990): although it is important not to equate the thinking of young school learners with that of experienced mature scientists working at a time when the science itself was less mature. Novak (1993: 167), for example, has commented how ‘the process of meaningful learning, as understood through assimilation theory, is fundamental to both the psychological process of cognitive development of individuals and the epistemological process of new knowledge construction’. Other fields from within the ‘domain’ certainly offer potential for informing further research into learning in science, especially as work in neuroscience and other areas of cognitive science offer increasingly detailed models of cognition. At a time when interdisciplinary work within the natural sciences seems more important than ever (to explore such issues as climate change, for example), it is clear that there is often much to be gained from working in multi-disciplinary teams, with colleagues who can contribute new perspectives and challenge our assumptions (cf. ThayerBacon, 2003).

7.9

Constructivism, Contingency and the Progressive Research Programme

The view strongly offered in this volume is that what has been described as the ‘constructivist’ programme in Science Education has helped to structure useful directions for research, which has resulted in an increasingly complex, but therefore probably increasingly accurate, picture of the nature of students’ thinking in science, and how it can be developed towards target knowledge set out in a science curriculum. It is ironic that in some of the countries most associated with the early pioneering work within the ‘movement’ constructivism may be seen as somewhat passé (Solomon, 1994) as its brave conjectures have come to be seen as commonplace and rather obvious (and so taken for granted); whilst in other countries where more ‘traditional’ approaches to science teaching remain the norm, teachers are being strongly encouraged to see the value of such ‘reforming’ perspectives as constructivism. I have suggested that the constructivist label may work against the future success of this RP and that an alternative descriptor might be ‘contingency’ (Taber, 2006b).

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Learning science is contingent on many factors: the available prerequisite knowledge (and its match with accepted science); various perceptual/cognitive biases in the learner’s cognitive system; the limitations of cognitive processing (e.g. working memory); features of the language of instruction; the pedagogic subject knowledge and scaffolding skills of the teacher; the social milieu in the classroom; and so much more. As is clear from Chapter 6, the initial focus of the RP on learners’ ideas (thus, the alternative label for the RP as the ‘alternative conceptions movement’) has broadened to consider the role of various contingencies influencing the learning of science: on existing learning, on the stability and coherence of existing representations, on the character and limitations of the cognitive apparatus, on the context and conditions of learning, etc. The RP may now better be understood as exploring the nature and relative importance and interactions of these various contingencies in learning science, and how they relate to aspects of the subject material to be learnt. If the Science Education community were to choose to acknowledge this ‘new’ ‘Contingent Learning and Science Teaching’ RP, then this would not indicate some paradigm-shift to a new orthodoxy that will usurp ‘constructivism’ as the key referent for Science Education research. Rather, from a Lakatosian perspective, this would actually demonstrate the success of constructivism, in showing how its hard core has given rise to a positive heuristic capable of promoting and evolving to a more inclusive understanding of the field. This type of ‘problem-shift’ through ‘a developing series of theories’ is what Lakatos suggests should characterise a progressive programme (Lakatos & Zahar, 1976/1978: 178). The constructivist RP into learning science was in effect set out over a period of a few years (I have suggested 1978–1983), and since then there has been an ongoing development of our understanding of learning and teaching in science. The hard core of the constructivist programme has done a great deal to allow Science Education to become a recognised field of scholarship and research in its own right, and its axiomatic principles continue to form part of the (often implicit) set of assumptions underpinning much research into learning and teaching in science. Whether or not we feel the RP has outgrown its constructivist label, it has achieved a good deal, and continues to suggest potentially fruitful directions for further research. There is still much work to be done in developing a synthesis that includes all the various contingencies that influence science learning within an overarching theoretical system. This is the main challenge if we wish to continue to progress Science Education.

Final Thoughts: Is There Really a RP, and Does It Matter?

This book has been about the progressive research programme (RP) into learning science. A key argument is that a good deal of research undertaken in Science Education over several decades can profitably be considered as a RP in the sense of Lakatos (1970). It is further suggested that this is a progressive programme, and so one that educational researchers can rationally associate themselves with. Throughout this book project I have been aware that this could be seen as purely an academic exercise, one of showing that by careful selection of material it is possible to demonstrate that much Science Education research can be shown to fit a Lakatosian model. It is certainly true that some of the research I would see as fitting within the RP would not be considered part of the RP (at least not this one that I have characterised) by the researchers concerned. Some, but not all, of the researchers might accept the ‘constructivist’ label: but that in itself offers little guarantee that the individuals concerned would all feel that they are part of the same common enterprise! Some of the material I would happily assign to ‘this’ RP would almost certainly be seen by its originators as being parts of continuing traditions of work that are alternatives to, and even prior to, the ‘constructivist’ bandwagon. This leads me to finish the book by facing the questions of (a) whether there really is something that can be considered as a RP, and (b) whether there is any validity in seeking heuristic guidance from a programme that may only exist as one characterisation of a field: that is, the public representation of one commentator’s mental model of an aspect of the world – and so perhaps an account that others might consider an alternative conceptual framework! It may be possible to apply Lakatosian methodology of SRP to this body of work, but if that is only an external or idiosyncratic exercise then should it be taken as anything more than a demonstration that a Lakatosian analysis is possible?

Does the Programme Exist? I hope I have been clear throughout the volume that the book was about producing, and learning from, a model of research in Science Education based on Lakatos’s notion of science proceeding through RP. So at one level my claim is that we can K.S. Taber, Progressing Science Education, Science & Technology Education Library 37, © Springer Science + Business Media B.V. 2009

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Final Thoughts: Is There Really a RP, and Does It Matter?

‘see’ this research in these terms, and that indeed it may make sense to do so. This is a weaker claim than arguing that there ‘is’ a RP, and that this book offers the definitive description of the programme. Having taken the time to develop this analysis, first outlined in Foundations of Chemistry (as a means of offering a defence against criticisms of constructivism in Science Education, the focus of Chapter 5 here) and in Studies in Science Education (where I turned to the positive heuristic, the focus of Chapter 6), and then expanded in the present volume, my own view is that there ‘is’ a RP in Science Education based in the work that became identified as the ‘alternative conceptions movement’ and ‘constructivism in science education’. Whilst I would accept that others may quibble over details, it seems fairly clear to me that around 1978–1983 a series of much-cited papers set out the basis for such a programme, including its hard core and heuristic guidance for researchers to follow. This is in essence the model that forms the core chapter of the book: Chapter 4. Whether the key players – Driver, Gilbert, Osborne, Watts, etc. – used the term ‘research programme’ or saw research in Lakatosian terms is not relevant to this claim – although, of course, Gilbert and Swift (1985) certainly explored this perspective. There is little doubt that the seminal corpus re-focused ongoing research approaches in a particular and highly influential way. So, I would strongly argue that this RP is a meaningful representation of much research and not just an idiosyncratic and personal view of the literature.

Has the RP Been Correctly Delineated? Whilst I feel this position is very secure, I am aware that there is potential for much more debate about some of the studies I have considered part of the RP when evaluating its achievements and status as a RP. This relates to a question of who is to decide whether a research study should be considered to fall within a particular RP or not. In some cases this is an easy decision. Some studies describe themselves as part of the Alternative Conceptions Movement or as constructivist, and support this with clear reference to the language and concepts used in the seminal papers, and cite these studies as authorities in their own conceptualisation. However, my own analysis would also include papers that did not include such indicators, where my reading of the conceptual framework offered in a paper aligns it with the hard-core assumptions of the RP (as outlined in Chapter 4). My assumption is that adopting hard-core assumptions, whether explicitly or not, is the key demarcation criterion to be used in making such a judgement. A study aligned with the hard-core assumptions will logically be influenced by the programme’s heuristics, inherently if not necessarily explicitly. Such an approach could seem to be inappropriate (perhaps ‘cheating’ or a sign of desperation) from a Kuhnian perspective that prioritises the paradigm in terms of a community of practice. However, the basis of Lakatosian methodology is not social linkages (such as mentor–student relationships) but the commitments that

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inform research, and in particular a programme’s hard core. Of course, few studies explicitly spell out all the hard-core assumptions identified in Chapter 4, so there is room for discussion over which papers should ‘really’ be considered to ‘belong’ in the RP in these terms. Such discussion, if carried out within the spirit of Lakatosian methodology, could only help strengthen and clarify our understanding of the RP. However, it is important to make the point that demarcation of the RP in this way is not inherently useful for dichotomising individual studies (as ‘in’ or ‘out’), but only has value to the extent that such classifications allow us to judge progress in, and so direct future research within, a RP.

Does It Matter if Judgements About the RP Are Disputed? So in this volume I have argued (in Chapter 6) that the RP has made significant if uneven progress, and should be considered progressive. Further, in Chapter 7, the current state of understanding in the RP is used to offer suggestions for the most useful directions for further research. The positions outlined in these chapters depend upon one reading of the literature and consequent judgements about studies. Decisions about whether a particular published study is informed by the hard core of the programme (sufficiently to be seen as being part of the programme) and contributes to the development of the protective belt, collectively inform my own judgements about promising directions for future research. In writing this book I hope that my views will influence others, especially new researchers to Science Education looking for important and fertile problem areas. I would obviously welcome further scholarship that would reinforce or dispute my analysis – as increased understanding of the programme can only clarify the heuristic guidance to researchers over what areas to explore, and how to take work forward to maintain a progressive programme of research. Ultimately, my main concerns in setting out on this analysis were to demonstrate that there is (still) a progressive RP into learning science, and by offering a model of what this is, and ‘where it is at’, to encourage others to be informed by the positive heuristic of the programme. In this way I hope to contribute in some way to maintaining the progressive status of the programme: for, as is clear from the book, although much has been achieved, there is much more useful work to do.

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Name Index

A Abimbola, I.O., 186 Adbo, K., 225 Adey, P., 47, 307 Aikenhead, G.S., 17, 35, 234, 240, 316 Al-Kunifed, A., 333 Alice, 244 Allen, D., 353 Alsop, S., 332 Anderson, C.W., 229 Anderson, D.S., 76 Andersson, B., 269, 271 Annie, 229, 260 Apple, M.W., 24 Arlin, P.K., 33 Arzi, H.J., 229, 266, 341, 342 Ashby, J., 333 Asoko, H.M., 199, 300, 311 Ault, C.R., 117, 136, 138, 278, 279, 281, 301, 341 Ausubel, D.P., 44, 126, 132–134, 137, 203, 228, 300, 312

B Bachelard, G., 294 Baddeley, A., 38, 139, 264 Bannister, D., 32 Beard, R.M., 26, 281 Beattie, G., 36 Becker, H.J., 312 Bednarz, N., 194 Beld, J.M., 163 Bell, B., 118, 126, 160, 206, 224, 306, 314, 322, 340, 343 Bentley, D., 68 Bentley, M.L., 52, 348 Bereiter, C., 195, 198 Berkeley, G., 54

Berkes, F., 68, 156, 157 Bickhard, M.H., 163 Biddle, B.J., 76 Biesta, G.J.J., 58, 90, 151, 277 Birley, G., 240 Black, P.J., 13, 186, 221 Bliss, J., 26, 240 Bodner, G.M., 26, 28, 126, 137, 138, 165, 167, 169, 172, 245, 307 Bourdieu, P., 236 Bowers, C.A., 28, 37, 148–156, 158–160, 178, 179, 203, 235 Brass, K., 165 Briggs, H., 118 Briggs, L.J., 137 Brock, R., 235, 300 Brook, A., 118, 224, 307 Brown, A.L., 353 Brown, D.E., 257 Brown, G., 26, 45, 335 Bruner, J.S., 45, 46, 89, 134, 264, 308, 310 Bunce, D.M., 243 Burbules, N.C., 54, 58, 70, 77, 78, 90, 151, 277 Butts, B., 260

C Cakici, Y., 348 Camacho, F.F., 255, 256 Cañal, P., 224 Carlton, K., 181 Carmichael, P., 117, 223 Carr, M., 245 Carr, W., 76 Carraher, T.N., 45 Cazares, L.G., 255, 256 Cerini, B., 207 Chalmers, A.F., 220 Champagne, A., 335

385

386 Chi, M.T.H., 279, 280, 282, 291, 293, 299, 308, 309, 312, 330, 341 Child, D., 45 Chiu, M.-H., 122, 180, 348 Chomsky, N., 38 Clark, L.H., 24 Claxton, G., 53, 109, 190, 230, 231, 233, 235, 237–239, 241, 255, 289, 299 Clement, J., 257, 309 Cobb, P., 194 Cohen, I.B., 223 Cokelez, A., 13, 350 Cole, M., 29 Coll, R.K., 139, 160, 164, 166, 192, 200, 207, 241, 309 Collins, S., 207 Conan Doyle, A., 62 Crain, W., 26, 29, 276, 310 Crick, F.H.C., 95, 97 Cromer, A., 154, 164, 165, 178, 179, 203, 204

D D’Andrade, R., 60 Daniels, H., 310 Danziger, K., 76 Darwin, C., 67, 97, 106 Dawson, C.J., 281, 305 Dawson, M.R.W., 37, 263 de Jong, O., 200 de Leeuw, N., 279 Denicolo, P., 161, 231, 252, 253, 257, 332 Descartes, R., 22, 53, 54, 63 Dewey, J., 22, 23, 148, 153, 154, 170, 238, 287 diSessa, A.A., 185, 186, 224, 226, 232, 237, 238, 241, 269, 271, 273, 274, 277, 278, 283, 307, 327, 340, 342 Donaldson, M., 26 Dorian, K.R., 333 Drever, J., 34, 227 Driver, R.H., 59, 113–120, 126, 131, 133, 134, 137, 138, 144, 166, 179, 181, 183, 188, 190, 193, 198, 199, 205, 219, 221, 223–225, 228, 229, 231, 234, 240, 246, 247, 251, 254, 257, 284, 285, 289, 300, 303, 304, 307, 311, 326, 327, 340, 341, 345, 353 Duit, R., 7, 117, 118, 127, 132, 191, 223, 280, 287 Duke, M., 165 Dumais, S.A., 236 Dumbrill, D., 240 Dumon, A., 13

Name Index Duschl, R.A., 17, 20, 34, 43, 195, 254, 280, 354 Dykstra, D.I., 281

E Easley, J., 113–115, 144, 190, 198, 219, 223, 228, 231, 247, 326 Edwards, D., 21, 29, 205, 275, 289, 309, 343 Egan, D.E., 265 Egan, K., 24 Einstein, 58 Elby, A., 296, 297 Ellis, A., 36 Elman, J., 22, 269 Engeström, Y., 30 Erickson, G., 49, 113, 115–117, 119, 120, 188, 219, 326, 340, 345, 353 Esterly, J.B., 226, 238 Evetts, J., 23, 24 Eybe, H., 334

F Fensham, P.J., 19, 44, 49, 113, 135, 165, 220, 303, 322 Feyerabend, P., 68, 77 Finster, D.C., 33 Flavell, J.H., 39 Fleury, S.C., 52 Fodor, J.A., 38–41, 198, 283 Fox, D., 127 Fox, M., 45 Fransella, F., 32, 232, 334 Freeman, M.M.R., 68, 156 Freire, 148, 152, 153 Freyberg, P., 117, 118 Frigg, R., 245 Frolov, I.T., 31, 104 Furnham, A., 183, 184, 329

G Gabel, D.L., 243 Gagné, R.M., 35, 43, 134, 137, 189, 203 Galileo, 66, 258 Gallimore, R., 45 García Franco, A., 36, 225 Garcia, R., 20 Gardner, H., 34, 40 Garnett, P.J., 305, 306 Garrison, J., 194 Gauld, C., 268 Geary, D.C., 22

Name Index Geelan, D., 165 Geertz, C., 351 Geiger, 64 Gelman, S.A., 40 George, J., 27, 235 Georgiou, A.K.A., 233 Gergen, K.J., 163, 195 Giddens, A., 173 Gilbert, J.K., 26, 27, 48, 70, 81, 113–117, 119–121, 123, 135, 136, 166, 180, 186, 188, 198, 219, 224, 227, 228, 233, 239, 240, 251, 252, 257, 291, 306, 307, 314, 322, 326, 336, 340, 358 Gilbert, P.J., 26 Gilland, T., 215 Gillespie, N.M., 226, 238 Glasersfeld, E.v., 21, 23–25, 28, 34–36, 130, 131, 133, 134, 138, 139, 164, 168–174, 179, 186, 187, 194, 197, 198, 238, 308, 322 Glasgow, J., 27, 235 Glass, J.C., 94, 198 Good, R.G., 163 Goodfield, J., 257 Goswami, U., 15, 264, 309 Gott, R., 337 Gowin, D.B., 117, 138, 186, 278, 281, 301 Grandy, R.E., 168, 181, 182 Gregory, R.L., 30, 35 Grevatt, A., 210, 333 Grevatt, J., 210 Griffard, P.B., 338 Griffiths, A.K., 225 Grosslight, L., 245 Guesne, E., 251 Guilford, J.P., 287 Gunstone, R.F, 335 Guo, C., 350

H Hacking, I., 8, 13, 163 Hackling, M.W., 305 Hall, A.R., 81 Hamilton, R.J., 17, 20, 34, 43, 195, 354 Hammer, D., 127, 229, 278, 296, 297, 325 Hammersley, M., 76 Harlen, W., 199, 200 Harrison, A.G., 225, 309, 341, 342 Hartmann, S., 245 Hennessey, M.G., 341 Hennessy, S., 127, 158, 289, 310, 311 Herron, J.D., 43, 46–49, 165

387 Hewson, M.G.A.B., 186, 297 Hewson, P.W., 341 Hicks, K., 333 Hirschfeld, L., 40 Hirst, P.H., 152 Holding, B., 118 Holzman, L., 28, 310 Howe, A.C., 197, 312, 330 Hume, D., 54 Hyland, T., 23

I Ingle, R., 204 Inglis, J.T., 156

J Jacobson, L., 348 Jeans, J., 22 Jenkins, E.W., 16, 49, 112, 203, 217, 223, 328 Jennings, A., 204 Jobling, W., 165 Johnson, M., 36, 145, 186, 245, 271, 273 Johnson, P.M., 225, 337 Johnson, W., 94, 198 Johnson-Laird, P.N., 39 Johnston, K., 118, 225, 307 Johnstone, A.H., 132, 199, 200, 217, 264 Justi, R., 81

K Karmiloff-Smith, A., 22, 40, 41, 275 Kaymaz, Z., 216 Keil, F.C., 22 Keller, E.F., 324 Kelly, G., 31, 32, 89, 116, 126, 128, 131, 163, 189, 192, 194, 237, 239, 252, 254 Kemmis, S., 76 Kind, V., 8, 52, 180, 190, 210, 239 Kitchener, R., 26 Klobuchar, M., 165 Klopfer, R.F, 335 Koffka, K., 35 Kozulin, A., 31 Kramer, D.A., 33 Kress, G., 333 Kuhn, T.S., 53, 65, 66, 70, 74, 80–82, 84–87, 89, 91, 92, 103, 115, 162, 189 Kuiper, J., 190, 191, 350 Kvale, S., 163, 334

388 L Lacey, A., 54 Lakatos, I., 9, 19, 52, 64, 70, 79, 80, 91–93, 95–106, 108, 109, 111, 119, 122, 219, 220, 223, 324, 326, 356, 357 Lakoff, G., 36, 145, 186, 245, 271, 273 Larochelle, M., 194 Laudan, L., 62, 87, 91, 177, 243 Laughlin, C.D., 233 Lave, J., 82, 157 Lawson, A.E., 264 Leach, J., 179, 181, 199, 212, 291, 304, 310, 311 Leibniz, G.W., 54 Levin, S.R., 89 Lewin, R., 221 Lijnse, P.L., 225 Linder, C., 224 Locke, J., 54 Longino, H.E., 62, 90, 197, 330, 339 Lucas, A.M., 13, 186, 221 Luria, A.R., 30

M Maloney, D.P., 332 Mariani, M.C., 334 Marsden, 64 Martín, F., 236 Marxist-Leninism, 104 Masterman, M., 82 Matthews, M.R., 11, 49, 112, 160, 161, 163–165, 167, 174–176, 179, 181, 183–185, 198, 201–205, 215 Matthews, P.S.C., 241 Mayer, R.E., 265 Mayr, E., 97 McCloskey, M., 94, 224 McComas, W.F., 160 Meadows, S., 45 Mercer, N., 21, 29, 205, 275, 289, 309, 343 Mestre, J.P., 241 Millar, R., 52, 121, 161, 178, 199, 200, 204, 312, 348 Miller, G.A., 265 Minstrell, J., 304, 306 Mintzes, J.J., 49, 122, 180, 322, 333, 348 Mithen, S., 40, 236 Moran, L., 95 Mortimer, E., 199, 295, 311 Mueller, M.P., 348

N Newberry, M., 210 Newman, F., 28, 310

Name Index Newton, D.P., 332 Newton, L.D., 290, 332 Newton, P., 290 Niaz, M., 119, 121 Nickerson, R.S., 255 Niedderer, H., 241, 253, 280, 285, 296, 337, 341, 342 Norman, D.A., 42, 186 Novak, J.D., 117, 126, 138, 141, 172, 186, 278, 280, 281, 292, 301, 333, 355 Novick, S., 117, 134, 166, 307 Nussbaum, J., 117, 134, 166, 307

O O’Hagan, T., 24 Ogborn, J., 205, 334 Oldham, V., 118, 137, 138, 179, 181, 205, 303, 307, 353 Opfer, J.E., 342 Osborne, J., 52, 118, 128, 167, 181, 204, 207, 216, 300, 314, 323, 332, 337, 340 Osborne, R.J., 113, 117, 118, 127, 130, 134–136, 138, 219, 264, 269, 296, 302, 306, 326, 332, 334

P Palmer, D., 240 Perkins, D.N., 193, 235 Perry, W.G., 33 Peters, R.S., 152 Petri, J., 241, 253, 280, 285, 296, 337, 341, 342 Phang, F.A., 42 Phillips, D.C., 54, 69–72, 76–78, 88, 115, 163, 181, 186, 231 Piaget, J., 20, 25–29, 33, 39, 47, 116, 128–131, 150, 151, 163, 194, 230, 268, 276, 286, 335, 336 Pintrich, P.R., 281 Pitt, V.H., 224 Plato, 55 Polanyi, M., 232, 275 Pope, M.L., 26, 27, 33, 71, 114, 116, 119, 131, 135, 138, 161, 166, 167, 231, 252, 253, 257, 296, 307, 332, 336 Popper, K.R., 53, 55, 56, 58, 60–62, 65–67, 74, 80, 88, 89, 92, 99, 103, 129, 130, 140, 169, 174, 196 Posner, G.J., 43, 280, 281, 287, 290, 292, 297, 298, 307 Potter, J., 163, 194 Preston, K.R., 225 Pring, R., 17

Name Index Q Quale, A., 166

R Raby, P., 97 Ramadas, J., 118 Ravitz, J.L., 312 Reddish, E.F., 125, 170, 186, 198, 199, 226, 248, 255, 263, 275, 278, 308 Reisman, K., 69 Renner, J.W., 204 Reynolds, D., 76 Richards, G., 37 Robinson, F.G., 44 Roschelle, J., 327 Rosenthal, R., 348 Roth, W.-M., 156, 264 Rowell, J.A., 281, 305 Rudd, T., 165 Ruddle, K., 157 Russell, B., 24, 76 Russell, T., 118, 128, 167, 181, 183, 206, 216, 300, 304, 306, 323, 332, 340 Rutherford, 64 Ryle, A., 31

S Salomon, G., 193 Sánchez Gómez, P.J., 236 Savinainen, A., 301 Scerri, E.R., 13, 48, 100, 126, 160, 161, 164, 165, 167, 169, 176, 177 Schmidt, D., 341 Schmidt, H.-J., 246, 302, 334 Schwandt, T.A., 73, 75, 194 Schwartz, B.J., 265 Schwedes, H., 341 Scott, P.H., 179, 181, 199, 205, 212, 285, 291, 300, 301, 304, 310, 311, 341 Shayer, M., 47 Sherin, B.L., 278, 342 Shipstone, D.M., 350 Siegler, R.S., 332, 342 Silverman, S.M., 86 Simmons, R., 235 Simon, S., 216, 314 Sizmur, S., 333 Sjøberg, S., 257 Slotta, J.D., 279, 280, 299, 308, 309 Smagorinsky, P., 30 Smith, E.L., 229 Smith, J.P., 283, 299, 327, 340, 345 Smith, R., 260

389 Solomon, J., 18, 41, 49, 112, 119, 123, 132, 167, 190–193, 196, 199, 200, 203, 216, 217, 233, 238, 241, 288, 290, 300, 301, 323, 324, 355 Solomonidou, C., 286 Souque, J.-P., 294 Spencer, J.N., 165, 176, 177 Spinoza, B., 54 Stafford, D.G., 204 Stavridou, H., 286 Steinberg, M.S., 257, 355 Strike, K.A., 280, 287, 292, 297, 298, 307 Student, T.A., 335 Suchting, W.A., 164 Sugarman, S., 26 Sutherland, P., 26 Sutton, A., 28–31, 35 Swann, J., 60, 67, 69 Sweller, J., 265 Swift, D.J., 48, 114, 119–121, 123, 166, 336, 358

T Taber, K.S., 8, 13, 36, 52, 55, 56, 59, 70, 71, 112, 122, 124, 136, 161, 169, 180, 181, 185, 187, 190, 191, 208, 210, 225, 229, 232, 235, 239, 243–246, 248, 249, 252–254, 257, 259–263, 267, 268, 271, 283–285, 287, 295, 296, 301–303, 308, 309, 312–315, 329, 333–335, 337, 341–344, 348, 350, 351, 355 Tajinder, 253, 254, 268, 295, 296 Tan, K.-C.D., 259, 350 Taylor, T.G.N., 139, 160, 164, 166, 192, 200, 241 Teitelbaum, K., 24 Thagard, P., 85, 88, 142, 292, 312 Tharp, R., 45 Thayer-Bacon, B.J., 11, 17, 58, 68, 88, 90, 157, 173, 195, 255, 355 Tiberghien, A., 251 Tobin, K., 49, 113 Tomlinson, M., 204 Tomlinson, P., 336 Toulim, S., 20 Toulmin, S., 86, 91, 257 Treagust, D.F., 187, 225, 301, 309, 338, 341, 342, 344 Trumper, R., 306 Tsaparlis, G., 243 Tyson, L.M., 309, 344 Tytler, R., 341

390 V van Eijck, M., 17, 156 van Zee, E.H., 304, 306 Venville, G.J., 309, 344 Viennot, L., 224, 238, 240, 241 Vosniadou, S., 280 Vygodskaia, G., 29 Vygotsky, L.S., 28–31, 44, 45, 126, 129, 141, 193, 194, 240, 244, 275, 276, 310

W Wallace, A., 97 Wallerstein, H., 34 Wandersee, J.H., 333, 338, 348 Watson, J.B., 34 Watson, J.D., 95, 97, 105 Watt, D., 118 Watts, D.J., 70, 115, 186, 188, 198, 227, 251, 291, 340 Watts, D.M., 68, 70, 113, 117, 166, 336 Watts, M., 33, 71, 114, 119, 131, 166, 167, 186, 191, 224, 233, 245, 251, 257, 271, 296, 350 Wenger, E., 82, 157 West, A., 204

Name Index West, L.H.T., 44, 303 Westfall, R.S., 37, 88 Whewell, W., 59–61 White, R.T., 35, 49, 286, 305, 322, 337 Wightman, T., 118, 225, 307 Wilensky, U., 69 Williams, M.D., 42 Windelbrand, W., 77 Wittrock, M., 130, 134, 136, 138, 219, 264, 269, 296, 302, 306, 326, 332, 334 Wolpert, L., 234 Wong, Y.T., 312 Wood, D., 45, 310 Wood-Robinson, C., 224 Woolhouse, R., 132

Y Yager, R.E., 166, 313 Young, J.Z., 37

Z Zahar, E., 93, 101, 102, 219, 223, 356 Zangwill, O.L., 30 Ziman, J., 20, 65, 129, 180 Zylbersztajn, A., 224, 257

Subject Index

A Accelerating learning, 344 Accommodation, 126, 130, 184, 185, 268, 269, 277, 281, 287 Active learning, 150, 207, 321 Affective factors in learning, 159, 288–291 Agency, 209, 271, 272 Algorithmic level, 264 Alternative conceptions, 5, 40, 115–117, 133, 189, 196, 211–214, 220, 227–230, 232, 236, 240–241, 246, 247, 251, 254, 260, 262, 268, 276, 278–283, 294, 302, 320, 331, 333, 338, 341, 355, 358 common, 120, 127, 128, 181, 235, 245, 248, 258–259, 270–272, 301, 303, 314, 317, 349, 350 nature of, 5, 135, 181, 210, 227, 232, 244, 245, 254, 257, 280, 298–301, 316, 321, 327 significance of, 135, 179, 210, 244, 327, 349 stability of, 318, 356 Alternative conceptions movement (ACM), 5, 117–121, 316, 327, 358 Alternative framework, from chemistry education, 248–249 Analogy, 62, 67, 82, 85, 236, 266, 309, 345 indeterminacy principle, 344 lock and key, 172 mind as a computer, 37, 39, 64, 141 words as tools, 29, 45, 184, 275, 330 Analysis (of research data), 186 Anomaly, quarantine of, 99–100 Anthropomorphism, 272 Apparatus (cognitive), 65, 132, 139, 182, 231, 264, 298, 356 bias of, 22, 134, 269, 317, 319 Application, 12, 14, 35, 48, 61, 65, 75, 106, 139, 152, 153, 185, 191, 231, 239, 241,

244, 253–256, 259, 271, 272, 274, 277, 279, 284, 293, 302–304, 315, 316, 318, 332, 336–338 Apprenticeship, 83, 158, 311 Argumentation, 181, 190 Assessment for learning, 321 Assimilation, 126, 185, 266, 268, 269, 277, 281, 355 Associations, 35, 60, 90, 112, 120, 128, 141, 142, 178, 209, 213, 232, 242, 248, 252, 253, 255, 278, 286, 296, 324, 332, 335, 346 Associative learning impediment, 324 Atomic structure, 109, 225–226, 281 Autonomous learning, 42, 150, 247

B Behaviour and learning, 10–11, 34, 35, 43, 117, 139, 144, 156, 157, 182, 198, 231, 232, 254, 263, 264, 272, 287, 317 Behaviourism/behaviourist school/perspective, 25, 34–35, 48–49 Beliefs, 9, 11–15, 18, 27, 43, 54, 61, 66, 73, 74, 77, 84, 86, 92, 157, 161, 167, 175, 185, 195, 211, 212, 216, 227, 228, 248, 287, 289, 296, 298, 305, 312, 315, 328, 349 Bias (in cognition), perceptual, 22, 356 Bootstrapping, 283

C Case study, 69, 75, 161, 216, 229, 241, 244, 253, 254 Causality, 228, 271, 272 Central dogma (of molecular biology), 95 Chemical bonding, 190, 225–226, 248, 249, 253, 254, 258, 260, 262, 295, 296

391

392 Children’s Learning in Science Project (CLiSP), 118, 137, 138, 215, 224, 303, 304, 307 Chunking (in memory), 265 Clinical approaches, 328 Cognition, 7, 20, 24, 25, 34–38, 40, 57, 60, 63, 116, 118, 169, 171, 187, 188, 196, 202, 205, 242, 245, 263–265, 269, 270, 272, 283, 289, 303, 316, 318, 320, 325, 333, 338, 355 Cognitive acceleration, 26, 47 conflict, 287, 307, 308 dissonance, 287, 307 structure, 26, 44, 49, 115, 134, 136, 141, 142, 182, 186, 188, 189, 229, 248, 255, 266, 274, 278, 281, 283, 287, 292, 298, 302, 318, 320, 330–335, 338, 341, 345 tension, 307 Coherence of ideas, 1, 191, 244, 279, 284, 293, 312, 318, 356 Cohort effects, 342 Commitment to ideas, 354 Commonality, 112, 142–144, 188, 199, 206, 221, 257–263, 317, 338 Communication, 9, 24, 37, 45, 84, 89, 91, 135, 144, 153, 173, 184, 198, 222, 234, 237, 290, 319, 330, 333 Community of discourse/practice, 184, 185, 290, 311, 358 Compartmentalisation of knowledge, 244 Complementarity of studies, 344–345 Complexity, 5, 10, 12, 62, 69, 75, 90, 129, 136, 157, 189, 199, 217, 220, 252, 255, 260, 322, 325, 328, 330–338, 342, 345–347 Concept, 29–30, 32, 33, 43, 49, 92, 103, 115, 134, 137, 142, 145, 195, 227, 244, 266, 271, 280–282, 286, 291, 295, 297, 309, 345 abstract nature, 46, 48 constrictor, 256 formal, 26, 47, 236 inventory, 15, 301 mapping, 300, 332, 333 metaphorical, 36 molecule, 117, 278 network of, 233, 292 relational perspective, 68, 195 scientific/academic, 48, 180, 213, 250, 282, 301 spontaneous, 30, 45, 276

Subject Index Conceptions, 12–15, 42, 117, 133, 141, 183, 186, 190–191, 224, 226, 227–238, 246–248, 251–252, 256, 258, 260, 269, 270, 278–279, 282, 286–287, 291, 293–294, 297–300, 304–306, 308, 312, 315–319, 327, 345, 348, 349–350 alternative, 5, 40, 113, 115–119, 133, 135, 175, 189, 196, 211–214, 219, 220, 227–228 intermediate, 284–286, 304 manifold, 190, 250–254, 262, 282, 296 Conceptual change, 42, 92, 185, 210, 211, 220, 226, 228, 234, 280–283, 286–293, 296, 297, 308, 309, 312, 313, 320, 337, 340–342, 344–346, 353 conflict, 307 ecology, 4, 184, 185, 297–298, 330, 345 framework, 47, 65, 69–71, 74, 75, 78, 81, 85, 91, 92, 95, 102, 103, 110, 113, 115, 161, 166, 184, 190, 191, 223, 233, 246–249, 251–254, 260, 261, 285, 293, 294, 311, 315, 316, 318, 320, 322, 324, 325, 338, 341, 358 profile, 295, 296 resources, 31, 153, 167, 219, 230, 277–279, 283–285, 296, 301, 303–305, 308, 318, 322 structure, 114, 123, 133, 138–146, 166, 171, 174, 186, 230, 231, 239, 242, 244, 248, 251, 257, 299, 316, 318, 320, 330, 332, 338, 339, 342, 346 trajectory, 304 Conceptualisation, 19, 80, 112, 119–122, 145, 161, 221, 227, 230, 279, 301, 307, 308, 329, 340, 358 Confabulation, 267–268 Consciousness, 15, 35, 41, 42, 45, 267, 274, 310, 318 Consensus, 33, 52, 57, 82, 84, 91, 139, 155, 168, 173, 175, 180, 188, 290, 299, 315 Consolidation (of learning), 266–267, 312 Constant transactional calibration, 89, 308 Constraint-based interactions, 279 Construct, 27, 31, 74, 75, 139, 141, 159, 164, 170–172, 179, 181, 187, 192, 196, 201, 202, 213, 255, 257, 267, 292, 303, 306, 333 personal, 130, 329 repertory grid, 334 system, 32, 115, 116, 254, 334 Constructionism/constructionist perspective, 195

Subject Index Construction metaphor, 8–9 Constructive alternativism, 32, 116 Constructivism/constructivist doctrine/ constructivist perspective cognitive, 168, 182 contextual, 168 critical, 6, 150, 153, 160, 168, 215 fine-grained, 125 hard, 122, 147, 148, 153, 163, 168, 172, 179, 180, 182, 193, 195, 202, 206, 209, 322, 324, 328, 347, 356, 358 human, 112, 122, 126, 139, 167, 191, 195 metaphysical, 182 pedagogic, 165, 176, 207–215, 328 personal, 32, 67, 116, 129, 148, 163, 187, 192–196, 221, 347 philosophical stance, 160–183 as a problematic label/term, 2, 5, 8, 160, 163, 194, 324, 355, 356 psychological, 164, 191 radical, 23–24, 166, 168–177, 181, 197, 202, 204, 207, 233, 277 in science education, 5, 6, 49, 55, 111–117, 119, 122, 147–217, 219, 221, 323, 327, 355, 358 social, 163, 165, 168, 191–199, 311 soft, 181 strong, 324 trivial, 6, 168 weak, 322 Content, 47, 93, 102, 109, 154–155, 177, 179, 180, 185, 197, 204, 207, 208, 211, 213, 215 Context educational, 178, 214, 215, 338, 347, 348, 351, 352 as mental phenomenon, 289 Contingency/contingent nature of learning, 6, 160, 303, 355–356 Conversational artifacts, 184 Coordination classes, 278, 279 Counter-examples, 99 Criticism of constructivism, 147, 159 Cross-cultural studies, 350 Cross-sectional studies, 341–342, 351 Cultural border crossing, 234 environment, 258 transmission, 152, 155, 160 Curriculum(ar) models, 8, 47, 114, 133, 180, 181, 196, 228, 239, 262, 304, 321, 350

393 Curriculum, 2–3, 11, 14, 45, 46, 47, 52, 61, 86, 104, 105, 114, 127, 132, 133, 134, 150, 154, 158, 159–160, 178–181, 189–190, 196, 205, 206–210, 214–216, 223, 227, 234, 236, 240, 243, 301, 303–304, 306, 350 Aotearoa/New Zealand, 160 development, 19, 46, 53, 148, 179, 202–207, 215, 307 English National, 59, 207, 208 initial teacher education, 208, 209 National Standards (US), 178, 196, 215 programme of activities, as a, 205, 303, 304 spiral, 45, 209

D Dance, 333 Deficiency learning impediment, 302 Development, 15, 20, 22, 24–26, 28–30, 33, 39, 40, 48, 96, 121, 150, 179, 235, 263, 268–269, 275, 278 cognitive, 7, 25, 26, 30, 40–41, 96, 111, 126, 129, 150–152, 268, 274, 319, 355 intellectual, 33 stage theory of, 26 Deviation conception (of charge), 260 Diagnostic assessment, 321 Dichotomy, 71, 76–77, 92 Disciplinary matrix, 82–84, 162, 189 Discipline, education as, 4, 16, 51–53, 57 Discovery learning, guided, 45, 46, 204–205, 307 Disequilibration, 185, 268, 277, 287 Distributed encoding, 277 Domain of enquiry, 4, 7–49, 79, 111, 298 of knowledge, 290 Drama, 333 Draw-a-scientist, 332 Drawing, 30, 70, 90, 119, 136, 164, 182, 205, 210, 212, 245, 247, 252, 254, 255, 300, 302, 304, 322, 323, 332–333, 337, 354–355

E Elicitation, techniques, 212, 300, 333 Empiricism, contextual, 90 Engrams, 141 Epistemic subject, 28, 31, 192, 197 Epistemological profile, 294

394 Epistemology, 21, 22, 24–27, 54, 59, 60, 76, 77, 161, 163, 172–175, 293 genetic, 26, 96, 150, 151 relational, 68 Equilibration, 268, 269, 273, 277 Evolution and cognitive apparatus, 132, 139, 182, 231, 264, 298, 356 Expectancy effects, 347 Experiential gestalt of causation, 270, 272 Experiments, 27, 29, 59, 60, 63, 66–70, 72–78, 80–84, 95–99, 107, 109, 151, 161, 202, 203, 229, 304, 307, 329, 335, 336, 347–352, 354 crucial, 98, 99, 103 design, 74, 78, 80, 81, 353 quasi-, 72, 74, 353 Expertise, 255 Explanation, 22, 25, 60, 65, 70, 76, 94, 100, 120, 127, 138, 160, 186, 205, 209, 229, 232, 239, 240, 243, 244, 250, 252, 253, 256, 267–269, 272, 275, 278, 287, 290, 293, 295, 296, 305, 310, 312, 330, 337, 348, 349 Explanatory coherence, 88, 292, 293, 312

F Facts, 13, 20, 48, 59, 60, 62, 65, 77, 78, 80, 101, 103, 108, 109, 111, 125, 127, 157, 238, 243, 264, 349 Falsification, 60, 62, 65, 69, 80, 98–100, 103 Feedback, 129, 268, 277, 283 Fitness for purpose, 328–329 Folk biology, 234–236 knowledge, 41, 197, 234, 245, 249, 262 mechanics, 234–236 model, of the mind, 41 molecular theory, 236 psychology, 127, 128, 130, 142, 234–236, 314, 317, 320, 321 Force & motion, 223–224, 232, 235, 245, 258, 317 Forgetting, 268, 317 Fragmentation of learning, 267 learning impediment, 267, 301, 302, 304, 324, 337 Framework alternative, 103, 113–117, 133–134, 144, 166, 186–191, 211, 212, 217, 227, 229, 247, 248, 251, 260, 262, 278, 279, 289, 301

Subject Index conceptual, 47, 65, 69–71, 74, 75, 78, 81, 85, 91, 92, 95, 102, 110, 113, 115, 126, 161, 166, 183, 184, 190, 191, 223, 233, 246–249, 251–254, 260, 261, 285 multiple, 92, 190, 252, 262, 263, 284 myth of the, 88, 89 theoretical, 65, 121, 161, 185, 345 Full shell explanatory principle, 253

G Generalisation, 59, 60, 65, 75, 227, 275, 314, 319, 328, 351 Generative learning model, 116, 130, 136, 138, 264, 269, 296, 302, 332 Genetic epistemology, 25, 26, 96, 150, 151 Genetics, 31, 86, 95, 104 Geocentric astronomy, 94 Gestalt-switch, 84–85, 291 Grain-size, 110, 318 Grounded learning impediment, 302 Grounded theory, 337 Gut science, 238, 239, 244, 274, 302

H Hard core of a programme, 95, 101, 122, 125, 147, 168, 219, 226, 359 Heuristic negative, 4, 5, 80, 94–96, 104, 108, 112, 113, 123, 147–217, 240, 242, 347 positive, 5, 80, 93, 96–98, 100–102, 104, 109, 111, 112, 123–125, 132, 146, 188, 189, 191, 192, 195 Heuristic method (to teach science), 203, 204 Hierarchical focusing, 336 Historical ideas recapitulated, 282

I Ideas children’s, 13, 18, 117, 133, 181, 186, 233, 254, 270, 306, 351 significance, 117, 226, 228 status, 190, 255, 257, 332 magical, 27 Idiosyncratic ideas, 114, 143 Ignorance (of teachers), 165 Imagery, 41, 45, 264 Imperialism, 147, 148, 151, 153 Impetus, 227, 258, 312 Implementational level, 263, 264 Incompatibility hypothesis, 280, 282, 291

Subject Index Inconsistency in thinking, 92, 262, 298 Independent learning, 29, 306 Individual differences, 75, 125, 142–144, 339 Induction, 59–62, 83, 102, 205 Industrialisation, 55, 149 Inference, 42, 43, 64, 145, 229, 256, 259, 278, 317, 331, 341 Information processing, 16, 37–39, 49, 116, 130, 136, 139, 217, 263, 264, 269, 322 Inquiry, 17, 46, 67, 69, 77, 78, 154, 160, 163, 193, 204, 250, 355 Insight, 11, 17, 18, 26, 35, 36, 55, 97, 116, 142, 148, 182, 204, 219, 223, 234, 240, 272, 296, 316, 317, 321, 327, 337–339, 346, 348–350, 352, 354, 355 Instinct, 132 Instrumentalism, 131 Instrumentation, 54, 63–66, 82, 95, 98, 331 Integrative reconciliation, 281 Intelligence artificial, 7, 34, 37 general component, 40 Intermediate notions, 284 Internalisation, 276, 291, 310 Interpretation, 12, 31, 32, 36, 39, 58, 66, 67, 72–74, 78, 97, 104, 109, 114, 129, 132, 142, 144, 153, 160, 167, 170, 187, 188, 193, 194, 197, 205, 221, 222, 237, 247 Interpretivist research, 73, 163 Interview about-events, 337 about-instances (IAI), 232, 336 clinical, 26, 223, 278, 335, 340 Intuition, 115, 229, 232, 245, 249, 255, 275, 276, 299, 318, 320 Intuitive physics, 22, 185–186, 235, 238, 273, 283 theories, 113, 183, 184, 189, 190, 231, 252, 262, 274, 302, 318, 332 Ionisation, 259

J Jargon, 148, 178, 184–185

K Knowledge, 9–16, 20–24, 26–28, 32, 37, 38, 41, 44, 53–54, 56–61, 63, 65, 68–78, 81, 86–90, 106, 115, 123, 125, 126–127, 128–132, 144, 153, 156–157, 161, 164–166, 168–175, 178–182, 185, 187, 191–196, 202, 205–206, 232, 239, 241, 243–244, 246–247, 250–251, 255,

395 269, 270, 273–281, 292, 296, 299, 311, 328, 347, 352 coherence of, 244, 293, 330 construction, 90, 117, 125–126, 130–131, 153, 179, 194, 195, 199, 201, 207, 268–298, 311, 318–319, 347, 355 explicit, 232, 235 facets of, 230, 275 foundations of, 54, 203 fragmentation of, 267 gut, 232 implicit, 235, 242 innate, 22, 54, 232, 269 integration of, 244, 255, 312 intergenerational, 149, 158, 159 normative, 106 objective, 53–55, 57, 58, 60, 62, 65, 69, 74, 77, 81, 129, 149, 158, 239–240, 329 personal, 20–21, 23, 24, 115, 123, 125–126, 128–130, 143, 175, 186, 192, 194–197, 238–240, 244, 255, 287, 296, 299, 324 in pieces, 232, 269–270, 277, 278, 283, 308 pragmatic view, 22, 23, 61 probable, 63 public, 56, 115, 129, 130, 175, 186 reliable, 52, 54, 56, 65, 70, 79, 81, 88, 105, 180, 325 robustness of, 255 symbolic universes of, 233, 234, 239, 289 tacit, 231–233, 238, 311 target, 2, 3, 6, 11, 24, 27, 48, 61, 133, 137, 154, 158, 167, 179–182, 189, 190, 194, 196, 205, 207, 209, 210, 236, 239, 240, 244, 246–248, 254, 258, 262, 263, 280, 282, 285, 299, 304, 307, 315, 316, 322, 331, 349, 355 tentative, 6, 60, 65 theoretical, 6, 65, 232, 247, 253, 270 traditional ecological, 17, 68–69, 105, 135, 147, 149, 151, 152, 155–158, 235, 288 transfer of, 127, 128, 135, 151, 153 viable, 171, 172, 174

L Label as a hidden persuader, 246 Language, acquisition device, 38 Lay science, 238, 239, 242, 244, 289

396 Learning, 3, 6, 8, 10, 21, 23–29, 30, 35–45, 49, 69, 75, 112, 116–117, 125–134, 138, 142, 150–154, 160, 165, 167, 182, 192–193, 196, 201, 212–213, 263–298, 301–303, 306, 308–309, 312, 318–319, 321, 327, 330, 338–341, 356 concept, 43, 48, 49, 121, 264, 266, 280 conditions for, 43, 44 demand, 181, 212, 304, 307 doctor, 301, 303 hierarchies, 43 impediments, 261, 301, 302, 304, 324, 337 meaningful, 44, 126, 132, 134, 150, 287, 302, 308, 312, 355 pathway, 149, 241, 253, 254, 285, 296, 340 pre-requisites for, 43, 135 rote, 45, 150, 177, 275–276 Learning in Science Projects (LiSP), 118, 224 Legitimate peripheral participation, 83, 157, 330 Lesson-study, 353 Levels of analysis in chemistry, 267 in cognitive science, 264 Levels of representation, 45, 264, 276 Life-world, 41, 92, 193, 233–236, 238–246, 249, 251, 258, 261, 262, 281, 289–291, 293, 299, 300, 316, 320 Longitudinal studies, 229, 340, 342–344

M Mediational tools, 184 Memory, 29, 38, 130, 139–142, 241, 243, 246–248, 250, 264–267, 283, 318, 356 association, 15, 126, 139, 142, 232 conceptual, 140, 141 context, effect of, 241 long-term, 38, 139, 140, 145, 264–266, 283, 318 semantic, 140–142, 265, 286 timescale, 267, 319, 340, 341 traces, 139, 140 working, 38, 139, 243, 248, 255, 265, 283, 318, 356 Metacognition, 42–44, 138, 296–297, 311 Metaphor, 8–9, 11, 36–37, 71, 88, 90, 102, 128, 147, 152, 185, 197, 207, 232, 245, 246, 266, 271, 272, 283, 287, 290, 298, 313, 318, 340 atoms need/want, 225, 260 border crossing, 316 clockwork universe, 86

Subject Index construction of knowledge, 3, 37, 112, 116, 125, 153, 154, 158, 193, 202, 203, 231, 310, 312, 347 constructivism as a Trojan horse, 153 crystallisation of student thinking, 345 ecology (conceptual), 297 goggles, 71, 98, 102 interview as a construction site, 163, 334 islands of thought, 316 learning bugs, 304 man-the-scientist, 32, 116 for memory, 139 mental toolkit, 341 mind as container, 236 nature as machine, 37, 88 neutralisation, 246 ontological trees, 280, 282, 291, 292, 299 quilting-bee, 90 sea of electrons, 246 teacher as learning doctor, 301 Methodology(ical), 4, 18, 21, 26, 29, 32, 48, 68, 69, 71, 74, 75, 77–79, 93, 94, 106, 110, 119, 161–163, 183, 185, 191, 221, 229, 237, 238, 242, 251, 307, 315, 331, 335–337, 342, 344, 357–359 Baconian, 76 pendulum, 337–339, 351–355 pluralism, 329 Mind, 15–16, 22, 28, 37–41, 44, 45, 53–56, 60, 68, 126, 127, 132, 141, 157–158, 172, 185–187, 194, 196, 201, 235–236, 276, 296, 312, 345 architecture, 39, 41 change of, 291 modules, 38, 41 structure of, 20, 22, 39–43 theory of, 15, 127, 235 Mind-matter dualism, 22 Minitheories, 236–240, 244, 246, 247, 250–253, 255, 262, 270, 274, 299, 316, 324 Misconception, acquired from teaching, 210–212 Models, 5, 13, 17, 25, 34, 38, 54–55, 64, 65, 67, 75, 81, 84, 92, 94, 97–98, 99, 103, 106–107, 112, 113, 114, 116, 129, 132, 138, 142, 144–145, 151, 159, 169–171, 177, 180, 186, 187–189, 192, 197, 207, 208, 212, 219, 221, 225, 231, 236, 243, 245, 251–252, 254, 255–256, 261, 264, 267, 269, 271, 281, 283–284, 292, 303, 310, 312, 316, 318, 320, 323, 325, 329, 333, 327, 338–339, 342, 346–347, 350, 351, 355, 357

Subject Index of the atom, 64, 136, 254, 267, 285, 286, 293 curriculum/curricular, 8, 47, 114, 133, 180, 181, 196, 228, 239, 262, 304, 321, 350 historical, 12 Ideal Gas equation (IGE), 107 mental, 23, 24, 27, 41–42, 76, 132, 145, 169, 186, 189, 323, 332, 357 normative, 112 planetary, 94, 136, 254, 286 possible partial, 255–256 reticulated, 87 scientific, 8, 33, 81, 92, 98, 119, 135, 159, 180, 181, 235, 260–262, 278, 280, 283, 284, 287, 304 submicroscopic, 225, 261 teaching, 47, 114, 180, 213, 214, 245, 246, 350 transfer, 126–128, 130, 176, 235, 301, 313, 314, 321, 346 van der Waals’ equation, 107 Molecular biology, 95 framework (for ionic bonding), 263 Motivation, 1, 8, 44, 73, 213, 262, 296, 303, 327

N Natural approach to research, 183–184 attitude, 233–236, 239, 241, 246, 270 environment, 143, 330, 348 experiments, 347–351 history, approach to research, 327 selection, 22, 57, 67, 86, 97, 104–105, 172, 287, 288, 319, 345 Naturalistic enquiry, 163 Nature of science, 52, 53, 59, 69, 80, 127, 160, 208, 215, 234, 254, 328 Null learning impediments, 302

O Objectivity, 56–58, 87 Observations, theory-laden, 64–66, 78, 85, 87, 121 Octet, 229, 253, 259, 281, 284, 296 Ontological trees, 280, 282, 291, 292, 299 Ontology, 54, 66, 161, 164, 173, 226, 280, 283, 299, 312 Orbitals, 136, 226, 245, 267, 296 Orientation, 36, 84, 215, 303, 306 Oxygen theory, 292

397 P Paradigm, 25, 49, 51, 66, 66, 70–72, 76, 78, 80–89, 95, 102–103, 112, 113, 115, 161–163, 177, 189, 271, 292, 322, 323, 352, 358 incommensurability of, 85, 86 shift, 84, 85, 91, 162, 292, 356 Partial learning, 136 Pedagogy, 43–45, 75, 127, 137, 141, 143, 145, 150, 153–155, 158–160, 172, 179, 199, 208, 210, 213–217, 300, 313, 326, 332, 339, 343, 347, 352, 354 Perception, 35, 37–40, 63, 84–85, 216, 265, 278 Personal construct theory (PCT), 32, 116, 232, 254 Phenomenological primitive. See P-prim Philosophical confusion, 164, 176–177, 182 Phlogiston theory, 292 Phonological loop, 265 Photosynthesis, 56, 201, 224, 229, 308 Physical environment, 235, 297, 317, 330 Plant nutrition, 224–225, 244, 260 Positivism, 53–55, 70, 72 Post-formal operations, 33 Postpositivism, 60 P-prim, 230, 264, 269, 270, 272–278, 318, 320 Practical work, 46, 115, 136, 205, 346 Practice, classroom/teaching (impact on), 137, 149, 199–201, 211, 216, 305 Preconception, 113, 115, 182, 228, 231, 307 Prediction, 62, 63, 65, 67, 69, 75–76, 87, 100–101, 107–109, 241, 255, 274, 320, 322, 350 Problem-solving, 22, 33, 42, 45, 97, 121, 151, 240, 265 Progress, 60–61, 65, 70, 72, 77, 79, 86, 87, 91, 101, 145, 167, 189, 191, 197, 209, 217, 219, 222, 242, 284, 294, 325, 326, 340, 346, 350, 351, 356, 359 Progressive differentiation, 281 Project, 46, 47, 59, 71, 118, 127, 137, 167, 181, 204, 215, 303, 304, 306, 307, 348, 353 Protective belt, 5, 40, 80, 93, 95–98, 112, 123–125, 217, 219–324, 326, 350, 359 Pseudoscience, 110

Q Quanticles, 55, 65, 132, 245, 261, 283 Quantum hypothesis, 109

398 Questioning, 27, 58, 76–77, 232, 234, 307, 335, 343–345 Questionnaires, 331

R Range of application/convenience, of ideas, 191, 239, 272, 332, 336 Rationalism, 294 Realism, 56–58, 162, 173–174, 177, 277 Reductionism, 68 Reflective discourse, 304, 306 Refutable variants, 5, 96, 98, 123, 125, 147, 192, 199, 219, 220, 227, 262, 304, 315, 316, 322–324, 326, 340 Refutation, 62–63, 65, 70, 80, 82, 83, 95–96, 98–100, 103, 109, 330–331 Reinforced outcome, 136 Relativism, 58, 66, 81, 87, 88, 91, 161, 163–165, 168, 175 absolute, 56, 89–90 qualified, 23, 89–91 vulgar, 173, 174, 177 Representation, 23, 33, 41–44, 61, 125, 129, 130, 141–142, 144–146, 171, 180, 186–189, 221, 232, 239, 243, 245–248, 255, 270, 271, 274, 293, 315, 316, 318–319, 333, 348, 358 enactive level, 45, 264, 276 iconic level, 45, 264, 276 of knowledge, 221 symbolic level, 45, 264, 276 Representational redescription, 40–41 Research confirmatory, 75–76, 162 discovery, 75–76 educational, 51, 53, 69–73, 77, 78, 161, 329 experimental, 69 ideographic, 144 interpretivist, 73 nomothetic, 74–76, 144 positivist, 70, 72–73 scientific, 51–78 Research programme, 1, 7, 19, 51, 79–110, 111 behaviourist, 34 constructivist, 9, 112, 119–121, 125, 130, 132, 139, 148, 151, 160, 167, 205, 209, 226, 356 axioms, 94, 125–126, 131–132, 134–135, 137, 139–140, 143–145 empirical premises, 115, 120, 122 fundamental premise, 116, 134 hard core, 94–95, 122, 179–180

Subject Index negative heuristic, 94–95, 147–217 positive heuristic, 93, 96–97, 123, 124, 132, 189, 202, 206, 242, 246, 252, 325–356 degenerate, 101, 216–217 Einstein’s, 107 Freudism, 106 high-energy particle theory, 97 Marxism, 106, 108 neo-Darwinian, 97, 101 Newtonian, 96, 107 origins of, 108–109 Piagetian, 46–48, 121, 151 progressive empirically, 101, 108, 109, 217, 324 theoretically, 101, 107–109, 130, 217, 324 scientific, 1–6, 51, 103–108 Research questions, 73–74, 124, 130, 138, 329, 339 Resources (cognitive/conceptual), 31, 153, 167, 219, 230, 277–279, 283–285, 296, 299, 301–304, 308, 318, 322 Restructuring, 304, 305, 320 Review, 116, 142, 183, 193, 289 Robustness (of learning), 282, 312, 319 Role play, 333 Romancing, 230 Rules of correspondence, 256

S Sample(ing), 59, 63, 65, 191, 248, 251–252, 259, 341–343, 351 Saturation (research findings), 252 Scaffolding, 45, 205, 309–311, 356 Schemes of work, 207, 209, 216 School science, 11, 13, 22, 52, 59, 104–105, 132, 133, 136, 178, 179, 190, 193, 205, 209, 217, 223, 224, 238–239, 242, 243, 246, 251, 254, 281, 299, 304, 316, 320, 328, 339 Science creation, 104, 105 curriculum, 27, 46, 47, 104, 158, 159, 181, 206, 210, 240, 315, 355 demarcation of, 52, 67, 87, 103–106 education as a field, 19, 24 empirical, 77 inductive, 59 life, 95 natural, 34, 51–54, 63, 68, 72, 79–80, 106, 162, 184, 189, 355

Subject Index normal, 81–83, 91, 102 physical, 62–63, 76, 329, 352 post-positivist, 53–58, 69–70, 77, 79, 329, 350 school, 52, 56, 104–105, 190, 211, 217, 223, 238–239, 241, 242, 246, 248, 251, 254, 268, 299, 304, 315, 316, 328, 339 social, 51, 52, 57, 63, 67, 76, 79, 89, 103–108, 162, 163, 172, 194 Science Processes and Concept Exploration (SPACE) Project, 118, 127, 137, 167, 181, 215–216, 304, 306 Scientific literacy, 52, 175 method hypothetico-deductive, 60, 62, 103 inductive, 59 revolution, 65–66, 81–82, 84–86, 91–93, 102, 162, 223, 293 Seminal corpus, 113, 122, 123, 133, 326, 358 Sense of mechanism, 237, 269, 270, 272, 273, 277, 283 Simplification, 59, 71, 114, 180, 181, 211, 220 Social environment, 197 influences, 196 processes, 58, 130, 193, 194, 196, 201, 324 Sociocultural perspective, 194 Soviet science/psychology, 28, 104 Spin, 283, 302 Stability (of ideas), 191, 318 Statistics, 72, 343 Structure cognitive, 44, 115, 134, 136, 141, 142, 182, 186, 188, 191, 193, 248, 255, 266, 278, 281, 287, 292, 298, 320, 330–332, 334, 335, 341, 345 conceptual, 139–140, 142, 145, 174, 186, 189, 239, 248, 299, 320, 339, 346 disciplinary, 7, 115, 162 Subjectivity, 58, 87–88 Substantive learning impediments, 302 Surveys, 258–259, 338, 350, 351, 353

T Tabula rasa, 132 Target knowledge, 11, 24, 27, 48, 61, 133, 137, 154, 158, 167, 179–182, 189–190,

399 194, 196, 207, 209, 210, 236, 239, 240, 244, 247, 248, 254, 258, 262, 263, 280, 285, 299, 304, 307, 315, 316, 322, 331, 349, 355 Teacher education, 16, 127, 145, 148–149, 208, 209, 313–314, 352 Teaching for understanding, 321 Terminology (of constructivism), 8 Theory, auxiliary, 109, 111 Thick-description, 346, 351, 352 Thinking, 7, 15–16, 26, 27, 30, 34, 36, 42, 45, 55, 91, 102, 126, 133, 139, 142, 144, 146, 151, 153, 194, 195, 221–223, 226–231, 235, 236–238, 247, 252, 255, 256, 258, 263, 272, 275, 284, 295–296, 300, 304, 305–307, 311–312, 315, 332–335, 338, 339, 344–345, 350, 355 lability, 135 stability, 135, 144, 237 subconscious, 42 Timescale for learning, 340–341 Translation between languages, 89 Triads (Kelly’s), 232 Triangulation, 334 Two perspectives outcome, 135 Typology of learning impediments, 301, 337

U Unified scientific outcome, 135

V Values (scientific), 62, 87, 94, 99, 243 Verbalisation, 232, 238 Visiospatial sketch pad, 265

W Warrant, 67, 77, 78 Word association, 141, 332, 335 Word meaning, 240, 275 Worlds, three, 55–56

Z Zone of next/proximal development (ZPD), 29, 310