Perspectives on Learning Disabilities in India: Current Practices and Prospects

Perspectives on Learning Disabilities in India

Perspectives on Learning Disabilities in India Current Practices and Prospects

Edited by

KOMILLA THAPA GEERDINA M. VAN DER AALSVOORT JANAK PANDEY

Copyright © Komilla Thapa, Geerdina M. van der Aalsvoort and Janak Pandey, 2008. All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage or retrieval system, without permission in writing from the publisher. First published in 2008 by SAGE Publications India Pvt Ltd B-1/ I-1, Mohan Cooperative Industrial Area Mathura Road, New Delhi 110 044, India SAGE Publications Inc 2455 Teller Road Thousand Oaks, California 91320, USA SAGE Publications Ltd 1 Oliver’s Yard, 55 City Road London EC1Y 1SP, United Kingdom SAGE Publications Asia-Pacific Pte Ltd 33 Pekin Street #02-01 Far East Square Singapore 048763 Published by Vivek Mehra for SAGE Publications India Pvt Ltd, typeset in 10.5/12.7 pt Garamond by Excellent Laser Typesetters, Delhi and printed at Chaman Enterprises, New Delhi. Library of Congress Cataloging-in-Publication Data Perspectives on learning disabilities in India: current practices and prospects/ editors: Komilla Thapa, Geerdina M. van der Aalsvoort, Janak Pandey. p. cm. Includes bibliographical references and index. 1. Learning disabled children—India. I. Thapa, Komilla. II. Aalsvoort, G. M. van der (Geerdina Maria), 1952– III. Pandey, Janak, 1945– LC4706.I4P47 371.910954—dc22 2008 2008022465 ISBN: 978-81-7829-825-2 (HB) The SAGE Team: Elina Majumdar, Jyotsna Mehta, Amrita Saha, Trinankur Banerjee

Contents List of Tables List of Figures Foreword by J.P. Das Acknowledgments Preface

7 10 11 17 18

01. Learning Disabilities: Issues and Concerns Komilla Thapa

23

02. Young-at-risk Children: An Educational Challenge or Clinical Group Only? Geerdina M. van der Aalsvoort 03. Learning Disability and Language Learning Prathibha Karanth 04. Developmental Dyslexia: Evidence from Hindi-speaking Children with Dyslexia Ashum Gupta 05. The Marginalized Dalits: Disadvantages in Learning Janak Pandey and S.K. Pant 06. Learning Disability: Challenges in Diagnosis and Assessment Preeti Verma 07. Profiles of Academic Skill Deficits in Indian Schools Malavika Kapur 08. Teacher Identification of Learning Problems: Comparisons with Other Measures Rajani M. Konantambigi and Mamatha Shetty

48 80

97 116

143 171

181

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09. Teachers’ Perception of Learning-related Problems in School-going Children: A Preliminary Report Nishi Tripathi and Bhoomika R. Kar 10. A Base-line Study of Learning Disabilities: Its Prevalence, Teacher Awareness, and Classroom Practices Dhananjai Yadav and Vidya Agarwal 11. A Theory-driven Approach to the Diagnosis and Remediation of Learning Problems in Children: CAS and PREP Sunita Pagedar and Jagruti Sarnath 12. Scaffolding to Learn: An Attempt Dharmishtha H. Mehta 13. Detailed Assessment of Specific Learning Disability and Intervention in School Children Monica Mongia, Raja Sadhu, and Manju Mehta

200

221

239 255

264

14. Identifying Issues and Looking Ahead Geerdina M. van der Aalsvoort

277

About the Editors and Contributors Author Index Subject Index

286 290 294

List of Tables 2.1 2.2

2.3

2.4

2.5

4.1

5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8

5.9

Overview of the Conditions Mean Scores with Respect to Age, Language Score, and Intelligence Score from the Four Groups Mean Scores and Standard Deviations with Respect to Seconds of Total Time Played and Number of Episodes Means and Standard Deviations with Respect to Number of Collaboration Type and Number of Complexity of Collaboration in Both Conditions Means and Standard Deviations with Respect to Number of Metaplays and Special Communications in Both Conditions Common Graphemic, Phonological, and Mixed Errors of Dyslexic Children Estimates of Incidence of Poverty in India Literacy Rates of the SCs, the STs, and the Rest of the Population Cropping Pattern in the Sample Villages Socio-Economic Profile of the Sample Villages Distribution of Social Infrastructure in the Sample Villages Gender and Caste-wise Distribution of School-going Children (6–11 years) Gender and Caste-wise Distribution of Dropout Children (6–11 years) Gender and Caste-wise Distribution of Children from 6 to 11 Years Who have Never Attended School Seasonal Working Pattern in Sample Villages

60

63

67

68

70

106 119 120 124 125 126 127 129

130 132

8 5.10 5.11 7.1

7.2 7.3(a) 7.3(b)

7.3(c)

8.1 8.2 8.3

8.4 8.5 9.1 9.2

10.1(a) 10.1(b) 10.2 10.2(a)

Perspectives on Learning Disabilities in India

Children’s Assistance Pattern Pattern of Migrant Households in Sample Villages Comparison of Academic Deficits in Children of Standard 5, from Urban Slum Schools and Middle SES Schools Academic Skills of Children from Classes 1 to 5 in a Single-teacher Rural School Comparison of Reading Skills among Children from Standards 1 and 2 of Central and State Schools Comparison of Writing Skills among Children from Standards 1 and 2 of Schools Following the State and Central Syllabi Comparison of Arithmetic Skills among Children from Standard 2 of Schools Following State and Central Syllabi

132 133

175 175 176

177

177

Criteria for Identifying Problem Children Problems Encountered Teacher Ratings of Learning Problems and Lack of Problems in Children, and Their Scores on the Screening Device and the LD Test Relationship between BCSLD and DTLD Learning Problems in Children by Sex

192 193

Demographic Data-Sample Distribution Identification of Children with Learning-related Problems from Classes 2 to 8 for Reading and Writing (English) as Reported by Teachers

209

Prevalence of Learning Disability Prevalence and Extent of Learning Disabilities Teacher Awareness about Learning Disability Listening and Cognition Behavior (in percentage) 10.2(b) Oral Language Problems (in percentage) 10.2(c) Written Language Problems (in percentage)

194 195 195

216 227 228 229 229 230 230

List of Tables

10.2(d) Mathematical Computation Problems (in percentage) 10.2(e) Behavior Related Problems (in percentage) 10.2(f) Conduct and Motor Behavior Problems (in percentage) 10.3 Classroom Practices for Dealing with Learning Disability 10.3(a) Classroom Practices for Dealing with Oral Language Problems (in percentage) 10.3(b) Classroom Practices for Dealing with Written Language Problems (in percentage) 10.3(c) Classroom Practices for Dealing with Mathematical Computation Problems (in percentage) 10.3(d) Classroom Practices for Dealing with General Behavior Problems (in percentage) 10.3(e) Classroom Practices for Dealing with Conduct and Motor Problems (in percentage) 11.1

12.1 12.2

12.3

13.1 13.2 13.3 13.4 13.5

WRMT-R (Word Identification and Word Attack) Scores Following Remediation and PREP

9 231 231 232 233 234 234

235 236 236

252

Description of the Sampling Process 256 Means, SDs and t-value of the Performance of the Subjects on Test of Problem Solving under Pre-test and Post-test Conditions 259 Co-efficient of Correlation between Pre- and Post-test Scores on TPS and Scholastic Achievement Obtained by the Subjects 260 IQ Subtest Scores of Experimental and Control Groups Problems Assessed by ANSERS Scale Abnormalities Found on Application of PANESS Scale on Experimental and Control Children Detailed Assessment of SLD: Comparison of Problems Seen in Both Groups Four Modalities of the Multi-sensory Approach

270 271 271 272 274

List of Figures 2.1 2.2

9.1 9.2

9.3

9.4

9.5 13.1

Histogram of the Collaboration Types in Sessions 1 through 8 in Both Schools Overview of the Frequency of Metaplay from Sessions 1 to 8 for Each School Condition

69 72

Plan of the Project on LDs Frequency Distribution of Language, Writing, Reading and Mathematics-related Problems from Classes 2 to 8 as Perceived by the Teachers Frequency Distribution of Behavioral Problems in Children from Classes 2 to 8 as Perceived by the Teachers Frequency Distribution of Comparative Evaluation of Learning-related Problems from Classes 2 to 8 as Perceived by the Teachers Implications and Directions for Future Research

208

215 218

Flowchart Showing Procedure

267

212

214

Foreword

A

ny book on learning disabilities needs to grapple with certain fundamental issues. Of these, definitional and identification issues assume salience. This book is based on the International Conference on Learning Disabilities and Young-At-Risk which was organized by the UGC Centre of Behavioural and Cognitive Sciences, University of Allahabad on, February 19–21, 2003. Selected papers from this conference are being presented in this book, and deal with issues of significance and relevance to the theory and practice in this area in India. A distinction between the garden variety poor reader and the poor reader with specific reading difficulties is widely accepted in current literature on reading disability. The first group has pervasive deficits in cognitive processing whereas the second has specific deficits in one or two cognitive processes. As Dr Thapa’s introductory review explains, the new American definition of learning disabilities requires that the acquisition of reading deficits must be identified. However, a consensus is lacking in identifying them. A prerequisite for identification is a theory to back it up, as without a theory, merely producing a list of observed difficulties would deteriorate to a laundry list, or worse, a meaningless bunch of eclectic scores on a meter without knowing what the meter really measures. I have suggested that in the initial stages of word reading, learning difficulty may be identified in terms of successive processing. This is the most salient cognitive processing deficit whereas at an advanced grade when some amount of skill in word reading has been acquired, planning also features prominently. Beyond word reading, children must be able to comprehend the meaning of sentences and passages. At this stage, simultaneous processing assumes a pre-eminent position. Moving ahead, children are also required to compose stories or other kinds of essays; here planning plays an important role (Das, 2001).

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Perspectives on Learning Disabilities in India

I wish the search for identification of a specific cognitive deficit would end here. It does not. The question now becomes defining what a “deficit” is. How to assess how much of a deficit is a deficit? And how much is the deficit relative to the statistical norm for the cognitive process (normative), and in relation to the child’s own scores in other cognitive processes (relative). For example, suppose the child has a score of 85 in Successive Processing, which is one standard deviation below the norm. This is a substantial formative deficit. However, the child’s scores on Simultaneous Processing, Attention and Planning are around 90. Then, we conclude that the child has a relative deficit in Successive Processing which is very small indeed! The above discussion is relevant only when it is assumed that the child is not struggling to read in his or her second or even third language, that he or she ought to be fluent in the language under normal circumstances of schooling. This happens to be a big assumption in India. Even in the so-called English medium schools, children’s grasp of the English language is often weak even after four years of schooling. The problem of bilingualism complicates the identification of dyslexia. This has been discussed in some of the chapters of the book. In spite of this, poor successive processing is often observed in children who are poor readers. So all is not lost and the same cognitive profiles in English as in Oriya have been found among dyslexics and also found in Oriya children (Das et al., 1996). Difficulty in comprehension is another major learning difficulty, and recognizing it among bilingual children is complicated. I have found that proficiency in word reading in English among Indian school children may be at par with American children of the same grade as measured by standard US reading tests (for example, Woodcock Reading Mastery), whereas comprehension scores are usually a year or two grades behind. This is as it should be because the majority language outside their school is not English. Reading comprehension depends on word identification proficiency in the early school years. Therefore, how we identify children with comprehension difficulty in research and in clinical settings is a legitimate question. Equate the children we are studying on word reading/ decoding, ensure that their performance is up to their grade level,

Foreword

13

and then to compare them on comprehension would be an obvious strategy. Bilingual education in Indian schools therefore may present a special problem for researchers and clinicians alike in identifying comprehension deficits. Phonological awareness and rapid automatized naming (RAN) speed are known to be associated with reading. More work on these two core components of reading and reading difficulties is needed in India. Research and clinical work can take advantage of the bilingual and multilingual education in Indian schools. Important questions in the field of learning disabilities can be investigated: Does dyslexia/poor reading in one language correspond to the other languages that a child has learnt given equal instructional opportunities? Since English orthography is distinctly opaque in contrast to most Indian languages, answers to such a question will have broad implications for reading research. The relative contributions of proximal factors such as phonological awareness and RAN in one language can be compared with other languages that the child has learnt. Important theoretical questions stemming from“granularity”, for example, can be answered. Awareness of fine features of two contrasting languages such as Hindi (transparent) and English (opaque) can be compared for phonemes, syllables, and words. Turning to distal factors that influence reading such as cognitive processes, bilingual as well as unilingual education provides a unique opportunity as well. Given that Successive Processing deficit accompanies and foretells reading difficulty, does that hold across all the languages that the child has learnt? Consider serial recall of words (a Successive test): Performance in Hindi word recall and English word recall may or may not be comparable. More importantly, if a child is poor in Hindi word recall and Hindi word recall predicts Hindi word reading, would it also predict English word reading? Multilingual education makes such comparisons more interesting! The central question is domain specificity. A domain-general cognitive process such as Successive Processing is likely to influence word reading ability and predict reading disability across languages learnt by a child, however phonological awareness or RAN may be language specific, and its influence is limited to the specific language.

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Perspectives on Learning Disabilities in India

One or more of the chapters in the book refer to domain-general cognitive processes such as the four PASS processes. Taking the next step in this research involves testing some hypotheses such as the above. That would make theoretical contributions and should have practical applications for teaching as well. Assessment of reading and intelligence-like abilities naturally leads to the question—what are the processes that determine performance in tests of assessment. I have discussed this in the preceding section although briefly. Intervention and remediation of learning difficulties is the last and final logical sequel. Some of the chapters have been written on this topic. I wish to complete my “Foreword” with a discussion of intervention. We know very little about the conditions that need to be in place to help the children who have failed to read adequately in spite of regular classroom instruction in reading. Even where traditional special education programs are designed for such children with severe reading disabilities, the aim has been to stabilize rather than remediate reading deficits. That is, the programs ensure that children do not fall farther behind in reading skills but they do not close the gap between them and their age-level peers. The challenge is to not only to construct and use appropriate remediation programs for disabilities related to English and regional languages but also to do better than that, to administer a remediation program that begins to close the gap between the current reading level and the level to be achieved appropriate for the child’s grade. One program associated with our PASS theory has been discussed in this book. It is the PREP program (PASS Reading Enhancement Programme; Das, 1999). COGENT (Das, 2005a) is a relatively new program that has been developed and had been effective with preschool children and with school-aged children. The COGENT program integrates direct instruction in pre-requisite reading skills and cognitive processing strategies. The program includes “modules” focusing on metalinguistic skills, syllable/phonemic discrimination, onset-rime distinctions, syntactic and semantic comprehension, and rapid automatic naming intertwined with cognitive processes, such as attention, strategy planning, simultaneous, and successive processing. Both programs are being used in India and report success. These are worthy of wider use as they are based on theoretically derived procedures. These two remediation programs should

Foreword

15

be easy to adapt in Indian languages besides being appropriate for children in English-medium schools because they have been translated and used in other languages including Japanese, Korean, and Spanish. I have raised the issues in learning disabilities that are unique to India as well as those that are commonly shared with American and European countries. Among these, the important one is still the issue of identification of learning disability, specifically the reading disability including dyslexia. However, a consensus seems to be emerging: learning and reading disabilities are to be defined by deficit in one or more cognitive processing rather than by IQ-achievement discrepancy. I have proposed above that a deficiency in cognitive processing can be framed within the PASS processes; normative as well as relative deficiency in children’s cognitive performance can help us in identification. Contemporary American definition has thus rejected the prominent role IQ tests enjoyed in the past. In India, we should not give the classical IQ testing based on WISC and Binet (translated or in original) any importance in determining learning or reading disability; thus, we will avoid the mistakes made in the past. An alternative to IQ testing is available in the form of Cognitive Assessment System especially as it works well with Indian children in English-medium schools. Moreover, the program is widely popular even using American norms. Our Indian children score even above the norm in Successive Processing (Das, 2005b). Sunita Pagedar and Jagruti Mehta’s research reported in this book supports this. I have also briefly mentioned the two cognitive intervention programs. In this way, both assessment and remediation can progress hand-in-hand. In addition to the advantages in India we have for studying multilingualism, the combination of assessment with remediation can secure an important place for Indian research in the field of learning disabilities. J.P. Das, Director (Emeritus) Developmental Disabilities Centre University of Alberta, Edmonton Canada

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Perspectives on Learning Disabilities in India

REFERENCES Das, J.P., S. Nanda and U.N. Dash (1996). ‘Cognitive Profiles of Poor Readers in Oriya Language: Are they Similar to English Readers?’, Psychology & Developing Societies, 8, 245–64. DAS, J.P. (1999). PASS Reading Enhancement Programme. Edmonton, Canada: Developmental Disabilities Centre, University of Alberta. ——————. (2001). Dyslexia and Reading Difficulties. Reprinted in India by Maharashtra Dyslexia Association, Mumbai. ——————. (2005a). COGENT. University of Alberta, Developmental Disabilities Centre, Edmonton, Canada. ——————. (2005b). Fair Assessment. Paper Presented in a Symposium at American Psychological Association, Washington D.C.

Acknowledgments

O

rganizing a conference and putting together its proceedings can never be a solitary endeavor. It invariably involves the combined efforts of a dedicated team of people, some of whom work by choice behind the scenes. We take this opportunity to thank the faculty, office staff, and the research and postgraduate students of the Department of Psychology, and the Centre of Behavioural and Cognitive Sciences (CBCS) who, in various ways, helped and supported us. In particular, we extend our gratitude to M.P. Shrivastav and Puneet Kumar. Meeta Malhotra was always there to handle glitches and hassles, big or small and contributed significantly in planning the scientific program. We thank all the contributors not only for their presentations in the conference but also for willingly revising their manuscripts, meeting editorial deadlines, and for their forbearance in the delay in publishing these proceedings. We are indebted to Dr J.P. Das who wrote the Foreword for this book. In the first phase of copyediting Drs Prachi Ghildyal and Nishi Tripathi rendered valuable services. We are indebted to Ms Elina Majumdar, Ms Jyotsna Mehta, and the entire SAGE Production Team for their professional rigor and meticulous approach. Again, reassuringly behind the scenes were our family members and their ungrudging support and tolerance is gratefully acknowledged. Komilla Thapa Geerdina M. van der Aalsvoort Janak Pandey

Preface

T

he International Conference on Learning Disabilities and Young-At-Risk was organized by the University Grants Commission (UGC) Centre of Behavioural and Cognitive Sciences, University of Allahabad on February 19–21, 2003. The UGC had selected the University of Allahabad under the scheme of identifying Universities with Potential for Excellence, for developing an Island of Excellence in Behavioural and Cognitive Sciences. The Centre of Behavioural and Cognitive Sciences (CBCS) was formally established in February 2003. The mission of the Centre is to provide superior education in the area and to further advancement of scientific knowledge through basic and applied research. The Conference on Learning Disabilities (LDs) and Young-At-Risk was the first initiative of the CBCS and was particularly apt, as this area is both cross-disciplinary and multidisciplinary in nature. Learning disorders have always remained an intriguing puzzle. The area has been widely researched and investigated from different perspectives. The field continues to be plagued by disagreements about basic issues pertaining to identification, assessment, and intervention. In India, since research and practice in the area of learning disabilities is still at a nascent stage, the issues that require greater focus and more intensive investigation may be more fundamental and more context-specific. These would include the definition of LDs, procedures for identification and assessment, the progression of LDs over the life span, prevention and interventions, and contextual factors. These were the themes identified for the conference and leading Indian experts, researchers, and practitioners and selected distinguished scholars from abroad were invited to participate in the deliberations. Two venues were selected: The main academic program consisting of invited lectures and paper presentations was held at the University of Allahabad. The second venue

Preface

19

was the Centre of Biomedical Magnetic Resonance, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, as a collaborative study exploring the brain mechanisms implicated in dyslexia using the MRI was being planned. In addition, a research program seeking to obtain baseline data regarding the prevalence and nature of learning disorders in schools in Allahabad was also initiated. The conference was held during February 19–20, 2003 at Allahabad and on February 21 at Lucknow. A large number of delegates participated in the proceedings, which consisted of invited lectures and paper presentations. The outstanding papers of the conference were selected and the authors were invited to send the manuscripts for inclusion in this book. The papers focused on issues related to the conceptualization and definition, assessment and interventions of learning disabilities, the role of the teacher in identification, the salience of contextual factors, and the language learning–learning disability connection in Indian languages. A brief overview of the chapters follows. Aalsvoort presents an account of the Dutch educational system and explicates how children requiring special education are identified by examining both child and environment-related characteristics using a mix of qualitative and quantitative methods. Using a micro-genetic approach, she studied play-in-process in young-at-risk children in two school conditions and concluded that school environment makes a difference in favor of children attending a regular primary school. The chapter by Karanth traces the history of the language learning and learning disability connection, its subsequent neglect, and the factors leading to the renewed interest, and the new thinking on this important connection. The implications of these results for the identification and management of children with learning disability in India are presented. Gupta presents an analysis of the reading errors of Hindi-speaking children with developmental dyslexia. Despite Hindi being a transparent orthography with consistent grapheme-to-phoneme mapping, it was found that dyslexic children were significantly poorer on reading speed as well as accuracy and showed a greater number of graphemic than phonological errors. It was suggested that by training children to gain conscious access to the phonological structures, they can be helped to improve the quality of initially inadequate phonological representations.

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Perspectives on Learning Disabilities in India

Focusing on contextual issues, the chapter by Pandey and Pant focuses on issues related to the education of socio-economically deprived and powerless sections of society, namely the Dalits. These marginalized sections have remained vulnerable due to their depleted socio-economic status and their engagement in the lowest level of occupation requiring no skill and education. This study analyzes how socio-economic factors influence the learning process of marginalized Dalits. Varma focuses on the concept and definition of learning disabilities and children ‘at risk’ and presents an analysis of the issues and problems inherent in the process. A theoretical framework of assessment is presented with reference to different domains including language, reading mathematics, and cognitive and meta-cognitive functioning. Assessment practices in the Indian context are discussed. The contribution by Kapur focuses on specific learning disabilities (SLD) in the Indian context and explores how the school system influences the attainment and deficits in basic academic skills. She points out that in India, assessment is a complex issue and needs to be examined in the context of the school system and psychosocial factors. Management needs to be developmentally based and both, eclectic and holistic. In Indian school settings, teachers have often been used for identifying children with learning disabilities. The next three chapters by Konantambigi and Shetty, Tripathi and Kar, and Yadav and Agarwal have examined how teachers can contribute to this process. Konantambigi and Shetty worked with teachers in municipal and private schools in Mumbai and found a close correspondence between teacher identification of children and their scores on the Diagnostic Test of Learning Disabilities. Tapping a hitherto unexplored area, Tripathi and Kar constructed checklists to facilitate the identification of learning problems in school children in Allahabad. The most frequently reported problems by teachers included language and writing problems while behavioral problems were found to decline with age. Another baseline study was conducted by Yadav and Agarwal to assess the extent and prevalence of learning disabilities in rural schools in Allahabad. The characteristics of learning disabled children, teachers’ awareness of learning and remedial classroom practices were also investigated.

Preface

21

Lamenting the fact that many assessment and intervention practices are neither based on any sound theoretical background, nor have stated objectives of facilitating transfer to other situations, Pagedar and Mehta presented a theory-driven approach based on the PASS model of cognitive functioning. They used the Cognitive Assessment System and the PASS Reading Enhancement Programme (PREP) on small samples of children with learning disabilities. Mehta, in her chapter “Scaffolding to Learn”, demonstrated the efficacy of a strategy training program (S-SWEL) in improving the problem-solving skills of students with learning disabilities. The next chapter by Mongia, Sadhu, and Mehta studied children with specific learning disabilities in a medical setting (All India Institute of Medical Sciences, New Delhi) and recommended the use of diverse assessment and intervention procedures. It is evident that the entire area of learning disabilities in India is still confronting fundamental and basic issues pertaining to assessment and interventions. Some beginnings have been made and but these have been sporadic, atheoretical, and at times ad hoc. This book is an attempt to present the current scenario in research and practice. On no account does it claim to be comprehensive. Many promising leads and initiatives have been taken and, in the meanwhile, the area itself continues to grow, disturb, and fascinate.

1 Learning Disabilities Issues and Concerns KOMILLA THAPA

When speaking to groups, I explain that being dyslexic is like running a 100-meter track race. In my lane I have hurdles, but no one else does. I have this feeling that it’s unfair that I’m the only one with hurdles but don’t know how to explain it. Soon the feeling leaves me as the starting gun shoots and I take off running. I try running like the other classmates, because we have all had the same education on how to run. But then I hit the first hurdle and fall flat on my face. My parents and teachers are yelling at me from the sidelines, try harder, the other kids are making it down the track ok, you must be lazy or slow. Pulling myself up I try running faster and fall even harder after hitting the next hurdle. Then someone takes the time to show me how to run hurdles and like an Olympic hurdler, I outrun the other classmates. The key, though, is that I have to do it differently, the way that works best for me. Learning is like a tailored suit; it takes a while and is unique to everyone. —(Girard J. Sagmiller, 2005, p. 1) There is a huge hill. I like to ride my bike down that very steep, dark, and bumpy hill. When I ride down that hill I feel the wind hitting my face. I like to pick up a lot of speed and perform some tricks on my bike. When I am at the bottom of the hill, I will turn a corner and ride over some bumps in the road. Once I come to a dead end, I circle around and peddle up the hill. And I will do the same thing over and over again. —Cameron (2005, p. 1), Grade 5, A student with a learning disability

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Komilla Thapa

This introductory section begins with two first-hand accounts which more evocatively than any other words illustrate the chiaroscuro of experiences and feelings that people with learning disabilities undergo. Learning disabilities (LDs) remain “one of the least understood and most debated disabling conditions that affect children” (Lyon, 1996b, p. 3). Indeed, the field continues to be beset by pervasive and occasionally contentious disagreements about the definition of the disorder, diagnostic criteria, assessment practices, treatment procedures, and educational policies. Learning disability is not a single disorder, but is composed of disabilities in any of the seven specific areas: 1. 2. 3. 4. 5. 6. 7.

receptive language (listening), expressive language (speaking), basic reading skills, reading comprehension, written expression, mathematics calculation, and mathematical reasoning.

These separate types of LDs frequently co-occur with one another and also with certain social skill deficits and emotional or behavioral disorders such as attention deficit disorder. LDs are not synonymous with reading disability or dyslexia although it is frequently misinterpreted as such. However, a caveat needs to be issued at this juncture. Lerner (1989) in her analysis of public school referral data found approximately 80 percent of children identified as LD to have their primary difficulties in learning to read. This high rate of occurrence in reading difficulties among learning-disabled youngsters has also been reported by Kavale (1984). More recent longitudinal and crosssectional studies have supported the high rate of learning difficulty among children with LDs, but have also found that reading deficits frequently co-occur with other academic and attentional difficulties (for example, Fletcher et al., 1994). Accordingly, many of the studies cited in this Introduction would refer to reading disabilities (RD).

Learning Disabilities

25

Learning Disabilities is an active area of research. Within the last few decades, many professionals from fields other than those traditionally associated with LDs have shown increased interest in the topic. In particular, well-trained researchers from the fields of psychology, medicine, and linguistics have made important new contributions to the knowledge about LDs. A distinction has been made between LDs as an applied field of special education and LDs as an area of research on individual differences in learning and performance. In the former sense, the field shares many attributes with other political–social movements, while in the latter sense, it is a loosely jointed, interdisciplinary area of scientific enquiry (Torgesen, 1991a). The confusion and occasional conflict between these two aspects of the field has created many problems over the course of its history and continues to be a source of difficulties for the field. Learning Disabilities is an unusual discipline as it contains two contrasting aspects: one, intellectual and the other practical (Wong, 1991, p. xvii). Although LDs is solidly established as an important category of exceptionality in both research and educational practice, it is also an area marked by controversy. As one writer suggested, “It seems as though the field is constantly getting into scrapes, is always on probation, is never really secure” (Stanovich, 1989). Despite the field’s solid accomplishments, controversy continues about many important issues. Some of these issues go to the very heart of the concept while others involve difficult and relatively esoteric research-conceptual issues. As elaborated by Torgesen (1991a) the issues that threaten the existence of the field include disagreements about basic definitions of learning disabled (LD) children, problems in diagnostically differentiating LD children from other types of children who show a variety of achievement and adjustment problems in school, challenges to the assumption that LDs results from inherent or biological impairment in specific brain function, and difficulties dealing with the heterogeneity of the LD school population. While there is some agreement about these general concepts, there is continued disagreement in the field about diagnostic criteria, assessment practices, treatment procedures, and educational policies for LDs. A number of influences have contributed to these disagreements which, in turn, have made it difficult to build a generalizable

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Komilla Thapa

body of scientific and clinical knowledge about LD, and to establish reliable and valid diagnostic criteria. As stated by Lyon (1996c, p. 57) “ . . . the field of learning disabilities emerged primarily from a social and educational need and currently remains a diagnostic practice that is more rooted in clinical practice, law, and policy than in science.” Accordingly, this introductory section will focus on some of the most pervasive and contentious issues that have stymied progress in this field. As pointed out by Karanth (2003), in India these issues have gained salience only during the last decade. While epidemiological studies in India have been few, there has been an increase in the identification of individual children with LDs and a consequent demand for services. Suresh and Sebastian (2003) have found a large incidence of LDs even in rural areas in Kerala, attesting to the view that LDs is a widely prevalent, life span disorder. There are many associated features of LDs that are specific to the Indian context. These include the fact that bilingualism and multilingualism are common, classroom conditions are far from ideal, and socio-economic factors, often mentioned in passing in Western studies, have undoubtedly a more significant role in this context. For instance, in the US it is accepted that poverty and disability are often found together and each tends to exacerbate the other; there are separate program to serve children with disabilities and children in poverty. As the number of economically disadvantaged children in India is much larger, this American blueprint, not supported by empirical data and based on exclusionary criteria would not be a useful model to emulate. Keeping in mind the fact that LDs research and practice is at a nascent stage in India, the issues that require greater focus and more intensive investigation in India may be more fundamental and basic, and at times more specific to this context. These would include the definition of LDs, procedures for identification and assessment, the progression of LDs over the life span, prevention and interventions, and contextual factors. An additional area would include findings from neuroimaging and brain research, which have led to quantum changes in the conceptualization of LDs. It is possible to take the position that many of these debates can be informed by converging scientific data. On the basis of this evidence, Lyon et al. (2001) in their authoritative paper have contended that many of

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the persistent difficulties in developing valid classifications and operational definitions of LD are due to reliance on incorrect assumptions about causes and characteristics of the disorders. They further argue that sufficient data exist to guide the development and implementation of early identification and prevention program for children at-risk for LDs. Another compelling reason is that the contributing authors to this volume have also dealt with these issues. Opinions about what constitutes a LD vary in part because LD is the concern of many disciplines and professions. Each of these disciplines has traditionally focused on different aspects of the child or adult with learning disability, so divergent ideas and contentious disagreements exist about the importance of etiology, diagnostic methods, intervention methods, and professional roles and responsibilities (Torgesen, 1991a). At the outset, a cautionary note is in order. There has been a veritable tidal wave of studies in this area. Clearly, a review of the same would not only be a daunting task but would also exceed the brief with which I started this section. As such, only such studies are being presented which would contribute to an understanding of LDs and the growth of the field in India. Further, as many of the issues under scrutiny have cross linkages, a more seamless account would have been fitting. However, to ensure clarity in discourse, an arbitrary distinction is being made though at times a discrete discussion of one issue without reference to the others is not possible.

DEFINITIONS

OF

LEARNING DISABILITIES

Definitional issues have been pervasive and continue to be marred by conflict and controversy. Arguments over definition have been continuous from the time that the term LDs was popularized in the early 1960s. Several revisions and modifications later, a consensual definition is yet to emerge, which has universal endorsement and approbation. The dominant definition incorporated into federal legislation was born out of compromise (Adelman and Taylor, 1986). The Education for all Handicapped Children Act of 1975 (PL-142) provides a definition based primarily on that proposed by the National Advisory Committee on Handicapped Children in 1968

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and subsequently incorporated into the Individuals with Disabilities Education Act of 1990 (IDEA) as follows: The term “specific learning disability” means a disorder in one or more of the basic psychological processes involved in understanding and using language, spoken or written, which may manifest itself in an imperfect ability to listen, speak, read, write, spell, or do mathematical calculations. The term includes such conditions as perceptual handicaps, brain injury, minimal brain dysfunction, dyslexia, and developmental aphasia. The term does not include children who have Learning Disabilities that are primarily the result of visual, hearing, or motor handicaps, or mental retardation, or emotional disturbance, or of environmental, cultural or economic disadvantage. —Individuals with Disabilities Education ACT (IDEA) (1990) PL101-476,20 U.S.C. Chapter 33, Sections 1400–485, p. 6).

Torgesen (1991b) wrote that this definition had at least four major problems. First, the definition did not indicate that LDs are a heterogeneous group of disorders; second, the definition failed to recognize the persistence of LDs into adulthood; third, it does not clearly specify that the final common path involves inherent alterations in the way information is processed regardless of the cause. Finally, the definition does not recognize that individuals with other disabilities or environmental limitations may have a learning disability concurrently with these conditions. This definition has four conceptual elements that are common across a number of definitions of LDs (Lyon, 1996a). These elements are: 1. the heterogeneity of LDs; 2. its intrinsic or neurobiological nature; 3. a significant discrepancy between learning potential (typically assessed by measures of intelligence) and academic performance (typically assessed by measures of reading, writing, mathematics, and oral language skills); and 4. the exclusion of cultural, educational, environmental, and economic factors, or other disabilities (mental retardation, visual or hearing impairments, emotional disturbance) as causes of LDs. Despite the ubiquity of these elements in LDs definitions, their validity has been rarely examined. As these aspects have

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far-reaching implications and consequences, it would be important to consider each of these aspects. However, the last two elements pertaining to IQ-achievement discrepancy and exclusion criteria will be discussed in the next section dealing with issues of identification and assessment. As far as the heterogeneity element is concerned, the definition includes seven areas of disability and the heterogeneity within and across each academic domain makes diagnostic precision impossible. There are, by and large, different forms of LDs. Their characteristics and learning needs vary. Reading and mathematics disorders, for example, vary along multiple dimensions. Thus Lyon et al. (2001) recommend that these disorders should be treated as seven separate disorders and emphasize the need to develop separate evidence-based definitions for each. Another essential element deals with the assumption that neurobiological factors are the basis of LDs. Most definitions of LDs continue to attribute disabilities in learning to intrinsic (neurobiological) rather than extrinsic (environmental or instructional) causes even though there was initially no objective way to assess the presence of putative brain dysfunction. Neurobiological factors have been most closely studied in the area of reading. Converging evidence from neuroimaging modalities indicates a pattern of brain organization in reading disorders that is different from non-impaired readers. These studies also suggest the possibility that the resultant neural circuitry reflects not only the individual’s biological makeup but also the environmental influences. Central among these influences is how reading instruction impacts brain circuitry. These findings suggest that neural systems develop and are deployed for specific cognitive function through the interaction of the brain and the environment. The controversies over definitions of LDs have been long-standing and some writers have recommended that the usage of the term be discontinued, particularly in the scientific realm and more in specific terms such as reading disability or arithmetic disability be used to describe the specific domain or deficit area where the problem exists. Berninger and Abbott (1994) have called for a redefinition of LD, departing from the concept of discrepancy between aptitude and achievement. In its place, they believe LD may be conceptualized as a failure to respond to validated intervention and treatment programs.

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Other terms that have gained currency include language learning disabilities used extensively by Butler and Silliman (2002). They emphasize the central role of language in all learning. Based on crosssectional and longitudinal studies of different aspects of language such as derivational morphology, they attempt to bridge the fuzzy boundaries between language disabilities and reading problems (Silliman et al., 2002). Similar concerns are dealt with by Karanth (Chapter 3). In summary, Lyon (1996b) stated that the federal definition is “virtually useless with respect to providing clinicians and researchers with objective guidelines and criteria for distinguishing individuals with LDs from those with other primary disabilities or generalized learning disabilities” (p. 6). In accord with Lyon’s earlier statement, Stanovich (1999) has written that the umbrella term LDs does nothing but confuse. “The domain specific disabilities should be treated separately and labeled separately . . . Comorbidity becomes an issue ‘after’ the initial domain-specific classification has been carried out” (p. 350): The logic underlying the development of such a classification system is that diagnosis, intervention, and prognosis . . . cannot be addressed effectively until the heterogeneity across and within domain-specific learning disabilities and subgroups and subtypes are delineated that are theoretically meaningful, reliable, and valid (p. 8).

PROCEDURES

FOR IDENTIFICATION AND

ASSESSMENT

To ensure logical consistency and coherence, the issues related to IQ-achievement discrepancy and exclusion criteria are included in this section as they specifically pertain to the identification of LDs. No definitional element has generated as much controversy as the use of IQ-achievement discrepancy in the identification of students with LDs (Fletcher et al., 1998). Initially, practitioners had been intrigued by the seemingly paradoxical inability of some children of average and superior intelligence to master academic concepts. At that point of time, the use of an IQ-achievement discrepancy as one way to “objectively determine” the presence or absence of LD was probably reasonable. The notion of using an IQ-achievement discrepancy as a marker for unexpected achievement was also

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consistent with the still prevailing, albeit inaccurate, view that IQ scores are robust predictors of an individual child’s ability to learn. Despite admonitions by Thorndike and others (Thorndike, 1963; Reynolds, 1974) that IQ scores reflect primarily a gross estimate of current general cognitive functioning and should not be used as a measure of learning potential, the IQ-achievement discrepancy as a meaningful diagnostic marker for LDs was accepted in policy and practice in 1977, and has been in general use ever since. Since the late 1980s and the early 1990s, studies published on reading disorders in children have cast doubt on the utility and validity of the notion of discrepancy (Fletcher et al., 1992; Siegel, 1993). It is the IQ component of the discrepancy model to which the majority of these researchers have objected. Reynolds (1974) has pointed out that the actual comparison of academic achievement scores with IQ scores to derive a discrepancy value is fraught with psychometric, statistical, and conceptual problems that may render many comparisons useless. When employed “inappropriately” as the primary criterion for identification of LDs, this discrepancy, may well harm more children than it helps. Most definitions of LDs have an exclusion clause, stating that LDs is not the primary result of other conditions that can impede learning. These include mental retardation; emotional disturbance; visual or hearing impairments; inadequate instructional opportunities; and cultural, social or economic conditions. Given the primacy of the exclusion element within definitions of LD, many children thus identified have been diagnosed on the basis of what they are not, rather than what they are. This is unfortunate for three major reasons. First, it downplays the development of clear inclusionary criteria, and second an exclusionary definition is a negative definition that adds little conceptual clarity. As Rutter (1978) has argued, this approach suggests that if all known causes of the disorder can be excluded, the unknown (in the form of LDs) can now be invoked. Third, and most important, many of the conditions excluded as potential influences on LDs are factors impeding the development of cognitive and linguistic skills that led to academic deficits frequently observed in LD children. One exclusionary criterion that is particularly difficult to reconcile is the student’s instructional history. All definitions exclude

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children from consideration if their learning problems are primarily a product of inadequate instruction. Of all the different assumptions in the concept of LDs, this one is the least examined. This criterion could be interpreted to indicate that children who profit from instruction do not have a biologically based LD. However, neuroimaging studies suggest that instruction may be necessary to establish the neural networks that support reading. This carries the clear implication that no child is born a reader; all children have to be taught to read. The ability to read and write is explicitly built upon our natural capacities for developing oral language. Similarly, most definitions exclude children from the LDs category whose learning difficulties may be related to environmental, cultural, or economic disadvantage. Yet these very conditions place some children at significant risk for weaker neural development and secondary learning difficulties. Poor socio-economic conditions (for instance, malnutrition and limited pre- and post natal care) can place children at-risk for neurological dysfunction leading to cognitive, linguistic, and academic deficits (Hallahan et al., 1996). By working with a disadvantaged group (the Dalits), Pandey and Pant (Chapter 5) have shown how centuries of social ostracism and educational deprivation have resulted in negative school outcomes and poor achievement. It is clear that there are a number of conceptual and methodological barriers to the accurate identification of LDs, and these impediments have lead to confusion about definitions, diagnostic issues, and rising prevalence rates. The substantial increase in the identification of LD in the US has caused many researchers to question the validity of the data. This issue is of salience in India as well where the field is still in its infancy and the problems of “false positives” and erroneous identification a very real one. No doubt, the failure to develop an accepted operational definition of LD gives credence to the concern about the validity of the identification process. Thus, it seems reasonable to assume that at least some of the increase in prevalence can be linked to conceptual, methodological, social, and political factors that have spuriously inflated the identification of children with LDs (Lyon, 1987). It has further been pointed out that improved research, broader definitions, increased identification of LDs in girls, increased awareness and understanding that even mild

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deficits are likely to portend significant difficulties are some of “sound reasons” presented by Lyon (www.futureofchildren.org) as explanatory factors in increased prevalence. To improve the diagnosis and remediation of LDs, a classification system is needed to identify different types of LDs as well as the distinctions and interrelationships among types of LDs and other childhood disorders (Lyon, 1996a; Fletcher et al., 1993). The prospective longitudinal studies are one of the most powerful means to study the different types of LDs and their relationships to other disorders and to obtain data for a focused and succinct definition. An agenda for research was proposed by Lyon (1996c) which would facilitate the identification of critical learning and behavioral characteristics that may be manifested in different ways at different developmental periods, help in the development of early predictors of under achievement for different domains (for example, reading, written language, math), as well as in mapping the developmental course of different types of LDs. In addition, there is a need to identify commonly co-occurring disorders and secondary behavioral consequences that develop in response to failure in school, and assess the efficacy of different treatment and teaching methods for different types of LDs.

PROGRESSION OF LEARNING DISABILITIES OVER THE LIFE SPAN The developmental, life span approach is pertinent to our concerns with LDs, as it is increasingly clear that LDs may not be limited to a particular age group or to a particular setting (Keogh and Sears, 1991). Learning Disabilities are no longer thought to be school specific or to be the exclusive province of elementary school children (Katz et al., 2001). Applying a developmental framework to LDs raises some interesting but troublesome questions pertaining to the developmental or educational implications of LDs over the life span, the validity of early indicators for predicting subsequent problems and the factors that contribute to change or stability within and across developmental periods. Of particular interest are issues of early identification and

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prediction drawing upon previous research on at-risk children. Geerdina van der Aalsvoort, in her Chapter 2, examines the educational alternatives available for at-risk children in the Netherlands. The findings from longitudinal research (for example, Nichols and Chen, 1981; Werner and Smith, 1982; Hartzell and Compton, 1984; and Badian, 1988) have identified two major sets of variables as important contributors to risk. These included characteristics of the children themselves (for instance, most studies have documented that more boys than girls were problem learners) and the impact of the social-familial environment (in particular poverty and the conditions associated with poverty) in the development of at-risk children was striking. While it is now accepted that LDs are, in part, a result of child and situational characteristics, procedures for identification are focused exclusively on the child. It is also clear that risks or disabilities are not always invariant or stable. Sameroff and Chandler’s (1975) review of the consequences of early problem conditions demonstrates clearly that arrangement of variables and experiences affect developmental outcomes for children identified as at-risk. In spite of the preoccupation with problems and deficits, it is important to recognize that developmental outcomes are also affected by children’s compensating abilities or strengths. While studies have identified a subset of children who continued to evidence problems across developmental periods, there are also children who developed well (the “vulnerable but invincible” group). The key factors in the development of resilient children were found in their homes and families which were characterized by strong affective ties and supportive kinship networks. The notion of resilience and the identification of positive attributes of children and families add to our understanding of risk and point to the direction of needed services and interventions. The formal screening to identify students who have problems or who are “at risk” is accomplished through individual or group procedures. Most of such procedures are first-level screens and are expected to over-identify problems. That is, they identify many students who do not really have significant problems (false positive errors). This certainly is the case for screens used with infants and primary grade children, but false positives are not uncommon when adolescents are screened. Errors are supposed to be detected

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by follow-up assessments. Because of the frequency of false positive errors, serious concerns arise when screening data are used to diagnose students, and prescribe remediation and special treatment. Screening data primarily are meant to sensitize responsible professionals. No one wants to ignore indicators of significant problems. At the same time, there is a need to guard against tendencies to see normal variations in students’ development and behavior as problems. Screens do not allow for definitive statements about a student’s problems and needs. At best, most screening procedures provide a preliminary indication that something may be wrong. In considering formal diagnoses and prescriptions for how to correct the problem, one needs data from assessment procedures that have greater validity. It is essential to remember that many factors found to be symptoms of problems also are common characteristics of young people, especially in adolescence. This means extreme caution must be exercised to avoid misidentifying and inappropriately stigmatizing a youngster. A dictum to be followed is to never overestimate the significance of a few indicators. As Garbarino (1990) has pointed out risks to development can come both from direct threats and from the absence of normal, expectable opportunities. Besides such obvious biological risks like malnutrition or injury, there are socio-cultural risks that impoverish the developing individual’s world of essential experiences and relationships, and therby threaten development. A systems approach may help in understanding the complex interplay of biological, psychological, social, and cultural forces in early developmental risks and their amelioration.

INTERVENTIONS

AND

PREVENTION

Over the past decade there has been renewed interest in facilitating early development and learning. Three movements have added impetus to formalize interventions to ensure this happens. One push comes from the interpretations of recent brain research that underscore the influence of early experiences on the developing brain. A second thrust arises from research showing positive outcomes from early interventions with children who have special needs. A third

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influence is filtering down from the school accountability movement which is pressuring kindergartens and pre-schools to focus their efforts on reading readiness. In doing so, the concern is with interventions that can counter the negative impact of external and internal factors that can interfere with development and learning. Another imperative to intervention comes from research evidence that has clearly indicated that the longer children with LDs, at any level of severity, go without identification and intervention, the more difficult the task of remediation becomes, and the harder it is for children to respond. Specifically, the data strongly suggests that children at-risk for reading failure should be identified before the age of nine if successful intervention results are to be anticipated (Lyon, 1996b). There are a variety of genetic, prenatal, perinatal, and postnatal factors that can lead to variations in development and problems with learning and behavior. Because the seeds are planted early, early-age intervention is indicated. In a real sense, early-age intervention represents a basic application of the principle of least intervention needed. This principle calls for efforts to prevent problems before they appear, meeting specific needs as soon as they are apparent, and doing so in the least intrusive and disruptive manner feasible. A proactive approach to addressing barriers involves doing something to prevent them. Some high-risk children are easier to identify than others. In the easy cases, procedures are used to find and refer them to special programs. However, because there are spurts and plateaus in human development, it can be difficult to differentiate problems from normal variations. When identification is difficult, rather than screening for individual problems, broad-band prevention programs are indicated. Two major forms of preventive intervention are advocated widely. One is the provision of pre-, peri-, and neonatal care, such as prenatal and well-child clinics and infant immunization outreach services. A second form is community education, such as parent programs to improve infant or child nutrition and physical safety, and to increase stimulation. A strong intervention emphasis is on enhancing individual capabilities (for example, assets) and protective factors in order to minimize the impact of current and subsequent environmental deficiencies

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and personal vulnerabilities. The focus for young, at-risk children may aim at fostering development in a combination of areas (perceptual, motoric, language, cognitive, social, and emotional). Usually there are activities related to gross and fine motor skills; language (especially communication skills), visual and auditory perceptions; memory, basic cognitive and social competence (problem solving and self-help skills, cooperative social interactions); and positive feelings about self and others. It should also be unequivocally stated that an introduction of this nature has its own agenda and cannot provide a comprehensive review of the varied intervention strategies and approaches that are prevalent in the field. Targeted early interventions are those intended to overcome the cognitive, emotional, and resource limitations that may characterize the environments of disadvantaged children during the first several years of life. They include programs targeting children as well as those targeting their mothers; interventions aimed at improving educational achievement and those aimed at improving health; and services as diverse as parent skills training, child health screening, child abuse recognition, and social-services referral. Instructional interventions include scaffolding (Stone, 2002). Central to the scaffolding metaphor are the two notions of support and relinquishment. Scaffolded instruction supports the child’s construction of new understandings, but it does so in a manner that allows for the eventual removal of that support. Such instruction has been seen as a powerful force in helping children to take ownership of new knowledge and procedures. This approach has also been used by Mehta and reported in this volume (Chapter 12). Other promising interventions include the use of peer discourse (Donahue, 2002) and social communication with the peer group (Prelock, 2002). Studies have provided convincing evidence that LD children are at high risk for difficulties in peer discourse. It is not enough to recognize that children with language and learning disabilities differ from peers in encoding and/or interpreting social cues and have less access to appropriate social responses. Interventions will not be effective until we have a deeper understanding of the interactive contributions of individuals’ database of experiences, social goals, and self-efficacy, and the feedback they receive from peers (Donahue, 2002). Many studies have also described the problems

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experienced by children with language learning disabilities when engaging in peer interaction. Withdrawal is a frequently cited characteristic of such children and is seen as a probable limitation for the successful access of peers in social interactions (Brinton et al., 1997). Three specific intervention strategies have been recommended— capitalizing on classroom literacy activities, utilizing classroom scripts in role play, and facilitating problem solving. These are promising interventions that could be used to enhance social competence, for as Donahue (2002) has pointed out children’s access to the academic curriculum is dependent on their ability to engage in cooperative peer group activities.

CONTEXTUAL FACTORS A number of studies cited in the preceding sections have already dealt with contextual factors. In particular while discussing at-risk children and poverty and disadvantage, contextual variables are inevitably interwoven in the discourse. However, the factors merit separate discussion as well. It has been argued that the majority of students identified as having LDs are not intrinsically disabled but have learning problems because of poor teaching, lack of educational opportunity, or limited educational resources (Coles, 1987). In addition, because the label of LD is not a stigmatizing one, parents and teachers may be more comfortable with a diagnosis of LD than with labels, such as slow learner, minimal brain dysfunction, or perceptual handicap. In India, contextual factors have rarely been subjected to scientific scrutiny and studies have in the main focused on the prevalence, identification, assessment, and cognitive profiles of LD students. While assessing risk to families from the social environment, economic deprivation or poverty has often been identified as the principal villain. The experience of poverty has extremely damaging effects in early childhood (Centre for Mental Health in Schools at UCLA, 2001). Scientific evidence has also begun to document that extreme poverty early in life has an even greater effect on children’s future life chances and development than less extreme poverty later in childhood (Korenman et al., 1995).

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Karanth (2003) has pleaded the case for environmental factors that are associated with LD. As enumerated by her, these include poverty, parental illiteracy, lack of exposure to literacy skills in the home environment, lack of access to pre-school instruction, lack of command over the instructional medium, overcrowded classrooms, and poor instruction. Thus she asserts, “Often LD reflects the accumulated effects of several of these risk factors” (p. 21). Snow et al. (2000) in their report have identified several group factors as constituting risk factors for LD. These include poor schools, low income/poor neighborhoods, limited proficiency in medium of instruction, and dialectal difference in language. Many of these factors are pervasive in the Indian socio-cultural context and educational systems and would require closer examination. Perhaps an ecological approach would be a more satisfactory approach and would enable us to study the many different factors that contribute to LDs. An ecological perspective (Garbarino, 1990) constantly reminds us that child development results from the interplay of biology and society, from the characteristics children bring with them into the world, and the way the world treats them, from nature and nurture. In this it reflects what Pasamanick (1987) calls social biology. It is important to recognize that the habitat of the child at-risk includes family, friends, neighborhood, and school, as well as less immediate forces that constitute the social geography and climate (for example, laws, institutions, and values), and the physical environment. The interplay of these social forces and physical settings with the individual child defines the range of issues in the forefront of an ecological perspective. The most important characteristic of this ecological perspective is that it both reinforces our inclination to look inside the individual and encourages us to look beyond the individual to the environment for questions and explanations about individual behavior and development. It emphasizes development in context. Another related issue that may be context-specific deals with bilingualism and multilingualism. Balasubrahmanyam (2001) has speculated that the incidence of dyslexia would be less in India as those literate in the major Indian scripts received intensive phonic training and the Indian methods of writing (orthographies) were

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transparent. Nehru (2001) has also pointed out that Hindi has a nearly absolute one-to-one grapheme-phoneme consistency. Studies of Hindi dyslexia repeatedly found error rates on non-initial vowels and bundled consonants were approximately 10 times the error rates on initial vowels and ordinary consonants. The spatial configuration of Hindi non-initial vowels and bundled consonants was exceedingly complex and it was hypothesized that at the time of learning to read, this placed extraordinary demands on right hemispheric strategies, already compromised in dyslexic children. Dyslexic reading errors, he maintained resulted from a mismatch between the perceived graphic character and its distorted graphemic representation. Gupta (Chapter 4) has analyzed the reading errors of Hindi-speaking dyslexic children and found a greater number of graphemic errors.

NEUROIMAGING STUDIES This final section will focus on some of the insights gained from neuroimaging studies, which have further refined and clarified our understanding of LDs. The research in brain-behavior relationships has a long history. Current research has benefited enormously from advances in neuroimaging techniques which “ . . . provide a window to the neurological bases of sensory, motor, attentional, perceptual, linguistic, and cognitive development” (Lyon and Rumsey, 1996, p. 1). It seems fair to say that neuroimaging techniques represent a quantum leap in our understanding of brain-behavior relationships and hold a great promise for the study of individuals with developmental and learning problems (Keogh, 2002). The Yale studies (Shaywitz et al., 1997; Shaywitz et al., 1998) studied three component processes of reading—orthographic coding (letter identification), phonological coding (phoneme identification), and lexical-semantic coding (word meaning). The findings confirmed that different areas of the brain are activated by specific aspects of the reading task. Orthographic stimuli activate regions in the back of the brain; phonologic stimuli activate Broca’s area; semantic stimuli activate regions in the midbrain. They also found that during phonological tasks, brain activation in men is lateralized to the left inferior frontal gyrus

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regions; in women, activation is more diffuse involving both left and right inferior frontal gyrus. The Colorado investigators (DeFries et al., 1997) have used neuroimaging methods to assess neural functions of children with reading disabilities and those with adequate reading skills, identifying gender effects, and a reading disability by gender interaction on brain structures. They have documented heritable influences as contributors to deficits in reading (Pennington, 1995). Researchers of this group have also developed and tested a computer-based instructional program targeted at deficits in phonological processing skills and reading comprehension (Wise and Olson, 1994; 1995). Several investigations have indicated that phonologically-based reading disabilities are linked to neurobiological and genetic factors. The functional and structural neuroimaging studies indicate that the poor phonological skills, which limit the development of basic reading abilities, are highly related to aberrant neuro-physiological processing (Wood et al., 1991). Moreover, there is increasing evidence from behavioral and molecular genetic studies that the phonological deficits observed in RD are heritable (Pennington, 1995). Taken together, longitudinal studies of the linguistic, neurobiological, and genetic factors in RDs provide strong and converging evidence that RD is primarily caused by deficits in phonological processing and, more specifically, phonological awareness. Likewise, the data derived from genetic and neurobiological studies suggest that some RDs are associated with subtle chromosomal and neurological differences, indicating that such disabilities are biologically “real” rather than socio-politically created. The primary emphasis of neuropsychological research concerning dyslexia has focused on the planum temporale (PT) of the left posterior temporal lobe, which is one of the neural regions implicated in phonological processing (Hynd and Hiemenz, 1997). For most people, the PT of the left and right hemispheres are asymmetric, the left PT being larger than the right (L > R). Neuroimaging reveals that dyslexic subjects often exhibit left–right PT symmetry (L = R) or reversed normal asymmetry (R > L). While early studies supported the idea that dyslexia was associated with anomalous PT asymmetry, recent work has failed to find this association (Eckert and Leonard, 2003).

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Two other neural regions have received attention in the study of dyslexia, the corpus callosum and the frontal cortex. These studies found that the anterior and posterior portion of the corpus callosum of dyslexic individuals either differed from, or were comparable to, the same regions of subjects who were not reading disabled (Larsen et al., 1992). Causal explanations centered on increased or decreased interhemispheric communication, or inappropriate inhibition of one hemisphere by the other. As far as the frontal cortex is concerned, researchers observed tentative differences between proficient and disabled readers. Children with dyslexia presented bilaterally smaller frontal cortexes than normal control children (Hynd et al., 1990) and the smaller width of the right anterior frontal cortex (Semrud-Clikeman et al., 1996) was one of the several anatomic variables that discriminated among dyslexic and normal children. As pointed out by Hoien and Lundberg (2000) cultural, social, and educational factors are of critical importance when trying to understand why some individuals have an unsuccessful relationship with the written language. But there is much to indicate that individual biologically determined factors are also important.

CONCLUSION The past decade has witnessed a significant improvement in the quality of research on LDs. Much of this recent research has been longitudinal in nature, thus opening the door to the identification of better predictors of different types of LD, their prevalence, developmental course, and response to intervention. The time is ripe for action, to replace rhetoric with reason. As stated by Lyon et al. (2001), “The real tragedy is that conceptualizations of LD have not changed over 30 years despite the completion of significant research in the past 15 years. What we know from research now needs to be implemented. Children deserve no less” (p. 25). With these perspectives in mind, an International Conference on Learning Disabilities and Young-At-Risk, sponsored by the UGC Centre for Behavioural and Cognitive Sciences, Allahabad University was organized on February 19–21, 2003.

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REFERENCES Adelman, H.S. and L. Taylor. (1986). ‘The Problems of Definition and Differentiation and the Need for a Classification Schema’, Journal of Learning Disabilities, 19(9): 514–20. Badian, N. (1988). ‘The Prediction of Good and Poor Reading before Kindergarten Entry: A Nine-Year Follow-Up’, Journal of Learning Disabilities, 21(2): 98–103. Balasubrahmanyam, S.N. (2001). ‘Dyslexia And Intercultural Comparisons’, Current Science, 81(8): 872–75. Available from http://www.ias.ac.in/currsci/ oct252001/872.pdf. (Accessed on 29 December 2005). Berninger, V.W. and R.D. Abbott. (1994). ‘Redefining Learning Disabilities: Moving Beyond Aptitude-Achievement Discrepancies to Failure to Respond to Validated Treatment Protocols’, in G.R. Lyon (ed.), Frames of Reference for the Assessment of Learning Disabilities: New Views on Measurement Issues, pp. 163–84. Baltimore, MD: Paul H. Brooks. Brinton, B., M. Fujiki, J. Spencer and L. Robinson. (1997). ‘The Ability of Children with Specific Language Impairment to Access and Participate in an ongoing Interaction’, Journal of Speech, Language, and Hearing, 40(5): 1011–25. Butler, K.G. and E.R. Silliman (eds). (2002). Speaking, Reading, and Writing in Children with Language Learning Disabilities: New Paradigms in Research and Practice. Mahwah, NJ: Lawrence Erlbaum. Cameron. (2005). ‘First Person.’ Available from www.LDonline.org. Accessed on 24 December, 2005. Centre for Mental Health in Schools at UCLA. (2001). An Introductory Packet on Early Development and Learning from the Perspective of Addressing Barriers. Los Angeles, CA: Author. Available from http://smh.psych.ucla.edu). Accessed on 12 April 2004. Coles, G. (1987). The Learning Mystique: A Critical Look at Learning Disabilities. New York: Pantheon Press. DeFries, J.C., P.A. Filipek, R.K. Fulker, R.K. Olson, B.F. Pennington, S.D. Smith and B.W. Wise. (1997). ‘Colorado Learning Disabilities Research Centre’, Learning Disabilities. A Multidisciplinary Journal, 8(1): 7–19. Donahue, M.L. (2002). ‘Hanging with Friends’: Making Sense of Research on Peer Discourse in Children with Language Learning Disabilities’, in K.G. Butler and E.R. Silliman (eds), Speaking, Reading, and Writing in Children with Language New Paradigms in Research and Practice, pp. 239–58. Mahwah, NJ: Lawrence Erlbaum. Eckert, M.A. and C.M. Leonard. (2003). ‘Developmental Disorders: Dyslexia’, in K. Hugdahl and R.J. Davidson (eds), The Asymmetrical Brain. Cambridge, MA: The MIT Press. Fletcher, S.E., S.E. Shaywitz, D.P. Shankweiler, L. Katz, I.Y. Liberman, K.K. Stuebing, D.J. Francis, A.E. Fowler and B.A. Shaywitz. (1993). ‘Classification of Learning Disabilities: Relationships with other Childhood Disorders’, in G.R. Lyon, D.B. Gray, J.F. Kavanagh, and N.A. Krasnegor (eds), Better

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Understanding Learning Disabilities: New Views from Research and Their Implications for Education and Public Policies, pp. 27–56. Baltimore: Paul H. Brookes. Fletcher, J.M., D.J. Francis, B.P. Rourke, S.E. Shaywitz and B.A. Shaywitz. (1992). ‘The Validity of Discrepancy-based Definitions of Learning Disabilities’, Journal of Learning Disabilities, 25(9): 555–73. Fletcher, J.M., D.J. Francis, S.E. Shaywitz, G.R. Lyon, B.R. Foorman, K.K. Stuebing and B.A. Shaywitz. (1998). ‘Intelligent Testing and the Discrepancy Model for Children with Learning Disabilities’, Learning Disabilities: Research and Practice, 13(1): 186–203. Fletcher, J.M., S.E. Shaywitz and D.P. Shankweiler, et al. (1994). ‘Cognitive Profiles of Reading Disability: Comparisons of Discrepancy and Low Achievement Definitions’, Journal of Educational Psychology, 86(1): 6–23. Garbarino, J. (1990). ‘The Human Ecology Of Early Risk’, in S.J. Meisels and J.P. Shonkoff (eds), Handbook of Early Childhood Intervention, pp. 78–96. Cambridge: Cambridge University Press. Hallahan, D.P., J.M. Kauffman and J.W. Lloyd. (1996). Introduction to Learning Disabilities. Boston, MA: Allyn & Bacon. Hartzell, H.E. and C. Compton. (1984). ‘Learning Disability: A Ten-year Followup’, Pediatrics, 74(6): 1058–64. Hoien, T. and I. Lundberg. (2000). Dyslexia: From Theory to Intervention. Dordrecht, the Netherlands: Kluwer Academic. Hynd, G.W. and J. R. Hiemenz. (1997). ‘Dyslexia and Gyral Morphology Variations’, in C. Hulme and M. Snowling (eds), Dyslexia: Biology, Cognition and Intervention, pp. 38–58. London: Whurr. Hynd, G.W., M. Semrud-Clikeman, A.R. Lorys, E.S. Novey and D. Eliopulus. (1990). ‘Brain Morphology in Developmental Dyslexia and Attention Deficit Disorder insert Hyperactivity’, Archives of Neurology, 47(8): 919–26. Individuals with Disabilities Education Act (IDEA). (1990). P.L. 101–476, 20 U.S.C. 1400 et seq. Karanth, P. (2003). ‘Introduction’, in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 17–29. New Delhi: Sage Publications. Katz, L.J., G. Goldstein and S.R. Beers. (2001). Learning Disabilities in Older Adolescents and Adults: Clinical Utility of the Neuropsychological Perspective. New York: Kluwer Academic/Plenum Publishers. Kavale, K.A. (1984). ‘Potential Advantages of the Meta-Analysis Techniques for Special Education’, Journal of Special Education, 18: 61–72. Keogh, B.K. (2002). ‘Research on Reading and Reading Problems: Findings, Limitations, and Future Directions’, in K.G. Butler and E.R. Silliman (eds), Speaking, Reading, and Writing in Children with Language Learning Disabilities: New Paradigms in Research and Practice, pp. 27–44. Mahwah, NJ: Lawrence Erlbaum. Keogh, B.K. and S. Sears. (1991). ‘Learning Disabilities from a Developmental Perspective: Early Identification and Prediction’, in B.Y.L. Wong (ed.), Learning about Learning Disabilities, pp. 485–503. San Diego, CA: Academic Press. Korenman, S., J.E. Miller and J.E. Sjaastad. (1995). ‘Long-term Poverty and Child Development in the United States’, Children and Youth Services Review, 17(1–2): 127–51.

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Larsen, J.P., T. Hoien and H. Odegaard. (1992). ‘Magnetic Resonance Imaging of the Corpus Callosum in Developmental Dyslexia’, Cognitive Neuropsychology, 9: 123–34. Lerner, J. (1989). ‘Educational Interventions in Learning Disabilities’, Journal of the American Academy of Child and Adolescent Psychiatry, 28(3): 326–31. Lyon, G.R. (1987). ‘Learning Disabilities Research: False Starts and Broken Promises’, in S. Vaughn and C. Bos (eds), Research in Learning Disabilities: Issues and Future Directions, pp. 69–85. San Diego, CA: College-Hill Press. ——————. (1996a). ‘Learning Disabilities’, in E. Marsh and R. Barkley (eds), Child Psychopathology, pp. 390–434. New York: Guilford Press. ——————. (1996b). ‘The State of Research’, in S.C. Cramer and W. Ellis (eds), Learning Disabilities: Lifelong Issues. Baltimore, MD: Paul H. Brooks. ——————. (1996c). ‘Learning Disabilities’, Special Education for Students with Disabilities, 6(1), pp. 54–74. (www.futureofchildren.org/usr_doc/vol16noART4. pdf). Accessed on December 24, 2005. Lyon, G.R. and J.M. Rumsey (eds). (1996). Neuroimaging: A Window to the Neurological Foundations of Learning and Behaviour in Children. Baltimore: Paul Brookes Publishing Co. Lyon, G.R., J.M. Fletcher, S.E. Shaywitz, B.A. Shaywitz, J.K. Torgesen, F.B. Wood, A. Schulte and R. Olson. (2001). ‘Rethinking Learning Disabilities’, in C.E. Finn, A.J. Rotherman and C.R. Hokanson (eds), Rethinking Education for a New Century, pp. 259–87. Washington, D.C.: Thomas B. Fordham Foundation and the Progressive Policy Institute. Available from http://www.ldonline.org/ ld_indepth/research_digest/rethinking_ld.pdf. Accessed on December 24, 2004. Nehru, R. (2001). ‘Distorted Grapheme Representation: A New Hypothesis to Explain Dyslexic Learning Errors’, Poster P1, Stream 4–6, 5th British Dyslexia Association International Conference. Nichols, P.L. and T.C. Chen. (1981). Minimal Brain Dysfunction. Hillsdale, NJ: Lawrence Erlbaum. Pasamanick, B. (1987, Winter). ‘Social Biology and Aids’, Division 37 Newsletter. Washington, DC: American Psychological Association. Pennington, B.F. (1995). ‘Genetics of Learning Disabilities’, Journal of Child Neurology, 10, supplement 1: 69–77. Prelock, P.A. (2002). ‘Communicating with Peers in the Classroom Context: The Next Steps’, in K.G. Butler and E.R. Silliman (eds), Speaking, Reading, and Writing in Children with Language Learning Disabilities: New Paradigms in Research and Practice, pp. 259–72. Mahwah, NJ: Lawrence Erlbaum. Reynolds, C.R. (1974). ‘Critical Measurement Issues in Learning Disabilities’, Journal of Special Education, 18(4): 451–76. Rutter, M. (1978). ‘Prevalence and Types of Dyslexia’, in A.L. Benton and D. Pearl (eds), Dyslexia: An Appraisal of Current Knowledge, pp. 3–28. New York: Oxford University Press. Sagmiller, G.J. (2005). ‘What is Dyslexia.’ Available online www.dyslexiamylife.org, accessed on December 24, 2005. Sameroff, A.J. and M.J. Chandler. (1975). ‘Reproductive Risk and the Continuum of Caretaking Casualty’, in F.D. Horowitz (ed.), Review of Child Development Research, Vol. IV. Chicago: University of Chicago Press.

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Semrud-Clikeman, M., S.R. Hooper, G.W. Hynd, K. Hern, R. Presley and T. Watson. (1996). ‘Prediction of Group Membership in Developmental Dyslexia, Attention Deficit Hyperactivity Disorder, and Normal Controls using Brain Morphometric Analysis of Magnetic Resonance Imaging’, Archives of Clinical Neuropsychology, 11(6): 521–28. Shaywitz, B.A., S.E. Shaywitz, J.M. Fletcher, K.R. Pugh, R. Gore, T. Constable, R.K. Fulbright, P. Skudlarski, A.M. Liberman, D.P. Shankweiler, L. Katz, R.A. Bronen, K.E. Marchione, J.M. Holahan, D.J. Francis, R. Klorman, D.M. Aram, B. Blachman, K.K. Stiebing and C. Lacadie. (1997). ‘The Yale Centre for the Study of Learning and Attention: Longitudinal and Neurobiological Studies’, Learning Disabilities: A Multidisciplinary Journal, 8(1): 21–29. Shaywitz, S.E., B.A. Shaywitz, K.R. Pugh, R.K. Fulbright, R.T. Constable, W.E. Mencl, D.P. Shankweiler, A.M. Liberman, P. Skudlarski, J.M. Fletcher, L. Katz, K.E. Marchione, C. Lacadie, C. Gatenby and J.C. Gore. (1998). ‘Functional Disruption in the Organisation of the Brain for Reading in Dyslexia’, Proceedings of the National Academy of Sciences, 95(5): 2634–41. Siegel, L.S. (1993). ‘Alice in IQ land or Why IQ is Still Irrelevant to Learning Disabilities’, in R.M. Joshi and C.K. Leong (eds) Reading Disabilities: Diagnosis and Component Processes. Dordrecht, the Netherlands: Kluwer. Silliman, E.R., K.G. Butler and G.P. Wallach. (2002). ‘The Time Has Come to Talk of Many Things’, in K.G. Butler and E.R. Silliman (eds), Speaking, Reading, and Writing in Children with Language Learning Disabilities: New Paradigms in Research and Practice, pp. 3–26. Mahwah, NJ: Lawrence Erlbaum. Snow, C.E., M.S. Burns and P. Griffin (eds). (2000). Preventing Reading Difficulties in Young Children. US National Research Council Report. Washington, DC: National Academy Press. Stanovich, K.E. (1989). ‘Discrepancy Definitions of Reading Disability: Has Intelligence Led us Astray?’ Address presented at the Joint Conference on Learning Disabilities, Ann Arbor, Michigan, June. ——————. (1999). ‘The Sociometrics of Learning Disabilities’, Journal of Learning Disabilities, 32(4): 350–61. Stone, C.A. (2002). ‘Promises and Pitfalls of Scaffolded Instruction for Students With Language Learning Disabilities’, in K.G. Butler and E.R. Silliman (eds), Speaking, Reading, and Writing in Children With Language Learning Disabilities: New Paradigms in Research and Practice, pp. 175–98. Mahwah, NJ: Lawrence Erlbaum. Suresh, P.A. and S. Sebastian. (2003). ‘Epidemiological and Neurological Aspects of Learning Disabilities’, in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 30–43. New Delhi: Sage Publications. Thorndike, J.L. (1963). The Concepts of Over and Underachievement. New York: Columbia University Bureau of Publications. Torgesen, J.K. (1991a). ‘Learning Disabilities: Historical and Conceptual Issues’, in B.Y.L. Wong (ed.), Learning about Learning Disabilities, pp. 3–31. San Diego, CA: Academic Press. ——————. (1991b). ‘Subtypes as Prototypes: Extended Studies of Rationally Defined Extreme Groups’, in L.V. Feagans, E.J. Short and L.J. Meltzer (eds),

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Subtypes of Learning Disabilities: Theoretical Perspectives and Research, pp. 229– 46. Hillsdale, NJ: Earlbaum. US Department of Education. (1977). Definition and Criteria for Defining Students as Learning Disabled. 42 Fed. Reg. 65, 083. Washington, DC: US Government Printing Office. Werner, E.E. and R. Smith. (1982). Vulnerable but Invincible: A Longitudinal Study of Resilient Children and Youth. New York: McGraw-Hill. Wise, B.W. and R.K. Olson. (1994). ‘Computer Speech and the Remediation of Reading and Spelling Problems’, Journal of Special Education Technology, 12: 207–20. Wise, B.W. and R.K. Olson. (1995). ‘Computer-based Phonological Awareness and Reading Instructions’, Annals of Dyslexia, 45: 99–122. Wong, B.Y.L. (ed.). (1991). Learning about Learning Disabilities. San Diego, CA: Academic Press. Wood, F., R. Felton, L. Flowers and C. Naylor. (1991). ‘Neurobehavioural Definition of Dyslexia’, in D.D. Duane and D.B. Gray (eds), The Reading Brain: The Biological Basis of Dyslexia, pp. 1–26. Parkton, MD: York Press.

2 Young-at-risk Children An Educational Challenge or Clinical Group Only? GEERDINA M. VAN

DER

AALSVOORT

GENERAL INTRODUCTION

T

his chapter contains an overview of the Dutch educational system that is followed by a description of the clinical group of young-at-risk students. The group is subject to studies on identifying educational opportunities. When the history of these children is discussed, we refer to a specific group of students for whom “atrisk” characteristics become manifest between four and six years, when they are preparing to start formal schooling. We define this group of at-risk students in line with Elliott and Hall’s (1997, p. 198) definition: . . . children who manifest some or all of the following behavioural characteristics: difficulty in using language fluently and effectively in a range of situations, inability to attend to and persevere with tasks and activities, lack of purposefulness, imagination and variety in play, lack of initiative; lack of ‘normal’ social and emotional maturity.

We start from the bio-ecological model as a developmental model and sociocultural theory as the main vehicle to study development. We argue that the multi-method approach offers opportunities to

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identify both child and environment-related characteristics of the clinical group. The results of an investigation on social play with at-risk students are presented to illustrate the point of view.

INTRODUCTION

TO THE

DUTCH EDUCATIONAL SYSTEM

Acts on the Educational System Caring for young children with various problems and educating them in the Netherlands is one of the main concerns of the Ministry of Education, Culture and Science as well as of the Ministry of Welfare, Health and Sports. It is characteristic of the Dutch system that policy decisions are the result of extensive consultations between policy makers at various levels as well as the organizations within the institutions. Child care centers and school boards, however, make decisions regarding educational and pedagogical aspects, autonomously, not in consultation with national or local authorities, and child care and schools are all financed on an equal footing. Moreover, the Dutch care and education system is based on the principle that special care or education should be started only when regular care fails. Making such decisions concerning the child is based on the advice of the referral board financed by the ministries as well as the municipality (Kloprogge, 1998). The Dutch education system has a history of being highly differentiated for the last 20 years. Two Acts have recently changed the education system. The first one, the Act on Primary Education (APE) (Van der Aalsvoort et al., 2002), came into force in around 1998. This Act includes the movement called “going to school together again”: School boards from regular schools within a specific region are combined with one school for special education where students with learning disabilities and slow learning students are educated. Thus, efforts aimed at including students with learning disabilities (LDs) and slow learners can be centralized so that the board succeeds in referring no more than 4 percent of the number of students to the special school. The APE allows regular teachers to profit from

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expertise that is offered through consultation by teachers from schools for special education. Teachers in regular primary schools can then keep students in need of special support in their regular classes (Meijer and Pijl, 2004). In special schools, students from the age of four are admitted. An independent committee bases admission on the results of a referral procedure. The committee weighs information from an educational psychologist, a medical doctor, a social worker who makes a report on the home and the parents, and a report with respect to academic progress of the child to decide upon referral to the special school. The APE aims at decreasing the number of students in special schools, but this goal is not explicitly reached through propagating inclusion. The second Act, however, regulates that students with special educational needs are included in regular primary schools as much as possible. The second Act came into force in 2003 and is called the Act on Centres of Expertise (Van der Aalsvoort et al., 2002). This Act provides the restructuring of special schools into four clusters from ages three to four years on for: 1. 2. 3. 4.

Blind or vision impaired students; Deaf or hearing impaired as well as language impaired students; Motor impaired and intellectually impaired students; and Students with behavior problems or psychiatric problems.

Each of the four clusters contain several schools within a region. Indication for one of the four clusters comes about after a decision that is based on information from an educational psychologist, a medical doctor, a social worker who prepares a report on the home and the parents, and a report with respect to academic progress of the child. Indication for a cluster means that impairment is accepted as the main cause of the problems in school. Parents receive a financial allowance that provides them with the payment of professional help for their child either in a school for regular education, a special school, or a school within the cluster that the child received an indication for. The Act on Centres of Expertise allows more room for parents to decide how they wish to receive support for their child’s upbringing within the school.

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The Dutch Pre-school and Primary School System In comparison with the Indian education system the Dutch children start primary school early from the age of four. Going to school however, is obligatory from the age of five. Primary schooling takes 8 years until the child is 12 years old. Then the student attends secondary school until he/she reaches 16 to 18 years depending on the level of secondary school, which may vary from low-level to highlevel school education, followed by either vocational training or college and university. Grades 1 and 2 of primary school are characterized as kindergarten. Becoming aware of letters and numbers is considered as a result of informal education. Formal education, which includes instructions on reading, writing, and mathematics starts in grade 3. In Holland, there is no national curriculum for kindergarten and primary education although general educational goals are defined. The pre-school period also has no laws governing the types of activities associated with it. Most children (94 percent of the population) who enter primary school have visited some form of day care or playgroup between ages two and four years. The APE, 1998 had a big impact on the school career of young students who were not developing according to their teachers’ and parents’ expectations. When the history of these children is explored, we refer to a specific group of students for whom “at-risk” characteristics manifest between four and six years, when they are preparing to start formal schooling. We define this group of at-risk students in line with Elliott and Hall’s definition: . . . children who manifest some or all of the following behavioural characteristics: difficulty in using language fluently and effectively in a range of situations, inability to attend to and persevere with tasks and activities, lack of purposefulness, imagination and variety in play, lack of initiative; lack of ‘normal’ social and emotional maturity (1997, p. 198).

Until 1998, transition to grade 3 would be postponed for many young-at-risk students when it seemed that they were not ready for formal education. A small percentage of the clinical group, 1 percent of the age group was referred to special education. Since the APE, the

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teacher of these students can be provided with either consultation from the special school or she or he can be offered extra support within the school, as it is hoped that young-at-risk students would stay in the regular primary school this way. The number of referrals, however, has been alike since the APE (Van der Aalsvoort et al., 2002). Much of the discussion revolves around diagnostic decisionmaking with the clinical group, as limited predictability and reliability of tests used has complicated assessment of young children. Moreover, the child’s behavior is often the result of characteristics that develop in interaction with the environment in which he grew up. Therefore, research carried out in the last five years has been designed within a framework that would allow investigations that include both child and environment-related characteristics. These investigations have always included a combination of quantitative as well as qualitative research. The multi-method approach offers several opportunities: 1. Comparing differences in interactions between experimental conditions by powerful tests. 2. Making sense of these differences by analyzing discourse during intervention sessions to identify meaningful patterns. 3. Giving voice to the children at-risk who have poor language abilities as both verbal and non-verbal exchanges are taken into account with discourse analysis. The bio-ecological model and sociocultural theory suit the research theme as they both underline the interaction between child and environmental-related characteristics. The model and the theory will be described followed by recent findings with respect to youngat-risk children.

THEORETICAL FRAMEWORK The Bio-ecological Model as a Developmental Model The bio-ecological model of Bronfenbrenner and Ceci (1994) espouses a transactional theory of child development, which results from

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proximal processes between a child’s genetic potential and his or her environment, leading to a certain level of effective psychological functioning of that child. Proximal processes in this model are defined as: . . . Progressively more complex reciprocal interaction between an active, evolving bio psychological human organism and the persons, objects, and symbols in its immediate environment . . . [In order to be effective] . . . the interaction must occur on a fairly regular basis over extended periods of time (Bronfenbrenner and Ceci, 1994, p. 572).

The consequences of the model are that the home environment followed by environments that provide professional care and education for a significant period of time, are held responsible for the quality of proximal processes in the institution (child care setting or school) when initiated by the adult. Information about the quality of social interactions in the home and/or in the child care setting or school will thus reveal whether the environment (material, activities, interactions initiated by the pre-school or the kindergarten teacher) is provided to enhance effective functioning.

Impasse in Early Childhood as an Operationalization of Development At-risk In case of a poor relationship between the child and his environment for a significant period of time, an impasse will occur that will be revealed in ineffective functioning. The impasse that occurs is the situation in which parents and/or professional caretakers and/ or teachers no longer see a way to improve the environment in such a way that developmental progress occurs. The concept “impasse” refers to a situation that occurs when the developmental needs of the child are persistently, poorly met by his environment. An impasse may include some or all of the elements of the bioecological model—characteristics of the child; proximal processes; the results of the relationship between the proximal processes and the child’s behavior, given the environment in which he or she grows up, and so on. Smits (1993) for example, found that young-at-risk students in grade 1 were treated less favorably than their normally developing peers in

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the same grade, and this attitude continued when they were in grades 2 and 3. The students at-risk showed an ongoing decrease in on-task behavior through grades 2 and 3, and moreover, they performed more poorly in grade 2 and 3 than their peers who had not been viewed as at-risk students. This finding is explained as follows. The proximal processes that seemed to have been poor in quality, based on low expectations of the children involved were transferred to the social interactions with each new teacher. The extended exposure to poor expectations elicited poor task behavior with the at-risk students, which, in turn, had a negative effect on their level of effective functioning. Findings like these challenge us to identify what processes take place when a teacher is expected to include students who perform poorly and are viewed as students with a development at-risk.

Socio-cultural Theory as the Main Framework Vygotsky’s (1978) socio-cultural theory on higher mental functions is used as the main theoretical framework for investigations on the relationship between child and environmental characteristics. The theory states that all knowledge is socially constructed by interaction with the environment, and it includes statements on how the child’s cognitive development proceeds from the interpersonal into the intrapersonal plane in the zone of proximal development (ZPD). This zone refers to the distance between a child’s developmental level as determined by independent problem solving, and to the level of potential development as determined through problem solving under adult guidance or in collaboration with more capable peers. Knowledge thus develops socially—the partners in interaction explore each other’s roles in the interaction and their participation in communication is bi-directionally oriented. Moreover, the social and cognitive aspects of the dynamic interaction in the ZPD require the student to adopt the definition of the task at hand in order to learn (Wertsch, 1984). The ZPD refers both to a set of steps as well as to the process that occurs when taking these steps. The ZPD has been compared with “scaffolding” by several authors (Stone, 1998). The scaffolding metaphor is derived from Wood et al. (1976) and has the following characteristics: It involves “recruitment

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by an adult and a child’s involvement in a meaningful and cultural desirable activity that is beyond the child’s current understanding or control.” Moreover according to Stone (1998, p. 349), “the assistance that the child needs in order to construct knowledge includes careful calibration of the support provided together with a process of ‘online’ diagnosis of the child’s understanding and/or skill level of the task at hand. Although the adult can provide a range of types of support,“this support is temporary and is gradually withdrawn in order to foster a transfer of responsibility from the adult to the child” (ibid., p. 349). Being together in a task is not sufficient to call it scaffolding. There must be a cycle of communicational challenge, and inference between adult and child. This interplay (Butler, 1998) may proceed both verbally and non-verbally and is driven by intentional conscious processes of affective guidance and instruction on the part of the teacher. The child, however, will only be actively involved in the teacher’s task definition when his linguistic, cognitive, and social skills are sufficient to engage in and profit from this affective guidance and instruction. Moreover, affective engagement is required on the part of the child with respect to the relationship with the adult using scaffolding. Not every instructional interaction serves to scaffold learning as scaffolding includes knowledge of instructional strategies and also encompasses pedagogical content knowledge. Effective instruction, thus, is both teacher and student dependent (Wood et al., 1976), and is negotiated between teacher and student (Palincsar, 1998). Scaffolding may enhance the opportunity for learning to take place. We believe that scaffolding has the potential to clarify whether the interactions between teacher and these students are successful or not when learning is at stake. We have concentrated on young students, as they demonstrate every day that instruction in the classroom requires more than just simply carrying out tasks. These students are inclined to learn both socially and cognitively, and these elements are situated in the interpersonal interactions with the teacher. When a child shows problems with learning, several questions can be put forward: 1. Is the interaction too hard to share? 2. Is knowledge of the required rules of the task overestimated?

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3. Is the child not sufficiently engaged in the task from a pedagogical point of view? A method that allows in-depth investigation in the dynamic flow of interaction is discourse analysis. Discourse Analysis In conducting the study of scaffolding with young-at-risk children as our main subject, we encounter a specific way of analyzing communication in the classroom referred to as discourse. Discourse analysis examines the ways in which knowledge is socially constructed in classrooms (Gee and Green, 1998). Discourse firstly refers to language embedded within socio-cultural practice—the classroom elicits “situated meanings” or patterns that are assembled “on the spot” while communicating. These situated meanings or scripts are constructed and negotiated within and across instructional events during communications between teacher and student. Discourse also refers to language as a means of communication between human beings—the ability to communicate without verbal utterances. There are prosodic and non-verbal socio-cultural cues that teacher and students draw on in order to proceed successfully during discourse. Both the teacher’s and the students’ scripts must meet in a social as well as in a cognitive sense to enable the successful construction of a joint local meaning. This then becomes a resource for the student that he may call on to guide his actions during the task. By analyzing discourse with young-at-risk students it becomes possible to study the way interactions emerge especially with respect to reciprocal processes, such as decreasing commitment in case of over stimulation or too complicated use of language.

Concluding Remarks In the preceding sections it has been stated that the clinical group of young-at-risk students requires specific attention with respect to the way investigations are carried out. Since their problems are related to an interaction of child and environment-related characteristics, investigations should include both factors in any study undertaken to

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collect reasoned advice for the education of the clinical group. Sociocultural theory allows inclusion of both characteristics, as learning is a social event. Especially with young-at-risk students who fail in verbalization, a method is required that draws attention to the weak spots of these children’s interactional capabilities. An approach most suitable then is a multi-method one. We include three methods in one: 1. We need information on the clinical group by comparing the children of that group with the normative group. 2. We require an in-depth investigation of the way in which the child interacts with the immediate environment during tasks. Discourse analysis will allow further understanding of the processes that come into play during these interactions. 3. A microgenetic approach needs to be included to answer the question of how an intervention brings about changes in that interaction.

PLAY AND YOUNG-AT-RISK CHILDREN In the preceding sections, the clinical group has been defined and the theoretical framework has been described. We will now continue with the results of a study that aimed at clarifying social play with young-at-risk students. We will first introduce a definition of play followed by the actual study. What can play mean for young-at-risk children? First these children often experience tasks in a classroom as too challenging. They tend to act in such a way that they succeed in either avoiding the task or preventing the teacher to confront them with failures that they learn to dread. In a play, however, children do not experience feelings of anxiety. They provoke their own anxieties and enact them in play, and learn how to cope with those feelings in real life settings (Stagnitti and Unsworth, 2000; Stagnitti et al., 2000; Van Oers and Wardekker, 1997). A play, therefore, is often used for therapeutic reasons. The value of play as therapy has been investigated in a metaanalysis (Fisher, 1992) of studies, which showed that play therapy resulted in an increase in compliant behavior, improved language development, and a decrease of socio-emotional problems.

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The question that we had with respect to the role of play for youngat-risk children was related to social play. Social play or co-operative play is supposed to elicit social skills, as the children practice and learn to get along with others. This is a major developmental task as the child is part of a community—the classroom, and the school. In peer collaboration, peers are approximately equal in status and competence. According to Verba (1993; 1994) this allows the processes of co-construction to emerge. Learning to co-operate can be studied by analyzing behaviors displayed during a play. There are different kinds of co-operative formats related to joint role-play as social, motivational, and cognitive factors are intertwined. Children learn skills to share, and these skills contain both social and cognitive elements. Verba (1998) showed repeatedly that even with very young children, joint elaboration occurs as reliable indications in non-linguistic exchanges that reveal emerging co-constructions through goal orientation, sharing of meanings, and management. The children’s play and learning are not cognitive activities in themselves but they are reflected through co-construction in situational factors like activity, time, and actors. A literature search with respect to social play in a socio-cultural frame revealed that the meaning of social play with children experiencing developmental delays could be understood in terms of childrelated characteristics only. Situatedness of learning opportunities has been an important question in several studies related to mathematics and reading with young-at-risk children. We wished to explore, however, how youngat-risk children would proceed when invited to play together as a function of situated behavior. Findings from Kontos and Keyes (1999), and Nolen (2001), who included environmental characteristics in their study, showed that quality of classroom environment adds to the probability that children would profit from interventions that take place in the classroom. The classroom as a community of practice in regular primary education could elicit learning opportunities different from those offered in special education. Placement in a special school has consequences, such as smaller groups, and therefore more attention from the teacher. However, the students placed in a special school on average have more problems compared to the students in a regular primary school. By including school

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type as a co-variable we could investigate whether going to school as an at-risk child in a regular primary school would be favorable to placement in a special primary school. Therefore, we wished to carry out a study that would include small groups of young-at-risk children from regular and special schools. The groups of children would get the opportunity to play together several times within a short period of time. We designed a task that would trigger the children’s interest, and look for materials that were intended as open-ended to elicit play behavior as well as chances to structure behaviors as the materials provided were to be used in cooperation. The study was exploratory. We took a limited number of schools to investigate play quality as a precursor of a bigger study that would include more schools in a controlled design.

Research Questions and Design The main question we had was, whether play with young-at-risk children in regular primary schools would develop into more complex ways of social play than the play shown by their peers attending special primary schools. We based this expectation on the fact that children with higher order learning surround at-risk children in regular primary schools more often, and their teachers would express higher expectations with respect to problem solving skills than their colleagues in a special school would. As play behavior varies between children, we designed a microgenetic study that would allow us to study both individual and social play, and to identify whether skills to collaborate and level of role-play would improve through peer exposure. A microgenetic design allows studying development from a specific domain, such as cognitive problem solving or motor development. The research model suggests collecting data within a short period of time to “catch” developmental leaps (Siegler and Crowley, 1991). The measures that we used to describe our findings aimed at revealing the socially defined setting by analyzing small group discourse within the wider socio-cultural context, the children’s school. The design allowed us to describe development in social play by following small groups of children in eight successive sessions.

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This procedure would permit us to study quality of play as an individual characteristic to develop in a short period of time.

Design The task offered was based on suggestions from Hännikäinen (1998) and Leseman et al. (2001). To provoke elaborated role-play, a story was read at the start of sessions 3, 5, and 7. Table 2.1 indicates the settings, groups, and the number of sessions of the study. Table 2.1 Overview of the Conditions Number of groups Number of sessions

Regular primary school

Special primary school

Total

2 8

2 8

04 32

Source: Based on data computed by the authors.

The eight sessions to be carried out were planned within three weeks. Before the first session, each group was made familiar with the video camera and the children were read the following instruction: “The three of you will come and play with me. Do you see the blocks and toy animals? Can you build a zoo for me? It is up to you to think about how to build the zoo and which animals are going to live in it. I will tape your play. Do you have questions?” In case of questions, the researcher answered them followed by the invitation to start playing. She also instructed that she would let them know when to stop playing. After 30 minutes, the researcher said: “You built a lot of things! I will make a drawing of your zoo so that you can play with it again next time.” The researcher was present during the sessions, but she did not participate or interfere in the unfolding activities. A group was allowed to stop playing when any participating child of the group so desired. In sessions 3, 5, and 7 a story was read before each session began. Story 1: “You built a zoo. The boss of the zoo told me that a special animal is coming to live there. It looks like a bird and it has colored wings. Can you please draw the animal and then build the cage? The bird

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needs a cage that he can sleep in. He should not be able to escape, but he needs a window so that he can take a look outside. Can you do that for me?” The researcher put paper and color pencils in front of the children. Story 2: “Tommy has his birthday. He loves to come to your zoo. His friends told him that a wonderful bird lives there. He has a problem though. Last week he broke his leg, and he moves around in a wheel chair. Can you ride Tommy through the zoo? He wants to see all the animals. He gets to feed one of the animals too! Can you do that?” Story 3: The researcher removed the apes from the cages. She then told the group: “Oh, something happened last night! Someone left the cage of the apes open. Now they have escaped! They are running around in the zoo! What can you do? Some animals are dangerous for the apes! Can you find them and bring them back into the cage? Please take care that the apes do not escape again!” The quality of play was defined by various variables to cover richness of behaviors displayed. The measures were part of a multi-step analysis. Data was collected by transcribing play from video-tapes made for each session followed by categorizing behaviors along different measures and adding frequencies per condition to compare group means. The means were compared statistically to test the following hypotheses: H1: The mean difference between time played and number of episodes is higher for the regular primary school than for the special school. H2: The most complex type of collaboration occurs more often in the regular primary school than in the special school. H3: Metaplay occurs more often in the regular primary school than in the special school. After the quantitative analyses we chose discourse fragments to grasp ongoing co-construction. This allowed us to use the transcripts as material to reveal situatedness of social play. Finally, since

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we collected the data in eight succesive sessions we were also able to identify patterns over time by visual inspection of categories within sessions.

Method Selection of Schools The schools were selected using the Early Childhood Environment Rating Scales (ECERS: Harms and Clifford, 1980). These scales examine the developmental appropriateness of classroom practices by assessing the following domains—routine care needs; furnishings and display; activities and experiences related to motor, language, cognitive, and social development; and adult provisions. The ECERS contains 37 items rated on a scale from 1 (inadequate) to 7 (excellent), and has demonstrated good reliability and validity (Harms, 1990, in Burchinal et al., 2000). The total score for the regular primary school was 166 whereas the score for the special primary school was 194. The differences between the two environments were mainly due to space, as room for motor and creative activities were less available in the regular primary school. As these domains were of minor importance to the investigation at hand, we decided to treat classroom practices as comparable between the schools. Subjects A language test and a non-verbal intelligence test were administered individually to the students from a classroom in order to select children for the study. The tests were: 1. Language test for children in Kindergarten (Van Kuijk, 1996): First, the child is offered items to practice the type of questions. Then the items were presented. There are two subtests on passive vocabulary and critical listening. The scores of the two subtests were added to obtain a performance score. This score was compared to a table of standard norms that could range from A (high) to E (low).

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2. Raven’s Coloured Progressive Matrices (Raven, 1965): This is a non-verbal intelligence test that can be administered to children aged 4 to 10. The test contains 36 items. The raw score was compared to a table of standard norms that could range from 0 to 9.9 (Van Bon, 1986). After the selection procedure, 12 children were selected—six of them attended a regular primary school and the rest attended a special primary school. Within each school condition, two groups of three students were formed after the matching procedure. Table 2.2 depicts the results with regard to the four groups. Table 2.2 Mean Scores with Respect to Age, Language Score, and Intelligence Score from the Four Groups Regular primary school Age Language score Intelligence score

Special primary school

Group 1

Group 2

Group 1

Group 2

69.3 (3.21) 3.3 (0.58) 6.2 (0.15)

73.0 (3.61) 4.3 (0.57) 5.5 (1.79)

69.3 (0.58) 3.3 (0.58) 2.8 (2.65)

73.3 (4.16) 4.0 (1.73) 3.6 (2.92)

Note: Standard deviations in brackets. Source: Based on data computed by the authors.

The scores of the two groups per school revealed comparable age and language development but the intelligence scores differed significantly (t(10) 2.329, p < .042). The scores were higher for children from the regular primary school than those from the special school. Data Analysis and Measures for Play Quality The play sessions were transcribed to identify quality of play. First, the level of play was assessed followed by identification of language use during play per child. Next types of collaboration and metaplay were categorized and added per condition. Finally, a rest category was identified as typical communication and the number of this communication was added per condition. Each type of qualitative analysis is described below including inter-rater reliability scores.

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Collaboration The procedure to assess collaboration was used according to Verba’s three steps (Verba, 1994). The data collected refer to group frequencies. • Step 1: Assessing episodes in the protocols. An episode starts when one of the children of the small group seeks contact with one of the other group members. The episode begins as soon as the child responds either verbally or non-verbally, and it stops when the child addressed does not respond anymore. The time of each episode is registered to test hypotheses. • Step 2: Assessing cognitive level as realism or play. Realism refers to use of materials according to their function in the real world: A child uses a wooden block for building a wall or a cage; he calls a toy giraffe by its name. Play refers to role-playing and pretending, and to using materials in an imaginary world. The wooden block is now a tree, and the toy giraffe is called the boss of the zoo. The number of each type of cognitive level was added. The findings were not used for testing hypotheses. • Step 3: Level of collaboration. As soon as an episode starts, types of collaboration can unfold. There are five types of collaboration. A number of collaborations were added and used for testing hypotheses: 1. Behavior intended to communicate with child(ren) from the small group; 2. Asking or being offered information; 3. Proposing ideas or giving directions and carrying them out; 4. Planning (role-) play; 5. Evaluating (role-) play. The number of types of collaboration were added and used for testing hypotheses. When we analyzed the types of collaboration we found that problems arose when collaborative efforts between two

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children ended fluently in collaborative efforts with the third boy in the party. We decided to define episodes as either including two or three boys. Moreover, we defined episodes as units of 30 seconds, as the main goal was to identify emerging types of collaboration. Next, inter rater reliability was assessed by comparing the results of eight protocols that were categorized twice by two independent researchers. The percentage agreement between the two coders was as follows: • Assessing episodes in the protocols: 75 percent • Assessing cognitive level as realism or play: 100 percent • Level of collaboration: 88 percent

Metaplay Role-play that refers to symbolic transformation was identified and categorized into three categories (Trawick-Smith, 1998): 1. Initiations—behavior to halt role-play by initiating new play through mentioning object transformation, suggesting pretend play, and so on. 2. Responses—behavior to step out of role-play and reply to initiations, such as agreeing, disagreeing, answering, verbal proclamations that a toy is theirs. Example of initiating and responding from one of the groups including Mark, Victor, and Bert from the regular primary school (Time: Minutes 3.00–3.30 of Session 8): “Boys, the guarding house!” Mark calls. Bert does not look up. “The chimney,” he says, and puts it on the cage that he is building. “Yes, I am going to build the guarding house,” Victor says. Bert looks at Victor. “Well, I am making it now,” he says. “You get to build the feeding house. That’s big most of the time,” he says looking at Bert. “You feed the animals, Bert!” Mark says. 3. Constructions—manipulating props used in role-play, such as stepping out of role-play to rebuild a house or a cage.

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Example from one of the groups including Michael, Nuhun, and Richard from the special primary school (Time: Minutes 2.30–3.00 of Session 7): Richard walks to the cage he built, sits down and asks: “Where is another board?” Michael looks up. Richard looks for it himself finds it and starts to expand the cage. Inter-rater reliability was assessed by comparing the results of eight protocols that were categorized twice by two independent researchers. The instances of metaplay as rated by the two observers were found to be similar. The content of play was not involved in the reliability check. The episodes that could not be identified as collaboration or metaplay were categorized separately. Procedure The principals of a school for regular primary education and of a school for special primary education were asked to participate in the study. When the principals agreed, ECERS was used to assess the developmental appropriateness of classroom practices. When the results of the assessment revealed that the schools matched, the teacher of the first grade for each school was approached to explain the procedure of the investigation. Parental permission was obtained before the study commenced. All students of the classroom were tested with respect to language development and intelligence score. As the intelligence scores differed significantly between school conditions it was not used for matching groups. Two groups of three boys from each classroom were selected, as there were too few girls in the special school classroom with respect to age and language development. The play sessions took place within three weeks of time after discussion with the teacher as to the weeks that would best fit in her routine. The sessions took place on the same days in both schools in a room outside the classroom. Before each session, the video camera as well as a portable microphone and the play materials were placed. Each session ended after 30 minutes. The researcher said: “You built a lot of things! I will make a drawing of your zoo so that you

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can play with again next time.” She then escorted the group back to the classroom, and invited the second group to come and play. Sessions were held despite a child being ill. Session 1 had one child missing in each group of the regular school. Sessions 3 and 6 had one child missing from the special school. Sessions 3, 5, and 7 (regular school) and 8 (special school) started with a story. After the last session, the children were thanked for their co-operation. They were told that the videotapes would be brought to their teacher, so that they could watch the play sessions themselves.

RESULTS The findings are presented to allow group comparison first. Then details of the discourse chosen are discussed. The data collected was calculated and was tested to determine whether the findings on the level of school condition were significantly different. T-tests for independent groups were used to test the three hypotheses. Table 2.3 shows the means and standard deviations with respect to time played, number of episodes, and cognitive content of episodes to test the first hypothesis. Table 2.3 Mean Scores and Standard Deviations with Respect to Seconds of Total Time Played and Number of Episodes Regular primary school Total time played Number of episodes

Special primary school

M

SD

M

SD

179.9 157.5

22.47 19.05

115.0 129.0

3.46 1.15

Note: Total time played is expressed in percentage. Source: Based on data computed by the authors.

Significant differences were found with respect to the time played (t (4.236) 6.368 = p .003) and number of episodes (t (3.002) 2.986, p. 058). Hypothesis 1 was accepted. The mean difference between time played and number of episodes was higher for the regular school condition than for the special school.

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Collaboration Our hypothesis was that the most complex type of collaboration would occur more often in the regular primary school. Table 2.4 describes the types of collaboration that supposedly express increasing collaboration both with respect to number and complexity. Table 2.4 Means and Standard Deviations with Respect to Number of Collaboration Type and Number of Complexity of Collaboration in Both Conditions Regular primary school M SD A ABCDE

33.0 16.5

9.86 8.22

Special primary school M SD 39.5 8.0

3.83 1.10

t

(df 10) p-value

–1,505, 2,512,

ns 0.31

Note: ‘A’ refers to behaviour intended to communicate; ABCDE refers to the total number of categories within sessions. Source: Based on data computed by the authors.

Table 2.4 shows that the number of collaboration type differed significantly with respect to the most complex type of collaboration only. This type includes initiation of and response to communication by one of the children at play, asking or being offered information, offering ideas and carrying them out, as well as planning (role-) play and evaluating (role-) play. The second hypothesis was confirmed. Figure 2.1 allows visual inspection of the microgenetic analysis undertaken. Only numbers 1, 4, and 7 are displayed as numbers in Figure 1. However, eight sessions took place. The histogram reveals that the simple type of collaboration is frequent in each session whereas the most elaborate form increased in the regular primary school from Session 1 onwards and decreases in the special school from Session 1 onwards. Moreover, the histogram shows no specific pattern with respect to the sessions that started with a story (sessions 3, 5, and 7 in the regular primary school; and sessions 3, 5, and 8 in the special school). The following fragment of a protocol illustrates collaboration in its most complex form.

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Figure 2.1 Histogram of the Collaboration Types in Sessions 1 through 8 in Both Schools

Source: Based on data computed by the authors.

The following is an example of a group session including Dillan, Stanley, and Tony from the special primary school (Time: Minutes 4.30–5.30 of Session 5): Stanley has placed toy-apes on a pencil by pulling the claws of the animals over the pencil and walks to a cage close to Dillan. “Yes, a slide, a slide,” he says. Tony watches him while moving a tiger and a lion on a wooden block. Dillan says: “Yes boys, I am going to make a hiding place and we will hide alright?” He says this in a special voice. Stanley continues sliding down the toy ape on a board and Tony also continues his play. Then Stanley says: “No, no! I know! Here, here, look!” Dillan watches Stanley. “You can hide here!” Stanley says in a special voice, and he points to a place where animals can hide. Tony watches Stanley. “Yes,” Dillan says. “We need to make it right!” He moves to Stanley’s cage and puts the blocks in a straight line. “Quick, be quick!” Stanley says. He puts the ape in the cage, takes the board he used as a slide before, waits until Dillan puts his

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toy apes in the cage and puts the board on the cage. Tony moves closer to Stanley. ‘I am not afraid!’ Dillan claims and he puts up the board to take out his toy ape. He makes noises with the toy apes. Stanley watches him. He removes the board from the cage and takes out his toy ape. Tony watches him. This fragments reveal the discourse emerging between two of the three children. One child is drawn into the pretend play of the other. The third child only watches. He is not a part of the social play and remains a spectator in most of the play sessions.

Metaplay and Special Communication Our hypothesis was that metaplay interactions would occur more often in the regular school condition than in the special school. Certain episodes were types of collaboration that displayed something special that was not related to the building of the zoo, such as starting a song, and joining in, talking about family members, and so on. After discussing the episodes not otherwise categorized we identified these so-called special communications and their number was added per condition. Table 2.5 describes the number of times that metaplay occurred and special communication took place. Table 2.5 Means and Standard Deviations with Respect to Number of Metaplays and Special Communications in Both Conditions Regular primary school M Metaplay 40.5 Special communication 39.5

Special primary school

SD

M

SD

13.69 22.46

34.5 24.0

1.64 6.57

df 10 t 1,066 1.623

p-value ns ns

Source: Based on data computed by the authors.

Table 2.5 shows the number of times metaplay occurred as well as the number of special communications. These types of collaboration did not differ significantly between the conditions. The hypothesis could not be confirmed.

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Examples of Metaplay We include excerpts from two protocols to illustrate examples of metaplay in both conditions. The first excerpt refers to not sharing toys and the second one to sharing toys in the same session. The following is an example of a group session with Dillan, Stanley, and Tony from the special primary school (Time: Minutes 6.00-6.30 of Session 3): “I had more apes . . . apes, where are my apes?” Stanley says. Dillan answers, “I have an ape, Dillan. You can take the last one from me. This one.” “Why do you get everything? Will you have this one?” Stanley asks and holds a toy ape up for Dillan to see. “Which one? I don’t want the koala,” Dillan says. “You have to give it back to me!” Stanley says. “No,” Dillan answers. The following is an example of a group session with Dillan, Stanley, and Tony from the special primary school (Time: Minutes 13.30– 14.30 of Session 3): “All right,” Dillan says. “Here you are, here you are. You get it for real!” He pretends to give a toy ape to Stanley. “Now I get it,” Stanley answers. “Will you now stop wrecking my cage? And do I get a gorilla? Just one?” Dillan asks. “No, I don’t want that,” Stanley says. “No? Then you can keep them all, ok?” “Yes, I don’t want that”, Stanley says. “Do you want to keep the gorillas?” Dillan asks. “Yes,” Stanley says. “That’s ok,” Dillan answers. The fragments listed earlier show different ways of stepping out of the play socially, pulling another child in, and continuing playing in rapid order. We found no systematic increase of frequency of metaplay in relationship to sessions starting with a story and sessions that opened with an invitation to work on the zoo between conditions. Figure 2.2 allows visual inspection of these data. Only number 1, 4, and 7 are displayed as numbers in Figure 2.2. However, eight sessions took place. Figure 2.2 reveals that the frequency of metaplay increased in the groups of the regular primary school whereas it decreased in the special school. No significant relationship was found with respect to storytelling before the play was started.

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Geerdina M. van der Aalsvoort Figure 2.2 Overview of the Frequency of Metaplay from Sessions 1 to 8 for Each School Condition

Source: Based on data computed by the authors.

Special Communication Certain episodes were types of collaboration that displayed something special that was not related to the building of the zoo, such as, starting a song, and joining in, talking about family members, and so on. Discussing leftover episodes identified these so-called special communications, and their number was added per condition. The following is an example from one of the groups including Mark, Victor, and Bert from the regular primary school (Time: Minutes 12.00–13.00 of Session 8): “Red, I see, I see what you don’t see and the colour is red,” Mark says. Bert says: “That umbrella there,” and points at it. “No,” Mark says, and pulls a face at Victor. “The book case,” Victor says and points at the case containing books. “You mean this one?” Mark asks. “No that one,” Victor says. “Right!” Mark answers, “I see. I see what you don’t see and the colour is brown.” The game that is played by the children occurred many times in Session 8. The children were very involved in the game. The

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examiner suggested to continue playing with the zoo after another of the games, but the children persisted. They seemed to enjoy having control while playing and sharing the game. The following is an example from one of the groups including Michael, Nuhun, and Richard from the special primary school (Time: Minutes 7.00–7.30 of Session 7): “This is a bridge. You need to hop there,” Michael says. “Don’t like it here!” Nuhun says. He pulls a face and moves his arms backwards. Richard looks at him. “No, this is stupid,” Michael says. Nuhun walks to the other side of the cage that he built, takes a toy cat and puts it somewhere else. “This cat belongs there,” he says. Michael puts down wooden plates in front of him. “I don’t like it here,” Nuhun says again. “Hate this,” Michael says. “I want to go home,” Nuhun says. Richard listens. “Stupid,” Michael says, and starts jumping again. “Have a sleep, play with Play Station, playing with my toy,” Nuhun says. “Computer,” Richard says. The fragments listed above are presented to show that the children were conscious of the situation that they experienced. They shared this knowledge with each other, and they showed their compliance to the special events. The playgroups from the special school, however, would often destroy their buildings halfway through a session. This never happened with the groups from the regular primary school.

CONCLUDING REMARKS The study was undertaken to explore play-in-process. Small groups of young-at-risk children were followed for a period of three weeks in which eight play sessions took place. We hoped to reveal development of social play with those at-risk children in two school conditions. The groups were comparable with respect to mean age and language performance. The mean difference between time played and number of episodes was higher in the regular primary school than in the special school. Moreover, the most complex type of collaboration occurred more often in the regular primary school than

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in the special school. Metaplay and special communication, however, did not occur more often in the regular primary school as compared to the special school. What do these findings mean within the socio-cultural framework? First of all, we designed a study that would allow us to clarify whether the school as a specific environment is related to social play. We analyzed the play sessions from an individual and a social perspective to know whether social play took place as a result of group and child-related behavior. We hoped to identify group processes, such as unfolding collaboration, and the results of collaboration expressed in an increased number and complexity of collaboration. As the children were comparable with respect to language performance, we expected no difference between conditions. The results, however, suggest that school environment makes a difference in favor of the children attending a regular primary school. The findings showcase the important role of classrooms as a community of practice. The class mediates opportunities to learn and the child shows what he has learned in situations that elicit these experiences. Learning in this context refers to both observing behaviors of others (Musatti, 1993; Rogoff, 1998) as well as profiting from collaboration. As the children in the study made efforts to achieve shared understanding and actions, these practices seemed to overstretch their cognitive potential in the small groups of the special school quicker, and this led to fewer initiations to start and maintain collaboration. The findings suggest that classroom as a situation in which young-at-risk students perform is related to the social play revealed during sessions and from one session to another in time. The small groups from the special school seemed to constrain the child’s potential even outside the classroom. Other researches partly confirm our findings. Sigafoos et al. (1999) followed young children with a developmental delay from ages three to six. They found that the relationship between opportunity to play and compliance in the classroom was minimal. Their finding suggests that when the developmental delay is too pervasive, children are unable to benefit from stimulation in a classroom. From the perspective that development is a process of transformation of participation, the findings suggest that placement in a special school puts both social and cognitive constraints on the child. The play

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sessions reveal that a child does not break these constraints through collaboration with peers automatically. The excerpts reveal that social play can become a constraint instead of a way out and this causes frustration. When social play reveals this type of classroom culture, it would be important to think again about diagnostic decisions made with respect to measures on social development. The findings of the study presented here suggest that social play with young-at-risk students indeed is a situated performance.

Alternative Explanations of the Findings There are elements that were underestimated in our study. One example is that we did not investigate the relationship between playing and watching peers play. Musatti (1993) claims that children also develop actively by watching peers play. In that case, a child may make progress even when he is not part of an episode. This may be an alternative explanation of the finding that collaboration in two of the four groups included two children at a time most of the time. It could also be that the children although matched with respect to language scores were not comparable, as intelligence score was not used for matching small groups. This can also be said with respect to temperament (Leseman et al., 2001). A future study needs to include more subjects as well as more matching variables to draw conclusions with more power.

Use of Method We carried out a microgenetic study. The advantage of this method is that you can describe detailed behavioral patterns to identify remarkable patterns and/or changes in patterns over time. These patterns, however, need to become stable over time in order to show that variations are part of steady increase or decrease. We found that the groups within each condition varied strongly. A follow-up study would require more groups in each condition to overcome that problem.

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As to the validity of the findings, we claim that the internal validity was strong as social play was followed for a prolonged period of time. Moreover, measuring inter-rater reliability of all the measures used ensured external validity. By using a multi-step procedure, we could compare findings empirically-analytically and illustrate significant differences by adding excerpts from protocols to trace the dynamic processes evident in the protocols (Anfara et al., 2002; van der Aalsvoort and Harinck, 2000). We did not limit ourselves to discourse analysis only, as the study was set out as a pilot to a more elaborate investigation. We raised questions about the value of the instrument to measure level of play and use of language in play, as it was not sensitive to reveal changes from session to session. This means that a measure needs to be found that offers reliable data on individual performance. The measures related to social play, collaboration, and metaplay showed processes during play that seemed to be behaviors referring to increasing social development with some children but not all of them. We already discussed that differences in cognitive ability and temperament could explain underlying differences in play sessions.

Social Play as a Means to Reveal Classroom Culture This chapter is part of a symposium that aims at constructing a shared language and methodology for studies of classroom cultures. The study presented here describes findings about young-at-risk children who experience their classroom as a community of practice in relationship to the school that they visit. Their social play reveals that they understand the specific situation they experienced and that they consciously comply as a group even when one of the members of the small group expresses a wish to stop the session. It seems that the social play is not constrained by the poor language level of the participants. Moreover, the subjects show that even within a very short period of time their potential to collaborate expands regardless of school setting thus inviting teachers to make use of their potential in the classroom. It was concluded that social play comes forward as a situated performance, and it was discussed that the meaning of the findings could be that information on situated social play is used for diagnostic decision-making of young-at-risk children.

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Musatti, T. (1993). ‘Meaning between Peers: The Meaning of the Peer’, Cognition and Instruction, 11(3–4): 241–50. Nolen, S.B. (2001). ‘Constructing Literacy in the Kindergarten: Task Structure, Collaboration and Behavioral Problems’, Cognition and Instruction, 19(1): 95–142. Palincsar, A.S. (1998). ‘Social Constructivist Perspectives on Teaching and Learning’, Annual Review Psychology, 49, 345–75. Raven, J.C. (1965). Guide to Using the Coloured Progressive Matrices. London: H.K. Lewis. Rogoff, B. (1998). ‘Cognition as a Collaborative Process’, in W. Damon (ed.), Handbook of Child Psychology, pp. 679–744. New York: John Wiley and Sons, Inc. Siegler, R. and K. Crowley. (1991). ‘The Microgenetic Method: A Direct Means for Studying Cognitive Development’, American Psychologist, 46(6): 606–20. Sigafoos, J., D. Roberts-Pennell and D. Graves. (1999). ‘Longitudinal Assessment of Play and Adaptive Behavior in Young Children with Developmental Disabilities’, Research in Developmental Disabilities, 20(2): 147–62. Smits, S.C.M. (1993). Pedagogische antecedenten van taakgericht gedrag en schoolvorderingen. [Pedagogical antecedents of on-task behavior and academic performance]. Utrecht: ISOR, dissertatie. Stagnitti, K. and C. Unsworth. (2000). ‘The Importance of Pretend Play in Child Development. An Occupational Therapy Perspective’, British Journal of Occupational Therapy, 63(3): 121–27. Stagnitti, K., C. Unsworth and S. Rodger. (2000). ‘Development of an Assessment to Identify Play Behaviors that Discriminate between the Play of Typical Preschoolers and Preschoolers with Pre-Academic Problems’, Canadian Journal of Occupational Therapy, 67(5): 291–303. Stone, A.S. (1998). ‘The Metaphor of Scaffolding: Its Utility for the Field of Learning Disabilities’, Journal of Learning Disabilities, 31(4): 344–64. Trawick-Smith, J. (1998). ‘A Qualitative Analysis of Metaplay in the Preschool Years’, Early Childhood Research Quarterly, 13(3): 433–52. Van Bon, W.H.J. (1986). Raven’s Coloured Progressive Matrices: Norm Tables. Lisse: Swets and Zeitlinger. Van Oers, B. and W. Wardekker. (1997). ‘De cultuurhistorische school in de pedagogiek’, in S. Miedeman (ed.), Pedagogiek in meervoud [Plural pedagogy], pp. 171–213. Houten/Dieghem: Bohn Stafleu Van Loghum. van der Aalsvoort, G.M. and F.J.H. Harinck. (2000). ‘Studying Social Interaction in Instruction and Learning: Methodological Approaches and Problems’, in H. Cowie and G. van der Aalsvoort (eds), Social Interaction in Learning and Instruction, pp. 5–21. Amsterdam: Elsevier. van der Aalsvoort, G.M. and A.M. Van Tol. (2002). ‘Where Inclusion Stops. An Investigation of Reasons Why Young Children are Referred to Special Education in the Municipality of a Middle Big Town in the Netherlands’, Educational and Child Psychology, 19: 59–75. van der Aalsvoort, G.M., A.M. Van Tol. and M. Thomeer-Bouwens. (2002). ‘Zorg bij jonge risicokinderen: professionele toewijding gevraagd [Care for young children: professional dedication required]’, Leiden: Universiteitsdrukkerij.

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Van Kuijk, J.J. (1996). Taal voor kleuters [Language for children in Kindergarten]. Arnhem: Centraal Instituut voor Toetsontwikkeling. Verba, M. (1993). ‘Cooperative Formats in Pretend Play among Young Children’, Cognition and Instruction, 11(3–4), 265–80. ——————. (1994). ‘The Beginnings of Collaboration in Peer Interaction’, Human Development, 37(3):125–39. ——————. (1998). ‘Tutoring Interactions between Young Children: How Symmetry can ModifyAsymmetrical Interactions’, International Journal of Behavioural Development, 22(1): 195–216. Vygotsky, L.S. (1978). Mind in Society: The Development of Higher Psychological Processes (trans. M. Cole). Cambridge, MA: Harvard University Press. (Published Originally in Russian in 1930.) Wertsch, J.V. (1984). ‘The Zone of Proximal Development: Some Conceptual Issues’, in B. Rogoff and J. Wertsch (eds), Children’s Learning in the ‘Zone of Proximal Development’, pp. 8–16. San Francisco: Jossey-Bass. ——————. (1991). ‘A Sociocultural Approach to Social Shared Cognition’, in L.B. Resnick and J.M. Levine (eds), Perspectives on Socially Shared Cognition, pp. 80–100. Washington DC: APA. Wood, D., J.S. Bruner and G. Ross. (1976). ‘The Role of Tutoring in Problem Solving’, Journal of Child Psychiatry, 17(2): 89–100. Wood, D., H. Wood, and D. Middleton. (1978). ‘An Experimental Evaluation of Four Face-to-Face Strategies’, International Journal of Behavior Development: 1: 131–47.

3 Learning Disability and Language Learning PRATHIBHA KARANTH INTRODUCTION

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ven as early as in the pioneering work of Orton (1937) as cited in Kamhi and Catts (1989) learning disability (LD), in particular reading disability, was reported to be associated with spoken language deficits. Mykleburst (1954), a pioneer in the field, observed that children with reading difficulties often had spoken language deficits. Subsequently, however, this early recognition that LD was closely associated with language learning deficits was overshadowed and neglected when the emphasis on LD shifted to the sensory– motor aspects of learning, such as the visual, auditory, and motor processing skills. The emphasis during the 1950s and the 1960s was on assessing and providing intervention on these prerequisite learning skills on the assumption that once the child was assisted in these basic skills, the LD would be taken care of.

THE LANGUAGE–LEARNING CONNECTION Since the 1970s there has been a renewed interest in the language and learning disability connection. The renewed acknowledgment of this connection was a consequence of several factors. A substantial

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number of children with LD were seen to have associated speech disorders, such as fluency and articulation disorders. Children with communication disorders, such as “Specific Language Impairment” and other such developmental language disorders in their pre-school years are documented to have later developed signs of LD (Bashir et al., 1987). Higher incidence of communication disorders both in children with LD and among their family members has also been reported (Catts, 1989; Scarborough, 1990). Around the same period, the new discipline of psycholinguistics emerged in the 1970s and the study of the acquisition of language in children received a tremendous boost and took centerstage in this newly developing field. It also began to be clear that the process of language acquisition is not restricted to early childhood alone and that the growing child continued to master the more subtle syntactic and semantic—pragmatic aspects of language. Further, the acquisition and mastery of the use of language for analytical as against social use, was documented to take place well into school age and beyond. Empirical studies of language acquisition during the 1970s and 1980s made it clear that language acquisition is a process not limited to early childhood alone but extended well into adulthood. Consequently, our understanding of the complexity of language acquisition process in its myriad aspects also grew. The perception of LD as a disorder that affected children in their school age had also begun to change in the last couple of decades of the 20th century. Children identified as having LD in the 1950s and the 1960s had grown into adulthood with some persisting difficulties. It increasingly appeared that LD was a life span disorder and not merely restricted to school age. The recognition that LD manifests well into adolescence and adulthood with changing manifestations, despite early intervention coupled with the realization that language acquisition too is a process that spans several years led to a shift from visually-based theories of reading disabilities to language-based theories. The identification of “auditory processing disorders” in the absence of any permanent peripheral hearing loss, has also been increasingly recognized as a contributor to language learning disability in children. Educators often describe these children who have difficulty in auditorily processing information as children “who do not

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follow instructions” or children “who are not listening”. The audiological model views these children as having Central Auditory Processing Disorders (CAPD), a perceptual disorder, involving problems of attending, analyzing, and comprehending relevant auditory stimuli. The Speech–Language Pathology (SLP) model views it as a language deficit involving poor linguistic, semantic, and cognitive processing skills for dealing with auditory stimuli. The difference between the two is that while the audiological model emphasizes the failure in the auditory processing system, which results in inaccurate or incomplete signals being transmitted, the SLP model focuses on the lack of established associations between linguistic forms at multiple levels that have never been established. The question whether the interaction between perceptual and linguistic factors is causative or co-relational, remains.

METALINGUISTICS A second major factor that led to the recognition of the importance of language in LD is the identification and acknowledgment of the role of metalinguistic skills in learning to read. Broadly defined metalinguistic skill refers to learning to treat language as a focus of cognitive reflection, that is, “thinking about language to use language to think” (van Kleeck, 1994). The role of metalinguistic skills in reading acquisition was first documented with reference to phonological awareness and early reading acquisition in children learning to read English. Subsequently, however, this area of study has broadened to include other aspects of metalinguistic skills and the latter is now seen as providing a link for moving children from social to increasingly instructional use of language.

Phonological Awareness Since the 1980s there has been increasing empirical evidence that a child’s awareness of and skill in manipulating the phonemes of a word is closely related to his reading skills. Consequently, phoneme awareness is seen as an essential step in the acquisition of reading.

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A child’s phoneme or phonological awareness is generally examined by getting him or her to perform a set of tasks, such as rhyming, phoneme deletion, counting, segmentation, and oddity tasks. In the simplest of these tasks, a child is required to state whether a given pair of words rhyme or not. In tasks such as phoneme counting, the child is required to listen to given words and count the number of phonemes in a word whereas the segmentation task requires that the word be broken down in to the smallest units possible, as illustrated. In the deletion task, the subject is required to delete a particular phoneme (first, last, or middle) and to say the remaining part of the word. Extensive empirical investigations on these lines clearly established that good readers were also good at phoneme awareness tasks, while poor readers were also poor at phoneme awareness tasks. This led to the postulation that good phoneme awareness was a necessity for becoming a good reader. However, it was also observed that with increased exposure to reading there was an increase in phonological awareness thus supporting not only a causal but also, perhaps, a reciprocal role for phonological awareness in reading acquisition. A direct clinical consequence of these findings has been a revival of focus on the assessment of phonological skills in children with difficulties in early reading skills and a subsequent intervention program based on these findings. In addition to a renewed interest in and a revival of assessment and intervention protocols such as the Lindamood Phoneme Sequencing Program for Reading, Spelling and Speech (Lindamood and Lindamood, 2000); a host of new assessment and intervention procedures for children with reading difficulties such as the Test of Phonological Awareness (Torgesen and Bryant, 1994) and Comprehensive Test of Phonological Processing (CTOPP—Wagner et al., 1999) have cropped up. In keeping with the current understanding of these difficulties spanning a wider age range, the assessment and intervention procedures also cater to a wider age range of the learning disabled from ages 5 to 24.11 years. The issue of the relatedness of phonological awareness and early reading, which began in the English-speaking world, not only continues to be investigated extensively there but has also spread to the readers of other European languages, as well as to those from

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the non-English-speaking world. Even though the sequence of phonological awareness development is similar across languages, the sub-syllabic units of which children become aware are likely to vary from language to language. The level at which correspondences between phonology and orthography are maximal could differ from one language to another. It is now increasingly recognized that the level of phonological awareness that is most predictive of reading development may vary with the orthographic transparency in general and with the spelling units at which the regularity is maximal. For instance, while children who are learning non-transparent alphabetic scripts like English develop a larger phonological–orthographic unit at which the correspondence is fairly consistent, children who read more transparent alphabetic orthographies, such as Spanish, make more fine-grained correspondences between graphemes and phonemes. However, it is generally agreed that the relationships between varieties of phonological awareness and the ability to read words holds for various European languages such as German, Spanish, English, and French despite some variation in the phonological input provided by different languages (Goswami, 1999). That this relationship holds equally in “nonEuropean languages and non-alphabetic scripts” is not, however, as well established and researchers such as Harris and Hatano (1999), and Goswami (1999), among others emphasize the need for crosslinguistic studies before any firm conclusions can be reached. Investigations on phonological awareness, similar to those described above, when conducted on children learning to read in the non-alphabetic Eastern scripts such as those of China, India, and Japan, do not seem to support such a robust relationship between phonological awareness and early reading skills. The scripts of these countries vary considerably from the Western alphabetic scripts. While both China and Japan use two scripts—an ideographic script in combination with a syllabic script, the Indian languages are written in a script type that is increasingly being classified as an alphasyllabary—a syllabary incorporating alphabetic principles in which the basic unit of writing the “akshara” is a syllable. For instance, the Kannada (one of the alphasyllabic scripts of India) word “pustaka” meaning book comprises three letters representing the syllables/pu/sta/and/ka/, each letter representing one or more

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consonants and a vowel. Unlike the alphabetic scripts like English, consonants cannot be written as independent letters in the Indian scripts like Hindi and Kannada, except in exceptional circumstances. (For more details on the Indian alphasyllabaries see Karanth, 2006.) The differences in phonological awareness, depending on whether one has learnt an alphabetic or syllabic orthography, along with the ideographic have been documented. Investigations on phonological awareness in China indicate that readers including good readers, who were exposed to the ideographic script alone without any prior exposure to alphabetic scripts “seem to lack entirely the ability to develop the knowledge of sub-syllabic phonology that seems to play such an important role in alphabetic scripts like English” (Share, 1995). It was also demonstrated that performance on phonological awareness tasks improved significantly in children after being exposed to alphabetic and syllabic scripts (Huang and Hanley, 1994; Leong, 1991). Phonological awareness of Chinese children immediately increased once they learnt an alphabetic or syllabic system. Learning an alphabetic script influenced phonological awareness skills in Chinese children and adults. Similarly, there are reports of Japanese children who learnt to read kana and kanji, with no exposure to an alphabetic script, performing well on syllable segmentation but poorly on phoneme deletion (Leong, 1991; Mann, 1986). The authors attribute these results to the syllable-based writing system. The relative lack of phonological awareness in Japanese children learning to read in any of the Japanese orthographies, as compared to their English peers is attributed to the difference in these orthographies. Similar results have been obtained in experimental investigations on readers of the Indian alphasyllabaries. In a series of studies on phonological awareness in children and adults (literate and nonliterate), whose primary language and script was one of the Indian languages/scripts such as Kannada or Hindi, Prakash (2003); Prema and Karanth, (2003); Prakash and Rekha (1992); Prakash et al. (1993) established that phonological awareness is neither as evident nor as crucial to successful reading in these writing systems. On tasks such as rhyme recognition, syllable deletion, phoneme deletion and phoneme oddity the different subgroups of their population— children learning to read alphasyllabaries and adult monoliterates

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in alphasyllabaries (those who had learnt to read only an alphasyllabary like Kannada or Hindi), performed well in rhyme recognition and syllable deletion tasks, but with a few exceptions they rarely performed well on the phoneme segmentation tasks. In contrast, the biliterate adults (those who knew how to read Kannada and English or Hindi and English) with exposure to the alphabetic script of English, were able to carry out the phoneme segmentation and oddity tasks successfully. As compared to Kannada monolinguals, the bilingual–biliterates who had exposure to the alphabetic script performed significantly better in tasks such as phoneme stripping and phoneme deletion. Prakash and Rekha (1992) documented that children studying in Kannada-medium schools showed a spurt in performance on phoneme awareness tasks such as phoneme stripping and phoneme oddity after having been introduced to English lanuage in the fourth grade. They concluded that the difference in phonemic awareness was due to the orthographic nature of the two scripts with phonemic awareness increasing when introduced to the alphabetic script of English. These results would support the theoretical position that phonological awareness is more a concomitant of, rather than a requisite for successful reading in alphabetic scripts as suggested by Morais et al. (1986). Taken together with the Japanese and Chinese studies, it would suggest that the kinds of connections that children and beginner readers make between phonology and orthography depend on the orthography of the language being learnt and the phonological units that this orthography makes salient rather than the other way around, that is, that the phonology makes the orthographic units more salient, as suggested by Goswami. For a more comprehensive discussion of the nature of orthography and phonological awareness as related to reading acquisition see Karanth (2003b).

NAMING While phonological awareness has received the greatest attention among metalinguistic skills, with reference to reading, other aspects of metalinguistic awareness are also related to reading and reading difficulties. Other levels of metalinguistic awareness, such as semantic

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and syntactic awareness have also been investigated in children with LDs in order to further explore the relationship between language learning and learning disability. Semantic skills for instance, have been and are increasingly being explored in the reading acquisition research. Distinct relationships between vocabulary and reading comprehension are now postulated. While it was generally known that the greater the vocabulary the more accurate the reading, other aspects of vocabulary such as the speed with which a word is retrieved is also increasingly linked to reading proficiency and in turn to reading difficulty. One such area that has been explored to a considerable extent is that of semantics and word retrieval in particular. The ability to retrieve words rapidly is often measured through word fluency tests in which subjects are asked to retrieve words of a particular category (semantic or phonological) as rapidly as possible. In the word fluency tests, the subject is asked to generate words from a given category, say animals or fruits, as rapidly as possible. These word fluency and letter fluency tasks (sometimes referred to as semantic fluency) often form part of standard assessment procedures. In the naming tasks, children are asked to name serially presented objects, colors, numbers, or letters, as rapidly as possible, with both time taken and errors made taken into account. Alternately, naming speed is evaluated through discrete naming tasks in which the subject is asked to name individual visual stimuli presented briefly either through tachistoscopes or on computer screens, once again with response latencies and errors being measured. Empirical research of this nature during the last two to three decades has established that rapid word retrieval is affected in children with LDs (Korhonen, 1995; Murphy et al., 1988). Children with LDs are reported to be poorer than their peer group in naming abilities and rapid lexical retrieval. Children with LDs are found to have a less extensive vocabulary, fewer semantic associations and inefficient strategies for acquiring word meaning as compared to their peers. Several investigators have documented naming speed deficits in children with developmental dyslexia over the last two to three decades (Gardener, 1979; Wolf, 1991). In fact, apart from the reading deficit, this subtle naming deficit or dysnomia is the most frequently identified characteristic in children with dyslexia, affecting their reading comprehension with an inevitable impact on

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academics. Children with LDs are found to have less extensive vocabularies, fewer semantic associations and inefficient strategies for acquiring word meaning, as compared to their peers. The impact of these deficits in semantic processing on academics is considerable.

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More recently, attention has been focused on the acquisition of syntax and higher-level discourse. Throughout the school years, the child is exposed to and is expected to master an increasing language facility for form and function. During the school years, the child’s language environment and use move from predominantly spoken texts, which are situation dependent and non-abstract to that what is typically informational, explicit, and abstract. These characteristics of classroom discourse are generally achieved through lexical density and complex syntactic constructions. This increased facility in language is a must as a child moves through elementary and secondary school. A child with difficulties in acquiring and mastering these complex forms of language would necessarily have difficulties in learning in classroom situations. Children with LDs are often found to have difficulties in verbal analogical reasoning (Kamhi et al., 1990). Their narrative discourse processing and production are often characterized by the use of the oral style (Liles, 1987; Merrit and Liles, 1987; Montague et al., 1990). The understanding and production of written expository discourse structures such as comparison, contrast, and problem solutions are particularly difficult for them (Scott, 1989a; 1989b). Another area of concern is the comprehension and production of non-literal language such as metaphor, idioms, similes, and irony, which are important not only in social situations but also increasingly necessary for academic success as children progress in school. The “communication hierarchy” of the growing child as postulated by van Kleeck (1994) moves from the non-linguistic through the linguistic to the metalinguistic. That is, in the pre-school years, the child depends largely on non-linguistic factors for effective communication. During the early school years there is an increasing emphasis on the linguistic such as grammar. Eventually, during the

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later school years and in adulthood, there is a need for increased awareness and use of metalinguistic skills in order to become a competent communicator. From the pre-school to the high school years, the communication hierarchy takes the child from a dependence on the contextual non-linguistic to the linguistic and finally to the abstract metalinguistic. Difficulties and/or delays in moving through this communication hierarchy are commonly associated with LD. These aspects of communication are particularly relevant to the more formal aspects of communication such as is present in the written medium. It is evident that there is a robust body of scientific literature on the language-learning disability connection that has been built over the last couple of decades. Much of the research on the language learning-learning disability connection, described above, has so far come from the Western world. Empirical data on language and LD is hardly present in India. In order to investigate whether this connection was also true of children in India who are learning to read and write the Indian alphasyllabaries, we conducted a few studies on children with LD whose mother tongue and medium of instruction was one of the many Indian languages. We report below a couple of studies carried out by us in this area, on speakers and readers of Indian languages, both Indo-Aryan and Dravidian. In the first of these studies, Sharma (2000) investigated the language skills of 23 Hindi-speaking children diagnosed as having LD. These children ranged in age from 7 to 15 years and were students from grades 1 to 10. All the 23 subjects were from Delhi. Of the 23, nine were studying in a regular school, seven were in a regular school but also received remedial reading instruction, and the remaining seven were enrolled in a special school. The subjects were evaluated on the Hindi version of the Linguistic Profile Test (LPT) (Karanth et al., 1984; Sharma, 1995). The LPT originally designed by Karanth (1980; 1984), in Kannada has subsequently been developed in several Indian languages including Hindi, Malayalam, Telugu, and Tamil. It evaluates language at the phonological, syntactic, and semantic levels through a wide range of tasks such as pointing, naming, repetition, indication of grammatical acceptability, rapidly listing words from given lexical categories, sentence completion, and matching synonyms and antonyms.

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On the whole, children with LDs performed poorly on the LPT. The scores obtained by these children with LDs differed significantly (.001) at all age levels from the norms. The language age of the children with LD ranged between < six years and eight years (six being the lower end of the cut off score for norms). Syntax and semantics were affected more than phonology. Within phonology, phonemic discrimination between minimal pairs posed some problems for children with LD. The younger learning-disabled children performed at a chance level in the section on syntax much like normal children below the age of six years. The older children with LDs performed well on items related to plurals, tenses, and case markers but had considerable difficulty with the more complex participial and conditional clauses. Interestingly, none of the 23 children was suspected of having particular difficulties in language since they “conversed normally”. Semantic relations such as paradigmatic and syntagmatic relationships, and contiguity were poorly understood by children with LD as compared to their normal peers. In order to verify these results further, we repeated the study with a group of children diagnosed as having LD, this time in a Dravidian language, in the southern state of Kerala (George, 2001). The same procedure was repeated on 21 children, diagnosed with LD at the Institute of Communicative and Cognitive Neuro Sciences (ICCONS), Trivandrum, with the Malayalam version of the Linguistic Profile Test (Mammen, 1997). The children, whose mother tongue and medium of instruction was Malayalam, ranged in age from 6 to 15 years and were enrolled in regular schools. Their linguistic skills were assessed in a similar procedure, this time on the Malayalam version of the LPT. Once again, with an exception, children with LD scored well below their normal peers. The differences between the scores of children with LD and the norms for their age differed significantly (.001). The finding of greater difficulty in syntax and semantics as compared to phonology was also replicated. The findings on phonemic discrimination, syntactic structures, such as conditionals, and participial and semantic features of paradigmatic and syntagmatic relationships, were also repeated. Another relevant observation that emerged was that the gap between the chronological age and language age of the children with LD increased with age.

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Our data on Indian children with LD indicates that they have specific delays or deficits in language acquisition as compared with their peers. Interestingly all of these children fared well at the conversational level, with the results of the formal language assessment coming as a bit of a surprise even to the speech pathologists who did the testing. A second pertinent observation that may be of particular relevance is the repeated finding that the discrepancy in scores (as compared to norms) was greater in the sections on syntax and semantics as compared to phonology. As seen earlier, phonological awareness does not appear to be as closely linked to success in learning to read the non-alphabetic scripts as it is in the case of alphabetic, particularly opaque alphabetic scripts like English and French. In any case, the phonological section of LPT tests phoneme discrimination and production, and not the metalinguistic skill of phoneme awareness. In contrast, the section on syntax in the LPT is heavily dependent on metasyntax, as the tasks in this section require the subject to perform grammaticality judgments. It is possible that these differences in findings reported in Western literature as compared to ours could be due to script and language specific features. We have argued elsewhere that the syllabic nature of the Indian scripts coupled with a high transparency, where with a few exceptions, the majority of the scripts show a high degree of grapheme–phoneme correspondence (gpc) preempts the need for a high level of phonological awareness for success in learning to read (Karanth 2002; 2003b). In contrast, the highly inflected, agglutinative nature of the Indian languages would require a high level of morphosyntactic awareness for efficient reading. Children who fail to perceive the significance of erroneous morphological endings in words with bound morphemes would necessarily have enormous difficulties in reading at the phrasal and sentence levels. For a lengthy discussion of these issues see Karanth (2002; 2003b).

IMPLICATIONS These findings hold enormous significance for the education of children in India, both in English and in vernacular languages. For years

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there has been a standoff between the East and the West on the issue of LD. Easterners, including Indians, dismissed the issue of reading difficulties in children as the consequence of the vagaries of writing systems like English and French while the Westerners attributed the seemingly lower incidence of the developmental dyslexias in Eastern countries to the lack of awareness and sensitivity among teachers who had to cope with large number of students in less than ideal conditions. We are now finding LD in Indian children, not only in English-medium schools but also in the vernacular, laying to rest the claim that LD was entirely due to the bizarre nature of opaque alphabetic scripts like English (Gupta, 2002; Suresh and Sebastian, 2003). Increasingly with more fine-tuned research into language learning and metalinguistic skills in particular, the nature of the language and script are gaining importance as possible contributory factors leading to these discordant viewpoints. If this turns out to be so then the implications that these findings hold for our educational practices, particularly those concerning the teaching of reading as also those that concern the reading disabled need to be carefully thought out, planned, and implemented. For education in English as the medium of instruction, extensive research on and recognition of the importance of phonemic awareness has now led to a series of assessment and remediation protocols and procedures; which with some modifications could perhaps be implemented for Indian children having difficulty in learning to read English. However, it needs to be acknowledged that for most of these children, English would still be a second language and the amount of input that the family can provide for language scaffolding needs to be considered. In addition, the effect of the native language, particularly on phonological processes cannot be ignored. Finally, despite its perceived lower social status, education in the vernacular as the medium of instruction should be seriously advocated particularly for those children who have a specific difficulty with grapheme–phoneme conversion or visual–auditory matching difficulties, given the higher levels of transparency and consistency that our scripts provide. On the other hand, the implications would be of a different nature for education in the vernacular. Under the influence of the

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pedagogic battles of the West, we have in the recent past introduced the teaching of our alpha-syllabic scripts through phonics. A measure that seems to be not only completely unnecessary but also perhaps counter-productive. (See Karanth, 2002; 2003a; 2003b; Karanth and Prakash, 1996 for a fuller discussion of this issue.) In contrast, given our findings on metasyntax along with the hyperlexia, reported by Prakash (1987), in children learning to read the Indian scripts our emphasis on semantics and syntax would have to be far greater. If our findings are substantiated further by empirical research, it is likely that we could guide parents into making informed choices on the medium of instruction, particularly for children with learning or reading difficulty rather than be influenced solely by perceived “social status” of a given language.

THE LARGER ISSUES There are of course the larger issues of bilingual–biliterate education. With the emergence of the global village the bilingual child is becoming more the rule than the exception. Predominantly monolingual societies are being forced to acknowledge and provide for bilingualism, thanks to the large numbers of children from immigrant families, who expect to be provided for in their schools. Therefore there is a body of literature beginning to emerge on the bilingual child in Western societies. It is important that we recognize the differences in the environmental or social factors that operate in their context as against ours before we implement their recommendations in our conditions (as in the case of the “phonics” method of teaching). Teaching as well as assessment and intervention for the child learning to read in the vernacular has to be influenced by empirical findings on our languages and scripts rather than by Western thought and literature alone. We need to recognize and capitalize on some of the inherent merits of our transparent alpha-syllabic scripts and the tradition of rote learning, at least in the initial stages as well as acknowledge the need to emphasize meaningful reading given the transparency of our writing systems once the child masters the syllabary.

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REFERENCES Bashir, A.S., E.H. Wiig and J.C. Abrams. 1987. ‘Language Disorders in Childhood and Adolescence: Implications for Learning and Socialization’, Pediatric Annals, 16(2): 145–56. Catts, H.W. 1989. ‘Defining Dyslexia as a Developmental Language Disorder’, Annals of Dyslexia, 39(1): 50–64. Gardener, R.A. 1979. The Objective Diagnosis of Minimal Brain Dysfunction. Cresskill, N.J: Creative Therapeutics. George, N. 2001. ‘Language Skills in Malayalam Speaking Learning Disabled Children’, Unpublished Masters Dissertation, Mangalore University. Goswami, U. 1999. ‘The Relationship Between Phonological Awareness and Orthographic Representation in Different Orthographies’, in M. Harris and G. Hatano (eds), Learning to Read And Write: A Cross-Linguistic Perspective. New York: Cambridge University Press. Gupta, A. 2002. ‘Developmental Dyslexia in a Bilingual Child’, Journal of Personality & Clinical Studies, 18: 19–26. Harris, M. and G. Hatano. 1999. Learning To Read And Write: A Cross-Linguistic Perspective. New York: Cambridge University Press. Huang, H.S. and R. Hanley. 1994. ‘Phonological Awareness and Visual Skills in Learning to Read Chinese and English’, Cognition, 54(1): 73–98. Kamhi, A.G. and H.W. Catts (eds). 1989. Reading Disabilities: A Developmental Language Perspective. MA: Allyn & Bacon. Kamhi, A.G., B. Gentry, D. Mauer and B. Gholson. 1990. ‘Analogical Learning and Transfer in Language—Impaired Children’, Journal of Speech & Hearing Disorders, 55(2): 140–48. Karanth, P. 1980. ‘A Comparative Analysis of Aphasic and Schizophrenic Language’, Unpublished Doctoral Thesis. Mysore: University of Mysore. ——————. 1984. Inter-Relationship of Linguistic Deviance and Social Deviance. Report on the Young Scientists Fellowship Award. New Delhi: Indian Council of Social Science Research. ——————. 2002. ‘Reading into Reading Research through Nonalphabetic Lenses— Evidence from the Indian Languages’, Topics in Language Disorders, 22(5): 16–27. ——————. 2003a. ‘Language and Learning Disability or Language Learning Disability’, in P. Karanth, and J. Rozario (eds), Learning Disability in India— Willing the Mind to Learn. New Delhi: Sage Publications. ——————. 2003b. Cross-linguistic Study of the Acquired Disorders of Reading: Implications for Reading Models, Instruction and Intervention. New York: Kluwer Academic. ——————. 2006. ‘The Kagunita of Kannada– Learning to Read and Write an Indian Alphasyllabary’, in R. Maltesha Joshi and P.G. Aaron (eds), Handbook of Orthography and Literacy, 389–404 . London: Lawrence Erlbaum Associates. Karanth, P., G. Gandhi, R. Pandit and K.R.Usha. 1984. Language disorders in Indian neurological patients: A study in neurolinguistics in the Indian context. Project

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No 5/8/101(oto)/84-NCD-IRIS Cell. New Delhi: Indian Council of Medical Research. Karanth, P. and P. Prakash. 1996. ‘A Developmental Investigation of Onset, Progress and Stages of Literacy Acquisition—Its Implications for Instructional Process’, Unpublished Project Report. New Delhi: NCERT. Korhonen, T. 1995. ‘The Persistence of Rapid Naming Problems in Children with Reading Disabilities: A Nine-Year Follow Up Study’, Journal of Learning Disability, 28(4): 232–39. Leong, C.K. 1991. ‘From Phonemic Awareness to Phonological Processing to Language Access in Children Developing Reading Proficiency’, in D.J. Sawyer and B.J. Fox (eds), Phonological Awareness in Reading: The Evolution of Current Perspectives. New York: Springer-Verlag. ——————. 1997. ‘Paradigmatic Analysis of Chinese Word Reading: Research Findings and Classroom Practices’, in C.K. Leong and R.M. Joshi (eds), CrossLanguage Studies of Learning to Read and Spell: Phonological and Orthographic Processing, pp. 379–417. Dordrecht: Kluwer Academic Publishers. Liles, B.Z. 1987. ‘Episode Organisation and Cohesive Conjunctions in Narratives of Children With and Without Language Disorders’, Journal of Speech & Hearing Research, 30(2): 185–96. Lindamood, P. and P. Lindamood. 2000 (3rd edition). The Lindamood Phoneme Sequencing Program for Reading, Spelling & Speech. Pro Ed: USA. Mammen, A. 1997. ‘Linguistic Profile Test in Malayalam- Normative Data for Children in Grades I to X’, Unpublished Master’s Dissertation. Mysore: University of Mysore. Mann, V.A. 1986. ‘Phonological Awareness: The Role of Reading Experience’, Cognition, 24(1–2): 65–92. Merrit, D. and B. Liles. 1987. ‘Story Grammar Ability in Children with and without Language Disorders: Story Generation, Story Retelling and Story Comprehension’, Journal of Speech Language and Hearing Research, 30: 539–52. Montague, M., C.D. Maddox and M.I. Dereshiwsky. 1990. ‘Story Grammar and Comprehension and Production of Narrative Prose by Students with Learning Disabilities’, Journal of Learning Disabilities, 23(21): 190–97. Morais, J., P. Bertelson, L. Cary, and J. Alegria. 1986. ‘Literacy Training and Speech Segmentation’, Cognition, 24(1–2): 45–64. Murphy, L.A., A. Pollastek, and A.D. Well. (1988). ‘Developmental Dyslexia and Word Retrieval Deficits’, Brain and language, 35(1): 1–23. Mykleburt, H.R. (1954). Auditory Disorders in Children: A Manual for Differential Diagnosis. New York: Grune & Stratton. Orton, S. 1937/1989. ‘Reading, writing and speech problems in children’, in A.G. Kamhi and H.W Catts (eds), Reading Disabilities: A Developmental Language Perspective. Allyn & Bacon: MA. Prakash, P. 1987. ‘Reading Development, Metalinguistic Awareness and Cognitive Processing Skills’, Unpublished doctoral Dissertation. Utkal: Utkal University. ——————. 2003. ‘Early Reading Acquisition’, in P. Karanth and J. Rozario (eds), Learning Disability in India: Willing the Mind to Learn, pp. 62–76. New Delhi: Sage Publications.

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Prakash, P. and B. Rekha. 1992. ‘Phonological Awareness and Reading Acquisition in Kannada’, in A.K. Srivastava (ed.), Researches in Child and Adolescent Psychology, pp. 47–52. New Delhi: NCERT. Prakash, P., D. Rekha, R. Nigam and P. Karanth. 1993. ‘Phonological Awareness, Orthography and Literacy’, in R. Scholes (ed.), Literacy and Language Analysis, pp. 55–70. New Jersey: Lawrence Erlbaum Associates. Prema, K.S. and P. Karanth. 2003. ‘Assessment of Learning Disability: Language Based Tests’, in P. Karanth and J. Rozario (eds), Learning Disability in India: Willing the Mind to Learn, pp. 138–49. New Delhi: Sage Publications. Scarborough, H.S. 1990. ‘Very Early Language Deficits in Dyslexic Children’, Child Development, 61(6): 1728–43. Scott, C. 1989a. ‘Problem Writers: Nature, Assessment and Intervention’, in A. Kamhi and H. Catts (eds), Reading Disabilities: A Developmental Language Perspective, pp. 303–44. Boston: College Hill Press. ——————. 1989b. ‘Learning to Write: Content, Form and Process’, in A. Kamhi and H. Catts (eds), Reading Disabilities: A Developmental Language Perspective, pp. 261–302. Boston: College Hill Press. Share, D.L. 1995. ‘Phonological Recoding and Self-Teaching: Sine Qua Non of Reading Acquisition’, Cognition, 55(2): 151–218. Sharma, M. 1995. ‘Linguistic Profile Test (Hindi)—Normative Data for Children in Grades I to X’, Unpublished Masters Dissertation, Mysore: University of Mysore. ——————. 2000. ‘Language Skills in Children with Learning Disability’, Unpublished masters dissertation, Mangalore: University of Mangalore. Suresh, P.A. and S. Sebastian. (2003). ‘Epidemiological and Neurological Aspects of Learning Disabilities’, in P. Karanth and J. Rozario (eds), Learning Disability in India: Willing the Mind to Learn. New Delhi: Sage Publications. Torgesen, J.K. and B.R. Bryant. 1994. Test of Phonological Awareness. Austin: Pro Ed. van Kleeck, A. 1994. ‘Metalinguistic Development’, in E. Wallach and K.G. Butler (eds), Language Learning Disabilities in School-Age Children and Adolescents. Second edition. New York Merrill/Macmillan. Wagner, R., J.K. Torgesen and C. Rashotte. 1999. Comprehensive Test of Phonological Processing (CTOPP). Pro Ed: Austin. Wolf, M. 1991. ‘Naming Speed and Reading: The Contribution of the Cognitive Neurosciences’, Reading Research Quarterly, 26(2): 123–42.

4 Developmental Dyslexia Evidence from Hindi-speaking Children with Dyslexia ASHUM GUPTA

D

evelopmental dyslexia has been regarded as a grapheme– phoneme conversion deficit, which affects all aspects of the written language. Children with dyslexia are very poor in reading non-words and low-frequency words but do not appear to have difficulty of similar magnitude in reading familiar and high frequency words. They cannot decode successfully a large number of unfamiliar words and non-words even when they are not under time pressure (Aaron, 1989). Van der Leij and Van Daal (1999) examined three characteristics of dyslexia: 1. speed limitations in word identification; 2. sensitivity to increasing task demands; and 3. orthographic compensation. When comparing the reading performance of students with dyslexia to chronological-age (CA) controls and reading-age (RA) controls, they found that the response latencies of students with dyslexia were slower when familiar words and letter clusters had to be named. A larger word-frequency effect and a larger word-length effect in these students indicated that they have difficulty with increasing task demands. Differences among the three groups were interpreted in terms of automatization.

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Reading aloud single familiar words is normally a top-down activity because the child can utilize stored orthographic representations and read words “automatically”. Reading aloud new and unfamiliar words is a bottom-up activity because there is no stored orthographic representation and therefore the word needs to be decoded by using letter–sound conversion rules (Stackhouse and Wells, 1997). According to Gough and Walsh (1991), two sources of knowledge are required for skilled word recognition—the cipher (knowledge of grapheme–phoneme correspondences) and wordspecific information. Stanovich et al. (1991) speculated that, while at an early stage of acquisition, reading problems could be accounted for by deficient phonological processing skills, problems in the ability to form, store, and access orthographic representations would result in reading difficulties at a later stage of development. Visual word recognition has largely been studied in English language. It was believed that reading processes (as well as other cognitive processes) are universal, and therefore, studies in English are sufficient to provide a complete account of the processes involved in recognizing printed words. If an orthography is highly transparent, with very consistent mapping from spelling to sound, then grapheme– phoneme correspondence (GPC) should be easier to detect. In a less transparent orthography, the underlying rules will be less consistent, and may be more complex in terms of being context sensitive and operating at different phonological levels. According to Wimmer (1996), such difficulties should be reduced for orthographies with consistent grapheme–phoneme relationships. Therefore, children with reading disabilities may have comparatively little difficulty acquiring phonological coding in a transparent orthography. In a study by Zoccolotti et al. (1999), the characteristics of surface dyslexia in Italian language with high grapheme–phoneme correspondence were examined. The most pervasive reading symptom was severe slowness. The results showed that parallel visual processing of words was impaired, and that the dyslexic boys analyzed words sequentially, presumably through an orthographic–phonological conversion. The analysis of the patterns of errors indicated that in most cases they were visual approximations of the target word. The word-reading errors involved elisions, insertions, or substitutions of one or more letters. In reading single words of different lengths,

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all the dyslexic children gave proof of proceeding sequentially in their analysis; thus, vocal reaction times grew monotonically with increasing word length. The present study is an examination of the word-reading errors of Hindi-speaking Indian children who were diagnosed as dyslexics. Zoccolotti et al. (1999) pointed out that in languages such as English and French where there is a “loose” relationship between graphemes and phonemes, the dyslexic syndrome results in a variety of errors, as the phonological analysis of words is often insufficient. In languages such as German and Italian, with considerably more regular grapheme–phoneme correspondence, the number of errors may be small, as sublexical procedures adequately solve most reading problems, and the most conspicuous symptom is reading slowness. In the present research, it was speculated that despite Hindi being a transparent orthography where the mapping from grapheme to phoneme is largely consistent, there may nevertheless be many signs of phonological deficits in children suffering from dyslexia. Children with dyslexia selected for the present study were not only slow in reading but also were poor decoders, committing different types of errors in reading words in Hindi. For understanding the findings of the present study, some information on Hindi orthography is provided in the following paragraphs.

HINDI ORTHOGRAPHY Hindi is written in Devanagari script. The Devanagari alphabet, which developed as the script used to write down Sanskrit, consists of 48 letters and several diacritical signs (Bright, 1996). The arrangement of the alphabet is strictly phonetic—letters are classified by place of articulation with vowels and diphthongs presented first followed by consonants. The details pertaining to the arrangement of letters are provided in an article by Vaid and Gupta (2002a). Hindi is written and read from left to right. Words are written with a horizontal bar linking the letters. Word boundaries occur at junctures coinciding with breath pauses in connected discourse. The letters are printed and there are no upper versus lowercase distinctions. Hindi consonants are pronounced with an inherent short schwa

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vowel, which has no independent graphemic form. Consonant clusters are written either by forming ligatures involving a half consonant attached to a full one or by adding a special sign to indicate the absence of the schwa. There are different graphemes corresponding to short and long vowels. Vowels appear as separate letters, in full form, in the word-initial position and as diacritical signs (known as maatraas) in the medial or word-final positions. In the non-initial positions, vowel signs are placed non-linearly above, below, or to the left or right of consonants. The Hindi script arguably has syllabic as well as alphabetic properties. The fact that phonemes are graphemically marked aligns it with other alphabetic scripts. However, unlike most alphabetic scripts, in which consonants typically stand alone as phonemes, consonants in Hindi have an inherent associated vowel. As such, Hindi resembles a syllabary. However, in contrast to a purely syllabic script, such as kana, which would employ distinctly different symbols for the syllables “ma” versus “mu”, in Hindi, the symbols for these syllables share a common graphic sign corresponding to the phoneme “m” and diacritical signs corresponding to the different vowel sounds. According to Gaur (1995), Indic scripts are thus more appropriately viewed as semi-syllabic in that, graphemes representing consonants are spatially grouped together with vowel signs to form a syllable bundle. The question whether words in Hindi are more phoneme delimited or syllable delimited was examined by Vaid and Gupta (2002a) in their study on the processing of words with consistent versus discrepant visual and auditory sequencing. The results supported a partly phonemic and partly syllabic level of segmentation, consistent with the structural hybridity of the script. Not much is currently known about how beginning or skilled readers of the Hindi writing system are influenced by the design of the script. Recent works with normal and dyslexic readers of Hindi (Gupta et al., 1997; Gupta and Vaid, 2002; Nehru and Garg, 1997), highlight specific problems in Hindi spelling related to vowel length and vowel placement confusion and in case of consonant clusters in ligatures. The current research has attempted to do a detailed analysis of single-word reading errors made by children with dyslexia to understand the nature of difficulties experienced by them in processing words in Hindi. The segmentation of words in Hindi may be done

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at the level of individual phonemes, (more so in case of consonants) and at the level of syllable units when vowels forms are placed above, below, or to the left or right of the consonants. Hindi script has certain specific features which need to be learnt adequately by children in the process of acquiring oral and written language skills. For example, consonants occurring in clusters may involve both initial and medial sequences of two or three consonants, for example, ty, pr, kv, st, ks, str, and ksm. Such conjunct symbols present a lot of difficulty to the learners of Hindi. Even the proficient users of Hindi face a lot of problems with a few consonant sequences corresponding to special conjunct symbols. The reading preparation starts in kindergarten where children start learning a few letters. The children are gradually introduced the grapheme–phoneme correspondences through the phonics program. They are trained to recognize words slowly by grapheme–phoneme conversion and blending. Graphical devices are used to mark syllabic boundaries. Initially children may learn incorrect stress assignments but with repeated practice, they learn them correctly. In case of normally progressing readers of Hindi, the combination of consistent orthography and a phonicsbased teaching approach should make the acquisition of phonological coding in word recognition rather easy. The main complexity of Hindi orthography concerns the orthographic markings of Hindi vowels varying in length. English vowels are phonologically irregular, making vowel-rule learning an extremely difficult cognitive task. Reading errors in case of English vowels and consonants have been analyzed in a number of studies. A study by Tal and Siegel (1996), for example, examined the reading performance of the three groups (dyslexic, poor, and normal readers) according to the type of reading error committed on a test of pseudoword reading (Woodcock Word Attack subtest). There was very little difference among dyslexic, poor, and normally achieving readers in the type of errors made. Nearly 50 percent of all the oral reading errors of all three groups were vowel substitutions, followed by consonant substitution, deletion and insertion errors. Sequential, reversal, and word substitution errors were committed infrequently for all three reader groups. Despite the regularity of Hindi vowels, readers of Hindi may face several difficulties because of the complex nature of these

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vowels. Thus the research question is—Are reading difficulties of Hindi-speaking children reflections of phonological impairments? The assumption is that despite the transparency of Hindi script, children with developmental dyslexia will exhibit reading difficulties as evidenced by their reading accuracy as well as speed. Both, speed and accuracy problems would be especially evident when relatively longer words are presented. The purpose thus was to examine single-word reading speed and accuracy of children with dyslexia in comparison to reading-age (RA) matched and chronological-age (CA) matched children. A detailed error analysis was carried out to understand the nature of reading difficulties.

METHOD Participants Children included in the present study were selected from four primary schools in Delhi. The diagnosis of dyslexia was based on multiple criteria including children’s performance on a standardized single-word reading test in Hindi (Gupta, 1997), performance on a spelling test, teacher ratings, and the author’s own observations over a period of time of the children’s spelling errors from their school notebooks. Only those children were regarded as suffering from dyslexia if their reading speed and accuracy was about two standard deviations below their chronological age as determined by the word reading test norms. Besides the reading test, children were made to read certain passages from their Hindi course books to ascertain their reading problems. Their Hindi notebooks were examined and it was found that they were frequently committing errors of substitution, deletion, and insertion with a few reversal errors. Only those children were included in the study whose intellectual ability was in the normal range as assessed by the Raven’s Coloured Progressive Matrices (Raven et al., 1992). Children with neurological problems, emotional disturbance, mental retardation, or environmental disadvantage as causes of their reading impairment were excluded from the study.

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The final sample consisted of 90 right-handed children (boys and girls) taken from four primary schools in Delhi. The schools were matched on a number of variables including geographical area, classroom size, and teaching methods. Three groups were included—30 children with dyslexia with mean age of nine years two months, 30 RA matched children with mean age of seven years three months and 30 CA matched children without reading difficulties with mean age of nine years three months. Each group had 15 boys and 15 girls. The sample from which the dyslexic children were selected was obtained by asking the school teachers of second and third grade classes whether they had any children in their classes with unexpected difficulties in learning to read and/or to spell. These children were reported to be facing difficulties right from their early stage of reading and writing. The children were retained in the regular classrooms as there are no separate special schools in Delhi for children with dyslexia, and there is very little awareness among school teachers and parents about dyslexia. The children had not been subjected to any remedial reading instruction program. The reading and spelling development of the RA and the CA controls was found to be age equivalent. The CA controls were matched with the children with dyslexia in chronological age while the RA controls were about two years younger than the corresponding children with dyslexia. All the RA and CA control children were judged by their teachers as showing normal reading and writing progress. The medium of instruction in the schools from which children were selected was English. Since the beginning, all the children had to study two languages, namely, Hindi and English, all the children were bilingual with their first language being Hindi. In the majority of cases, Hindi was the language spoken at home and with peers in the school. In school they were exposed to a phonics teaching program which directly presented all grapheme-phoneme correspondences and induced word decoding via training on “sounding out and blending”.

Materials A single word reading aloud task was used to assess the reading skills of the three groups of children. A list of 30 familiar Hindi words was

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prepared. The 30 words included an equal number of two-, three-, and four-syllable words, ranging from two to six letters strings. The list was constructed so as to represent various levels of orthographic complexity. Each of the words was printed on a 3×5" white card with black letters.

Design and Procedure A 3 (Group) × 2 (Gender) × 3 (Syllable Length) factorial design, with group and gender as between–subjects factors and syllable length as within–subject factors, was employed. Two separate dependent measures were used: reaction time and accuracy. Children were tested individually in a quiet room in their school and the items were presented one by one. The child was required to read each word aloud into a microphone as quickly and as accurately as possible and the responses were tape recorded for error analysis.

RESULTS The analysis of variance of reading aloud latency resulted in a significant main effect of Group, F(2.84)=5.26, p<0.05, with the reading latency of dyslexics being significantly greater than that of the CA controls, but not significantly greater than the RA controls. RA controls were significantly slower than CA controls. No significant main effect of gender was found. There was a significant main effect of syllable length (p<0.001) with the mean reaction time for two-syllable words being significantly shorter (p<0.05) than for either three- and four-syllable words. None of the interactions was found to be significant. The analysis of variance on reading errors indicated a significant main effect of Group, F(2.84)=39.34, p<0.01, with children with dyslexia making significantly greater number of errors than either the RA or the CA group. There was no significant main effect of gender. None of the interaction effects was found to be significant.

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Nature of Errors The errors produced by the children were classified into: 1. graphemic errors, 2. phonological errors, and 3. mixed errors. Graphemic errors were those that had visual similarity with the target word. Phonological errors were sound based errors. There were other errors that had both graphemic and phonological similarity and other features because of which they could not be placed in the category of either graphemic or phonological errors. Out of the total errors made by children with dyslexia, 72 percent were graphemic errors, 11 percent were phonological errors and 17 percent were mixed errors. The RA group also produced a far greater percentage (68 percent) of graphemic errors as compared to phonological (17 percent) errors while the remaining errors (15 percent) were of a mixed nature. For the CA controls, 38 percent were graphemic errors, 54 percent were phonological errors, while 8 percent of the errors were of mixed nature. The CA group tried to follow the grapheme– phoneme conversion rules as far as possible except for the long words where they tended to produce errors of single consonant or vowel substitution, deletion and insertion, while children with dyslexia tended to produce more of double or multiple consonant or vowel substitution, deletion, and insertion errors. The error patterns for all the groups indicated single or multiple substitutions, deletions, and insertions, with substitution and deletion errors being committed most frequently, followed by deletion, insertion, and transposition errors. A sample of different types of errors made by children with dyslexia is shown in Table 4.1. Vowel errors or maatraa errors were made more often than consonant errors by all the three groups. The consonant errors made by children with dyslexia were 35 percent while the vowel errors were 65 percent. The RA also produced far greater percentage (68 percent) of vowel than consonant errors (32 percent). Similar was the case for the CA controls (42 percent consonant errors, 58 percent vowel errors).

dey dks;y( gksyk; fejuk( fe[ku( eD[ku rkfjey( rkfj[k y;keu( yiuk;k dfufjdk( dfuokl

rey gks;y fe[kuk rkfj;y yiukiu dkfudkjd

rcek dey tkdj tgku( tky viuk;r( viuk;( vuk;ku vuq'kh( vuqfdch vfook'ku( vuq'keo

rcyk dejk tkuoj tgkt viukiu vuqHkoh vuq'kklu

Source: Computed by the author.

Response

Target

Graphemic Errors

Response

Graphemic Errors

Target

rcyk dejk tkuoj tgkt viukiu vuqHkoh vuq'kklu

Target

rckyk dkekjk( dej tuoj( tuokj tkt viukuk vuqHkkoh( vuqHko vu'ku( vklu

Response

Phonological Errors

reky gksy fe[kkuk( e[kuk rfj;y yiukuk duhdj

Response

Phonological Errors

Words

rey gks;y fe[kuk rkfj;y yiukiu dkfudkjd

Target

Non-words

rc de tku viuk vuqc vuq'kk

viukiu vuqHkoh vuq'kklu

Response

Mixed Errors

re gks; feuk rkfj yi( liuk dkfud( dfu

Response

Mixed Errors

rcyk dejk tkuoj

Target

rey gks;y fe[kuk rkfj;y yiukiu dkfudkjd

Target

Table 4.1 Common Graphemic, Phonological, and Mixed Errors of Dyslexic Children

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DISCUSSION The results showed that children with dyslexia suffered from speed as well as accuracy deficits. According to Bowers and Wolf (1993), slow reading rate may prevent the appropriate amalgamation of the connections between phonemes and orthographic patterns at word and sub-word levels of representation. It can limit the quality of orthographic representations in long-term memory. Further, the amount of reading practice required would be much greater before an orthographic code is learned as a lexical or sub-lexical unit and before representations of sufficient quality are achieved. Nicolson and Fawcett (1990) argued that automatization problems may hold the key to the cause of underlying dyslexic performance.The better the automatization of each of the sub-skills involved in fluent reading, the lower is the cognitive load and higher the processing speed. Perfetti (1985) demonstrated that dyslexic readers show longer vocalization latencies, slower lexical access, and less efficient use of phonological encoding in single word identification. This slowness may overtax short-term memory. In addition, dyslexics seem to have a problem in the organization of the phonological lexicon in long-term memory. Longer words place increasing demands on working memory. Further, the complexity of a particular rule will influence the difficulty of word recognition because the number of possible alternative grapheme–phoneme pronunciations may have an influence on the ease or difficulty of reading a particular word. Given more alternatives, pronunciation reading will be slower and less accurate until the individual items are mastered (Siegel, 1992). Poor reading skill might lead to a dependence on the sight-word reading strategy. According to Snowling (1987), dyslexics probably face difficulty with phoneme segmentation and phonological memory which sets them at the greatest disadvantage. Dyslexics may be either late in acquiring skills of letter–sound association or they may fail to do so. The results showed that all the three groups had produced a greater number of errors on 3- and 4-syllable words as compared to 2-syllable words. Children with dyslexia are expected to recognize familiar words (for example, two-syllable words which they use very often) quite accurately although they are slower

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than normal children but they have greater difficulty with recognizing longer and unfamiliar words. However, in the present study, dyslexic children were found to have difficulty even with twosyllable words. With increasing length of syllables, the performance of children with dyslexia was observed to be deteriorating far more than that of the CA controls, although the Group x Syllable Length interaction failed to reach statistical significance. Children with dyslexia often read the letters in the word individually, exhibiting poor phonemic/syllabic blending skills. Poor ability to blend the various phonemes or syllables of a word may indicate impairment at the level of grapheme-to-phoneme conversion (Aaron, 1989) as well as a deficit in lexical access. Further, the pronunciation of multi-syllable words involves processes that go beyond those required for monosyllable words—for example, the assignment of syllabic stress and the systematic reduction of unstressed syllables. Children with dyslexia are possibly extremely sensitive to increasing task demands related to factors such as higher phonological complexity, lower word frequency, longer word length, or the need to process rapidly (Van der Leij, 1993). The consistencies in spelling–sound correspondences are relevant to the pronunciation of lower frequency mono- and multi-syllabic words. In English, these inconsistencies may in turn contribute to the effect of syllabic structure on naming while in Hindi, where this inconsistency does not occur, the cause seems to lie somewhere else. In the Hindi script, syllables may tend to act as perceptual units because of their orthographic and phonological properties. According to the model by Seidenberg and McClelland (1989), knowledge of orthographic–phonological correspondences is encoded by the weights of connections between processing units in a network structure. By using this type of knowledge representation, reading can be modeled by a single process that takes orthographic input into phonological codes which are then converted into pronunciation. The knowledge of spelling–sound correspondences includes a broad range of facts about grapheme–phoneme correspondences. Perception of the visual stimulus initiates parallel activation process driven by all the letters within the perceptual display. Typically, the number of letters within the perceptual span exceeds the length of a

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syllable. Given the nature of input to the system, the characteristic of the computation from orthography to phonology will be affected by more than individual syllables. When the input pattern is not familiar, the computation is relatively “incorrect” in the sense that it is affected by spelling–sound correspondences. Performance on a multi-syllable word depends on the GPC vis-à-vis other words. Children with dyslexia seem to fail to complete the process of increasing segmentation. The nature of errors committed by these children indicates that they are not able to do fine-grained segmentation, that is, phonemes, which is further evidence for their phonological deficits. The errors committed indicate that a simple grapheme–phoneme system is not being used for their translation despite the transparency of the Hindi script. Reading, in the case of Hindi-speaking dyslexics, seems to proceed via whole-word recognition systems, and where these fail, appropriate visual access may trigger the response of a visually similar stimulus. Long stimuli are subject to visual segmentation with approximate visual access used to identify the large subcomponents. According to Perfetti (1992), in normal reading development, a reciprocal relationship exists between specification of phonological representations especially at the phonemic level and of orthographic representations. As a consequence, orthographic representations are developed that are suitable for transfer to new words by mapping. However, reciprocity between the two sources of information may be less balanced in children with dyslexia than in average readers. Dyslexic children seem to show deficits at the level of phonological representations which compromise their ability to set up mappings between orthography and phonology (Hulme and Snowling, 1992). It was seen that children with dyslexia produced a greater percentage of graphemic errors than phonological errors. It seemed that they tried to apply GPC rules in the perception of the initial segments of the words, and in some cases in the final segments, but the middle letters were perhaps processed as pictures without exhibiting phonemic awareness. In the case of mixed errors, they tended to process the words superficially without attempting to proceed letter by letter from the beginning until the end. The problem may also be due to incomplete or inaccurate knowledge of letter– sound rules and poor blending skills. It was observed that in their

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laborious attempt to pronounce the words, children with dyslexia as well as the RA controls, most of the times succeeded in identifying the initial letters/syllables correctly. They continued with the effortful task of sounding out. Not being able to blend or assemble the segments happened to produce errors of different types. If they had continued to follow grapheme–phoneme conversion rules, they would have been slow readers but perhaps could have identified all the letters in the words correctly. The distribution of single versus multiple and mixed errors as a function of word length indicated that single errors predominantly occurred for short words while multiple and mixed errors mostly occurred for long words. While the CA controls seemed to have acquired mastery of letter–sound correspondences reflected in their good phonological recoding abilities, children with dyslexia and many of the RA controls seemed to present the typical profile of “plodders”, characterized as those children whose reading strategies seem to be restricted to the use of partial letter-sound knowledge. The error analysis further revealed that all the three groups produced greater vowel (maatraa) than consonant errors. This shows problems in perceiving the complex graphemic and phonological features represented by the Hindi vowels. In Hindi, complex consonant clusters with diacritical signs placed non-linearly above, below, or to the left or right of the consonants present unique visuospatial and phonological processing problems even to normal readers unless they have acquired mastery in their use. Since in Hindi vowels are essentially subsidiary being positioned non-linearly around the consonants, they present a lot of problem to the readers of Hindi. Children with dyslexia are particularly deficient in their perception of different graphemes corresponding to short and long vowels. To attain mastery in the perception of Hindi script, the learner needs to do a very fine-grained visuospatial and phonetic analysis of the bundled syllables. The nature of reading errors made by children with dyslexia shows that these children are deficient in such phonemic as well as syllabic-level analysis and synthesis. More research needs to be done to know how beginning or skilled readers of the Hindi writing system are influenced by the design of the script. The findings of the present research are supported by

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earlier findings on normal and dyslexic readers of Hindi which have highlighted specific problems in Hindi reading and spelling related to vowel length and vowel placement confusion, and in case of consonant clusters in ligatures (Gupta and Garg, 1995; Gupta et al., 1997; Gupta, 2001; Gupta and Vaid, 2002; Nehru and Garg, 1997; Vaid and Gupta, 2002b). It seems that segmentation of words in Hindi may be done at the level of individual phonemes (more so in case of consonants) and at the level of syllable units when vowel forms are placed above, below, or to the left or right of the consonants. The specific features of Hindi need to be learnt adequately by children in the process of acquiring oral and written language skills. Nehru (2001) reported that in Hindi dyslexics, error rates on Hindi non-initial vowels and bundled consonants are about 10 times those on initial vowels and ordinary consonants. In a study of reading vowels in Kannada script, Purushothama (1990) found that 74 percent of the poor readers and 26 percent of the good readers of grade 3 had a high rate of misreading vowels. This was attributed to the complex and weak representation of vowels in Kannada script. A few studies in English also have presented evidence for greater vowel than consonant errors. Examining the English pseudoword reading errors of dyslexic readers, Tal and Siegel (1996) found that nearly 50 percent of all the oral reading errors were vowel substitutions, followed by consonant substitution, deletion, and insertion errors. Sequential, reversal, and word substitution errors were committed infrequently. They suggested that disabled readers lag behind normally achieving readers in phonological decoding skills. Tal and Siegel (1996) reported that normally achieving readers as well as disabled readers committed more than twice as many vowelsubstitution errors as consonant substitution errors, despite the fact that there were more opportunities to misread consonants than vowels. The incidence of vowel errors relative to the total number of errors committed actually increased with reading experience for both disabled and non-disabled subjects. English vowels are phonologically irregular, making vowel rule learning an extremely difficult cognitive task. Even though Hindi vowels are phonologically regular, learning of these vowels requires very fine-grained perceptual analysis, which seems to be deficient in children with dyslexia.

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CONCLUSION

AND IMPLICATIONS

Overall, the present findings show that despite transparency of Hindi script, children with dyslexia were found to show both speed and accuracy deficits in reading. This is consistent with the phonological deficit explanation of dyslexia, according to which learning to read is affected by impaired acquisition of grapheme–phoneme correspondences. Children with dyslexia seem to have poor letter–sound knowledge, along with problems in pronunciation assembly and sound blending. As suggested by Goswami (1997), the fundamental difficulty for dyslexic children irrespective of language seems to lie in developing high-quality segmentally organized phonological representations of words, and that a process of gradual lexical reorganization and restructuring is necessary for this segmental organization to occur. This restructuring, particularly at the phonemic level, may be significantly helped by learning to read and the transparency of the orthography being learned could affect this process. Children learning to read highly transparent orthographies may gain better conscious access to phonological structures at the phonemic level because this level is unambiguously represented by the orthography. Further, keeping in view the complex nature of vowels being attached to the consonants in the form of diacritical signs, dyslexic children need to be specifically trained to be able to analyze such complex visual and auditory features of Hindi script to be able to read and write accurately. It is necessary to understand how children respond to the orthographic features of Hindi in their attempt to read. Such an understanding is essential in dealing with specific reading problems in the classroom instructional process. Detailed observations of reading errors by Hindi-speaking dyslexic children should prove to be useful for individualized diagnostic profiles and for designing instructional programs for remediation of specific reading problems. Particular attention needs to be paid to the vowel signs attached to the consonants. Remediation has to be based on theoretical rationale and on an understanding of the underlying significant cognitive factors, which are expected to be associated with the nature of orthographic representation of the Hindi writing system.

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It has been suggested that, in the case of children with dyslexia, poor quality of phonological representations may be compensated by better quality of orthographic representations to a certain extent. Yap and Van der Leij (1994) argued that individuals with dyslexia need to see the orthographic structure of words over and over again in order to use it, in the long run, as a way of compensating for the phonological deficit. However, Van der Leij and Van Daal (1999) point out that the concept of orthographic compensation must be interpreted with caution. Training studies indicate that even when dyslexics are taught to use word-specific knowledge and knowledge at the sub-lexical level or to apply proper decoding strategies, transfer effects of training over a period of time have been reported to be small.

REFERENCES Aaron, P.G. (1989). Dyslexia and Hyperlexia: Diagnosis and Management of Developmental Reading Disabilities. Boston/London: Kluwer Academic Publishers. Bowers, P.G. and M. Wolf. (1993). ‘Theoretical Links among Naming Speed, Precise Timing Mechanisms and Orthographic Skill in Dyslexia’, Reading and Writing: An Interdisciplinary Journal, 5(1): 69–85. Bright, W. (1996). ‘The Devanagari Script’, in P. Daniels and W. Bright (eds), The World’s Writing Systems, pp. 384–90. New York: Oxford University Press. Gaur, A. (1995). ‘Scripts and Writing Systems: A Historical Perspective’, in I. Taylor and D.R. Olson (eds), Scripts and Literacy: Reading and Learning to Read Alphabets, Syllabaries, and Characters, pp. 19–30. Dordrecht: Kluwer Academic. Goswami, U. (1997). ‘Learning to Read in Different Orthographies: Phonological Awareness, Orthographic Representations and Dyslexia’, in C. Hulme and M. Snowling (eds), Dyslexia: Biology, Cognition and Intervention, pp. 131–52. London: Whurr Publications Ltd. Gough, P.B. and M.A. Walsh. (1991). ‘Chinese, Phoenicians, and the Orthographic Cipher of English’, in S.A. Brady and D.P. Shankweiler (eds), Phonological Processes in Literacy: A Tribute to Isabelle Y. Liberman, pp. 199–210. Hillsdale, New Jersey: Erlbaum. Gupta, A. (1997). ‘Reading Test in Hindi’, Unpublished Report, Department of Psychology. University of Delhi, India. ——————. (2001). ‘Identification and Cognitive Assessment of Children with Dyslexia’, Unpublished Report. New Delhi: Indian Council of Social Scientific Research. Gupta, A. and A. Garg. (1995). ‘Reading and Spelling Skills among Dyslexic Children’, Indian Journal of Disability and Rehabilitation, 8 and 9, 7–18.

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Gupta, A. and J. Vaid. (2002). ‘Reading Strategies in Developmental Dyslexia’, Paper presented at the International Dyslexia Association Conference on Multilingual and Cross-cultural Perspectives on Dyslexia, Washington, DC. Gupta, A., J. Vaid and A. Garg. (1997). Word-nonword Reading in Hindi Language by Developmentally Dyslexic Children. Poster presented at the annual meeting of the Psychonomics Society, Philadelphia. Hulme, C. and M. Snowling. (1992). ‘Deficits in Output Phonology: An Explanation of Reading Failure?’ Cognitive Neuropsychology, 9(1), 47–72. Nehru, R. (2001). ‘Distorted Grapheme Representation: A New Hypothesis to Explain Reading Errors’, Paper presented at the Fifth British Dyslexia Association International Conference, York, UK. Nehru, R. and A. Garg. (1997). ‘A Cross-Linguistic Study of Biliterate Developmental Dyslexia’, Paper presented at the Annual Conference of the Indian Academy of Neurology, Madras, India. Nicolson, R.L. and A.J. Fawcett. (1990). ‘Automaticity: A New Framework for Dyslexia Research’, Cognition, 35(2): 159–82. Perfetti, C.A. (1985). Reading Ability. New York: Oxford University Press. ——————. (1992). ‘The Presentation Problem in Reading Acquisition’, in P. Gough, L. Ehri and R. Treiman (eds), Reading Acquisition, pp. 145–74. Hillsdale, New Jersey: Erlbaum. Purushothama, G. (1990). ‘Reading Vowels in Kannada Script’, Journal of Learning Disabilities, 23(3): 198–200. Raven, J.C., J.H. Court and J. Raven. (1992). Colored Progressive Matrices. Oxford: Oxford Psychologists Press. Seidenberg, M.S. and J. L. McClelland. (1989). ‘A Distributed Developmental Model of Word Recognition and Naming’, Psychological Review, 96(4): 523–68. Siegel, L.S. (1992). ‘An Evaluation of the Discrepancy Definition of Dyslexia’, Journal of Learning Disabilities, 25(10): 618–29. Snowling, M. (1987). Dyslexia: A Cognitive Developmental Perspective. Oxford: Basil Blaskwell. Stackhouse, J. and B. Wells. (1997). ‘How do Speech and Language Problems Affect Literacy Development?’ in C. Hulme and M. Snowling (eds), Dyslexia: Biology, Cognition and Intervention, pp. 182–212. London: Whurr Publications Ltd. Stanovich, K.E., R.F. West and A.F. Cunningham. (1991). ‘Beyond Phonological Awareness: Print Exposure and Orthographic Processing’, in S.A. Brady and D.P. Shankweiler (eds), Phonological Processes in Literacy: A Tribute to Isabelle Y. Liberman, pp. 219–36. Hillsdale, New Jersey: Lawrence Erlbaum Associates. Tal, N.F. and L.S. Siegel. (1996). ‘Pseudoword Reading Errors of Poor, Dyslexic and Normally Achieving Readers on Multisyllable Pseudowords’, Applied Psycholinguistics, 17(2): 215–32. Vaid, J. and A. Gupta. (2002a). ‘Exploring Word Recognition in Semi-Alphabetic Script: The Case of Devanagari’, Brain and Language, 81(1–3): 679–90. ——————. (2002b). How do Spatial Characteristics Affect Reading? Poster presented at annual meeting of the International Dyslexia Association conference on Multilingual and Cross-cultural Perspectives on Dyslexia, Washington, DC.

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Van der Leij, A. (1993). ‘The Development of the Autonomous Lexicon of Reading Disabled Students’, in S.F. Wright and R. Groner (eds), pp. 393–410, Facets of Dyslexia and Its Remediation. Amsterdam: Elsevier/North Holland. Van der Leij, A. and V.H.P. Van Daal. (1999). ‘Automatization Aspects of Dyslexia: Speed Limitations in Word Identification, Sensitivity to Increasing Task Demands, and Orthographic Compensation’, Journal of Learning Disabilities, 32(5): 417–28. Wimmer, H. (1996). ‘The Non-Word Reading Deficit in Developmental Dyslexia: Evidence from Children Learning to Read German’, Journal of Experimental Child Psychology, 61(1): 80–90. Yap, R. L. and A. Van der Leij. (1994). ‘Automaticity Deficits in Word Reading’, in A. Fawcett and R. Nicolson (eds), Dyslexia and Children: The Acquisition and Development of Skills, pp. 77–107. Hemel Hempstead, England: Harvester Wheatsheaf. Zoccolotti, P., M. De Luca, E. Di Pace, A. Judica, M. Orlandi and D. Spinelli. (1999). ‘Markers of Developmental Surface Dyslexia in a Language (Italian) with High Grapheme–Phoneme Correspondence’, Applied Psycholinguistics, 20(2): 191–216.

5 The Marginalized Dalits Disadvantages in Learning JANAK PANDEY

T

AND

S.K. PANT

he country, at the dawn of independence, had inherited a battered economy. It was an economy of rampant poverty, malnutrition, unemployment, and other socio-economic malaise without a sound infrastructural base necessary for promoting developmental activities. To counter the challenges posed, the nation rightly switched over to planning from the very beginning. The impact of planning during all these years has resulted in ubiquitous development in all areas. For example, the country has achieved self-sufficiency in many of the core areas like agriculture, science, medicine, technology to name a few but achievements have been disappointing in some other areas like eradication of poverty, illiteracy, unemployment, and malnutrition. The model of development adopted in the post-colonial period, perhaps rested on the belief that economic growth was sufficient for removing poverty and triggering the process of development (Papola, 1984). The realization of lack of automatic linkages between growth and poverty reduction led to the stepping up of affirmative action through massive poverty alleviation and employment generation programs. However, despite improvement in the level of income of the masses, the problem of inequitable access to social goods, education, employment, health, and so on, continued to persist (Rajeev, 1999; Mishra et al., 2003).

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The failure of planning to distribute the fruits of development evenly has also heightened the process of lop-sided development, resulting in the emergence of developed as well as undeveloped pockets. The developed pockets, instead of acting as the harbingers of growth have stifled the process of development for some others (Prabhu, 1998). The overall growth pattern has thus isolated a sizeable population like the Dalits as marginalized in India. The roots of the educational deprivation of Dalits could be historically traced back to their position as untouchables in the caste structure of traditional Hindu society. They were considered the most “polluted” of castes that were hereditarily assigned the most defiling of occupations. They could own no productive assets and were completely dependent on the higher castes, who they served. A number of norms and taboos restricted the mobility of the Dalits and prescribed certain kinds of behaviors and patterns of interactions. Access to learning was prohibited and the Dalits could not enter indigenous schools that taught elementary skills to other castes in the preBritish India (Nambissan and Sedwal, 2002). The National Policy on Education (NPE) 1986, recommends, as a goal, to integrate the handicapped with the general community at all levels as equal partners, to prepare them for normal growth and to enable them to face life with courage and confidence (Mukhopadhyaya and Mani, 2002). And to achieve this objective, the policy also underlines the importance of instructions through mother tongue and encourages incorporating locally relevant content and curriculum, besides emphasizing the localized production of textbooks in local languages. Based on these considerations, the norms for establishing primary schools were relaxed to suit the tribal areas in order to improve access to education. For instance, Andhra Pradesh adopted a policy to establish schools in habitations where there are at least 20 children of the school-going age. Similarly, Madhya Pradesh has steadily decreased population size norms in order to open schools in habitations with population of over 200 people. However, inspite of such relaxation of norms, many tribal localities are still without schools, as they do not meet even the relaxed criteria (Sujatha, 2002).1 The visible scenario in this respect is far from “what should have been” and it does not require clever tools of measurement to

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demonstrate that there are millions of children in our country who are totally deprived of any education worth the name. They are invisible, remote, and therefore unreachable. In fact, they are everywhere—in the cities, on the streets, wiping cars at traffic junctions, picking rags in mound of wastes, in the dhabas (road side eateries), in small factories as cheap labor or domestic help at home engaged in household chores. In the villages, again they are everywhere, responding to the contextual demands of family work as well as bonded labor (Jain et al., 2002). In fact, the magnitude of the problem could be gauged from the fact that in 1986–87, in the country as a whole two-fifth of the rural and one-fifth of the urban children between the age group of 6 and 14 years were not found enrolled in schools (Visaria et al., 1993). It has also to be understood that the lack of education permanently damages the individual’s future prospects and an uneducated person ends up as an unskilled adult worker whose family is unable to escape the vicious cycle of educational deprivation and other disadvantages (Majumdar and Vaidyanathan, 1994). According to the Eighth Five Year Plan (Planning Commission, 1991) a majority of the Scheduled Castes (SCs) and the Scheduled Tribes (STs), who form nearly one-fourth of the total population, were below the poverty line, and in rural India the incidence of poverty among the SC and ST population was much higher as compared to the other social groups. For example, in rural areas in 1993– 94, the percentage of SC population living below the poverty line was estimated to be 48.1 percent and that of the ST to be 52.6 percent as compared to the all India figure of 31.3 percent. In urban areas, almost 50 percent of the SCs were below the poverty line in the same year. Further, almost 70 percent of the rural Dalit households owned an acre or less of land and 61 percent were wage labor households (Thorat, 1999). Though various studies have shown that while there has been a visible decline in the percentage of population living below the poverty line, in absolute terms, the magnitude is still quite staggering (Table 5.1). Likewise, there has been no conspicuous change in the occupational pattern of SCs and STs and they still constitute the bulk of the cultivator class, agricultural landless workers, and construction workers in the unorganized sector where they invariably suffer from long periods of unemployment and under-employment (Singh, 1997).

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Poverty Ratio (%) Rural

1973–74 1977–78 1983 1987–88 1993–94 1999–2000 2007*

56.4 53.1 45.7 39.1 37.3 27.1 21.1

Urban Combined 49.0 45.2 40.8 28.2 32.4 23.6 15.1

54.9 51.3 44.5 38.9 36.0 26.1 19.3

No. of Poor (million) Rural 261.3 264.3 252.0 231.9 244.0 193.2 170.5

Urban Combined 60.0 64.6 70.9 75.2 76.3 67.1 49.6

321.3 328.9 322.9 307.1 320.3 260.3 220.1

Note: *Poverty Projection for 2007. Source: Tenth Five-Year Plan, Vol. 1, Planning Commission, New Delhi.

It is really ironical to see that despite the provision for reservation, their representation in the formal sector has been abysmally low. Their proportion, which was hardly around 2.58 percent in Class A, 4.6 percent in Class B, 9.59 percent in Class C, and around 18.37 percent in Class D categories for 1971 has further declined to 2.53 percent for Class A, 2.35 percent for Class B, 4.98 percent for Class C and 6.82 percent for Class D by 1991 (Government of India, 1993). It has also become a known fact that a large number of the SC and the ST children discontinue their studies prematurely, that is, before completing the level for which they were enrolled. The dropout rate in 1990–91, for classes 1–8 for SC children was reported to be 67.8 percent and for ST children it was even higher at 78.6 percent, which marginally declined to 66.6 percent and 74.4 percent respectively for 1997–98. What has been really disturbing is the fact that this incidence was sharper among girl students (Planning Commission, 2002). The dropout rate among the disadvantaged section clearly points out to the fact that access to educational rights still remains a distant dream. Although there has been a gradual increase in the overall literacy rates benefiting the marginalized section, the gap between them and the rest of the population is still reported to be quite high (Table 5.2). This substantiates the presumption that education has not been accorded priority among the disadvantaged groups. The above data reveals that despite the presence of a large number of programs for education, poverty alleviation, and employment

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Table 5.2 Literacy Rates of the SCs, the STs, and the Rest of the Population Year

SC

ST

Rest of the Population

1961 1971 1981 1991

10.27 14.67 21.38 37.41

08.53 11.30 16.35 29.60

27.86 33.80 41.22 52.21

Gap with Rest of the Population SC ST 17.59 19.13 19.84 14.18

19.33 22.00 22.87 22.67

Sources: (i) Census of India, Series 1, 1991. (ii) Mid-Term Appraisal of the Ninth Five-Year Plan (1997–2002), Planning Commission, New Delhi. (iii) India 1993, Annual Reference, New Delhi.

of the Dalits, not much has been achieved in terms of improving their overall status. The marginalized section of Dalits is still languishing at the bottom of the social hierarchy. What has gone wrong with these programs? Plausible explanations would include: 1. their nature namely, their implementation has been done on an ad-hoc basis (dealing with the problem only superficially); 2. and that they were lacking in those vital ingredients that are closely rooted in people’s activity and the social fabric of the community, and which are considered necessary to motivate people to shed their inhibitions and to come out and participate in the programs willingly and whole-heartedly. Thus, it could be said that the problem of social deprivation in the context of the deprived community could better be understood in the light of the “environment” in which they are located and their subsequent interaction with it and not in an isolated manner as has been done so far.

OBJECTIVES This study was planned in 2001 to access the current status of literacy among the Dalits and to identify the socio-economic factors

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that adversely affect schooling and the learning process among this disadvantaged section in the three districts of Bihar namely Bhojpur, Rohtas, and Muzaffarpur. More specifically the objectives were: 1. To study the pattern of enrolment and dropout among the children of SCs and other socio-economic groups. 2. To study the socio-economic activities associated with children of the region and their schooling. 3. To assess the opportunities, facilities, and amenities offered by the schools and to suggest an appropriate intervention strategy for the improvement of schooling.

METHODOLOGY The study covered a total of 54 villages with 18 villages from each of the three selected districts of Bihar. The identification of these villages was done using the stratified random sampling technique. For selection of 18 villages in each of the districts, a three-by-three matrix (3×3) was used for classifying the villages according to their demographic size (small, medium, and large) on the one hand, and the three social categories of castes (SC, ST and Others) on the other. The villages were accordingly distributed over these nine cells. Thus, each cell in the three-by-three matrix represented one set of socioeconomic feature consisting of size and caste. In case any of the cells did not contain any village, then the village having the next highest proportion of population, as characterized by that cell, was allocated to that cell. Further, in order to give more weightage to the SC and ST villages, the remaining villages were purposively selected from SC and ST categories, keeping in view the other features of the cell. Thus, the selection of villages was undertaken in two rounds. In the first round, all the nine cells of the matrix were used while in the second round, villages falling only in SC and ST cells were considered. For identifying the villages as SC or ST or of other category, the criteria adopted were as follows: A village was considered to be a SC village if the proportion of the SC population was 5 percent higher than its district average of the SC population. A similar criterion was used for identifying ST and other category villages.

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The Participatory Rural Appraisal (PRA) technique was used for collecting primary data for the study. This technique uses the following tools: 1. 2. 3. 4. 5.

Resource Mapping Trend Analysis Seasonal Analysis Social Mapping Educational Mapping

In addition, focus group discussions provided data for real social interactions. The advantage of PRA technique over other techniques is that the task of collecting the field data lies with local investigators who work with PRA participants and who are quite familiar with the topography, other geo-physical features of the region, the socio-economic and cultural practices, ethnic, and social issues. Three types of schedules namely the village schedule, school schedule, and the general respondent schedules were specifically designed and used to record all possible information in the field.

RESULTS

AND

DISCUSSION

In order to understand the priorities and problems of the households included and their engagement in their environment, the data collection was done by local villagers, and an appropriate analysis was carried out for the PRA data. The analysis also presents salient features of the economy, cropping patterns, infrastructural facilities, and the profile of the sample villages.

SALIENT FEATURES

OF THE

SAMPLE DISTRICTS

Demographic Profile The economy of all the three districts, namely, Bhojpur, Rohtas, and Muzaffarpur was found to be predominantly agricultural. About 27.2 percent of the sample consisted of workers. About 81 percent of the inhabitants was engaged in agricultural and allied activities.

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The proportion of SC households in the sample was 20.5 percent with the highest and the lowest being 26.0 percent and 15.2 percent in Rohtas and Bhojpur districts, respectively. The proportion of ST households in the sample was marginal (.98 percent). In the Rohtas district, however, they constituted 4.2 percent of the total households in the sample. Further, the findings also show that the proportion of SC families, constituting the labor force in the primary sector was high. Apart from the agricultural sector, the labor force was engaged in the industrial sector. However, the proportion of SC population in the industrial sector was marginal and insignificant. The highest proportion of SCs were engaged in the agricultural sector (Pandey et al., 1997). The overall literacy rate of the sample was about 39.6 percent, which was higher than the Bihar state’s average of 37.5 percent (Census of India, 1991). The inter-district comparison showed that Bhojpur district had the highest percentage (48.2 percent) of literates followed by Muzzaffarpur (36.1 percent). In Rohtas the study of distribution of schools revealed that in the rural areas, over 95 percent of the primary and about 85 percent of the upper primary schools were government-owned. Of the three sample districts, Rohtas had the highest proportion of government schools located in the rural areas (about 96 percent of the primary and 86 percent of the upper primary schools, respectively) (Sixth All India Educational Survey (Provincial, 1993).

Cropping Pattern The study of the cropping patterns of the three districts showed that paddy was the staple crop in the Kharif season and wheat in the Rabi season. The data related to cropping revealed that the cultivation of paddy and wheat was taking place in over 88 percent and 94 percent of the villages, respectively. However, in the Muzaffarpur district paddy and wheat cultivation was done in all the 18 sample villages while in the other two districts the ratios of paddy and wheat cultivation differed marginally (Table 5.3). The other major crops grown were pulses, mustard, and cash crops like sugarcane and tobacco. Fruits and vegetables were significant cash crops.

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Janak Pandey and S.K. Pant Table 5.3 Cropping Pattern in the Sample Villages

Name of the Crop Paddy Wheat Maize Mustard Pulse Sugarcane Lentil Gram Sweet Potato Fruits Potato Other vegetables Tobacco Others

Rohtas

No. of Villages Muzaffarpur

Bhojpur

Total Sample

17 (94.4) 17 (94.4) 2 (11.1) 3 (16.7) 9 (50.0) 7 (38.9) 8 (44.4) 10 (55.6) 1 (5.6) 1 (5.6) – 3 (16.7) – –

18 (100.0) 18 (100.0) 16 (100.0) 15 (83.3) 12 (66.7) 5 (27.8) – – – 16 (88.9) – 9 (50.0) 2 (11.1) 15 (83.3)

13 (72.2) 16 (88.9) 3 (16.7) 5 (27.8) 12 (66.7) 5 (27.8) 10 (55.6) 11 (61.1) – 3 (16.7) 3 (16.7) 9 (50.0) 3 (16.7) 2 (11.1)

48 (88.9) 51 (94.4) 21 (38.9) 23 (52.6) 33 (61.1) 17 (31.5) 18 (33.3) 21 (38.9) 1 (1.9) 20 (37.0) 3 (5.6) 21 (38.9) 5 (9.3) 17 (31.5)

Note: Figures in brackets denote percentages. Source: Based on data computed by the authors.

Profile of the Sample Villages The 54 sampled villages of the three districts constituted about 0.7 percent of the total villages of these districts. The number of blocks included in the study was 35, representing about 63 percent of the total. The caste groups that were overwhelmingly dominant were the SCs, STs, and the OBCs. The household distribution pattern revealed that the OBC with an overall representation of 52 percent was dominant followed by the SC whose ratio was about 21 percent. The representation of the minorities and the upper caste was about 13 percent and 12 percent respectively. The demographic profiles of these villages showed, that the proportion of children between the age group 6 and 11 years was about 24 percent, with boys out-numbering the girls by over 10 percent. The study also shows that there were on an average 19 primary schools with 70 teachers per sample district with the average teacher–student ratio of the sample being about 1:48 (Table 5.4). The study also showed that inter-district teacher–student ratio was the lowest in Bhojpur where one teacher catered to the educational

Table 5.4 Socio-Economic Profile of the Sample Villages Particulars Bhojpur Rohtas Total No. of Sample Villages 18 (0.8) 18 (0.5) Total No. of Blocks in the District 19 (100.0) 22 (100.0) No. of Blocks included in the Sample 13 (72.2) 11 (50.0) No. of SC Villages 3 (16.7) 4 (22.2) No. of ST Villages – 3 (16.7) No. of Minorities Villages 2 (11.1) – No. of OBC Villages 11 (61.1) 11 (61.1) No. of other Villages 2 (11.1) – Total No. of Households 3,286 (100.0) 2,681 (100.0) No. of SC Households 502 (15.2) 696 (26.0) No. of ST Households – 112 (4.2) No. of Minorities Households 690 (21.0) 159 (5.9) No. of OBC Households 1,617 (49.2) 1,516 (56.5) No. of Other Households 477 (14.5) 198 (7.4) Total No. of Children (6–11 years) 5,347 (100.0) 3,308 (100.0) Boys 2,983 (55.8) 1,781 (53.8) Girls 2,364 (44.2) 1,527 (46.2) Total No. of Primary Schools 20 17 Total No. of Working Teacher 60 68 Total No. of Students Enrolled 2,375 (44.4) 2,761 (83.5) Boys 1,446 (48.3) 1,667 (93.6) Girls 929 (39.3) 1,094 (71.6) Teacher–Student Ratio 1: 39.6 1: 40.6 Note: Figures in brackets denote percentage. Source: Based on data computed by the authors. Muzaffarpur 18 (1.0) 15 (100.0) 11 (61.1) 8 (44.4) 1 (5.6) 2 (11.1) 7 (38.9) – 5,955 (100.0) 1,251 (21.0) 6 (0.1) 728 (12.2) 3,166 (53.2) 804 (13.5) 8,260 (100.0) 4,582 (55.5) 3,678 (44.5) 20 83 4,927 (59.6) 2,901 (63.3) 2,026 (55.1) 1: 59.4

Total Sample 54 (0.7) 56 (100.0) 35 (62.5) 15 (42.9) 4 (11.4) 4 (11.1) 29 (82.9) 2 (5.72) 11,922 (100.0) 2,449 (20.5) 118 (1.0) 1,157 (9.7) 6,299 (52.8) 1,479 (12.4) 16,915 (100.0) 9,346 (55.3) 7,569 (44.7) 57 211 10,063 (59.5) 6,014 (59.8) 4,009 (40.2) 1: 47.7

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needs of about 40 students while in Muzaffarpur, this ratio worked out to be about 1:59 students, which was the highest (Table 5.4).

Social Infrastructural Facilities The profile of social infrastructure provided insights of their distribution and their facilitating role in the development process. The study reveals that only 24 percent of the villages in the sample had a panchayat bhawan (PB), about 10 percent had telephone connectivity, about 44 percent of the villages had electricity and only about 2 percent had an adult education center (AEC). The facility of nonformal education centers (NFCs) was available only to 28 percent of the villages. Mahila Dal (MD) and Yuvak Mangal Dal (YMD) were operational in hardly 6 percent and in about 15 percent of the villages, respectively. The other grass-roots level institutions like the cultural centers (CCs) and village education committee (VEC) were operating in about 20 percent and 54 percent of the villages, respectively. Another disheartening feature of the study was that in around 35 percent of the villages, the sub-centers (SC) were functional and about 9 percent villages enjoyed the facility of veterinary centers (VC). The cooperative society (CS) was found to be operative in only 11 percent of the villages (Table 5.5). Table 5.5 Distribution of Social Infrastructure in the Sample Villages (in percentage) Amenities or Resources Panchayat Bhawan Telephone Electricity Adult Education Center Non-Formal Education Center Mahila Dal Yuvak Mangal Dal Cultural Center Village Education Committee Mahila Samakhya Jagajugi Center

Bhojpur 22.2 22.2 38.9 – 33.3 – 16.7 11.1 38.9 – –

Source: Based on data computed by the authors.

Rohtas Muzaffarpur 27.8 – 44.4 – 33.3 – 5.6 11.1 50.0 16.7 11.1

22.2 22.2 50.0 5.6 16.7 16.7 22.2 38.9 72.2 16.7 11.1

Total Sample 24.0 14.8 44.4 1.9 27.8 5.6 14.8 20.4 53.7 11.1 7.4

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Distribution Pattern of the School-going Children The survey also revealed that about 60 percent of the total children in the age group of 6 to 11 years of the villages were school-going, thereby implying that about 40 percent of the children were not attending the schools. The study also showed that in terms of enrollment the boys clearly exceeded the girls.

Outward Enrollment Trend According to the statistics provided by the schools, the school register showed the enrollment number of students. The total number of enrollment was 10,063 (Table 5. 4). However, the validation exercise, conducted by our investigators during household survey, revealed that the number of school-going children in the sampled villages was 11,692 (Table 5.6), which exceeded the figure of school enrollment by over 16 percent. This could only have been possible when there had been an outward movement of students from these sample villages. The analysis also showed that this outward Table 5.6 Gender and Caste-wise Distribution of School-going Children (6–11 years) Caste

Rohtas

Muzaffarpur

Bhojpur

Total Sample

Boys

Girls

Boys

Girls

Boys

Girls

Boys

Girls

300 (62.1) ST 39 (58.2) Minorities 90 (81.8) OBC 771 (78.7) Upper Caste 122 (86.5) Total 1,322 (74.2)

170 (42.7) 22 (37.3) 71 (67.0) 477 (58.5) 118 (79.1) 858 (56.2)

681 (67.8) –

426 (53.9) –

315 (76.3) –

135 (50.2) –

483 (81.3) 1,754 (72.7) 513 (91.9) 3,431 (74.9)

353 (72.8) 1,085 (56.4) 405 (86.4) 2,269 (61.7)

387 (62.0) 1261 (81.1) 353 (90.3) 2,316 (77.6)

288 (53.9) 764 (60.6) 309 (89.3) 1,496 (63.3)

1,296 (68.2) 39 (47.6) 960 (72.3) 3,786 (76.5) 988 (90.6) 7,069 (75.6)

731 (50.2) 22 (37.3) 712 (65.9) 2,326 (58.2) 832 (86.3) 4,623 (61.2)

SC

Note: Figures in brackets denote percentage. Source: Based on data computed by the authors.

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movement, on an average, was about 18 percent and 15 percent for boys and girls, respectively. The outward enrollment movement of students was more conspicuous in the two districts of Muzaffarpur and Bhojpur where the overall rate worked out to be about 16 percent and 61 percent, respectively whereas in the Rohtas district, there was an inward enrollment movement of students and their rate was estimated to be 21 percent, thereby implying that about 21 percent of the students from outside the sample villages were getting enrolled in the schools located in the sample villages. Some of the factors contributing to this phenomenon have been summarized as follows: 1. Social factors such as fear of the influential upper castes and communities, which forced the socially disadvantaged households to send their children to schools that were located outside their villages. 2. Poor quality of instruction provided by primary schools in some of the sample villages discouraged the parents from sending their children to these schools. 3. It was also found that, generally, the households belonging to the SC and other socially disadvantaged classes were located in the periphery of the sample villages while the schools were located in the heart of the villages. The general fear of upper caste community supplemented with the advantageous geographical location of other schools also figured as an important factor that contributed in lowering the enrollment level of students in the sample schools. 4. At times, it was also observed that a large proportion of villages in the hilly regions had very low population and also had no schooling provision. This also compelled the parents to send their children to schools located in other villages (Table 5.6).

Dropout Pattern The importance that villagers give to education and educating their children can be estimated by studying the pattern of the dropout rate of children as well as by examining the proportion of children

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who do not go to schools. The findings show that the overall dropout rate of students in the sample schools was about 5.8 percent. The proportion of boys dropping out was reported to be 5.4 percent while in the case of girls this was estimated to be 6.2 percent. The results show that about 6.0 percent of the dropout cases was reported from Muzaffarpur district while this rate was about 7.0 percent in Bhojpur. The dropout rate was the lowest in the Rohtas district where about 4.0 percent of the students had dropped out of schools. The inter-caste comparison showed that the incidence of dropout was highest among the SCs followed by the STs. Together, these two categories accounted for about 9.0 percent of students who had dropped out of school. The dropout rate was observed to be least among the children of the upper caste where, hardly 4 percent of the students had dropped out (Table 5. 7). The findings revealed that about 20 percent of the boys and about 34.9 percent of the girls in the total sample had never attended school (Table 5.8). Thus, a little more than about 25 percent of the total number of children in the age group of 6 to 11 years did not attend school. This also indicates attitudes related to the education of girls and the way they have been perceived by the sample households. Table 5.7 Gender and Caste-wise Distribution of Dropout Children (6–11 years) Caste

Rohtas

Muzaffarpur

Bhojpur

Total Sample

Boys

Girls

Boys

Girls

Boys

Girls

Boys

Girls

30 (10.2) ST 5 (12.8) Minorities 4 (4.4) OBC 33 (4.2) Upper Caste 1 ( 0.8) Total 73 (5.5)

25 (14.7) 4 (18.2) 2 (2.8) 33 (6.9) 6 (5.1) 70 8.2)

103 (15.1) –

79 (18.5) –

40 (12.7) –

34 (25.2) –

18 (3.7) 124 (7.1) 11 (2.1) 256 (7.5)

6 (1.7) 120 (11.1) 18 (4.4) 223 (9.8)

57 (14.7) 62 (4.9) 21 (5.9) 180 (7.8)

38 (13.2) 83 10.9) 21 (6.8) 176 11.8)

173 (13.3) 5 (12.8) 79 (8.2) 219 (5.8) 33 (3.3) 509 (7.2)

138 (18.9) 4 (18.2) 46 (6.5) 236 (10.1) 45 (5.4) 469 (10.1)

SC

Note: Figures in brackets denote percentag. Source: Based on data computed by the authors.

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Janak Pandey and S.K. Pant Table 5.8 Gender and Caste-wise Distribution of Children from 6 to 11 Years Who have Never Attended School

Caste

Rohtas Boys

SC

153 (33.8) ST 23 (37.1) Minorities 16 (15.1) OBC 176 (18.6) Upper Caste 18 (12.9) Total 386 (22.6)

Girls

Muzaffarpur Boys

Bhojpur

Girls

203 220 285 54.4) (24.4) (40.1) 33 15 9 (60.0) (100.0) (100.0) 33 93 126 (31.7) (16.1) (26.3) 305 533 720 (39.0) (23.3) (39.9) 25 34 46 (17.5) (6.2) 10.2) 599 895 1,186 (41.1) (20.7) (34.3)

Total Sample

Boys

Girls

Boys

Girls

58 (45.5) –

100 (42.6) –

180 (31.7) 232 (15.5) 17 (4.6) 487 (17.4)

163 (36.7) 413 (35.1) 16 (4.9) 692 (31.6)

431 (25.0) 38 (49.4) 289 (23.1) 941 (19.9) 69 (6.5) 1,768 (20.0)

588 (44.6) 42 (65.5) 322 (31.1) 1,438 (38.2) 87 (9.5) 2,477 (34.9)

Note: Figures in brackets denote percentage. Source: Based on data computed by the authors.

The analysis also showed that the incidence of children, not attending schools was highest in Rohtas (about 30 percent) district while it was about 25 percent in Muzaffarpur district. The study also shows that about 22 percent of the students in Bhojpur did not attend any school. The inter-caste comparison showed that the highest proportion of children not attending schools came from the SC and the ST communities. Together, over 31 percent of the children belonging to these communities did not attend any school. The gender-wise analysis shows that over 25 percent of the boys and about 44.6 percent of the girls in the SC category did not go to any type of school. The problem of the children not attending school among the upper caste was found to be the lowest (about 4 percent only). Thus, it can be concluded that the number of children not attending schools among the marginalized sections was high and clearly reveals the severity of the problem (Table 5.8). The findings clearly reveal that for the disadvantaged sections, education (schooling) of their children was still a serious issue and the educational backwardness among the children of the SCs and STs was significant. Their dropout rate was higher than children of

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OBC and the upper castes. This may be partly due to socio-economic compulsions and partly due to their lack of awareness and appreciation of the importance of education. An attempt was made to analyze other factors responsible for the educational disabilities of this group.

SEASONAL WORKING PATTERN The three sample districts were agricultural in nature and the agricultural sector employed the highest proportion of laborers from the SC class. The cropping pattern revealed that the extent and nature of farming pertaining to paddy and to some extent wheat required a higher level of labor input in agricultural operations such as sowing, planting, cultivating, and harvesting. Additional demand of labor was supplemented by involving the entire household including children. The children formed a significant and important proportion of the seasonal labor force in the region. An attempt was made to study the working pattern of seasonal laborers, the contribution of children in the farm operations, and their migration pattern. The working pattern of the households engaged in agriculture showed that, on an average, they were working for about 53 percent of days in a month, with minor variations in the three sample districts. March, April, August, November, and December were busy months attracting more laborers (Table 5.9). On an average, the children provided assistance in over 52 percent of the sample villages, the highest being in Bhojpur and the lowest in Rohtas. Further, the analysis also showed that the involvement level steadily increased to over 67 percent and 77.8 percent in the villages during the months of November and April before dropping to about 50 percent in January. Likewise, the results revealed that the involvement level of children further peaked to over 80 percent in April and over to 66 percent in August, respectively (Table 5.10). Another important aspect affecting the educational disabilities of the disadvantaged section of children were the movement of (migration) households during the peak harvesting period. The study of migration revealed that there were about 4 percent of the households in the sample that was permanently on the move. The highest movement of the households was observed in Muzaffarpur district

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Janak Pandey and S.K. Pant Table 5.9 Seasonal Working Pattern in Sample Villages

Month January February March April May June July August September October November December Total

Rohtas

Working Days Muzaffarpur

Bhojpur

Total Sample

14 (45.2) 08 (28.6) 12 (38.7) 19 (63.3) 13 (41.9) 08 (26.7) 17 (54.8) 20 (64.5) 16 (53.3) 14 (45.2) 16 (53.3) 23 (74.2) 180 (49.3)

16 (51.6) 17 (60.7) 20 (64.5) 26 (83.9) 22 (70.9) 16 (53.3) 19 (61.3) 16 (57.6) 4 (13.3) 10 (32.3) 23 (76.7) 25 (80.6) 214 (58.6)

16 (51.6) 12 (42.9) 19 (67.9) 25 (83.3) 14 (35.5) 06 (20.0) 13 (41.9) 18 (58.1) 12 (40.0) 13 (41.9) 22 (73.3) 24 (74.4) 191 (52.3)

46 (49.5) 37 (44.0) 51 (54.8) 70 (77.8) 46 (49.5) 30 (33.3) 49 (52.7) 54 (58.1) 32 (35.6) 37 (39.8) 61 (67.8) 72 (77.0) 585 (53.4)

Note: Figures in brackets denote percentage. Source: Based on data computed by the authors. Table 5.10 Children’s Assistance Pattern Month January February March April May June July August September October November December Total

Rohtas

Villages Muzaffarpur

Bhojpur

Total Sample

10 (55.6) 04 (22.2) 09 (50.0) 16 (88.9) 05 (27.8) 01 (55.6) 13 (72.2) 15 (83.3) 05 (27.8) 05 (27.8) 11 (61.1) 17 (94.4) 111 (51.4)

10 (55.6) 10 (55.6) 09 (50.0) 12 (66.7) 11 (61.1) 13 (72.2) 13 (72.2) 10 (55.6) 02 (11.1) 03 (16.7) 10 (55.6) 09 (50.0) 112 (51.9)

12 (66.7) 07 (38.9) 09 (50.0) 15 (83.3) 07 (38.9) 02 (11.1) 09 (50.0) 11 (61.1) 06 (33.3) 06 (33.3) 13 (72.2) 16 (89.9) 113 (52.3)

32 (59.3) 21 (38.9) 27 (50.0) 43 (79.6) 23 (42.6) 16 (29.6) 35 (63.8) 36 (66.2) 13 (24.1) 14 (25.9) 34 (63.0) 42 (77.8) 336 (51.9)

Note: Figures in brackets denote percentage. Source: Based on data computed by the authors.

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(about 5 percent) and lowest in Bhojpur district (under 1 percent). It also showed that the rate of migration climbed to about 5 percent and over 6 percent in the months of November and December, respectively. The migration level of the households was reported to be about 5 percent, 4 percent and 6 percent in January, August, and September, respectively (Table 5.11). Apart from providing assistance in farm operations, these children were also required to perform many other supplementary functions, which kept them busy all through the day. Some of the work they did were cattle grazing, looking after the cattle, collecting fuel (wood) for domestic use, non-agricultural wage work, looking after the younger siblings in the family, and providing help in household work. It appears that education and going to school received the lowest priority.

Quality of Services Another factor that seemed to influence the enrollment level of the children in school was the quality of schools and facilities or Table 5.11 Pattern of Migrant Households in Sample Villages Month Rohtas January February March April May June July August September October November December Total

90 (3.4) 40 (1.5) – 135 (5.4) 75 (2.8) 50 (4.3) 115 (4.3) 190 (7.1) 145 (5.4) 45 (5.4) 175 (6.5) 232 (8.7) 1,292 (4.0)

Households Muzaffarpur

Bhojpur

Total Sample

433 (7.3) 400 (6.7) 240 (4.0) 140 (2.4) 105 (1.8) 195 (3.3) 140 (2.4) 275 (4.6) 527 (8.8) 567 (9.5) 375 (6.3) 406 (6.8) 3,803 (5.3)

10 (0.3) – 20 (0.6) 35 (1.1) – – 10 (0.3) – – – 35 (1.1) 96 (2.9) 206 (0.5)

533 (4.5) 440 (8.7) 260 (2.2) 340 (2.6) 180 (1.5) 245 (2.4) 265 (2.2) 465 (3.9) 672 (5.6) 612 (5.1) 585 (4.9) 734 (6.2) 5,301 (3.7)

Note: Figures in brackets denote percentage. Source: Based on data computed by the authors.

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services offered to students. The services included both the physical infrastructure of schools and the quality of teaching. The findings revealed that majority of the schools did not even offer the most rudimentary services and facilities. Only about 44 percent of them had drinking water facility, another 26 percent had toilets, and about 46 percent had playground facilities. The study showed that 28 percent provided teaching aid facilities, 78 percent had black boards and only around 11 percent of them provided games kits to their students. The inter-district comparison shows that the level of facilities offered varied and the Rohtas district figured at the top in terms of offering services figured while the Bhojpur district was at the bottom. It is an already established fact that the quality of teaching depends, to a large extent, upon the teacher’s qualification and facilities available in the school. The analysis showed that about 7 percent of the total teachers in class 1 was being provided the teachers guide book. These percentages correspondingly declined to about 4 percent for subjects like Literature and about 2 percent for Mathematics as one moved from class 1 to class 5. It was found that teachers of the higher classes were least equipped and prepared in terms of facilities, which in due course was likely to affect their quality of teaching.

RESIDENTIAL SETTING

OF

TEACHERS

The location of residences of the teachers has a significant bearing on the quality of teaching. The basic premise is that if the teacher resides at a far off distance from the school, then it leads to high incidence of absenteeism, dilution in the quality of teaching on account of fatigue, and exhaustion caused by commuting long distance. The findings revealed that about 91 percent of the teachers were commuting daily around 5 kilometer and about 9 percent resided near the school premises. The inter-district study revealed that this problem was being felt more acutely in Muzaffarpur district while the position at Rohtas and Bhojpur were marginally better.

MONITORING

AND

SUPERVISION PATTERN

The monitoring and supervision of the schools form a very crucial, important, and integral part of the mechanisms through which the

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The Marginalized Dalits

school authorities get adequate feedback that helps them to prepare appropriate intervention strategies. The field studies adequately demonstrated that the performance of school was closely linked to its monitoring and supervision activities. The efficient supervision and monitoring of schools has a positive influence on overall school performance. An analysis of monitoring and support services showed several lacunae. The district level officials who were supposed to provide supervision and monitoring services were the Basic Education and Extension Officer (BEEO), Area Education Officer (AEO), Adult Education Officer (AEO), District Education Officer (DEO), District Superintendent of Education (DSE), District Magistrate (DM), and so on. Their frequency of visits to the schools in their area in the last three years was studied. It was disappointing to note that the frequency of visits which in the initial years itself was low, further declined with the passage of time, and this drop was conspicuous at all levels of the supervisory cadres. Thus, it could be said that the poor level of monitoring and supervision services coupled with fewer visits adversely affected the quality of teaching and maintenance of school services which in turn demotivated both students and teachers both.

DISCUSSION The study provides an interesting account of the working of primary schools in three districts of Bihar and also attempts to highlight the forces that are operating within and outside the system affecting the access, achievement, and quality of elementary education. Some of these factors could broadly be identified, on the basis of their nature and coverage as, physical, social, managerial, teacher’s training, and community support.

Physical Factors The study has clearly brought to the fore that the performance of schools has suffered on account of a highly skewed distribution of

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schools combined with the closure of substantial number of schools in geographically inaccessible regions. Further, the geographic location of schools generally favored the high caste households. The fear of a violent backlash from the upper castes frequently troubled the Dalits and discouraged them from sending their children, particularly girls to school. All these factors acted as barriers in the universalization of education. At times, schools were not assigned to certain villages as the population of the village was low and it was not in accordance with the norms devised for the setting up of schools. Hence, a recommendation could be made to introduce schooling facilities in those regions where the proportion of girls was high. It is also evident that school education can get a boost if the norms for establishing schools are relaxed to meet the contingencies of the local situation. Besides this, an attempt should also be made to provide basic infrastructural facilities such as drinking water, toilets, games, teaching aids, and teachers’ guide book. It was also observed that a substantial number of schools had poor road connectivity. Access to schools was often difficult during the monsoon season and thus also led to lowered attendance during these months. It is suggested that through the convergence of rural development programs with school development, some of these problems could be effectively addressed. The study showed that many of the schools in the sample districts did not have additional rooms and multi-grade teaching was taking place in most of the schools, affecting the quality of teaching. Hence, it is recommended that additional classrooms be provided in those schools where a large number of students are enrolled. It was observed that many of the schools in the villages do not have a boundary wall as a result of which the distinction between the community land and the school premises was often blurred. The school boundary also provides a sense of belongingness and identity to the school and also to the students, which in turn facilitate the learning–teaching process. In a neat and clean school campus, a boundary should be encouraged to foster a sense of identity, security, and privacy. This would lead to a sense of pride in the school, which would be beneficial to the school community as a whole.

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Social Factors Effective and successful functioning of any institution requires active support of the community and other local resources. As the findings revealed, the performance of the schools suffered due to lack of community support. The program of elementary education needs to be taken up along with other development programs in the district so as to bring qualitative as well as quantitative improvement in the system. It is therefore suggested that both the programs of formal and non-formal education should work in tandem. This could only be achieved if the level of education imparted in both streams is of equal level so that the students could have the option of switching from one stream to another, if the cirumstances do not permit them to continue in the formal stream. Thus, by mobilizing grassroots institutions like the MYD, VEC, the CC, and so on to act as watchdogs and monitor school activities, the quality, in both the formal schools as well as in the NFC, where literacy programs are organized by the government, could be maintained. It was also found that the VEC has remained passive and dormant largely because the members do not evince interest in the development program. Hence, there is a need to reconstitute the VEC and only those people should be made members who are deeply involved and committed to the village and school development. Similarly, it was also found that the non-availability of female teachers in adequate numbers also decreased the prospects of female education. It was found that in the absence of female teachers, the parents were not particularly keen to send their daughters to such schools. Thus, efforts should be made to appoint more female teachers and also organize social awareness programs that inform and sensitize people towards the benefits of education and motivate them to send their children to schools. The findings also imply that agricultural operations also had a significant bearing on the enrollment, continuation in school, and achievement levels of children. In the peak harvesting season, which generally coincided with the academic session of the school, children were frequently withdrawn from school and were required to assist their parents in farm operations. Therefore, efforts should be made to initiate measures to compensate the loss by introducing

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bridge courses for these students. The modalities of such courses could be worked out between parents and school authorities. Likewise, by changing the academic calendar, to ensure that peak academic activities do not fall at harvesting times, the educational needs of children working in the fields could be addressed to some extent. The migration factor needs special mention. The study shows that there were some families, where the entire household migrated every season for a few months. The migrant families generally belonged to the lower caste and also had low literacy levels as a result of which they failed to appreciate the importance of education. Their problem could also be tackled along with the problem of working children by adopting innovative incentive and motivational strategies.

Community Participation It was found that the schools were operating in isolation. It was also found that there has been no communication or interaction between the local population and the school authorities. In the absence of any community involvement, the working of these schools was affected. The teachers and the authorities were not getting the feedback on a regular basis and were thus unable them to modify their educational approach to meet the specific needs and requirements of the community. The study also showed that a significant number of teachers were commuting to school on a daily basis. Not only was this time consuming but was also a drain on their physical and mental resources. This led to poor quality teaching. It is equally true that schools have limited resources and cannot tackle the teachers’ problem alone. Thus, the community needs to be involved. The problem of teachers’ residence could be effectively solved if school authorities and the community work in close association with each other. Similarly, by involving many of the local level institutions like the panchayats, local bodies, and local committees, the functioning of the schools could further be streamlined. The study has shown that these bodies have remained by and large inactive. It is strongly felt that universalization of education cannot take place unless

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139

community participation and involvement is secured. For invoking their participation, the community needs to be sensitized regarding these issues. Community mobilization can be effected through street plays, rallies and cultural programs. Co-operation and assistance of other professional bodies with requisite experience could also be sought.

Dropout Problem The study also brought to the fore the serious problem of student dropout. The incidence of dropout was quite high among the Dalits. Efforts need to be made to motivate and encourage parents to value education and to view education as a means of achieving a better quality of life. Building an environment conducive to education and deployment of some of the other strategies mentioned earlier could be effective ways of countering school dropout. To encourage enrollment and attendance of children in school, it is recommended that the schools showing high performance in terms of enrollment, attendance, and examination performance should be publicly felicitated. Likewise, making provision for scholarship to meritorious students irrespective of caste could also act as a motivating factor and spur other students as well as their parents to send them to school. The analysis of findings also shows that there is a need to make the school curriculum meaningful and compatible with the agricultural operations of the region. This would reduce the incidence of absenteeism of children to a marked extent and help in improving their school performance.

Teachers’ Problem The teachers are a primary as well as a cardinal source that play a very crucial role in the school system. The study has also shown that the teachers also faced many problems which contributed to their poor performance. A perusal of their problems shows that many of them were inter-related and could be ameliorated through changes in educational policies.

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The study showed that a majority of the teachers lacked appropriate teaching aids, prescribed guide books, and were untrained. Thus they were not instructed in using the different pedagogies to make the learning process both stimulating and enjoyable. Therefore, it is recommended that they may be provided with the relevant teaching aids to enable them to perform better. In the absence of a regular feedback, the performance of the schools suffered and provided wrong signals to the sincere and dedicated teachers who felt dejected and demotivated. If the process is allowed to continue, it may adversely affect their performance also. Therefore by introducing the process of a feedback mechanism and evaluation of training, the confidence of teachers could be restored. The feedback would help the school authorities to focus on their weaker points and thereby reduce their deleterious impact on the entire school system. Efforts need to be made to encourage teachers to reside near the school premises. Non-academic tasks should not be given to teachers so that they may devote more time to their academic work. Likewise, provision of a lady teacher should be made in those schools where the enrollment of girls exceeds a stipulated level. The supervision and monitoring aspects need to be improved. Over dependence on the government agencies for management of primary schools in the districts is a major problem. It is imperative to encourage private agencies or even non-government organizations with relevant experience to become involved and collaborate with the community in primary education. This would generate a healthy competition between the two classes of schools and will thus contribute positively to the system as a whole. The above-mentioned issues assume salience as a number of studies have shown that academic and scholastic achievements are negatively affected by social disadvantage (Panda, 1988). The studies by Misra (1983) have shown that the scholastic achievement of disadvantaged children is lower than that of advantaged children. Tripathi (1988) in his review has cited studies that showed that deprivation had a deleterious effect on cognitive functioning, motivational patterns, aspiration levels, and academic achievement. As far as achievement is concerned, studies have shown that children from socially disadvantaged backgrounds are victims of unfavorable teacher expectations. Sharma (1985) found that social class and caste

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significantly influenced teacher expectations about student success. In a similar vein, Pande (1980) found that lack of peer and student support was responsible for the irregular attendance of SC students at school. As pointed out by Karanth (2003), socio-economic factors have been linked to the prevalence of learning disabilities. Against this backdrop, the present chapter can be viewed as an attempt to understand through the lens of the educational practices prevalent in three rural districts of Bihar, how these contextual factors can lead to poor quality schooling, negative school experiences, and learning difficulties and problems.

NOTE 1.

Under the Sarva Shiksha Abhiyan (SSA), which is a very comprehensive and integrated flagship program of the Government of India, to attain universalization of elementary education for all children in the 6–14 age group by 2010, an array of provisions have been made to address the critical issues affecting the access, retention, girl child education, quality of education, children with special needs, teachers’ training, and so on. According to the guidelines, the norms for opening of new schools have been as follows: Primary School: Within one-kilometer radius of every habitation having population of 300. For upper primary schools the distance and population norm was of 2 kilometers and 800 respectively. Further, Education Guarantee Schools (EGS) centers at the primary level would be opened in un-served habitations where no school existed with a radius of 1 kilometer and at least 15 children in the age group of 6–14 who are not going to schools, are available. However, in exceptional cases, in remote areas. The EGS schools could support 10 children also.

REFERENCES Census of India. (1991). Series 1, India, Paper 2 of 1991. Delhi: Controller of Publications. Government of India. (1993). A Reference Annual. New Delhi: Ministry of Information and Broadcasting. Jain, S., A. Mathur, S. Rajgopal and J. Shah. (2002). ‘Children, Work and Education: Rethinking on Out of School Children’, in R. Govinda (ed.), India Education Report, pp. 47–58. New Delhi: Oxford University Press.

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Karanth, P. (2003). ‘Introduction’, in P. Karanth and J. Rozario (eds), Learning Disabilities: Willing the Mind to Learn, pp. 17–29. New Delhi: Sage Publications. Majumdar, M. and A. Vaidyanathan. (1994). ‘Access to Education in India: Retrospective and Prospective’, Journal of Education Planning and Administration, 7(4). Mishra, R., R. Chatterjee and S. Rai. (2003). India Health Report. New Delhi: Oxford University Press. Misra, G. (1983). ‘Deprivation and Development: A Review of Indian Studies’, Indian Educational Review, 1: 12–22. Mukhopadhyaya, S. and M.N.G. Mani. (2002). ‘Education of Children with Special Needs in India’, in R. Govinda (ed.), Education Report. New Delhi: Oxford University Press. Nambissan, G.B. and M. Sedwal. (2002). ‘Education for All’, R. Govinda (ed.), The Situation of Dalit Children in India, in India Education. New Delhi: Oxford University Press. Panda, K.C. (1988). ‘Social Psychology of Education’, in J. Pandey (ed.), Psychology in India: The State-of-the-art, Vol. 2, Basic and Applied Psychology, pp. 279–337. New Delhi: Sage Publications. Pande, N. (1980). ‘Irregular Attendance at School: Climate Support for SC Students’, Social Change, 10(March–June): 19–22. Pandey, J., S.K. Pant, and K.N. Bhatt. (1997). ‘Social Assessment Study of District Primary Education Programme (DPEP) in Bhojpur, Rohtas and Muzaffarpur districts of Bihar’. Project Report. Allahabad: G.B. Pant Social Science Institute. Papola, T.S. (1984). ‘Foreword’, in J.L. Bajpai and C. Shastri (eds), Rural Poverty: Issues and Option. Lucknow: Print House. Planning Commission. 1991. Eighth Five Year Plan, 1992–93, Vol. 2, New Delhi: Planning Commission. ——————. (2002). Mid-term Appraisal of the Ninth Five-Year Plan (1997–2002). New Delhi: Government of India. Prabhu, S. (1998). ‘Social Sector in Economic Development’, Journal of Social and Economic Development, 1(2), July–December, pp. 268–87. Rajeev, P.V. (1999). Planning to Social Reforms: The Key to Economic Progress. New Delhi: Deep and Deep Publications. Sharma, R. (1985). ‘Attribution of Success and Failure in School’, Unpublished Doctoral Dissertation. Allahabad: University of Allahabad. Singh, A.K. (1997). ‘Social Structure and Development Process: A Study of Scheduled Castes in Uttar Pradesh (1971–91)’, Man and Development, 19(4): 41–53. Sujatha, K. (2002). ‘Education among the Scheduled Tribes’, in R. Govinda (ed.), India Education Report, 87–94 . New Delhi: Oxford University Press. Thorat, Sukhdeo. (1999). ‘Social Security in Unorganised Sector in India: How Secure are the Scheduled Castes’, Indian Journal of Labour Economics, 42(3): 451–70. Tripathi, R.C. (1988). ‘Applied Social Psychology’, in J. Pandey (ed.), Psychology in India: The State-of-the-art, Vol. 2, Basic and Applied Psychology, pp. 95–157. New Delhi: Sage Publications. Visaria, P., A. Gumbar and L. Visari. (1993). ‘Literacy and Primary Education in India, 1980–81 to 1991: Differentials and Determinants’, Journal of Educational Planning and Administration, 3(1): 13–62.

6 Learning Disability Challenges in Diagnosis and Assessment PREETI VERMA

P

arents nurse hopes and aspirations for their newly born child. Knowing that the child may have a learning disability (LD) wrenches their heart. They fear that their child will not be able to optimize his or her full potential and remain an unfulfilled individual, which creates a sense of loss in parents. The locus of blame focuses on internal as well as external causations. The reaction perhaps marks the beginning of an attitudinal change from grieving for something that is deemed as a loss, to trying to find the best ways to help the child do better and succeed. Before the term “learning disabilities” (LDs) was introduced in 1963, the individuals studied by neurologists and psychologists appeared to have had problems more severe and pervasive than those of many children identified, as having LDs today, but the question what is LD remains unanswered.

LEARNING DISABILITY—THE CONCEPT

AND ISSUES

One of the recent yet most controversial exceptionalities is termed LDs. The major concern is how severe and pervasive learning problems must be to qualify for the label LD. Critics of the field maintain that LDs are too loosely defined. The term emerged out of the need

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to identify and serve students who show a gap between what he or she should be able to achieve or do and what they actually achieve or do—despite no sensory deficit or mental retardation. PL 94–142 defines specific learning disability as, . . . a disorder in one or more basic psychological processes involved in understanding or using language, spoken, or written, which may manifest itself in an imperfect ability to listen, think, speak, read, write, spell, or to do mathematical calculation. The term [learning disability] includes . . . developmental aphasia. The term does not include children who have learning problems, which are primarily the result of visual, hearing, or motor handicaps, of mental retardation, of emotional disturbance, or of environmental, cultural or economic disadvantage (Federal Register, 1977, p. 65083).

The definition has four component parts: 1. “a disorder . . . spoken or written,”—this component leaves the psychological process operationally undefined making room for different interpretations; 2. (a disorder) “which may manifest itself . . . do mathematical calculation”. These skills form the core of academic performance (good or bad), and from them the learning disability may be inferred; 3. the term includes developmental aphasia; 4. the term (disability) does not include children’s cultural or economic disadvantage. Learning disabilities are often diagnosed through the process of elimination. The key word in this component is primarily—a student with LD may have secondary problems related to other handicapping conditions. The difference between primary and secondary handicapping conditions is not always clear. Another definition formulated by the National Joint Committee on Learning Disabilities (NJCLD) 1982 reads as: ‘Learning disabilities’ is a generic term that refers to a heterogeneous group of disorders manifested by significant difficulties in the acquisition and use of listening, speaking, reading, writing, reasoning, or mathematical abilities. These disorders are intrinsic to the individual and

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presumed to be due to central nervous system dysfunction. Even though learning disability may occur concomitantly with other handicapping conditions (e.g., sensory impairment, mental retardation, social and emotional disturbance) or environmental influence (e.g., cultural differences or inappropriate instruction, psycholinguistic factors), it is not the direct result of those conditions or influences (p. 107).

The NJCLD definition deletes the phrase “basic psychological process”(of the Federal definition) and replaces it with a statement that the problem is “intrinsic” to the person (that is, the “disorder” is due to factors within the student, not due to external factors) and may be due to the central nervous system dysfunction. Ysseldyke et al. (1979) considered under-achievers and students labeled as learning disabled as “identical twins with different mothers”. Zigmond (1983) suggests a definition of LD based on an “easyto-teach” to “very-hard-to-teach continuum. Researchers, Algozzine and Ysseldyke (1983); Ysseldyke et al. (1982) on the strength of their data, indicate that nearly any low-achieving student could be classified as learning disabled. Kavale et al. (1994) analyzed the same data and concluded that this is a serious mis-statement. The percentage of the population with LDs is actually quite small. Everyone recognizes that some students who are said to have LDs have problems that are not very different from those of average students and that other students have problems so severe and pervasive that they are “off the scale”. The history of the field has set the stage for further controversies about how test score discrepancies are used to indicate LDs—are students having a relatively flat profile of scores on the IQ subtests or a nearly uniform pattern of achievement in various academic and social skills less likely or unlikely to be considered as having LDs? Is a highly uneven developmental profile or a large discrepancy in the areas of performance usually a criterion for designating a LD, and what degree of severity and pervasiveness of LDs requires teaching by special educators? Children with LDs have difficulty in the way they take in, remember, make sense of, or communicate information. Learning disability is a disorder that affects people’s ability to either interpret what they see and hear or link information from different parts of the brain. These limitations can show up in many ways—as specific difficulties with spoken and written language, co-ordination,

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self-control, or attention. Such difficulties, when they extend to schoolwork, can impede learning to read, write, or do math. Other traits that may be present in a child with LD include unpredictable or uneven test performance, perceptual impairments, motor problems, and behaviors such as impulsiveness, poor attention span, and difficulty in social situations. Learning disability is a broad term that covers a pool of possible cause, symptoms, treatment, and outcomes. The definition of LD is constantly undergoing churning as a consequence of debate sans any consensus. No authentic database is available to estimate the incidence of LD in the Indian context. Due to lack of explicit cause and effect relationship that make under-achievement an essential precondition for LD, and other ambiguities associated with the term, it is difficult to diagnose or to pinpoint the causes, conduct needspecific formal or informal assessment, and plan remedial education or therapy.

COMMON CHARACTERISTIC “AT RISK”

OF

CHILDREN

Some of the common characteristics associated with LDs as cited in literature are—poor co-ordination and depth perception; distractibility; short attention span; impulsivity; hyperactivity; delayed speech; limited vocabulary; inappropriate use of words; difficulty remembering what is heard; aversion to being touched and cuddled; very low or very high pain threshold; over reaction to noise; difficulty following simple directions, and so on. The Diagnostic and Statistical Manual (DSM-IV-TR) (2000) of the American Psychiatric Association provides one of the most commonly used categorizations. It lists three types of LDs: 1. Reading Disorder or Dyslexia; 2. Mathematics Disorder or Dyscalculia; and 3. Disorder of Written Expression or Dysgraphia. The research literature and assessment reports refer to two other types. They are non-verbal learning disability and language

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learning disability. Three characteristics must be present in order to categorize learning difficulties as LDs. These are: 1. significant areas of academic difficulties (listening comprehension, oral expression, written expression, basic reading skills, reading comprehension, mathematical calculation, and mathematical reasoning); 2. relative areas of academic strengths; and 3. a significant deficit in one or more areas of information processing (auditory, visual, memory). It is possible to have a combination of disabilities and special talents. If a LD has a neurological cause, it may be expected to have more than one disability such as forms of brain damage like cerebral palsy, traumatic brain injury, and other conditions that virtually result in multiple disabilities affecting several areas of functioning (Cruickshank, 1976; Hallahan and Kauffman, 1994). Thus LDs could be co-morbid with other conditions, such as emotional or behavioral disorders, or disorders of hearing or vision. It is possible for an individual to have a specific LD (reading or mathematics) and exhibit good performance in an area not well represented in our curriculum and scholastic tests ( for example, divergent thinking which is an essential characteristic of creativity is not necessarily a prerequisite for success in school) or in an area not directly impeded by the disability.

DIAGNOSING LEARNING DISABILITIES: ISSUES AND PROBLEMS In order to make a diagnosis of LD one has to establish that: 1. The student’s learning difficulties significantly interfere with academic and daily living that requires reading, mathematical, and writing skills. 2. A discrepancy between intelligence and academic achievement. (The student is of average or higher than average intelligence but below average in academic achievement.)

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3. There are no other apparent causes that could account for the level of learning difficulties that the student is experiencing. Historically, every field of disability has sought diagnostic purity— clear distinctions between a particular disability and all other categories—but this purity has always proven elusive. Inappropriate diagnostic practices and procedures have contributed to misclassification of individuals and questionable incidence rates of LDs. Such practices and procedures result in erroneously including individuals whose learning and behavioral problems are not attributable to LDs and excluding individuals whose deficits are manifestations of specific learning disabilities. Many children, regardless of what they look like in research journals, may have incredible talents generally under valued or not well expressed in our curriculum and scholastic tests. For example, divergent thinking considered a characteristic of creativity is not necessarily a prerequisite for success in school. Learning disorder may be informally flagged by observing significant delays in the child’s skill development but actual diagnosis of LDs is made using standardized tests that compare the child’s level of ability to what is considered normal development for a person of his age and intelligence. A comprehensive assessment for diagnosis and planning appropriate intervention program to differentiate between “diagnosing for learning disability and eligibility for specific services and concessions” is another difficulty to be surmounted before we can make the diagnosis process more successful and scientific. The NJCLD views the following issues as important to an understanding of current concerns: 1. The lack of adherence to a consistent definition of LDs that emphasizes the intrinsic and life-long nature of the condition. 2. The lack of understanding, acceptance, and willingness to accommodate normal variations in learning and behavior. 3. The lack of trained professionals to diagnose and manage exceptional behavior. 4. The false belief that under-achievement is synonymous with specific learning disability. 5. The incorrect assumption that quantitative formulas alone can be used to diagnose LD.

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6. Failure of multi-disciplinary teams to consider and integrate findings related to the present problem(s). 7. The lack of comprehensive assessment practices, procedures, and instruments necessary to differentiate LDs from other types of learning problems. 8. And general preference for the label “learning disability” over “mental retardation” or “emotional disturbances”, which leads to the misclassification of some individuals. Further, it is important to integrate assessment, diagnosis, and other non-formal procedures that lead to the diagnosis of LD. Learning disabilities, like other handicapping conditions, are manifested differently over time, in severity, and in various settings, therefore, differential diagnosis is necessary to distinguish between and among other disorders, syndromes and factors that can interfere with the acquisition and use of listening, speaking, reading, writing, reasoning, or mathematical abilities. Once a particular disability is identified, there is always a temptation to assume the label, which summarizes all the difficulties. Disabilities seldom affect every area of functioning; that is, an individual can exhibit superior abilities in unaffected areas of performance. If LDs have a neurological cause, it may be expected to have more than one disability such as forms of brain damage like cerebral palsy, traumatic brain injury, and other conditions that virtually always result in multiple disabilities affecting several areas of functioning (Cruickshank, 1976; Hallahan and Kauffman, 1994). Thus, LDs could be co-morbid with other conditions, such as emotional or behavioral disorders, or disorders of hearing or vision. It is possible for someone to have a specific LD that is, reading or mathematics, and exhibit brilliance in performance not directly impeded by the disability. These problems have an implication for conducting a diagnostic exercise.

ASSESSMENT: THEORETICAL FRAMEWORK Assessment is a systematic process of ascertaining the status of a child, his capabilities and limitations, in respect of a diagnosed

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disability. It includes identifying the impaired functioning, how it occurred, what are the consequences and what to do in order to optimize his potential functioning. It helps in better understanding of the individual as also in achieving greater control over their functioning, contributing to improvement in their self-esteem and emotional health. In the West, it serves the purpose of determining placement. In India, the field is in its nascent stage and is not also favorably viewed. The concept of multi-disciplinary approach involving professionals from education, psychology, and medicine (regular teacher, specialist, psychologist, counselor, speech therapist, physician, pediatrician, opthalmogist, ENT specialist, neurologist, and so on) working together to understand the child is yet to be realized and put into gear. Why the child under-achieves or does not learn is not examined in depth. Assessment is wherever or howsoever little practiced, leaving the child stigmatized for a disability by a once-in-a-lifetime testing result instead of continuous assessment. Various theories of assessment have been proposed. Assessment of traits suggests a classification of LDs and identifies patterns of strengths and weaknesses in basic abilities or processes underlying academic performance and social acceptability. Strengths and weaknesses in certain characteristics (for example, intelligence, auditory processing, impulsivity, visual-motor abilities, academic achievement) are assessed, usually by means of either standardized or formal or informal tests that are assumed to produce reliable and valid measurements. The pattern of these strengths and weaknesses provides the basis for selection of instructional methods to address the underlying ability or process that produced the learning difficulty. In the diagnostic–prescriptive teaching approach the assumptions about assessment is that testing will lead to a “diagnosis” of the underlying difficulty. For example, testing might reveal a weakness in auditory discrimination that is the basis for difficulties in listening and reading skills, or we might interpret test results as indicating an impulsive cognitive style that has led to social rejection. Once the diagnosis is made, an instructional “prescription” can be written (for example, teach the student to tell the difference between a variety of sounds, or work on getting the student to slow down and consider alternatives before reacting in social situations). In contrast, the

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direct instruction theory of assessment focuses on the academic or social performance problem itself, not on traits, abilities, processes, or stages assumed to underlie LDs. For example, if the student is having difficulty in beginning reading, assessment may start with measuring the extent of the student’s knowledge of letter–sound correspondence and identification of those correspondences the student does not know. Formal assessment involves the use of standardized tests including tests of cognitive functioning and projective tests (in a clinical setting), which demand specialized training for administering, scoring, and interpreting them. A large number of tests standardized on foreign, as also on Indian population to measure intelligence, aptitude, and personality are commercially available. Tests can contribute in understanding the child, provided the tests are used, administered, scored, and interpreted scientifically. How to select a test? How to score and interpret responses are discussed in the Assessment of Exceptional Students (Taylor, 1984). Before using these tests, the year of construction, revision, if any, population, age, and grade norms along with their reliability and validity data need to be thoroughly checked. Informal assessment constitutes observation, interview, even checklists and rating scales are also used. As a precaution, behavior to be observed needs to be problem specific and operationally defined. Observations should be made over a period of time at different intervals and extended to different settings. Observations should be recorded systematically and the strategy used by the child while attempting the task should also be noted. Control of observer’s bias is no less important.

Domains of Disorder and Assessment Regardless of the theoretical frame of reference for approaching assessment, specific domains of performance must be assessed, including aptitude, intelligence, attitude, and a variety of abilities related to sensory and social perception. These domains may also involve the basic processes or curriculum areas in which LDs may be suspected or confirmed. Each domain presents unique challenges in conceptualizing the problem of poor performance as well

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as unique difficulties in measuring the characteristics and abilities deemed most important. These domains are inter-related in such a way that problems in one domain may be intimately connected to problems in other. For instance, assessment of language also requires an assessment of cognition, socialization, and the learning environment. Language “Language is a system of verbal symbols used for human communication” (Wallace and McLoughlin, 1998). Language is essential to interact and communicate with other individuals. Communication is the ability to decode (receive and understand) and encode (express and send) messages. We communicate ideas through language, using arbitrary code or system of symbols. These symbols may be sounds, as in oral language, or visual forms, as in reading, writing, and sign language. Without the ability to use language effectively and efficiently, an individual’s everyday life is handicapped. Much about how language develops, brain injury affects language, and impaired language can be restored remains to be learned (Nelson, 1993). In order to assess students’ language competencies and specific problems, one must understand how language develops, and how spoken and written language is interrelated. Every language has distinct speech sounds or phonemes. Spoken Language Disorders of spoken language may affect its form, content, or function. The form of spoken language includes phonology, morphology, and syntax, semantics and pragmatics, which are the basic building blocks of language. An individual can have difficulty with any one or any combination of these basic elements of language. Phonology is the system of sounds and sound combinations that are used according to linguistic rules; for example, sound substitutions (for example, “wabbi” for “rabbit” or “shun” for “sun”). Morphology is the system of rules used to construct words and word forms from basic sounds and involves the structure of basic units of meaning. Difficulty in forming plurals, possessives, and tenses, for example, are morphological problems. Syntax is the set of rules

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that governs how words are put together in combinations and proper order to form sentences. For example, a child with a syntax problem may say, “He tapped the computer on his key” for “He tapped the key on his computer”. Effective use of the form of a spoken language requires a person to produce the individual sounds and sound combinations of the language, combine these sounds to form words and word variations, and put the words together to form sentences. Other disorders of language involve its content, or semantics— the intent and meanings of words and sentences. An individual who has problems in the area of semantics may be able to make all the word sounds and word forms correctly and to put words in correct order, yet be able to convey little or no meaning. Problems of semantics may involve incomplete thoughts or misused words that partially or totally obscure the intended meaning. Still other language disorders involve pragmatics, the social use of language. Disorders of pragmatics entail the inability to use language to achieve desired social purposes, even though the language used may be appropriate in form and content. They may not know how to make requests, give feedback to others, or respond to criticism in ways that are understood and socially acceptable. The acquisition of language is in fact a synthesis of factors like heredity, maturation, and environment (Marge, 1972). Assessment Language assessment needs to include tests of hearing; tests of sound discrimination; tests of speech mechanism; tests of developmental language ability, and appropriate models in environment (Houck, 1984). A few tests used in researches abroad are, Naming Picture Objects (Semel and Wiig, 1980), Test of Language Development (TOLD) by Newcomer and Hammill (1977), and Peabody Picture Vocabulary Test (Dunn and Dunn, 1981). Reading Reading is an extension of the language process. It represents the means by which much of the information presented in school is learned and is the academic area most often implicated in school

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failure. Reading is an extremely complex process that requires an understanding of the correspondence between written symbols and the sounds to which they refer. Understanding that these symbols are arranged into words is also essential, as is understanding that the words are arranged to represent the language we hear. The individual who reads must be able to decode the written symbols, to translate them into oral language or obtain the meanings of the oral language they represent (Gelzheiser and Clark, 1991). Thus, phonology, morphology, syntax, and semantics are skills critical to reading as well as oral language. Pragmatics is also necessary for skillful reading (Garner et al., 1991). It allows the individual to decode (that is, read) a word never seen before either in isolation or in context. The term dyslexia is derived from the Greek word “dys” (meaning poor or inadequate) and “lexis” (words or language). Reading achievement of dyslexic children on a standardized test fall much below the expected level as compared to their age, intelligence, and age-appropriate education. Poor vocabulary, inadequate comprehension, absence of sequence add further to suspicion of this disorder. He or she might be given to reversing letters word or numbers, making guesses, adding or omitting words while reading. Critchley (1970) described dyslexia in two ways: 1. as a disorder manifested by difficulty in learning to read despite conventional instruction, adequate instruction, intelligence, and socio-cultural opportunity; it is dependent upon fundamental cognitive disabilities, which are frequently of constitutional origin; 2. as a disorder in children who, despite conventional classroom instruction fail to attain the language skills of reading, writing, and spelling commensurate with their intellectual abilities. The dyslexic child is generally of average or above-average intelligence, maybe spatially disoriented with left-right confusion, are poor in respect of figure ground perception, may be impulsive, suffer from stuttering or lisping, have short attention span, and have inefficient visual or auditory memory.

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ASSESSMENT The guiding principle in planning assessment is to find the answer to how best the child can be helped. Teachers need to be familiar with reading process and areas of reading skills, which require assessment. Literature shows that some of the tests used for formal assessment are Woodcock Reading Mastery Tests (Woodcock, 1967); Gray Oral Reading Test (Gray and Robinson, 1967); Wide Range Achievement Test (Jastak and Jastak, 1978); which provide an overall assessment of spelling, reading recognition, and math computational skills; and Peabody Individual Achievement Test (Dunn and Markwardt, 1970).

Pre-reading Skills This stage covers the pre-school years during which children learn to discriminate shape, size, and colors. Visual tracking from leftto-right, eye-hand motor co-ordination, following instructions and directions as well as listening skills are some of the basic skills required to read. Pre-reading skill includes ability to “read” pictures, to complete rhymes and identify words that do not rhyme; distinguish between verbal and non-verbal sounds; recognize similar and different sounds, segments, blends; and store and retrieve sounds learnt. Reading skills can be divided into two general categories— word recognition and comprehension. A number of skills are used when attempting to identify, pronounce, or retrieve a word. The child can use four types of analyses—visual analysis (that is, the use of visual features), contextual analysis (that is, using the surrounding words for clues about a given word), phonological analysis (that is, using information about the sounds in the word), and structural analysis (that is, recognizing and giving meaning to specific word parts, such as prefixes, suffixes, or syllables). The assessment of reading needs to address the ability of the child to recognize individual words and to comprehend text, identify errors in decoding, and determine fluency and accuracy when reading. It also includes the student’s ability to understand the main idea of the story, capture its detail, or place events in sequence, paraphrase

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or retell the story in his or her own words, and also identify which sentence out of several means the same thing.

Written Language The ability to write at an age-appropriate level is required for all academic purposes. For some children, the acquisition of written expression skills is a difficult and enduring problem. Writing is a complex task requiring the mastery and integration of a number of sub skills. It is a form of communication that consists of three areas—spelling, handwriting, and written expression or composition. A good reader is not necessarily a good writer. Many good readers are unable to produce writing that others like to read and can understand. Written language is directly tied to reading, listening, and speaking and there is an overlap of skills in these areas. Encoding written language requires skills somewhat different from those required for decoding it. Handwriting refers to motor skills involved in handwriting. But more complex skills are required, to spell or reconstruct a word. The essential feature of this disorder (dysgraphia) is writing skills, which are much below the level expected for a child of a given age, intelligence, and age-appropriate education. It also presents the inability of the child to deal with abstract ideas. Lerner (1981) defined dysgraphia as extremely poor handwriting or the inability to perform the motor movements required for handwriting. Individuals with this disorder may have poor vocabulary, commit excessive spelling errors, and/or are poor in grammar and punctuation. Assessment An informal assessment is considered a quick way of identifying what kind of writing deficit is present. It should help in ascertaining whether the problem is one of visual perception, memory or motor co-ordination. Assessment of manuscript (printing) includes evaluating the position of the hand and paper, size of letters and the proportion of letters to each other, quality of the actual pencil line, the amount and regularity of the slant of the letters, letter formations and alignment, letter or word spacing, speed of production, and the

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way in which letters are connected (cursive). Written composition refers to creative writing. Alley and Deshler (1979) suggest three general areas that need to be addressed—the student’s attitude toward writing, ability to express content (for example, skill in describing or reporting events, or in expressing views or feelings), and the student’s ability to “craft” a paragraph (for example, ability to organize sequence, choose effective words, use punctuation, capitalization, and notes taking). Test of Written Expression (TOWE) (Hammill and Larsen, 1988) used measures of written expression disorder is among the widely.

Mathematics The essential feature of this disorder is mathematical ability of calculation or reasoning that measures much below the expected level for the individual’s chronological age, measured intelligence, and age-appropriate education. The disturbances in mathematics significantly interfere with academic achievement or with activities of daily living that require mathematical skills. Individuals with this type of disorder may have difficulty recognizing or reading numbers, copying numbers correctly or counting objects. Mathematics though used interchangeably means different things. Mathematics is the study of the numbers and their relationships to time, space, volume, and geometry while Arithmetic refers to the operations or computations performed. Skills related to mathematics include— problem solving, the ability to use mathematics in practical situations, performance of appropriate computational skills, use of mathematics to predict, understand and use of concepts related to measurement, interpretation and construction of graphs, ability to estimate, understanding and application of geometric concepts, ability to recognize the reasonableness of results, and computer knowledge. Wood (1980) suggested that many learning disabled children find the modern math approach difficult because of the language and vocabulary used, notations which cause directional problem and parents, unfamiliarity with modern math. They also find it difficult to discriminate between right and left, following sequence, distinguishing reverse numbers, making estimation of space, time shape,

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and weight. Skrtic (1980) showed that processes of formal reasoning and concept development among learning disabled are delayed. As is the case with language, the teacher assessing mathematics must be able to identify precisely what the student does not know and to understand what concepts and skills he needs to master. The term arithmetic is required for learning more complex ideas and competencies (Smith and Rivera, 1991). Basic Concepts and Operations At the most fundamental level, individuals learning arithmetic must understand the concept of number, the oral and written symbols for numbers, how to count to a number, and number–numeral correspondence. They must also learn the meaning of computational operations (addition and subtraction and their abbreviated versions, multiplication, and division) and the signs used to prompt them. Reading and writing arithmetic operations, as algorithms, are also necessary skills. These operations become complex by the introduction of fractions and various units of measurement (for example, time, distance, weight, or money). The assessment of mathematics should measure a student’s ability in both calculation and reasoning (application). Assessment must begin by analyzing actual samples of the student’s work and identifying specific errors and any apparent pattern to those errors. Some students acquire most computational skills but have little or no understanding of how these skills can be applied to solve actual problems. Reasoning and Problem Solving At the most basic level, teachers ask students to learn how to translate “story problems” or their own questions regarding quantities into algorithms for solution. At higher levels, students are expected to reason through algebraic equations, theorems, and proofs and then apply these to the solution of practical problems. As problems in mathematical reasoning become more complex, assessment of students’ language and cognitive abilities become increasingly critical to the accurate assessment of their abilities to use mathematical concepts.

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The best method of assessing mathematical disorder is to use classroom tests. The desired areas of assessment are—written assignments, oral work, capacity to verbalize, and explain the steps being followed in solving the problem. The test constructed, should see that there is a relation between the skill to be assessed and the nature of the problem. Teacher doing informal assessment needs to rule out sensory deficits of vision and hearing, know the reason for referring the child for assessment, evaluate span of attention, learning style, and the context that finds the child puzzled. Interest in, and attitude towards math, work sample over a period of time as well as instructional adequacy also need to be scanned. Formal assessment uses standardized tests. A number of tests, for different areas of math, are commercially available with varying degree of usability, age and grade norms for use of learning disabled children. The foreign tests reported to have been used widely for assessing basic arithmetic concepts, numeration, operations and computational skills are California Achievement Test (Tiegs and Clark, 1963), Peabody Individual Achievement Test (Dunn and Markwart, 1970), SRA Achievement Series in Arithmetic (Thorpe et al., 1970), and Stanford Diagnostic Arithmetic Test (Beatty et al., 1966).

Cognition Individuals with LDs have adequate cognitive skills in most areas but difficulty with specific cognitive tasks such as deploying their attention or processing specific types of information. Cognition includes a wide variety of information-processing skills and processes including perception, attention, memory, comprehension, and selfguidance of mental processes (Conte, 1991; Swanson and Cooney, 199; Wong, 1991). One or more of these processes (for example, attention) may be impaired across all types of academic tasks, leaving the individual with inadequate task–approach skills even though the other cognitive processes are intact. Alternatively, an individual may have difficulty processing information only in a particular area, such as a poor ability to remember words or word sounds even though memory for other information is unimpaired.

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Attention The ability to focus on a given activity for extended periods is important if a student is to take in information or complete the dayto-day tasks in school. To perform effectively in any area of learning, we must be able to initiate, direct, sustain, and shift our attention (Conte, 1991). Students who have attention problems may appear restless, inattentive, impulsive, emotionally volatile, socially inappropriate, and unable to predict the consequences of their behavior. Assessment of how they direct their attention to specific tasks may be critical in helping them respond successfully to academic demands and social situations. Difficulties in any of the phases of attention can interfere with a student’s ability to learn or share what he or she knows in a consistent manner. Bender Visuo-Motor Gestalt Test (BGT) (Koppitz, 1975), Wechsler Intelligence Scale (rev.) (1974), Porteus Maze Test (Porteus, 1965), and Swarup & Verma Test of Cognitive Processes (1997) have been used in studies related to assessment of attention problem. Meta-cognition Meta-cognition is the ability to control and direct one’s own attention and mental processes (Wong, 1991). Students who lack metacognitive skills do not seem to have developed an internal dialogue about what they know and what they are trying to do that might help them perform better. Strategies for remembering, listening, connecting what they already know to what they are trying to learn, problem solving, or making sense of what they read have not been learned adequately. The assessment of cognitive processes should indicate how students think about academic tasks and social interactions, how they would approach problems, evaluate solutions, solve the problem using systematic and effective strategies.

Socialization The behaviors that is off-target academically or socially—in attention, being out of seat, talking too much, hitting or biting, missing school, can distract learning. When a student’s behavior appears to

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be interfering with his school performance and his relationships with others, or when that behavior is maladaptive or bizarre, it becomes important to assess the student’s behavior (when does the behavior occur, how often does it occur, and what are the reasons for its occurance), as well as his emotional and social development. Learning disabilities are assumed to be characterized primarily by problems in academic performance, but problems in social relationships are also said to be associated with academic inadequacy. Although it is true that some individuals with LDs have excellent social skills, it is also true that many have very poor social skills and consequently experience serious social problems (Bryan, 1991). Many students with LDs have emotional or behavioral problems, and a substantial percentage of these can be said to have a co-existing emotional or behavioral disorder. Social Perception and Cognition Accurate perceptions of self and others are critical to successful socialization. Students with LDs have poor feelings of self-worth. Assessment should indicate whether the student has unrealistic views of himself and the basis for his self-evaluation. Students with LDs also often have skewed negative perceptions of others. If they are to be socially successful, they need to be able to interpret the social meaning of others’ behavior, and to read both obvious and subtle social cues. They sometimes seem to lack the ability to understand why social events occur, are unable to attribute the causes of social circumstances and interactions properly, and are not able to take responsibility for their own behavior. All of these skills require an understanding of verbal and non-verbal communication, social customs, moral standards, and negotiation to resolve conflicts. Social Interaction Social isolation or rejection is what the students with LDs sometimes experience. Their social behaviors at times irritate others and some of them do not know how to approach others for specific purposes, such as asking to play with or share something. They may also lack skills in responding to the approach of others. Assessment and remediation would include modeling of and feedback on such

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subtleties of social intercourse as reactions to directions; praise; criticism; eye contact, posture and other non-verbal cues; distance maintained when conversing with someone; turn-taking, loudness of voice, and so on.

Environment Learning problems do not occur without a context or environment. It is important to ascertain whether an inadequate environment could be the primary cause of the student’s difficulty or are there any factors that are contributing significantly to inadequate performance. Assessment of the learning, social, and instructional environment would reveal significant information to identify those who are “at risk”.

INDIAN CONTEXT It is also imperative to examine the issues pertaining to assessment and remediation in the Indian context. As pointed out by Karanth (2003), the understanding of LD in India is dependent on Western literature and “the practices of assessment and remediation are influenced, often inappropriately and unduly, by Western thought, practice and materials” (p. 27). In the assessment of LD, practitioners in India, such as Sankaranarayanan (2003) has used reading assessment tests (letter identification, word recognition and reading texts 1 and 2) as well as tests used on Western subjects, such as the Rhyming, Torgesen Elision, Rapid Automatized Name, Rapid Alternating Stimulus, Short-term Memory for Digits, Conservation, Handedness, and Vocabulary. She found that the best predictor of reading ability for the Indian sample were speed of naming letters, vocabulary, and phonological awareness. In the assessment of LDs, Rozario (2003) prepared an informal reading inventory by carefully selecting graded reading passages and identified specific reading errors, such as word-by-word reading, incorrect phrasing, poor pronunciation, omissions, repetitions, inversions or reversals, insertions and substitutions, consonant and

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vowel sounds not known, vowel pairs and consonant clusters not known, poor structural analysis and an inability to use context clues, similar procedures were evolved for the assessment of writing and spelling. Rozario (2003) emphasized the need to identify the student’s strengths and weaknesses and to present a highly individualized profile of both cognitive and personality styles. As most of the tests used in India are either Western tools or adaptations of Western tools, Prema (1998) developed the Reading Acquisition Profile in Kannada (RAP-K) which is an indigenous, language-based reading assessment battery designed to profile the language and reading skills of children learning to read and write Kannada. Results of studies using this measure suggest that some reading processes depend on the nature of language and its scriptspecific features. Thus Prema and Karanth (2003) recommend the use of language-based tests that are sensitive to the characteristics of each language and its script-specific features. As far as the remediation of reading disabilities is concerned, Srikanth and Karanth (2003) used a remedial program based on the Aston Teaching Programme, through which individual cases were assessed and remedial work was done keeping in mind individual error patterns and areas of difficulty. Thus, remediation focused on auditory visual channel deficits, specific spelling rules and cues, training in comprehension skills, oral expression, written expression, and visuo-motor perceptual aspects. They concluded that a complete remedial program should aim at both reading and spoken language proficiency. In India, as also anywhere else, parents, educationists, and psychologists are becoming more and more concerned to know why children fail. What is it due to? Which specific disability do they have? Why is that some students find it difficult to focus and concentrate on a task are impulsive, hyperactive, and even aggressive in homes and classrooms? In recent years, human rights activists, social organizations, and government and academic institutions have awakened to the need for putting in place more initiatives, resources, research, and policy support to understand and help them optimize their potential. Research efforts have been geared up to develop objective measures to identify, diagnose, and assess what the child can do rather than what he cannot do, and plan informed intervention and

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monitor the progress. If educational assessment reveals significant discrepancies between the ability and performance on academic achievement, identifies difficulty in one or more areas in information processing and is not a direct result of one of the other possibilities of LDs, the individual may be referred for LD assessment. Learning disability is relatively a new and less explored area. Only selected centers and departments have been interested and involved in researching this field. By and large, documented literature and search reveal that many of the researches include master’s level dissertations and a few doctoral theses. Commercial tests of questionable value and hurried adaptation of foreign tests with poor psychometric properties and inadequate age-grade and disability specific norms are being used across regions for identification, diagnosis, and assessment. Some of these are culturally biased and amenable to errors of measurement and tend to misclassify students due to deficiency inherent in the instruments used. Some of the measures adapted or constructed to identify, diagnose, and assess learning disabled children are listed below. A number of tests have been constructed in India. Among these Rama (1984) constructed a measure for diagnosing dyslexia while Purusottama (1988) constructed a test for assessing capability for reading Kannada letters. Chatterji (1991) compared speech-related process of skilled and unskilled readers using the matrix analogy test of Das and Naglieri and Mohanty and Sahoo developed the reading comprehension test. Das and Naglieri developed selective attention and figure memory test. Das included serial recall, naming test, speech rate test, and memory test to assess levels of reading skills. Kapur et al. (1991) constructed the NIMHANS Index of specific learning disability. Mohapatra (1991) used the decoding, comprehension test, oral reading, digit span, letter cancellation, visual closure, visual memory, auditory closure, and auditory memory tests to differentiate between the normal and reading disabled children. Swarup and Mehta (1991) developed a behavioral checklist for screening the learning disabled. Swarup and Verma (1997) constructed a measure of cognitive processes (consisting of experimental tasks) like attention, perception (auditory discrimination, visual discrimination, and figure ground perception), and memory (auditory memory, auditory sequential memory, and visual sequential memory) to study

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the cognitive make-up of learning disabled children. Chopra (1997) developed a handbook for parents and teachers of children with Attention Deficit Hyperactivity Disorder; Mehta (2000) developed a test of Mathematics disability while Paushikar (2004) adapted a test of reading dyslexia. A number of teacher-made and standardized tests of achievement in different subject areas are available and used by researchers, but most of them are a one-time-task and have hardly undergone any process of revision. There is an urgent need to set up a body of experts (psychometricians, psychologists, and educationists) with established credence and financial resources to review all tests at regular intervals and make public their credibility with respect to their usability, reliability, validity, and norms across different states.

CONCLUSION A comprehensive assessment involves diagnostic interview; assessment battery aptitude including measures of academic achievement, information processing, and other or informal measures; test scores and specific diagnosis; and a feedback interview, whose test results and professional recommendations are explained in clear, jargonfree language, and opportunity is provided to ask questions. A LD assessment, which involves a battery of tests referred to as psychoeducational assessment (conducted by a clinical psychologist), would reveal academic difficulties as a result of learning difficulties or disability and the nature of that disability. It is important to remember that all assessments involve error. What emerges from the assessment process is not a “true” picture of the student but rather a patchwork of pictures that have captured the student at various moments in time. Informed decision-making is contingent on comprehensive assessment. More comprehensive the assessment, better would be the decision-making. Clinical and school psychologists are being held increasingly accountable for their assessment practices. Forces, both inside and outside the profession are posing hard questions. Are assessment practices cost effective? Are they scientifically sound? Are they fair and unbiased? The field of assessment is in the midst of significant

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change. New pressures are forcing psychologists to demonstrate that their assessment techniques are scientifically sound. The science and practices of assessment are consequently exposed to reforms. Assessment techniques need to be developed or re-conceptualized to ensure validity. Development and validation of new tests are important components of the assessment process, clinical judgment, and decision-making. Assessment could be standard based that is, what students know and are able to do is compared to standards of knowledge and skills expected of them commensurate with their potential rather than to the performance of other students.

Development of Assessment Assessment may not have appropriate items for students with disabilities. Therefore, in the development of tests and assessments it is essential to involve individuals who are fully aware and knowledgeable about disabilities. Another thing that makes assessment suspect is that students with disabilities are not considered when items are developed, and they are not included when assessments are fieldtested. Field-testing helps to identify problem and provides more varied items by modifying, deleting or adding test items during this phase. Some of the difficulties are that written guidelines are exclusionary or vague and poor performance may have negative effects on students with disabilities. This is based on the assumption that students with disabilities will perform poorly while desiring to do well. Building a system that is accountable for all students should be the goal of education. Assessment planned with this end in view can proactively address the issue of accountability of learning for all students and help policy makers make decision to improve educational programs.

Who Can Diagnose Learning Disability? A good number of professionals are involved in the diagnosis of LDs. They include registered psychologists, educational specialists,

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and other professionals working in specialized fields having a specialized training in interpreting psychological tests and diagnosing LD. Many professionals can suspect LD, but they do not have necessary certification or licence to diagnose the disorder. Those professionals who are eligible and competent to carry out diagnosis and identification—for example, clinical psychologists with a licence to diagnose LD by doing psycho-educational assessment; school psychologists with school certification; educational psychologists who are qualified to do assessment of intellectual functioning and use results of assessment; neuro-psychologists, educational specialists; and psychometrists—should form a team. A Master’s and Ph.D degree in the related speciality should be made mandatory.

REFERENCES American Psyciatric Association (APA). (2000). The Diagnostic and Statistical Manual of Mental Disorder —Text Revision (DSM-IV-TR). Washington, D.C.: APA. Alley, G. and D. Deshler. (1979). Teaching the Learning Disabled Adolescent: Strategies and Methods. Denver: Love Publishing. Algozzine, B. and J.E. Ysseldyke. (1983). ‘Learning Disabilities as a Subset of School Failure: The Over Sophistication of a Concept’, Exceptional Children, 50: 242–46. Beatty, L.R., Madden and W. Gager. (1966). ‘Stanford Diagnostic Achievement Test’, in Onita Nakara (ed.), Children and Learning Difficulties, p. 16. New Delhi: Allied Publishers. Bryan, T. (1991). ‘Assessment of Social Cognition: Review of Research in Learning Disabilities’, in H.L. Swanson (ed.), Handbook on the Assessment of Learning Disabilities: Theory, Research and Practice, pp. 285–311. Austin, TX: Proed. Chatterji, M. (1991). Attention, Coding and Speech Related Process of Skilled and Less Skilled Readers. Unpublished M.Phil. dissertation, Utkal University. Cited from M.B. Buch (ed.), Fifth Survey of Research in Education. New Delhi: NCERT. Chopra, S. (1997). ‘A Handbook for Parents and Teachers of Children with Attention Deficit Hyperactivity Disorder’, M.Ed. (Spl. Edu.) Dissertation, SNDT Women’s University, Mumbai. Conte, R. (1991). ‘Attention Disorders’, in B.Y.L. Wong (ed.), Learning about Learning Disabilities, pp. 55–101. New York: Academic Press. Critchley, M. (1970). The Dyslexic Child. London: William Heinemann Medical Books, Ltd. Cruickshank, W.M. (ed.). (1976). Cerebral Palsy: A Developmental Disability (3rd rev.ed.). Syracuse, New York: Syracuse University Press.

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Dunn, L. and L. Dunn. (1981). Peabody Picture Vocabulary Test (revised), Circle Pines, Minn.: American Guidance Service. Dunn, L. and F.C. Markwart. (1970). Peabody Individual Achievement Test. Circle Pines, Minn.: American Guidance Service. Federal Register. (1977). Public Law 94–142, the Education for All Handicapped Children Act. Washington, D.C.: U.S. Government Printing Office. Garner, R.P.A. Alexander and V.C. Mare. (1991). ‘Reading Comprehension Failure in Children’, in B.Y.L. Wong (ed.), Learning and Study Strategies: Issues in Assessment Instruction and Evaluation, pp. 193–214. San Diego: Academic Press. Gelzheiser, L.M. and D.B. Clark. (1991). ‘Early Reading and Instruction’, in B.Y.L. Wong (ed.), Learning about Learning Disabilities, pp. 261–81. New York: Academic Press. Gray, W.S. and H.M. Robinson. (1967). Gray Oral Reading Tests. Indianapolis: Bobs Merrill. Hallahan, D.P. and J.M. Kauffman. (1994). Exceptional Children: Introduction to Special Education (6th ed.). Boston: Allyn & Bacon. Hammill, D. and S.C. Larsen. (1988). Test of Written Language (TOWL). Austin, Texas: Pre-ed. Company. Houk, Cherry K. (1984). Learning Disabilities: Understanding Concepts, Characteristics and Issues. New Jersey: Prentice-Hall, Inc. Englewood Cliffs. Jastak, J. and S. Jastak. (1978). Wide Range Achievement Test (revised). Wilmington, Del: Jastak Associates. Kapur, M., A. John, J. Rozario and A. Oommen. (1991). NIMHANS Index of Specific Learning Disabilities. Bangalore: Department of Clinical Psychology, National Institute of Mental Health and Neurosciences. Kavale, K.A., D. Fuchs and T.E. Scruggs. (1994). ‘Setting the Record Straight on Learning Disability and Low Achievement: Implications for Policymaking’, Learning Disabilities Research and Practice, 9: 70–77. Karanth, P. (2003). ‘Introduction’, in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 17–29. New Delhi: Sage Publications. Koppitz. (1975). ‘Bender Visual Motor Gestalt Test’, in Cherry, Learning Disabilities, Understanding Concepts, Characteristics and Issues. New Jersey: Prentice-Hall. Lerner, J. (1981). Learning Disabilities: Theories, Diagnosis and Teaching Strategies. Boston: Moughton-Mifflin. Marge, M. (1972). ‘The General Problem of Language Disabilities in Children’, in J.V. Irwin and M. Marge (eds), Principles of Childhood Language Disabilities, pp. 75–98. New York: Appleton Century Crofts. Mehta, H. (2000). ‘A Low Cost Diagnostic Test of Mathematics Disability (TMD) in Children Aged 7 to 10 Yrs’, M.Ed. (Spl. Edu.) Dissertation. Mumbai: SNDT Women’s University. Mohapatra S. (1991). ‘Reading, Memory and Attention Processes of Normal and Reading Disabled Children’. M.Phil. dissertation, Utkal University. National Joint Committee on Learning Disabilities. (1982). ‘Learning Disabilities: Issues of Definition’, Asha, 24(11): 945–47.

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Nelson, N.W. (1993). Childhood Language Disorder in Context: Infancy through Adolescence. Columbus, OH: Merrill/Macmillan. Newcomer, P.L. and D.D. Hammill. (1977). The Test of Language Development (TOLD). Austin, Texas: Empire Press. Paushikar, A. (2004). ‘Adaptation of Diagnostic Test of Reading Disorder in Marathi’, Unpublished M. Ed. dissertation. Mumbai: Centre of Special Education SNDT Women’s University. Prema, K.S. (1998). ‘Reading Acquisition Profile in Kannada’, Doctoral dissertation. Mysore: University of Mysore. Prema, K.S. and P. Karanth. (2003). ‘Assessment of Learning Disability: Language based Tests’, in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 138–49. New Delhi: Sage Publications. Porteus, S.D. (1965). Porteus Maze Test, Fifty Years’ Application. California: Pacific Book Publishers. Purusottama, G. (1988). ‘Reading Kannada Letters’, Indian Journal of Disability and Rehabilitation, July–December, pp. 59–62. Rozario, J. (2003). ‘Assessment of Learning Disabilities’, in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 101–10. New Delhi: Sage Publications. Rama, S. (1984). Diagnosis and remediation of dyslexia—An attempt. Ph.D. (edu) thesis Mysore University. In M.B. Buch (ed., 1991), Fourth survey of research in education, vol. II. New Delhi: NCERT. Sankaranarayanan, A. (2003). ‘Cognitive Profiles of Children Learning to Read English as a Second Language’ , in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 77–90. New Delhi: Sage Publications. Semel, E.M. and E.H. Wiig. (1980). Clinical Evaluation of Language FunctioningScreening Test. Columbus Ohio: Charles E. Merril Publishing Co. Srikanth, N. and P. Karanth. (2003). ‘Speech Language Pathologists and the Remediation of Reading Disabilities’, in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 150–65. New Delhi: Sage Publications. Skrtic, T. (1980). Formal Reasoning Abilities of Learning Disabled Adolescents: Implication for Mathematics Instruction. Research report no. 7. Lawrence: University of Kansas, Institute for Research in Learning Disabilities: Emphasis on Adolescent and Children. Smith, D.D. and D.P. Rivera. (1991). ‘Mathematics’, in B.Y.L.Wong (ed.), Learning about Learning Disabilities, pp. 345–74. New York: Academic Press. Swarup, S. and D.H. Mehta. (1991). Behavioural Checklist for Screening Learning Disabled. Mumbai: SNDT Women’s University. Swarup, S. and P. Verma. (1997). Test of Cognitive Processes. Mumbai: Centre of Special Education, S.N.D.T. Women’s University. ——————. (2006). ‘Cognitive Processes Differences among Learning Disabled and Non- learning Disabled Children’, Perspectives in Education, 22(1), Jan.: 29–40. Swanson, H.L. and J.B. Cooney. (1991). ‘Learning Disabilities and Memory’, in B.Y.L. Wong (ed.), Learning about Learning Disabilities, pp. 103–27. New York: Academic Press.

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Taylor, R.L. (1984). Assessment of Exceptional Childern: Educational and Psychological Procedures. Englewood Cliffs, NJ: Prentice-Hall. Thorpe, L.P., O.W. Lefever and R.A. Naslund. (1970). SRA Achievement Series. Chicago: Science Research Associates. Tiegs, E.W. and W.W. Clark. (1963). ‘California Achievement Test’, in Onita Nakara (ed.) (1998). Children and Learning Difficulties, p. 175. New Delhi: Allied Publishers. Wallace, G. and McLoughlin. (1998). ‘Learning Disabilities: Concepts and Characteristics’, in Onita Nakara (ed.), Children and Learning Difficulties, pp. 43–77. New Delhi: Allied Publishers. Wechsler, D. (1974). Wechsler Intelligence Scale for Children (revised). New York: The Psychological Corporation. Wood, M.H. (1980). ‘Modern Math and LD Child’, Academic Therapy, 15(3): 279–90. Woodcock, R.W. (1967). Woodcock Reading Mastery Tests. Circle Pines, Minn.: American Guidance Service. Wong, B.Y.L. (1991). ‘The Relevance of Metacognition to Learning Disabilities’, in B.Y.L Wong (ed.), Learning about Learning Disabilities, pp. 231–58. San Diego, CA: Academic Press, Inc. Ysseldyke, J.E., B. Algozzine, M. Shinn and M. McGue. (1979). Similarities and Differences between Underachieving and Students Labeled Learning Disabled: Identical Twins with Different Mothers. Research Report. 13. Minnesota: Institute for Research on Learning Disabilities, University of Minnesota. ——————. (1982). ‘Similarities and Differences between Law Achievers and Students Classified Learning Disabled’, Journal of Special Education, 16(1): 73–85. Ysseldyke, J.E. (1983). ‘Current Practices in Making Psychoeducational Decisions about Learning Disabled Students’, Journal of Learning Disabilities, 16(2): 226–33. Zigmond, N. (1983). ‘Towards a New Definition of Learning Disabilities’, Paper presented at Annual Meeting of the American Educational Research Association, Montreal, Canada.

7 Profiles of Academic Skill Deficits in Indian Schools MALAVIKA KAPUR

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he term “learning disability”(LD) has been used in the United Kingdom to describe mental retardation. In India, the term “specific learning disability” is used as a synonym for “learning disability”. Specific learning disabilities (SLDs) are commonly encountered in school settings. The term refers to difficulties in reading, writing, and arithmetic in children with average intelligence. The prevalence is estimated to be about 10 percent in the Englishmedium schools. Prevalence may vary across schools, medium of instruction, and gender. A detailed assessment of the individual child’s assets and liabilities is essential for a developing remediation package tailored to suit the educational and psycho-social needs of the children. There are several aetiological theories about SLDs. In the biological realm, these range from genetic, biochemical, neuro-physiological, neuro-psychological, prenatal influences, and opthalmological explanations. The linguistic, behavioral, psycho-analytical, and educational approaches offer environmental explanations. However, these theories often fail to lead to effective remedial strategies. The reason probably lies in the complex nature of interactions of multiple factors causing learning deficits. In the present chapter, three important aspects related to SLD are examined. These are: 1. Assessment and remediation of SLD in the Indian context.

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2. Profiles of academic skill deficits across different kinds of Indian schools. 3. Academic skill deficits and psycho-social factors. The scholastic difficulties amongst children have several causes. The level of intellectual functioning and sensory–motor deficits has been recognized as major causes. However, the school systems have been implicated only to the extent that they are deficient. The present chapter highlights the possible variations across different school systems (or streams) of education across India. These are urban and rural schools under the state syllabus or the other urban streams such as Indian Council of School Certificate (ICSC) or Central Board of Secondary Education (CBSE), which come under the Central syllabus. The state syllabus is relatively easier and more often adopted by schools run by the government and are funded wholly or partly by the state governments. The Central syllabus is of higher difficulty level and mostly adopted by privately or centrally funded schools. Since the 1980s, the broad definition of LD formulated by the US National Joint Committee on Learning Disabilities (Wong, 1998) has been widely used and is as follows: LD is a general term that refers to a heterogeneous group of disorders manifested by significant difficulties in the acquisition and use of listening, speaking, reading, writing, reasoning, and mathematical abilities. These disorders are intrinsic to the individual, presumed to be due to central nervous system dysfunction and may occur across the life span.

In the above definition, psycho–social concomitants and extrinsic factors though contributory, are not considered within the ambit of the definition of the term. The present chapter makes a case for studying these extrinsic variables to promote effective assessment and remediation. In the developing countries it is even more essential to study the extrinsic reasons before blindly arriving at the diagnosis of LD. The present chapter focuses primarily on how the school systems influence the attainment of basic academic skills in the Indian context. It is necessary to keep in mind that the terms like “dyslexia” have become commonplace due to media exposure, but the study of LDs specifically in reading, writing, and mathematics though a matter of concern to teachers, children, and parents alike, have

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received scant attention. The focus also has been entirely on the pupil’s intrinsic learning difficulties and the contribution of the school system has largely been overlooked. In a recent Indian publication on LDs (Karanth and Rozario, 2003), the focus is on the relationship between LDs and cognitive ability, language acquisition, auditory processing deficits, neuro-psychological processing, bilingualism, and on the co-morbid psychiatric conditions. In the present chapter too, the emphasis is on the intrinsic factors and issues of assessment, identification, and remediation.

ASSESSMENT

ACADEMIC SKILL DEFICITS INDIAN CONTEXT

OF

IN

Although several tests of Western origin of academic skill deficits have been used a great deal in India, these are often not appropriate in the Indian school context. In the present chapter, the interplay of some of the school-related factors and academic skill deficits as assessed on the NIMHANS INDEX for SLDs is examined. The data is mainly drawn from the work at the Child and Adolescent Mental Health unit at the National Institute of Mental Health and Neurosciences, Bangalore. In the face of the difficulties faced in the clinic in the assessment and the management of learning difficulties, a need was felt for an assessment battery for SLDs. This in turn formed the basis for developing strategies for remediation. This led to the development of the NIMHANS INDEX for SLDs (Kapur et al., 1991). The battery consisted of tests at Level-I for the assessment of pre-academic skills for children between five and seven years. At Level-I, the assessment of attention, visual, and auditory discrimination; visual and auditory memory; speech and language; visual– motor; and writing and number skills was carried out. At Level-II, for the children from classes one to seven, the assessment of attention, reading, spelling, perceptual–motor, visuo–motor integration, memory, and arithmetic skills was carried out. In addition, intelligence was assessed with the Indian modification of Weschler’s Intelligence Scale for Children (WISC) termed MISIC (Malin’s Intelligence Scale for Children) (Malin, 1971). The language assessment was based on the state level textbooks in English, Kannada, and Tamil

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for classes 1 to 7. These tests were not theoretically anchored but were assembled based on the empirical studies elsewhere and data obtained in the clinic and schools in Bangalore (Uma et al., 2002). John and Kapur (1986) in a study of children with average IQs compared 50 children from regular schools and 50 of those brought to the child guidance clinic with the complaints of scholastic backwardness on a battery of tests. The scholastically backward showed significant errors of distortion, rotation, and poor integration in copying designs of the Bender Gestalt test using Koppitz (1975) method of scoring. The scholastically backward also had significant deficits in reading, writing, and arithmetic on NIMHANS SLD INDEX. The profile of deficits was suggestive of a maturational lag. For example, on a visual inspection task, the profile of scores on the tests of a fifth grader was similar to that of a third grader. On the NIMHANS SLD INDEX, the performance of the normal children is expected to be class appropriate from nursery to seventh grades. It is expected to be two classes below in children with academic skill deficits. The approach to assessment is developmental, being age and class appropriate from 4 years to 12 years. Remediation based on the NIMHANS SLD INDEX has been found effective in the clinical setting and was evaluated in the school setting by Rozario and Kapur (1992), and Rozario et al. (1994). Based on the assessment package by John and Kapur (1986), Rozario (1992) developed a remediation package and evaluated it. The results indicated that in a sample of 25 children, in the age range of 9 to 11 years, significant improvement was found in reading, writing, spelling, comprehension, arithmetic, and visuo-spatial skills over 25 sessions. Attempts at providing norms to a limited extent has been made by Kapur and her co-workers (Uma et al., 2002). However, the detailed discussion of the development of the SLD battery and efficacy of intervention based on it is beyond the scope of the present chapter.

RELATIONSHIP OF TYPES OF SCHOOLS AND ACADEMIC SKILLS IN THE INDIAN CONTEXT The NIMHANS SLD INDEX was administered to children in different types of schools. These reports are qualitative and impressionistic

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Profiles of Academic Skill Deficits in Indian Schools

and aim at pointing to some of the trends that need to be further examined using rigorous methodology by other researchers. 1. Comparison of academic deficits in children of 5th standard from urban slum schools and middle socio-ecomic status (SES) schools. (Note: The SES of the children could not be assessed from the school records. The schools which receive partial government grants were considered as belonging to the middle SES and the slum schools were run wholly by government funding were considered as belonging to the low SES.) Table 7.1 Comparison of Academic Deficits in Children of Standard 5, from Urban Slum Schools and Middle SES Schools Schools

N

No Deficits

Language Deficits

Arithmetic Deficits

Slum Middle SES

54 35

15% 66%

65% 02%

17% 09%

Source: Based on data computed by the authors.

Table 7.1, demonstrates that the children in slum schools have comparatively more language deficits than children in middle SES schools. But the arithmetic deficits are not as poor in comparison but the fact remains that in both the groups, they were tested at 3rd standard levels, which was two years below the expected level of performance, as they were in class 5. This indicates that the performance of both the groups is below the expected level (S. Srinath, October 15, 2000, personal communication). Table 7.2 Academic Skills of Children from Classes 1 to 5 in a Single-teacher Rural School (N=26) Class Number Reading Compre- Writing (in %) hension (copying) (in %) (in %) I II III IV V

6 4 4 6 6

70 50 25 100 100

83 75 100 100 100

83 75 100 100 85

Source: Based on data computed by the authors.

Writing Spelling Dictation (in %) (in %) 83 100 100 83 85

83 50 100 83 100

Class Level 1 & less 1 & less 2 & less 3 & less 4 & less

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Table 7.2 shows the academic skill profile of 26 children from classes 1 to 5 in a single-teacher, rural school. The table indicates that all the children are far below the expected level in reading, comprehension, writing (copying and dictation), and spelling. As the number of pupils in each class was very small, the results on the NIMHANS SLD INDEX indicating performance at much lower class levels are reported only in terms of percentages. Subsequent to the remediation, most of the pupils improved dramatically indicating that the poor performance was the function of the deficient school system (Kapur and Uma, 2004). 2. Comparison of academic skills of children in schools followings state and central syllabuses. The following data (Tables 7.3a–c) aims at exploring the impact of the so-called good schools on academic skills. The results indicate some trends that need to be further validated with sound research methodology on much large samples. Some of the results are also qualitative and global being rated as “adequate” or “inadequate” due to very large individual variations in the performance of the pupils. Table 7.3a Comparison of Reading Skills among Children from Standards 1 and 2 of Central and State Schools (State N=13, Central N=17) Adequate (in %) State Central Reading 31 Reading 53 Comprehension

18 42

Has Difficulties (in %) State Central 31 38

64 35

Inadequate (in %) State Central 38 9

18 23

Source: Based on data computed by the authors.

The findings from a comparison between urban slum and rural schools and the findings from a comparison between schools following central and school syllabi showed marked differences. In the urban slum schools, the academic skills at the grade 5 level is much lower than in the rural schools. In schools following the central syllabus the performance at standards 2 and 3 was not up to the expectation.

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Profiles of Academic Skill Deficits in Indian Schools

Table 7.3b Comparison of Writing Skills among Children from Standards 1 and 2 of Schools Following the State and Central Syllabi (State N=16, Central N=10) Skills

Adequate (in %)

Copying Spelling 4 words Spelling 15 words

Inadequate (in %)

State

Central

State

Central

81 10 50

60 90 80

19 40 50

40 60 20

Source: Based on data computed by the authors. Table 7.3c Comparison of Arithmetic Skills among Children from Standard 2 of Schools Following State and Central Syllabi (State N=20, Central N=20) Skills Addition Subtraction Multiplication Division

Adequate (in %)

Inadequate (in %)

State

Central

State

Central

78 95 55 45

100 100 090 062

22 05 45 55

– – 10 38

Source: Based on data computed by the authors.

The first graders from schools following the central syllabus have more language difficulties than first graders from schools following the state syllabus. This raises the question whether the central syllabus is too hard for the first graders. The children from school following the central syllabus seem to be have better arithmetic skills. Further examination reveals that “division” is especially hard for the second graders in the central stream. The expectations appear to be too high, as the skills required are developmentally not appropriate according to age norms. The academic skills deficits across schools need to be examined carefully using sound research methodology on large samples across the country. The performance in rural schools is extremely inadequate and in the slum schools it is only marginally better. The deficits seem to be entirely due to poor school infrastructure in terms of teachers and resources. The contribution of poor family back-

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ground also needs to be examined. Even in the so-called middle class schools, there is a two-year lag from the expected level, which can be diagnosed as LD. Paradoxically, the good schools with the central syllabus appear to overburden the children while the state syllabus appears to be more appropriate for most children especially in the first and second grades.

PSYCHO–SOCIAL FACTORS AND SPECIFIC LEARNING DISABILITIES It is generally believed that rate of emotional and behavioral problems is higher among poor performers than normal achievers in schools. Some of the Indian studies have focused on psycho–social problems among children with SLD. The studies have focused on anxiety and self-esteem (Mukerjee et al., 1995), self-perception (Bhola et al., 1997), perceived peer relations, and social competence (Lall et al., 1997). These studies highlight the need to incorporate these psycho–social components in the management strategies. A test developed by Kapur (1995) that is, the Developmental Psychopathology Check List (DPCL), Kapur et al. (1994; 1995) provides a profile of co-morbid disorders in addition to LD, developmental history, temperament, family and peer interactions, stressors, and assets of the child. The above studies indicate that there is some association between LDs and psycho-social problems. This needs to be accommodated in building the intervention strategies. Learning disabilities do not occur independently of psycho–social factors. As the treatment cannot be carried out only through remedial work, a holistic approach to the intervention is indicated.

IMPRESSIONS These impressions need to be empirically validated through further research. 1. Poor school system has significant influence on the skill acquisitions amongst the children. The Academic Skill Deficit profiles may be the result of deficiencies in the school system.

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2. The central syllabus in India evidently over burdens the children. If the basic skills at the first grade level are not achieved by a majority of the children, they are likely to be more vulnerable for acquiring more deficits in higher classes. 3. The optimal level of academic inputs appears to be unavailable in most Indian schools being either too much or too little. 4. The diagnosis of SLDs thus has to be made with great caution especially in the developing countries. 5. The psycho–social factors too have a significant role to play and are not to be overlooked both in the assessment and in the management of academic skill deficits. 6. The intervention for SLD needs to adopt a developmental and holistic approach. To sum up, in the Indian setting, the assessment of SLD is a complex issue and needs to be examined in the context of the school system and psycho–social factors. The acquisition of academic skills is the function of the child’s potential, age, gender, school system and is mediated by psycho–social factors. The assessment and the management of academic skill deficits need to be developmental, eclectic, and holistic in perspective.

REFERENCES Bhola, P., U. Hirisave and M. Kapur. (1997). ‘Self Perception and Learning Environment in Children with Scholastic Skill Disorders’, in R. Hegde, S. Malhotra and L.P. Shah (eds), Research Endeavours in Child and Adolescent Psychiatry, Goa: R. Hegde. John, A. and M. Kapur. (1986). ‘Correlates of Scholastic Backwardness’, NIMHANS Journal, 4(1): 55–59. Kapur, M. (1995). Mental Health of Indian Children, New Delhi: Sage Publications. Kapur, M., A. John, J. Rozario and A. Oommen. (1991). NIMHANS Index of Learning of Disability Manual, Department of Clinical Psychology. Kapur, M., I.P. Barnabas, M.V. Reddy, J. Rozario and H. Uma. (1994). ‘Development of a Check List for Assessment of Childhood Psychopathology in the Indian Setting’, Indian Journal of Clinical Psychology, 2(1): 40–52. ——————. (1995). ‘Developmental Psychopathology Check List for Children (DPCL) (a preliminary report)’, NIMHANS Journal, 13(1): 1–9. Kapur. M. and H. Uma. (2004). ‘Promotion of Psychosocial Development of Rural School Children’, Unpublished Project report submitted to National Council

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of Rural Institutes, New Delhi and National Institute of Mental Health and Neurosciences, Bangalore, India. Karanth, P. and J. Rozario (eds). (2003). Learning Disabilities in India: Willing the Mind to Learn, New Delhi: Sage Publications. Koppitz, E.M. (1975). The Bender Gestalt Test for Young Children (Vol. 2). New York: Grune & Stratton. Lall, A., U. Hirisave, M. Kapur and D.K. Subbakrishna. (1997). ‘Perceived Peer Relations, Social Competence in Children with Specific Disorders of Scholastic Skills’, NIMHANS Journal, 15(2): 133–37. Malin, A.J. (1971). ‘Malin’s Intelligence Scale for Indian Children’, Indian Journal of Mental Retardation, 4(1): 15–25. Mukherjee. S., H. Uma, M. Kapur and D.K. Subbakrishna. (1995). ‘Anxiety, SelfEsteem with Specific Disorders of Scholastic Skills’, NIMHANS Journal, 13(2): 117–21. Rozario, J. (1992). ‘Intervention Strategies for Scholastic Backwardness’, Unpublished Doctoral Thesis. Bangalore: Bangalore University (NIMHANS). Rozario. J. and M. Kapur. (1992). ‘Interventional Strategies for Students with Problems in Learning Arithmetic’, Perspective in Education, 8: 205–10. Rozario, J., M. Kapur and S. Rao. (1994). ‘Effectiveness of Remedial Education in Children with Reading Disorder’, NIMHANS Journal, 12(2): 153–56. Uma, H., A. Oommen and M. Kapur. (2002). Psychological Assessment of Children in the Clinical Setting. Bangalore: NIMHANS. Wong, B.Y.L. (1996). The ABC’s of Learning Disabilities. San Diego: Academic Press.

8 Teacher Identification of Learning Problems Comparisons with Other Measures RAJANI M. KONANTAMBIGI AND MAMATHA SHETTY

INTRODUCTION

T

AND

REVIEW

OF

LITERATURE

his chapter is based on a study whose aim was to see how accurate our teachers are in perceiving the learning problems in children. The motivation for this study was the first author’s exploration into classroom interactions in the adjustment of first grade children to their class. In the course of this study, it was found that Indian teachers get a fairly good insight into the learning and problems of children. Their understanding of the learning problems of their students was obtained in the absence of information and formal assessment. The West, notably the US and the UK have a very specialized approach to the understanding of learning problems, which has been termed as “learning disabilities” (LDs). If India has to provide such services to its children, it translates into huge economic costs, which it can ill afford. Therefore we need to understand how much of children’s learning problems our teachers perceive and understand, and what actions they are able to pursue. This feedback would then be useful to determine what should be the training so that teachers get better equipped to deal with these issues. This chapter

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also addresses the issue of teachers’ assessment of children’s learning problems, and how well it matches a screening device for learning and behavioral problems and a standard measure for LDs. One of the issues concerning universal primary education in our country has to do with tackling dropout rates. Most research studies and reports talk of issues external to the child, or they are factors that have a direct impact on the child (Weiner, 1991; Lambay and Chavan, 1993; UNICEF, 1999). Some of the important factors identified that pertain to the school are the education system, the instructional skills of the teacher, the child’s socio-economic status (SES) and home related stimulation factors. Using the child’s SES as the broad base, attributions are made regarding the lack of motivation on the part of parents as well as the child (Konantambigi, 2000), or the social class to which they belong is blamed (Weiner, 1991). There is also a need to take cognizance of two issues in the process of attributions. One is variability in the children’s abilities for learning academic skills. The other is learning-outcomes, which depend upon the abilities and efforts of the child, and the quality or nature of teacher instructions and interactions. The education system from time to time does address the quality of instruction as and when formal and informal, in-service training is undertaken for teachers [DPEP’s efforts throughout the country, Lok Jumbish in Rajasthan (Jain, 2004), Nali Kali in Karnataka (Ramachadran, 2003), and expansion of the Joyful Learning in the state of Maharashtra, are some examples (UNICEF and Amravati Zilla Parishad, 1997)]. A cognizance of individual variation in learning rates has been shown in the Joyful Learning approach by adopting mainly learning through the play–way method and promoting students to the next class by providing extra attention or inputs to those who lag behind (UNICEF and Amravati Zilla Parishad, 1997). The West has faced these problems and continues to do so. Generally, in any given classroom, there are children who lag too far behind the grade expectations. In the 1950s and early 1960s, the developed countries, especially the US, began looking for the reasons and causes for children not being able to meet the grade expectations. Children with behavioral or emotional problems, children with mental retardation or other organic conditions could be identified. However, there were also groups of children who did

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183

not have any apparent organic conditions but they were found to lag behind in language or mathematical skills too far below expected from children for that particular grade. Such conditions began to be identified as “learning disability”. Investigations into the organic and learning processes revealed perceptual–motor, neurological processrelated language developmental lags, and so on, depending upon the theoretical orientation of the education specialists and the tests used. This has posed problems in arriving at a consensus about LDs, which influence the use of intervention strategies. Therefore, a look at the current definitions and intervention strategies is in order. This has important implications for pupils identified as learning disabled and the strategies one would like to adopt in intervening for learning disabled children. Perceptual deficit theory of LD was put forth by Bender and Frostig separately and Kephart (in 1971), and Gutman (in 1960) espoused the visual–motor perspective in LDs (Levine et al., 1993). These and other theories of the time (patterning/neurological organization by Delacato and the sensory integration model) were single deficit model theories of LDs (Levine et al., 1993). The perspectives on LDs that built on perceptual–motor deficits, language delay, and neurological process deficits (as individuals classified as learning disabled do have some deficits in learning some tasks) do not have unanimous results when they are put into practice to help the learning disabled (Bender, 1998). However, these perspectives are being grouped together under the “cognitive processing deficits” and in spite of setbacks, theorists in the field adhere to the view that it may re-emerge as a field. Behavioral theorists address specific difficulties in the mastery of the tasks, provide behavioral interventions, and have shown that these strategies work. Criticism here is that, such specific learning does not take care of problem-solving skills, academic problems, inefficient methods of problem solution, emotional distress that are outcomes of continued academic failure, and their interaction (Bender, 1998). The behavioral perspective has also been criticized because remedial teachers are implementing the strategies in behavioral intervention and the special educationists then have no role! One of the current perspectives to gain favor (there is empirical field support too) has been the meta-cognitive perspective

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(Graham and Wong, 1993). Some of the evidence has come from another country, Greece (Sideridis and Padeliadu, 2001). The metacognitive perspective encompasses thinking and planning about an educational/cognitive task, as well as motivational and self-concept issues associated with inactive learners. This strategy for intervention with the learning disabled, which emphasizes meta-cognitive skills, has been found to be paying dividends. In the US, this approach is being incorporated in the instructional approach, through workshops or training sessions. The meta-cognitive approach runs into problems because it encompasses a process approach and therefore is difficult to define. Constructivism and the multiple intelligences view of Howard Gardner (2000), which are alternate strategies for the normal classroom, are receiving some support under the constructivist approach to understanding learning, as the name suggests, the learner constructs meaning or make sense of the environment and learning, and this learning takes place in context, relates to the phenomenon and to the environment the child or the learner is in. Context-based learning is more effective, as it combines cognitive domains, aspects of the self and also focuses on the social and affective nature of learning. The emphasis of the multiple–intelligences viewpoint is that learning can take place through a different sense medium, other than the conventional academic learning through the purely cognitive approach. For instance, an insight into a lesson or history lesson could be through enacting it and not through reading for some children. The types of intelligence conceptualized by Gardner are logical mathematical intelligence, linguistic intelligence, bodily–kinesthetic intelligence, spatial–mechanical intelligence, musical intelligence, inter-personal intelligence, and intra-personal intelligence. The curriculum could give scope for different kinds of learners. Bloom had emphasized this aspect way back in 1976 when he put forth his theory of classroom instruction that has the children’s learning as a central issue. Effective learning takes place when learning experiences are designed with the intention of instilling mastery in the topic. A number of cognitive and affective entry behaviors, instructional practices, and environment in the classroom could be monitored to bring about mastery, according to Bloom. After two decades, like elsewhere in the Third World countries, American school education is fraught with severe limitations (Bloom, 1987).

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The various multi-dimensional approaches to the understanding of learning are reflected in certain conceptualizations of LD too. But these are arrived at empirically through cluster analysis, rather than resulting from theoretical premises. A lack of theoretical consistency is also reflected in the absence of an agreed upon definition of LD (Levine et al., 1993). However, together with considering the academic performance lag, deficits in certain areas of information possessing, ruling out mental retardation and brain damage, emotional disturbances, and slow learners, LD has been operationalized to provide a cut-off point and identify children for special education. This then tends to become a political issue on what is LD or special education and who gets the resources. This also gives rise to issues in basic and applied research in the field. The Individuals with Disabilities ACT 1990 (of USA) defines LDs as: The term children with specific learning disabilities’ means those children who have a disorder in one or more basic psychological processes in understanding language, spoken or written, in which the disorder may manifest itself in imperfect ability to listen, think, speak, read, write, spell, or do mathematical calculations. Such disorders include conditions like, perceptual handicaps, brain injury, minimal brain dysfunction, dyslexia and developmental aphasia. Such a term does not include children who have learning problems which are primarily the result of visual, hearing, or motor handicaps, of mental retardation, of emotional disturbance, or environmental, cultural, or economic disadvantage. (Zigmond, 1993, p. 254).

The developmental interactive model of Torgesen includes earlier models of LDs but is more holistic and multi-dimensional, goes beyond diagnostic labels, and is based on . . . rich clinical description and the rigorous study of the interactions among elemental functions and task production components that contribute to school-related tasks (Levine et al., 1993, p. 233, emphasis original). The school-related tasks have been analyzed into their requisite sub skills (production components), and have been mapped into the psychological processes (the elemental functions) and into how the production components are related to the underlying psychological processes. The relationship between elemental functions and a range of environmental and historical factors in generating critical production components and ultimately school-related outcomes. The latter aspect would take

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into account the fact that a person who is LD at one stage of development, will not be at another and will not remain so throughout life. The ecological component together with the psychological processes and dimensions will help identify specific disabilities and help remedial action which is more individual specific (Levine et al., 1993).

OVERVIEW

OF

DIFFERENT CONCEPTUALIZATIONS

OF

LDS

Exclusion Criteria 1. Low intelligence quotient (IQ) or Mental retardation 2. Slow learners 3. Minimal brain damage, perceptual deficit theory, neurological– decoding problems (arrived at by Bender and Frostig separately) 4. Intellectually average and above average

Inclusion Criteria 1. A number of deficit theories 2. Interactive developmental model (Torgesen) (i) holistic (ii) rich clinical description (iii) explains performance on school-related tasks (iv) at some age and not all through life 3. Cognitive perspective—through understanding nature of human intelligence, thinking, information processing, and attempt is made to identify information processing lags 4. Educational perspective, grade lag

OBJECTIONS

TO

LD AS

IT IS

UNDERSTOOD

1. Based solely on academic performance; 2. Generality of performance of LD and mentally retarded children;

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187

3. Area of deficit neither exclusive nor adequately understood; 4. Fails to take into consideration poor social skills and low selfesteem; and 5. Compounding of emotional and behavioral disorders and LDs (Rock et al., 1997). In the current perspectives on LDs and the strategies that yield better dividends, there are some lessons for our country. The strategies make more sense especially because we are a resource-starved country. If LDs in a pupil is largely because of a neurological processing deficit, the intervention would either be logically limited, or would necessitate huge costs in terms of specialized education. Developmental and ecological perspectives could be used in early detection and support. A developmental perspective would mean that focused attention is required at that particular stage. Multipronged individualistic interventions that would require a large amount of resources and would need special educationists to cater to millions of our children are definitely not viable options. If certain behavioral, ecological, and meta-cognitive approaches result in better dividends and reduce the school population at-risk for academic failure and dropout, it would go a long way in the education of children. Children with more complex learning problems, coupled with say, for example, Attention Deficit Hyperactivity Disorder or severe language delays could receive attention from special education cells. At present, in India, the LD problems are not adequately addressed because special education schools are few in number. Given the additional costs of special schools, mainstreaming is the answer. Moreover, labeling learning disabled children or children having learning problems impacts their self-efficacy beliefs and labels them for life. The labeling effects are severe and long term (Holt, 1972). In addition to the learning problem or LD tag, children belonging to the lower SES already carry enough burdens that affect their selfconfidence and self-esteem.

Rationale A small proportion (about 10 percent) of children are identified by teachers as having difficulty in learning or in coping with the bare

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minimum requirements of the class. In this context, a research study was planned to ascertain the terms and criteria teachers adopt to identify children as having learning problem or difficulty, and the strategies that they spontaneously employ to teach such children. This would help us understand the strategies used by teachers as well as additional inputs in training that is required by them. Therefore, another objective of this study was to closely observe a small group of teachers in interaction with children having learning problems. The open-ended observations were planned with a view that they would help delineate various strategies and nature of assistance extended by teachers to the pupil. In this chapter a teacher’s criteria for identifying learning problems in children, a teacher-use checklist which screens children with LDs, and how this compares with a diagnostic test of LDs are reported.

Methodology Sampling All school teachers in Mumbai could be the sample. However, constraints in terms of time and resources forced a choice of a sample. Teachers in municipal and private schools of Mumbai of both Marathi- and English-medium schools, and which were co-educational in nature, formed the major category of schools in existence. Among the private schools in the population, single sex schools were excluded to maintain parity with the municipal schools, which were all coeducational schools. Considering the constraints of resources, a sample of 12 teachers in class 4 of a north-western suburb school was chosen. A small sample was chosen because this study formed a part of a larger study that was qualitatively exploring whether teachers utilize various strategies in teaching children identified with learning problems. Class 4 was chosen because some municipal schools and a few non-aided (private) schools have classes only from classes 1 to 4. After class 4, children move on to middle school. In such schools, teachers in class 4 may make extra efforts to teach children to avoid retaining them in the same class (they may also grade them leniently). Certain developmental and adjustment-to-school delays are also taken care of, if a higher grade in primary class is chosen.

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The sample characteristics were as follows: 1. The schools selected were located in a suburb of Greater Mumbai (convenience sampling; had to visit the school a number of times; constraints in terms of resources). 2. Stratified Random sampling was done so that different types of schools were included in the sample. 3. Twelve schools were selected. These included three municipal, four private English-medium schools, one English-medium school partly funded by the state, and four private Marathimedium schools. 4. Ten children from grade 4 per school were selected—five with problems (teacher identified) and five without problems (randomly chosen from attendance register). Tools and Method Teachers were interviewed about the problems they faced in class and how they identified and what criteria they used to identify children who have learning difficulties or problems. The terms they used and the criteria used were noted. Teachers were asked to informally identify children who have learning and associated problems (like difficulty in focusing attention on tasks). Thereafter they were asked to rate all children identified as having learning problems and those without any problems on the screening device, the Behavioral Checklist for Screening the Learning Disabled (BCSLD) (Swarup and Mehta, 1991). This checklist was developed by Swarup and Mehta at the Special Education Centre, SNDT Women’s University, Juhu Campus, Mumbai. The Aston Index for screening for language difficulties has been adapted for use in the Indian context. The Diagnostic Test of Learning Disabilities (DTLD) (Swarup and Mehta, 1993) has been adapted for use in India, was used in the Special Education Centre (mentioned above), and was used in this study as well.

SUBTESTS

OF

SCREENING DEVICE

BCSLD 1. Visual processing 2. Auditory processing

AND THE

LD TEST

190 3. 4. 5. 6. 7.

Rajani M. Konantambigi and Mamatha Shetty

Motor co-ordination Cognitive domain Deficits in memory Perseveration tendencies Disorders in the affective domain

DTLD 01. Eye-hand co-ordination 02. Figure ground 03. Figure constancy 04. Position in space 05. Spatial relation 06. Auditory perception 07. Cognitive abilities 08. Memory 09. Receptive language 10. Expressive language Both English and Marathi schools in the sample meant that translation work was required, as the language structures are very different. It could be like doing two different studies. But without Marathi schools, the relevance of the study was limited (external validity issue). The Marathi version of the BCSLD was translated and was translated back to ensure conceptual equivalence, and efforts were made to keep translation errors to a minimum. The BCSLD has been standardized on a small sample of Mumbai teachers or schools. The DTLD ( Swarup and Mehta, 1993) has not been standardized and a Marathi version was not available. At present, there is no LD test in Marathi. The Maharashtra State Council for Learning Difficulties is currently using an information processing-based test, and the Aston Index is in use in the Institute for Psychological Health, Mumbai, and at the Manav Seva Sangh, Sion, Mumbai where LD diagnosis is in progress. This test was translated and then translated back to its original form to ensure equivalence in meaning. The person who administered the tests was oblivious of the teacher’s

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191

rating. The DTLD was administered in small group settings of 10 children each.

ANALYSIS OF DATA AND RESULTS The interview data was tabulated to ascertain the trends and variability in the teacher criteria for identifying problems in children and the problems they faced. The problems encountered have also been included, as they throw some light on teachers’ perception of children’s problems as well as the educational context. Interview data had not yielded very rich data. One of the reasons is that teachers are not generally able to or are not inclined (because of work pressure) to lengthy articulation of their teaching strategies or to abstractions (Konantambigi, 2000). This data has been presented in Tables 8.1 and 8.2. The tests administered were scored as per the directions in the respective manuals. The lower the scores on the BCSLD, the fewer problems the child has. Conversely, higher scores on the DTLD indicate fewer problems in the child (no LD). The person who administered and scored the DTLD was not aware of the teacher’s rating of the particular child, that is, if he or she was identified as having problems by the teacher, and was also unaware of the scores on the BCSLD. Correlations and T-tests were performed to determine the relationship of BCSLD and DTLD, and to know if the children who were identified by teachers having problems were so detected by both the devices. T-values were also computed to see if more boys than girls are identified as having LD. The results are presented in Tables 8.3, 8.4, and 8.5. The teachers were not able to explicate the criteria used in identifying the problems. When they were asked about these, they tended to describe the problems themselves, though of course these are not mutually exclusive. Further probing in this area is required. Teachers were fairly good at identifying children with problems, and more incisive probing would have facilitated comparison and correspondence between the criteria used by teachers and the standardized measures used. The criteria used for assessing children’s problems were few, and what is of significance is that both English and Marathi

1 3 3 – 3 2 4 4 1 1 1 2 1 1 –

• Distinguishing written and spoken Marathi • Accent, pronouncing • Non-clarity, grammatically not correct • Cannot describe pictures, limited use of words • General problem with English language Math—oral math is fine, written work is a problem Reading out of 40; 10 read still at the word level Restlessness in children Slow learners Stammering or lisping Inattentiveness, troubling other children Does not do homework often Low grasping power/no writing/no reading Four wheels essential for learning are lacking—Listening, speaking, reading, and writing Facial expressions

07. 08. 09. 10. 11. 12. 13. 14. 15. 16.

Source: Computed by the authors.

7 2 4 7 1

Alphabet reversals in Marathi Alphabet confusion, dh for gh, ke for ph, ee for Ha Similar sounding words and problems Specifics of form and no. problems or reversals, 20% of children wrote unclear form Tracing the letters or overwriting on the letters Quality of language

– – – 2 – 2 2 – – – – – – – 1

5 – 2 5 –

Schools N=12 Marathi N=7 English N=5 (frequency) (frequency)

01. 02. 03. 04. 05. 06.

Sr. Criteria No.

Table 8.1 Criteria for Identifying Problem Children

–

–

1 1

– –

1 1

– – –

2 2 1

English N=5 (frequency)

– – – – –

Schools

1 1 1 1 1

1 1 1

• Mugging up/stammering as they reproduce • Failing the grade, tag of lagged-behind child and related depression • Lack of follow-up in every day lessons

Emotional problems Child took tuitions from a person who had failed X standard public examinations Retarded children in the class (Municipal school) Lack of co-operation from parents (Municipal school problem) Lack of compliance to instructions like not bringing the required materials Physical learning and problems in vision and refer to doctor, doctor visits the school once a year There is no school counselor No time to make too many teaching aids or models for science teaching (The teacher had done a number of them) ‘Some of the techniques suggested in the books are tough, the old ones were better, or teacher innovations have been better’

4 4 –

Marathi N=7 (frequency)

Not speaking up when required, scared of teachers, scared of new teachers Not getting up from seat, some get up more often Vision Problem Repercussions of not learning

Source: Based on data computed by the authors.

13.

11. 12.

05. 06. 07. 08. 09. 10.

01. 02. 03. 04.

Sr. Problems Encountered No.

Table 8.2 Problems Encountered

56 51 55 51

BCSLD No problems Learning problems DTLD (Total) Learning Problems No problems

Note: **Significant at .01 level of significance. Source: Based on data computed by the authors.

N

Teacher’s Ratings for Learning Problems 33.36 17.84 43.13 53.37

Mean 15.59 15.82 14.61 15.83

Std. Deviation 2.08 2.21 1.97 2.22

Std. Error Mean

103.7666 101.539

–3.454

df 5.103

t

Table 8.3 Teacher Ratings of Learning Problems and Lack of Problems in Children, and Their Scores on the Screening Device and the LD Test

00

00

P**

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Teacher Identification of Learning Problems Table 8.4 Relationship between BCSLD and DTLD Test

Statistics

BCSLD X1 = V15 DTLD X2 =

26.29 47.56

Sd = 17.14 Sd = 114

N = 115 N = 114

Note: r = .492**One – tailed significant at .01 level of significance. Source: Based on data computed by the authors. Table 8.5 Learning Problems in Children by Sex Gender

N

Mean

Std. Deviation

Std. Error Mean

t

BCSLD Female Male V15 DTLD Male Female

49 63 49 62

24.02 28.48 47.02 47.47

16.65 17.54 17.76 14.81

2.38 2.21 2.54 1.88

–1.373 .142

Df

p

105.665 .173 93.128

.354

Source: Based on data computed by the authors.

medium teachers encountered similar problems. The case in point is that both the language mediums teachers reported alphabet and number reversals, illegible handwriting, and ill-formed letters as problems in children’s written work. Another significant finding is the close correspondence between teacher’s identification of children with problems and their scores on the DTLD. These findings highlight the importance of sharpening teachers’ observation skills, which would facilitate early and accurate identification of children’s problems. Studies elsewhere have also shown that it is possible for teachers to identify problems and that early identification pays (Hecht and Greenfield, 2001; Sharma cited in Nitasha and Sangwan, 1999; Al-Otaiba, 2001). The BCSLD has emerged as a fairly good predictor of LDs. Teachers have also been found to be good judges in detecting learning problems in children. Gender differences were not found to be significant. Further, the BCSLD and DTLD showed a moderate positive relationship (as indicated by the correlation coefficient), which is indicative of fair coherence as well as difference.

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Using a developmental interactive perspective, there is a need to study the relationship between the criteria used by teachers to identify children and the sub-scale items scores of both the BCSLD and the DTLD. In this study, a detailed list of each child’s problems as seen by the teacher was not obtained. A note of caution is in order as it was found that two teachers were random in their ratings of the child. Further, the DTLD may yield best results if administered individually. Both the tools were translated from English to Marathi. The Marathi translation was done adhering to the practices followed in translation. However, the DTLD translation needs a fresh translation as Marathi and English language structures are different. This awareness helped us to be alert to issues, but a more thorough scrutiny is in order. However, the merit of this study is that it has showcased the utility of these measures. It has also demonstrated that with some guidelines and intensive training, teachers can be a reliable source of information and can identify learning problems in children. Their observations were authentic. Most of the problems identified were in the area of dealing with everyday problems. The teachers also stated, “such problems are there, and we either send the children to a doctor or make a referral, or the problems persist as nothing can be done about them.” This was the predominant theme and reflected in the main attitude of the teachers. Interviews with the teachers were reviewed to elicit the criteria they used to identify children with learning problems. The tests administered were scored as per the directions in the respective manuals. The lower the scores on the BCSLD, the lesser problems the child has. Conversely, the higher the scores on the DTLD, the fewer the problems in the child (no LD). Correlations and t-tests were computed to determine the relationship of BCSLD and DTLD, and to know whether the children who were identified by teachers having problems were so detected by both the devices. t-tests were done to see if more boys than girls had LD. Although the cognitive and information processing aspects get reflected in the LD tests, and the screening devices focus on sensory and achievement on school related skills, the self and self-efficacy beliefs generally are not considered. Bandura and colleagues (1996)

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and Zera (2001) have proposed looking at the self-efficacy beliefs and its relation to learning. This brings forth the role of affect in education; the teacher’s role as a facilitator of learning through affect–being understanding, believing in the child as a person and her/his abilities and according due respect to child as a person. This could be the reason for varied perspectives and the effectiveness of various approaches. The limitations of cognitive approaches (Tonnessen, 1999; Swanson, 1993), the neuropsychological stance including the learner and the context (Goldstein and Obrzut, 2001; Moje, Dillon and O’Brien, 2000), the link between the visual deficits and dyslexia (Skotten and Parke, 1999) the premise of multiple intelligences (Gardner, 2000), and the constructivist approach [which considers the whole learner in context, (North Central Regional Educational Laboratory, May 2002) are some of the perspectives that are being examined, implemented in the classroom, and have been reported to increase learning outcomes for the students.

SCOPE

AND

LIMITATIONS

OF THE

STUDY

The study was carried out on a very small sample of schools. It was also carried out in a city that has been providing inputs to enhance teacher skills based on child-centered approach. This study may be considered as a beginning in assessing the competency of our teachers in dealing with children manifesting learning problems. A more exhaustive sampling design to include rural and tribal schools is required. Samples from areas where teacher training is limited need to be undertaken. The interviews with the teachers have not been exhaustive and therefore have yielded scanty data.

REFERENCES Al-Otaiba, S. (2001). ‘IRA Outstanding Dissertation Award for 2001: Children Who do not Respond to Early Literacy Instruction: A Longitudinal Study Across Kindergarten and First Grade’ [Abstract], Reading Research Quarterly, 36(4): 344–45. Ananthakrishnan, S. and P. Nalini. (2002). ‘School Absenteeism in Tamil Nadu’, Indian Pediatrics, 39: 847–50. (http://www.indianpediatrics.net/sep2002/sep-847850.htm)

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Anitha, B.K. (2005). ‘Quality and the Social Context of Rural School’, Contemporary Education Dialogue, 3(1): 28–60. Bandura, A., C. Barbaranelli, G.V. Caprara and C. Pastorelli. (1996). ‘Multi-faceted Impact of Self-efficacy Beliefs on Academic Functioning’, Child Development, 67: 1206–22. Bender, William. N. (1998). Learning Disabilities: Characteristics Identification and Teaching Strategies. Third Edition. Boston: Allyn and Bacon. Bloom, B.S. 1976. Human Characteristics and School Learning. New York, London, Sydney Toronto: McGraw Hill. Bloom, A, 1987. The Closing of the American Mind. New York: Simon and Schuster. Gardner, H. 2000. The Disciplined Mind: Beyond Facts and Standardized Tests, the K-12 Education That Every Child Deserves. New York: Penguin. Goldstein, Bram H. and John E. Obrzut. 2001. ‘Neuropsychological Treatment of Dyslexia in the Classroom Setting’, Journal of Learning Disabilities, 34: 276–85. Graham, Lorraine and Bernice Y.L. Wong. 1993. ‘Comparing Two Modes of Teaching a Question-Answering Strategy for Enhancing Reading Comprehension: Didactic and Self-instructional Training’, Journal of Learning Disabilities, 26(4): 270–79. Hecht, S.A. and D.B. Greenfield. 2001. ‘Comparing the Predictive Validity of First Grade Teacher Ratings and Reading Related Tests on Third Grade Levels of Reading Skills in Young Children Exposed to Poverty’, School Psychology Review, 30: 50–69. Holt, J. (1972). The Underachieving School. Harmondsworth: Penguin. Jain, R. (2004). ‘Lok Jumish: Alternative Models of Education’, Unpublished Research Study. Tata Institute of Social Science, Mumbai. Konantambigi, R.M. (2000). Home-School Transition: Adjustment and Performance of School Children. Tata Institute of Social Sciences, Mumbai. Lambay, F. and M. Chavan. (1993). Basic Education in Bombay: A Rapid Appraisal. Bombay: United Nation’s Children’s Fund, Maharashtra State Office. Levine, M.D., S. Hooper, J. Montgomery, M. Reed, A. Sandler, C.W. Swartz, and T. Watson. (1993). ‘Learning Disabilities: Towards an Interactive Developmental Paradigm’, in G.R. Lyon, D.B. Gray, J.F. Kavanaugh, and N.A. Krasnegor (eds), Better Understanding Learning Disabilities: New Views from Research and their Implications for Education and Public Policies, pp. 229–50. Baltimore: Paul Books Publishing Co. Moje, Elizabeth B., Deborah R. Dillon and David. O’Brien. 2000. ‘Reexamining Roles of Learner, Text, and Context in Secondary Literacy’, Journal of Educational Research, 93: 165–70. North Central Regional Educational Laboratory. (May 2002). ‘Constructivist Teaching and Learning Models.’ Available from http://www.ncerl.org/sdrs/areas/ issues/environment/drugfree/saconst.htm. Nitasha, S. and S. Sangwan. (1999). ‘Extent of Learning Disabilities and Related Factors.’ Disabilities and Impairments, 13(1&2): 105–10. Ramachandran, V. (ed.). (2003). Getting Children Back to School: Case Studies in Primary Education. New Delhi: Sage Publications.

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Rock, Dana, E, M.A. Fessler and P. Robin Church. (1997). ‘The Concomitance of Learning Disabilities and Emotional Behavioural Disorders: A Conceptual Model’, Journal of Learning Disabilities, 30: 245–63. Sideridis, Georgios D. and Susana Padeliadu. (2001). ‘The Motivational Determinants of Students at Risk of Having Reading Difficulties’, Remedial & Special Education, 2: 268–79. Skotten, Brent C. and A. Parke Lesley. (1999). ‘The Possible Relationship between Visual Deficits and Dyslexia: Examination of a Critical Assumption’, Journal of Learning Disabilities, 32: 2–5. Swanson Lee, S. (1993). ‘Learning Disabilities from the Perspective of Cognitive Psychology’, in G.R. Lyon, D.B. Gray, J.F. Kavanaugh and N.A. Krasnegar (eds), Better Understanding Learning Disabilities: New Views from Research and Their Implications for Education and Public Policies, pp. 199–228. Baltimore: Paul Brooks Publishing Co. Swarup, Smriti and Dharmishta H. Mehta. 1991. Behavioural Screening Device for Learning Disabilities. Mumbai: Department of Special Education, SNDT Women’s University, Juhu Campus, Mumbai. ——————. 1993. Diagnostic Test of Learning Disabilities. Mumbai: Department of Special Education, SNDT Women’s University, Juhu Campus, Mumbai. Tonnessen Finn, E. 1999. ‘Options and Limitations of the Cognitive Psychological Approach to the Treatment of Dyslexia’, Journal of Learning Disabilities, 32: 386–93. UNICEF. (1999). The State of the World’s Children: Education. New York: UNICEF. UNICEF and Amravati Zilla Parishad, Primary Education Division, Maharashtra. (1997). Ananddayee Prakalap (Amravati): Amravati zillyatil Ananddayee Prathamik Shikshan. Mumbai: Authors. Weiner, M. (1991). The State and the Child in India. Delhi: Oxford University Press. World Bank. (1997). Primary Education in India. Washington, DC: World Bank. Zera, D.A. (2001). A Reconceptualization of Learning Disabilities via a Selforganizing Systems Paradigm. Journal of Learning Disabilities, 34: 79–94. Zigmond Naomi. (1993). ‘Learning Disabilities from an Educational Perspective, in G.R. Lyon, D.B. Gray., J.F. Kavanaugh and N.A. Krasnegor (eds), Better Understanding Learning Disabilities: New Views from Research and their Implications or Education and Public Policies, pp. 251–72. Baltimore: Paul Brooks Publishing Co.

9 Teachers’ Perception of Learning-related Problems in School-going Children A Preliminary Report NISHI TRIPATHI AND BHOOMIKA R. KAR

A

ll children learn in highly individual ways. Despite having average or above average intelligence, some children perform poorly in academics. Such children are generally described as, slow learners, dyslexics, learning disabled, dyslexics, and so on. Children with learning disabilities (LDs) simply process information differently, but they are generally of normal or above average intelligence. Having LDs can affect a child’s ability to read, write, speak, do math, and build social relationships (CCLD, 2003). Defining LDs in operational terms has been difficult. The early definitions emphasized the medical framework in terms of minimal brain damage, gradually shifting to the educational framework focusing on visuomotor processing and discrepancy between scholastic ability and IQ (John et al., 2002). Debates about definition and identification of LDs arise from a range of factors causing it which could range from biological factors such as soft neurological signs, lack of asymmetry in temporal and frontal lobes to environmental factors like poverty, illiteracy, lack of access to pre-school instruction, medium of instruction, and over crowded classes (particularly relevant in Indian context). Kirk (1963) coined the term “learning disability” and under his leadership, the National Advisory Committee on Handicapped

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Children submitted its first definition. Since then, a number of definitions have been produced but none of them was totally acceptable. The federal government (USA) defined LD learning in Public Law 94–142 (Education for All Handicapped Children Act, 1975) as follows: Specific learning disability means a disorder in one or more of the basic psychological processes involved in understanding or in using language, spoken or written, which may manifest itself in an imperfect ability to listen, think, speak, read, write, spell, or to do mathematical calculations. The term includes such conditions as perceptual handicaps, brain injury, minimal brain dysfunction, dyslexia, and developmental aphasia. The term does not include children who have learning problems, which are primarily the result of visual, hearing, or motor handicaps, of mental retardation of emotional disturbance, or of environmental, cultural or economical disadvantage.

The DSM-IV of American Psychiatric Association (1994) defines LDs as follows: Learning disorders are diagnosed when the individual’s achievement on individually administered, standardized tests in reading, mathematics or written expression is substantially below that expected for age, schooling and level of intelligence. The learning problems significantly interfere with academic achievement or activities of daily living.

In other words, LDs is a general term that refers to a heterogeneous group of disorders manifested by significant difficulties in the acquisition and use of listening, speaking, reading, writing or mathematical abilities. These disorders are intrinsic to the individual, presumed to be due to dysfunction of the central nervous system and may occur across the life span. Problems in self-regulatory behavior, social perceptions, and social interactions may exist with LDs, but they do not by themselves constitute LDs (Wong, 1996).

EPIDEMIOLOGICAL DATA ON LDS The first step in solving any problem is realizing that there is one. LDs are often not easily recognized, accepted, or considered serious once detected. LDs affect one in seven people according to the National Institute of Health, USA. It is believed that in the US,

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1–5 percent children in a classroom are learning disabled and up to 10 percent are mildly disabled (Karanth, 2003). Epidemiological studies of LDs in India are fraught with difficulties ranging from the very definition of LDs, identification, assessment, to socio-cultural factors unique to India. In India, LDs are compounded by factors like parental illiteracy and lack of exposure to literacy-related skills in the home environment (Suresh and Sebastian, 2003). Learning Disabilities that are reported in Western countries are common in India as well but the context differs. In India, LDs have been the focus of attention only during the last decade. As a consequence, there have been hardly any epidemiological studies of LDs in India though there has been an increase in the identification of children with LDs and a subsequent demand for services. In India, specific learning disability (SLD) is observed in 7–8 percent of the general population the age range of 0–18 years (Suresh and Sebastian, 2003). Not only is there a dependence on Western literature for an understanding of LDs but also practices of assessment and remediation show this influence. The most common LDs are difficulty with language and reading. A recent National Institute of Health study showed that 67 percent of young students identified as being at-risk for reading difficulties were able to achieve average or above average reading ability when they received help early (CCLD, 2003). Being aware of the warning signs and ensuring that children get the earliest possible help will increase the chance of meeting this goal, and will greatly improve the chances of those with LDs for greater academic achievement and self-esteem. Many children and adults with LDs remain undiagnosed and go through life with this “hidden handicap”. The resulting problems can lead to poor self-esteem, failure to thrive in school, and difficulty in the workplace. With early detection and intervention, parents can give their children the necessary skills for coping with and compensating for the LDs, an opportunity that was denied to many of today’s adults. Although LDs may occur concomitantly with other handicapping conditions (for example, sensory impairment, mental retardation, serious emotional disturbance), or with extrinsic influences (such as cultural differences, insufficient or inappropriate instruction), they are not the results of those conditions or influences (National

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Conference on Learning Disabilities, 1988). About 5 percent of the school-aged population has been classified as learning disabled; about 28 percent to 64 percent of the students receiving special education in recent years were identified as learning disabled (Ysseldyke and Algozzine, 1990). Recent estimates suggest that at least 30 percent of the learning-disabled children also have Attention-Deficit Hyperactivity Disorder (ADHD) (Lambert and Sandoval, 1980; Safer and Allen, 1976). In the context of the complexities associated with the definition and identification of LDs, there is some evidence with respect to the characteristics of SLD that aids in further understanding the nature of LDs and the basis for identification of children with LDs.

CHARACTERISTICS

OF

LDS

The characteristics of LDs are as follows (John et al., 2002): 1. Discrepancy factor: A discrepancy exists between a child’s ability and academic performance across one or more skill areas. 2. Academic learning difficulty: Academic problems exist in the area of reading, writing, spelling, and mathematics. 3. Perceptual disorder: These include inability to recognize, discriminate, and interpret sensation. It can be the area of auditory channel or/and visual channel. 4. Meta-cognitive deficits: Meta-cognitive abilities involve the ability to use self-regulatory mechanisms such as planning moves, evaluating effectiveness of ongoing activities, checking the outcome, and remediating the errors. 5. Memory problems: Most students complain of poor memory. The learning-disabled students fail to use strategies that nondisabled students readily use. In addition, LD students may have difficulty because of their poor language skills. 6. Motor disorders: Children with this problem are clumsy, unable to skip or hop. Some exhibit fine motor difficulties such as in cutting with scissors. 7. Attention problems and hyperactivity: Many researchers have documented that many LD children have short attention

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span, distractibility, and impulsivity. Some are restless and hyperactive. 8. Social emotional problems: The prevalence rate of psychological disturbance is high among the learning-disabled children as compared to the normal children. A continuous failure in academics results in poor self-concept and self-esteem. Children with LDs have both academic and non-academic difficulties as is evident from the list of characteristics. Hence, the identification of LDs should aim at a comprehensive assessment of both academic difficulties, that is, reading, spelling, writing, and mathematics as well as non-academic difficulties, that is, visuomotor problems, perceptual visual/auditory discrimination, figure/ground discrimination, memory, phonological processing difficulties, and language problems (Karanth, 2003).

Teachers’ Perception of Classroom Behavior of Children with LDs By and large, the results of classroom observation studies indicate that compared with normal-achieving classmates, the off-task behavior is more frequent in children with LDs and they are less likely to interact with teachers (Feagans and Mc Kinney, 1981; Mc Kinney and Specce, 1983). Mc Kinney and Feagans (1984) classified students into subtypes on the basis of teacher ratings, measures of intelligence, and achievement on the basis of teachers rating of first and second grade students: 1. Task independent behavioral deficits, socially well adjusted, with average verbal skills but poor scholastic achievement. Deficits in behavior, uneven cognitive abilities, and severely deficient in achievement. 2. Deficits in task orientation, high on extroversion and hostility, and average cognitive ability but mildly deficient in achievement. 3. No behavioral problems and deficient only in academic achievement.

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These findings suggest that the scholastic problems are many and complex. Each student is unique. One differs from another intellectually, emotionally, socially, and physically. Some students, however, deviate so greatly from normal limits that the regular classroom teaching is inadequate. These students may have difficulties in one or several of the academic areas, such as reading, arithmetic, spelling and writing, or may have poor study habits. A few, besides academic problems also exhibit emotional or conduct problems. Educational factors such as crowded classrooms, inadequate and inappropriate teaching can also give rise to learning difficulties, but they are not called LDs since the context seems to elicit LDs. The causes related to context may also be found in the family of the child, such as family disintegration; poverty, social class discrimination; and other negative social and cultural factors can give rise to LDs. Since, LDs is a heterogeneous group of difficulties related to reading, writing, language, mathematics, and behavior, each of these disabilities has specific characteristics, which need to be assessed while identifying children with LDs. A range of tests with respect to the strengths and deficits of the child in academic skills is required not only for identifying children with LDs and specific deficits but would also have implications for remediation.

Difficulties in Writing The majority of students who receive services for LDs have severe writing problems that persist over time (Graham and Harris, 1989, 1990). Writing-related problems include errors in spelling, punctuation, capitalization, and handwriting. It is believed that at least three factors may account for students’ difficulties in writing (Graham and Harris, 1990). First, their problems in producing text may interfere with other important writing processes, such as generating ideas. Second, their lack of knowledge about writing or their ability to access what they do know may impact on their ability to operate and deploy the cognitive process considered central to effective writing. Third, the cognitive moves or writing strategies employed by LD children may be immature or ineffective. This also calls for an evaluation of the cognitive profile of children with SLD.

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Difficulties in Reading The essential feature of reading disorder is reading achievement (that is, reading accuracy, speed, or comprehension as measured by individually administered standardized tests) that falls substantially below the expected level given the individual’s chronological age, measured intelligence, and age-appropriate education. Individuals who have SLD in reading have difficulties decoding or recognizing words (that is, letter/sound omission, insertions, substitutions, reversals), or comprehending them (that is, recalling or discerning basic facts, main ideas, sequence, or themes). They may also display other difficulties such as losing their places while reading or reading in a choppy manner (Torgesen and Wagner, 1998).

Difficulties in Mathematics Poor mathematics achievement may be due to a variety of reasons. Difficulties in abstract thinking, language, reading, motivation, and memory can impede the ability to learn mathematical skills and concepts (Hammill and Bartel, 1986; Bley and Thornton, 1989). Teachers at the secondary level indicated that children with LDs require instruction with skills (for example, fractions, decimals) associated with fourth and fifth grade mathematics curriculum (Mc Leod and Armstrong, 1982). Secondary level children with LDs have difficulties due to the vocabulary used in mathematics instructions (for example, binomial) and the reading level of the material (Woodward and Peters, 1983). Ineffective instruction also has been identified as a factor that interferes with successful mathematical learning.

LDs in the Early Years The study of LDs from a developmental perspective holds promise for new insights and proved practices. The developmental life-span approach is pertinent to our concerns for LDs as it is increasingly clear that LDs may not be limited to a particular age group or to a

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setting. Recognition of the importance of early identification and intervention with young LD children has resulted in the implementation of numerous screening, diagnostic, and intervention programs and the publications of a plethora of early-identification tests and procedures (Mastropieri, 1988). Applying a developmental framework to LDs raises some interesting but troublesome questions. What is the level of awareness of teachers regarding LDs? What is the diagnostic significance of particular behavioral signs or “symptoms” in the early years? Do teachers have the knowledge and understanding of these signs and are they sensitive to these early indicators? Do teachers with overcrowded classrooms have the time to pay attention to the individual child? How valid are the early indicators for predicting subsequent problems? In India, very few epidemiological studies have been conducted. In cities like Allahabad which lack organized services for conditions like LDs, many schoolteachers are unaware of these problems. To answer the questions raised above, there is a need to reach out to the school system and address the issue of identifying children with LDs. Initial screening of children with LDs could be possible based on teachers’ classroom observations and evaluation. Teachers’ perception of LDs can further lead to a thorough formal assessment of specific LDs, and assessment of cognitive processes, such as attention, visuo-spatial ability, and fine motor skills. Hence, the present chapter is the first step towards identification of children with LDs in school settings. The present chapter has focused on teachers’ perception of LDs of their students in the areas of reading, writing, mathematics, and oral language that can further be utilized for a formal assessment of LDs (Figure 9.1).

THE PRESENT STUDY The present chapter is based on a study which is a part of the first phase of the ongoing project on “teachers’ perception and identification of children with LDs in school settings in Allahabad city”. The present study aimed to explore teachers’ perception of learning-related problems in school children from classes 2–8.

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Nishi Tripathi and Bhoomika R. Kar Figure 9.1 Plan of the Project on LDs Project on teachers’ perception and identification of children with LDs in school settings in Allahabad city

Phase 1 Teachers’ perception of learningrelated problems in children (Classes 2–8.)

Part 1 Teachers’ perception of the prevalence of problems related to language, reading writing, mathematics & behaviour

Phase 2 Identification of children with LD on the basis of formal assessment

Part 2 Teachers’ perception of the prevalence and intensity of the learning-related problems with reference to the specific children identified by the teachers

The present study Source: Computed by the authors.

Aim and Objectives 1. To construct a “Problem Checklist-Teacher Report Form A” on learning-related problems of language, reading, writing, mathematics, and behavior. 2. To construct a “Problem Checklist-Teacher Report Form B” on learning-related problems of language, reading, writing, mathematics, and behavior with reference to the specific children identified by the teachers. 3. To assess teachers’ perception of learning-related problems in children from classes 2–8 with respect to each class and further with respect to each child reported with LDs using the problem checklist Form A.

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Participants The sample consisted of 102 teachers teaching English language and Mathematics from classes 2 to 8. Four schools were randomly selected from different areas in Allahabad. These schools were me dium-level schools having children from all socio-economic strata. Two English-medium schools were included in the pilot phase. Table 9.1 presents demographic information about the respondents. The findings indicate that the most of the teachers teaching English language and Mathematics were in the age range of 36–39 years. Most of the teachers were females (91.2 percent) and most of them were postgraduates (61.2 percent). On an average, the teachers had long years of teaching experience (9–10 years). Table 9.1 Demographic Data-Sample Distribution Demographic Characteristics

English N=51

Age (Years)

26–62 M=36.3 F=48 M=3 G=17 PG=34 1–28 M=9.1

Gender Education Teaching Experience (Years)

Mathematics N=51 26–60 M=39.3 F=45 M=6 G=22 PG=29 2–32 M=10.2

Source: Computed by the authors.

Tools Problem Checklist RATIONALE

Problem checklists forms A and B were developed by the investigators on the basis of the existing literature. The checklist was developed to ensure the appropriateness of the tool with respect to the feasibility and suitability to the educational and socio-cultural context. Form A was developed to assess the teachers’ perception of problems related to reading, writing, mathematics, and behavior.

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Form B was developed to assess the prevalence and intensity of learning-related problems of children identified by the teachers. Two separate forms for English Language (45 items) and Mathematics (20 items) were developed. First, a dichotomous response Yes/No was taken. If the answer was “yes” then rating was done on a 3-point scale to assess the intensity of each of the specific problems with reference to the particular child. Both forms A and B also elicit demographic details about child’s age, gender, date of birth, mother tongue, father’s and mother’s education and occupation, previous school record, and attendance. Form B was used only in the second part of the first phase. Form A was used in the first part of the first phase that is to assess the teachers’ perception of the prevalence of learning-related problems from classes 2–8. Problem Checklist–Teacher Report Form A Two separate forms for English Language and Mathematics were developed to assess teacher’s perception of learning-related problems of language, reading, writing, behavior (25 items), and mathematics (12 items), respectively with respect to the class in which he/she is teaching. Each form consists of demographic details about the school, class, and teacher. All responses were dichotomous in nature and open-ended questions were framed to obtain information about the causes of LDs.

PROCEDURE The schools were selected randomly from Allahabad city. The schools selected were medium-level schools, which have children from all socio-economic strata. All the schools selected were English-medium schools. Five schools were approached but permission could be obtained from four schools only. Out of these four schools, two schools were co-educational. The other two schools had separate wings for girls and boys. After taking permission and the written consent of the Principal, the individual teachers teaching English language and Mathematics from classes 2 to 8 were included in the sample using the purposive sampling method. Teachers teaching English language

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were also the class teachers. This ensured that they had close contact and knowledge of their students and hence enhanced the reliability of the information provided by them. Separate problem checklists were developed for English language and Mathematics as the subjects were taught by separate teachers. The Problem Checklist Form A was administered to teachers teaching English language and Mathematics from classes 2 to 8. Subsequently, Form B was administered to the same teachers to collect specific information about LDs and associated behavioral problems with reference to the particular child identified. The data collected from Form B has not yet been analyzed and the results presented below are based on the analysis of data from Form A.

RESULTS

AND

DISCUSSION

Data was analyzed with respect to the following research questions: 1. Teachers’ perception of the prevalence of difficulties related to language, reading, writing, and mathematics from classes 2 to 8. 2. Teachers’ perception of the prevalence of difficulties related to behavior from classes 2 to 8. 3. Identification of children with LDs by the teachers from classes 2 to 8. The results are presented with reference to each of the research questions. 1. Teachers’ perception of the prevalence of difficulties related to language, reading, writing, and mathematics across classes 2–8 (Figure 9.2). The results presented in Figure 9.2(a) indicate the frequency of language related problems. As this figure shows, problems related to language are found across all classes. It is lesser in classes 4–5 and highest in class 3. English, being the second language could be the reason for this consistent high prevalence of problems related to language. Language acquisition is largely determined by the type of orthography and its relationship with the phonology of the

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Nishi Tripathi and Bhoomika R. Kar Figure 9.2 Frequency Distribution of Language, Writing, Reading and Mathematics-related Problems from Classes 2 to 8 as Perceived by the Teachers

Source: Based on data computed by the authors.

language. It is presumed that if there is a consistent relationship between phonology and orthography, such as in Indian languages, language acquisition may be simpler. On the contrary, where the relationship between the sound and spelling is inconsistent, as in English, the child has difficulty in understanding and internalizing

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the orthographic principle. Such difficulties related to second language acquisition extend to further difficulties in learning to read. However, this can be understood from a different angle also. When children learn to read and write they would have already mastered the language. So, it is natural for them to relate written symbols and language structure they have mastered (Prakash, 2003). It is also reported that phonemic awareness is not so crucial in learning to read Indian languages, such as Hindi, Kannada, and Oriya (Karanth and Prakash, 1996). Such reports explain the dependence on phonological strategy used for learning English language. Results presented in Figure 9.2(b) indicate high prevalence rates of problems related to writing across all classes. Writing is a tool for communication and is both a skill and means of expression. Results also indicate specific problems in writing, such as poor handwriting, problems related to spelling and sentence structure, problems in using prepositions, letter reversals, and inability to write on the line. The complex process of writing integrates visual–motor and conceptual abilities, and it is a major means through which students demonstrate their knowledge in academic subjects, classroom. After the third grade, emphasis is placed on writing as a form of meaningful self-expression. Mercer and Mercer (1985) also list the following common errors among LD children—slowness, incorrect directionality of letters like too much or too little slant, spacing difficulty, messiness, inability to write on a horizontal line, illegible letters, too much or too little pencil pressure or mirror writing. Such problems are consistent with the findings of the present study. The high prevalence of writing-related problems to writing can also be explained in terms of close supervision and emphasis on writing skills in the school curriculum. Results presented in Figure 9.2(c) indicate that reading-related problems were found to be highly prevalent in lower classes more so from classes 2 to 5 and then decrease from classes 6 to 8. Specific problems in reading, such as letter and sound omissions, substitutions, reversals, difficulty in reading fluently, and reading the same line again and again was observed. High prevalence of reading difficulties in the lower classes indicates the difficulties associated with learning to read and second language acquisition. Such difficulties in reading the English language can be attributed to the aspect of high

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reliance on phonological awareness required in reading acquisition. Mercer and Mercer (1985) reported that from 10 to 15 percent of the general school population experience difficulty in reading. The reason behind this could be the home environment, slow development in verbal skills, speech defects, and motor skills. Figure 9.2(d) indicates a decrease in mathematics related difficulties across grades, which seems to be a natural improvement in mathematical skills with advancement in age and grade. Problems related to mathematics were not perceived to be significantly present overall in each class across all the classes as reported by the teachers. There could be specific and subtle difficulties that would be evident in the second phase of the present study aiming at the learning difficulties reported with reference to the particular children identified. Highest prevalence rates for all the learning-related problems such as writing, language, mathematics, and behavior in class 3 alone can be explained as an artifact in terms of respondent’s error. 2. Teachers’ perception of the prevalence of difficulties related to behavior from classes 2 to 8 (Figure 9.3). Figure 9.3 Frequency Distribution of Behavioral Problems in Children from Classes 2 to 8 as Perceived by the Teachers Behavioral Problems

Source: Based on data computed by the authors.

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215

Figure 9.3 indicates that high prevalence rates of behavioral problems were found in lower classes (classes 2–4) and in a decreasing order in upper classes. It is generally found that prevalence rate of behavioral and emotional problems are higher among the poor performers than the average students. Results of the present study also indicate higher prevalence rates of behavioral problems in students who had more learning-related problems (Figure 9.4). Hyperactivity and restlessness were the most commonly reported behavioral problems in the lower classes. Yet, such behavioral problems should not be taken as a confounding effect of the learning difficulties observed as reading and writing-related problems reported were more specific in terms of problems related to reading acquisition, phoneme to grapheme correspondence, and problems related to orthography and composition. Figure 9.4 depicts an overall comparative evaluation of learningrelated problems and indicates high prevalence rates of language and writing-related problems. Problems related to behavior seem to show a pattern of progressive decrease in higher classes, that is, after class 5, whereas, high frequency of behavioral problems were reported in lower classes from classes 2 to 4 which could be a reflection of Figure 9.4 Frequency Distribution of Comparative Evaluation of Learningrelated Problems from Classes 2 to 8 as Perceived by the Teachers

Source: Based on data computed by the authors.

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normal developmental process. This high prevalence of language and writing-related problems could be interrelated. Problems related to language pertain to the difficulties in second language acquisition, phonological awareness particularly with respect to English language. Such difficulties in language acquisition and dependence on phonological awareness relates to the problems observed in reading. Difficulties in learning to read relate to problems in writing. Hammill and McNutt (1981) observed that writing skills are among the best correlates of reading. According to them, writing skills include competence in writing, punctuation, spelling, capitalization, and distinguishing one letter from another. These aspects of writing skills are related to the processes through which the child learns to read. 3. Identification of children with learning difficulties by the teachers across classes 2–8 (Table 9.2). The results presented in Table 9.2 indicate that the percentage of children with learning-related problems as identified by the teachers, decreases from classes 2 to 3 and remains constant through classes 4 to 7 and decreases sharply in class 8. This identification made by the teachers is based on their overall perception of learning difficulties and behavioral problems. Hence, it would be difficult to comment on what basis these children have been identified, whether Table 9.2 Identification of Children with Learning-related Problems from Classes 2 to 8 for Reading and Writing (English) as Reported by Teachers Classes II Total No. of Children 312 Children Identified (%) 8.3 Children Recommended For 2.8 Counseling & Remediation (%)

III

IV

V

VI

VII

VIII

287 5.9 2.4

328 4.8 3.3

407 4.6 2.9

508 4.5 2.7

491 4.2 4.2

496 2.0 1.2

Source: Based on data computed by the authors.

Teacher’s Perception of Learning-related Problems

217

it is based on the perception of problems in reading or writing or mathematics or behavior. There was also a discrepancy in percentage of children identified as having learning-related problems and children recommended for counseling and remediation across classes 2 to 8 for English language as reported by teachers. This discrepancy could be due to the teachers’ perception of the need for counseling only for those who also had behavioral problems and the belief that learning-related problems will improve with age. Such findings indicate the need for a formal assessment of the children identified on a measure of LDs to determine the nature and extent of specific learning-related problems and for proper guidance to the teachers, parents, and children with learning-related problems. The problem checklists developed by the authors, to assess the teachers’ perception of learning-related problems in reading, writing, and mathematics across classes 2 to 8, have emerged as a useful instrument for the first level screening of children with learningrelated problems in terms of the characteristics of LDs. The checklists have provided an insight into the prevalence and nature of problems related to language, reading, writing, mathematics, and behaviorial problems. The data obtained on these checklists will be further validated once the children identified are assessed on a formal assessment of LDs.

CONCLUSIONS The present study is the first step towards identifying children with LDs in school settings in Allahabad. It has provided with the first level screening to further conduct formal assessments of LDs on children identified by teachers using appropriate tools. The teachers’ report has indicated high prevalence of language related problems particularly in expression and grammar was perceived across all classes. Writing-related problems were perceived as most prevalent across all classes. Problems related to reading were observed to be higher in lower classes and gradually decreased across the higher classes. Problems related to mathematics and behavior showed a decreasing trend across classes 2 to 8. Identification of children with

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learning-related problems by teachers appeared to be based on poor achievement and behaviorial problems. The present chapter is based on the first part of the first phase of the ongoing project on LDs. The second part of the first phase aimed to examine learning-related problems in reading, writing, mathematics, and behavior with reference to each of the specific children identified from classes 2 to 8 by the teachers in the previous study. The first phase would therefore give a lead to the second phase on formal assessment to identify children with LDs in school settings. Figure 9.5 Implications and Directions for Future Research

The Present Study

Teachers’ report on the prevalence of learning-related problems in children

Awareness Programs (Conceptual understanding of LDs)

Detailed formal assessment of specific LDs and cognitive processes on children perceived as having learning-related problems by teachers

Individualized remediation program for children with LDs

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219

REFERENCES American Psychiatric Association. (1994). Diagnostic and Statistical Manual of Mental Disorders. Washington, DC: American Psychiatric Association. Bley, N.S. and C.A. Thornton. (1989). Teaching Mathematics to the Learning Disabled. Texas: Pro-Ed. Austin. Coordinated Campaign for Learning Disabilities (CCLD). (2003). LD-in Depth: Early Warning Signs of Learning Disabilities. Available from http://www.ldonline. org. (accessed on) Education for All Handicapped Children Act. (1975). US Federal Public Law No. 94–142. S.6, 94th Congress, 1st session, Report no. 94–168. Feagans, L. and J.D. Mc Kinney. (1981). ‘The Patterns of Exceptionality across Domains in Learning Disabled Children’, Journal of Applied Developmental Psychology, 1: 313–28. Graham, S. and K.R. Harris. (1989). ‘Cognitive Training: Implications for Written Language’, in J. Hughes and R. Hall (eds), Cognitive Behavioural Psychology in the Schools: A Comprehensive Handbook, pp. 247–79. New York: Guilford Publishing Co. ——————. (1990). ‘Cognitive Strategy Instruction in Written Language for learning disabled Students’, Unpublished manuscript. Hammill, D.D. and N.R. Bartel. (1986). Teaching Students with Learning Disabilities. Colombus: Merrill Publishing Company. Hammill, D.D. and G. McNutt. (1981). Correlates of Reading: The Consensus of Thirty Years of Correlational Research. Austin TX: Pro-Ed. John, A., J. Rozario, A. Oommen and H. Uma. (2002). ‘Assessment of Specific Learning Disabilities’, in U. Hirisave, A. Oommen and M. Kapur (eds), Psychological Assessment of Children in the Clinical Setting, pp. 75–140. Bangalore: National Institute of Mental Health and Neurosciences. Karanth, P. and P. Prakash. (1996). ‘A Developmental Investigation of Onset, Progress and Stages of Literacy Acquisition—Its Implications for Instructional Process’, Unpublished project report, NCERT, New Delhi. Karanth, P. 2003. ‘Introduction’, in P. Karanth and Joe Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 17–29. New Delhi: Sage Publications. Kavanagh J.F. and T.J. Truss. (1988). Proceedings of the National Conference on Learning Disabilities. Parkton, Maryland: Yorkton Press. Kirk, S.A. (1963). ‘Behavioural Diagnosis and Remediation of Learning Disabilities’, Proceedings of Conference of Exploratory Problems in Perspective of Handicapped Children, 1: 1–23. Lambert, N. and J. Sandoval. (1980). ‘The Prevalence of Learning Disabilities in a Sample of Children Considered Hyperactive’, Journal of Abnormal Child Psychology, 8: 33–50. Mastropieri, M.A. (1988). ‘Learning Disabilities in Early Childhood’, in K. Kavale (ed.), Learning Disabilities: State of the Art and Practices, pp. 161–79. Boston: Hall Press.

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Mc Kinney, J.D. and L. Feagans. (1984). ‘Adaptive Classroom Behavior of Learning Disabled Students’, Journal of Learning Disabilities, 16: 360–67. Mc Kinney, J.D. and D.L. Specce. (1983). ‘Classroom Behavior and Academic Progress of Learning Disabled Students’, Journal of Applied Developmental Psychology, 4: 149–61. Mc Leod, T.M. and S.W. Armstrong. (1982). ‘Learning Disabilities in MathematicsSkill deficits and Remedial Approaches at the intermediate and Secondary levels’, Learning Disabilities Quarterly, 5: 305–11. Mercer, C.D. and A.R. Mercer. (1985). Teaching Students With Learning Problems. London: Merril Publishing Co. Prakash, P. (2003). ‘Early Reading Acquisition’, in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 63–75. New Delhi: Sage Publications. Safer, D. and R. Allen. (1976). Hyperactive Children: Diagnosis and Management. University Park Press, Baltimore. Suresh, P.A. and S. Sebastian. (2003). ‘Epidemiological and Neurological Aspects of Learning Disabilities’, in P. Karanth and J. Rozario (eds), Learning Disabilities in India: Willing the Mind to Learn, pp. 30–43. New Delhi: Sage Publications. Torgesen, J.K. and R.K. Wagner. (1998). ‘Alternative Diagnostic Approaches for Specific Developmental Disabilities’, Learning Disabilities Research and Practice, 13: 220–32. Wong, B.Y.L. (1996). The ABC’s of Learning Disabilities. San Diego: Academic Press. Woodward, D.W. and D.J. Peters. (1983). The Learning Disabled Adolescent. New York: Apsen Publication. Ysseldyke, J.E. and B. Algozzine. (1990). Introduction to Special Education. Houghton Mifflin: Boston.

10 A Base-line Study of Learning Disabilities Its Prevalence, Teacher Awareness, and Classroom Practices DHANANJAI YADAV

AND

VIDYA AGARWAL

The learning disabled children are often categorized by their teachers as “slow learners” but unlike the mentally retarded they may have average or even above average IQ scores. Their symptoms are also thought to be signs of immaturity and emotional disturbance. The children with learning disabilities (LDs) may have different kinds of problems that involve reading disability, lack of memory, poor concentration, motor disability, and disruptive behavior. Given the heterogeneous nature of the LD population, it should come as no surprise that there is a vast array of techniques and materials available for teaching children with LDs. But matching the educational programs to the child’s particular educational needs is no easy task, especially given the fact that many teachers are burdened with an excess of paperwork and an abundance of students in their classes (Katzen, 1980). The task is even more difficult in parishadiya primary schools of India especially those in rural areas. Parishadiya primary schools are government primary schools managed by local bodies that is, village education committees under Panchayati Raj provisions. By the adoption of Operation Black-board Scheme and the very recent Sarva Shiksha Abhiyan, minimum physical infrastructure have been made available to these institutions

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but still a lot of disparity exists in terms of human inputs. The B.T.C. trained teachers, special B.T.C. trained teachers, and Shiksha Mitras from varied educational and professional backgrounds are working together. Despite these very real problems, teachers must become knowledgeable and skilled to assess child’s educational and emotional needs; collect and analyze important data; and prepare relevant, individualized educational programs. This is possible only when teachers are prepared or trained in such a way that they are able to identify the LD children in their classes and schools. Before a preparatory model program for teachers is developed, primary data is required regarding the extent and prevalence of different kinds of LDs, teacher awareness about LDs, and prevailing classroom practices. Although the area has been widely researched and investigated in India and abroad, the major thrust has been restricted to urban population, and the rural population has been neglected. Therefore, the rural population of such children specially those studying in rural parishadiya primary schools in India requires more attention on the part of investigators. The present study is an attempt in this direction. The main thrust of the study has been on identification of LDs in rural parishadiya primary schools in Allahabad, teacher awareness of LDs and classroom practices by teachers for identification, and remedial interventions to deal with different kinds of LDs. A model program for teacher orientation will be developed later based on primary data collected and results obtained in the present study.

LEARNING DISABILITIES DEFINED It is not an easy task to define LDs, as the term has different meanings to different persons. Warren (1934) in the dictionary of psychology has defined the term disability as a “Structural impairment of some organ or member of the body, which results in impairment of certain functions”. Warren’s clear-cut statement includes only one class of disabilities—those due to structural impairment. But the teacher encounters other kinds of disabilities, such as disabilities in reading, spelling, writing, arithmetic, music, and so on.

A Base-line Study of Learning Disabilities

223

The phrase LDs was first acknowledged in 1963 at a meeting of parents whose children were having difficulties in schools. Since that time, the term has been in constant transition. The definition of LD proposed originally by the national advisory committee on handicapped children in 1968 and modified by the federal government for the PL 94–142 regulations is the most widely accepted one. The definition reads as: Specific learning disability means a disorder in one or more of the basic psychological processes involved in understanding or in using language, spoken or written, which may manifest itself in the ability to write, spell, or to do mathematical calculations. The term includes such conditions as perceptual handicaps, brain injury, minimal brain dysfunction, dyslexia, and developmental aphasia. The term doses not include children who have learning problems which are primarily the result of visual, hearing, or motor handicaps, of mental retardation or emotional disturbance or of environmental, cultural, or economic disadvantage.

This definition is ambiguous is in the sense that any variety or types of students might be considered as LD. There has been a movement over the last decade to once again change the definition of LDs. One such attempt was made by the National Joint Committee for Learning Disabilities in 1981 (Reddy et al., 2000). In 1985, the federal Interagency Committee on Learning Disabilities was formed by American congress and recommended the NJCLD definition with slight modifications. The definition follows: Learning disability is a generic term that refers to a heterogeneous group of disorders manifested by significant difficulties in the acquisition and use of listening, speaking, reading, writing, reasoning, or mathematical abilities, or of social skills. These disorders are intrinsic to the individual and presumed to be due to central nervous system dysfunction. Even though a learning disability may occur concomitantly with other handicapping conditions, (such as sensory impairment, mental retardation, social, and emotional disturbance) or social-environmental influences, (such as cultural differences, insufficient or inappropriate instructions, psychogenic factors), and especially with attention deficit disorders, all of which may cause learning problems. A learning disability is not the direct result of those conditions or influences.

Although there are slight differences between these two definitions, the two are actually quite similar in that a number of academic

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Dhananjai Yadav and Vidya Agarwal

and cognitive areas can be affected by LD. As a teacher, one will be concerned not with the cause of LDs as much as with the behavior in class that manifests the most obvious symptoms or characteristics. A Taskforce on LDs (Clements, 1966) found 10 commonly mentioned characteristics that are listed below: 01. hyperactivity; 02. perceptual—motor impairment; 03. emotional instability; 04. general co-ordination deficit; 05. disorders of attention; 06. impulsivity; 07. disorders of memory and thinking; 08. specific learning disabilities; 09. disorders of speech and hearing; and 10. equivocal neurological signs.

PREVALENCE

OF

LEARNING DISABILITIES

Estimates of the prevalence of learning disorder range from 2 percent to 10 percent depending on the nature of ascertainment and the definitions applied. Approximately 5 percent of students in the public schools in the United States have been identified as having learning disorders.

OBJECTIVES

OF THE

STUDY

This study aims at accomplishing the following objectives: 1. To study the extent and prevalence of LDs in rural parishadiya primary schools of Allahabad. 2. To study the awareness of primary schoolteachers of rural areas regarding different dimensions of LDs. 3. To study actual classroom practices concerning identification and remedial interventions for dealing with different aspects of LDs.

A Base-line Study of Learning Disabilities

225

4. To work out basic framework to be incorporated in developing a model of teacher training program to orient teachers in dealing with LDs.

METHODOLOGY Since the study is an exploratory one, the researchers have used survey method of investigation.

SAMPLE Since it is not possible to survey all the rural parishadiya primary schools of Allahabad district due to paucity of time, only 25 schools have been selected in the sample. Out of these 25 schools, 800 students and 50 teachers have been selected as sample respondents.

TOOLS FOR DATA COLLECTION The following tools have been used for collecting relevant information from the sample respondents: 1. Raven’s Coloured Progressive Matrices and school achievement records have been used to identify underachievers. 2. The Learning Disabilities Scale (LDS) constructed by the investigators was used to find out the extent and prevalence of LDs. It consisted of 19 questions in five areas—Verbal Disability–2, Oral Attention Disability–2, Writing Disability– 4, Mathematical Computation Disability–6, and Written Attention Disability–5. 3. Learning Disabilities Awareness Schedule (LDAS) developed by the researchers was used to find out the teachers’ awareness of LDs. It consisted of 41 questions in seven areas (General–3, Listening and Understanding–5, Oral Language–5, Written Language–4, Mathematical Problems–4, Behavior Problems– 8, and Motor Behavior Problems–12). The schedule has

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3–point response categories, for example, often, seldom and never, for each item and is meant for teachers. 4. Teacher Behavior Observation Schedule (TBOS) was also developed by the researchers and was used to study the current practices of identifying and dealing with different kinds of LDs. It consists of 27 questions in six areas (Listening and Understanding–4, Oral Language–4, Written Language–4, Mathematical Practices–4, Behavior Related–5, and Motor Behavior–6). The schedule has three response categories— absent, below average, and average. This is meant for observers for recording classroom practices. For the purpose of identifying learning-disabled children, first of all teachers from selected schools were contacted and information was gathered about children who they perceived as having LDs during their routine teaching. On the basis of this information, 250 such children were identified out of the total strength enrolled. Then, Coloured Progressive Matrices were administered on these 250 children and their achievement data from school records was collected. Sixty children were identified as learning disabled after matching their IQ scores with achievement scores. In the end, LDS was administered to these 60 children to identify different kinds of LDs in the children. For the purpose of studying teachers’ awareness regarding LDs, teacher awareness schedule was administered to 50 teachers selected in the sample. Fifty teachers were observed while teaching in their classrooms in order to obtain relevant informations about classroom practices. Each teacher was observed twice, thus, 100 observations in all were made. Since the present study is a base-line study, the data have been analyzed by using frequencies and percentages. The results have also been presented in a graphical form.

ANALYSIS

AND INTERPRETATION

Table 10.1(a) shows the overall prevalence of LD to be 18 out of 800, that is, 2.25 percent, (which comprises 2.66 percent males and

227

A Base-line Study of Learning Disabilities Table 10.1(a) Prevalence of Learning Disability Status of LD Total no. of 8–10 yrs children Primary screening through teachers IQ & achievement analysis (LD) Actual LD on LD identification scale Prevalence of LD

Male

Female

Total

450 150 40 12 2.66%

350 100 20 06 1.71%

800 250 60 18 2.25%

Source: Based on data computed by the authors.

1.71 percent females), of the population in rural area. This finding confirms the earlier findings of researches. Prevalence of LDs in males is more than that in females. Table 10.1(b) reflects that the prevalence of LDs in the area of writing skills is more as compared to oral skills in both boys and girls. Regarding oral learning disabilities, the extent of language disability was found to be more as compared to that of attention disability. As far as language disability was concerned, written language disability was found to be much more as compared to oral language disability in both boys and girls. The average scores on colored progressive matrices were found to be higher in males than in females (M>F=27.16>22.33) but on the contrary, total disabilities scores of males was also more than that of females. This shows that boys with higher intelligence levels have comparatively higher extent of LD. The table also reveals that 25 percent of male students could not attempt the tasks given on the writing disability scale whereas only 16.66 percent of female students fall under this category. Regarding mathematical and computation disability, the situation was alarming where 33.33 percent of male students could not attempt the tasks and scored zero on the mathematical disability scale. Overall, the average score of disability was higher in males than in females. Regarding written attention disability, 16.66 percent of male and femal students failed to attempt the tasks and scored zero on the attention disability scale. The average number of errors in this category ranged between three and eight. Case numbers 1, 5, and 7 needed special attention and remedial interventions, as they failed to respond at all while their level of

2

Oral Attention disability

14*

Total disability Score

43

6

2

30

1

9

43

8

5

27

–

3

40

26

9

M

3

31

4

3

20

1

3

41

30

10

M

4

2

6

38

20

8

M

5

13*

5

NR

NR

Source: Based on data computed by the authors.

7

Written attention disability

NR

5

NR

4

Achievement (in %) 39

Oral Language disability

Mathematical computation disability

35

24

CPM Score

Written Language disability

22

10

Age

M

M

Sex

2

1

S. No.

35

3

2

28

2

–

36

22

9

M

6

2*

NR

NR

NR

–

2

42

30

10

M

7

44

4

3

31

1

5

40

30

8

M

8

32*

NR

2

27

–

3

41

31

9

M

9

45

5

5

32

2

1

35

32

9

M

10

45*

3

NR

35

1

6

37

27

10

M

11

Table 10.1(b) Prevalence and Extent of Learning Disabilities

40

7

2

28

–

3

35

32

8

M

12

34

6

2

24

2

–

41

24

10

F

13

34

6

3

22

1

2

37

22

9

F

14

45

8

2

31

–

4

37

21

9

F

15

34*

NR

4

26

2

2

40

25

10

F

16

12*

3

3

NR

1

5

38

22

10

F

17

36

4

2

27

3

–

35

20

8

F

18

229

A Base-line Study of Learning Disabilities

intelligence was above average. Case number 7 who could not respond at all the writing skills tasks, showed evidence of writing disability to a maximum extent. These cases need to be dealt with separately. The table also reveals that no universal intervention program can meet the heterogeneous nature of LDs prevalent in rural populations. Table 10.2 Teacher Awareness about Learning Disability Areas General 1. Identifying IQ of student 2. Relating achievement with IQ 3. Identifying LDs

Never (%)

Sometimes (%)

Always (%)

Total (%)

0 2 2

10 24 20

90 74 78%

100 100 100

Source: Based on data computed by the authors.

Table 10.2 shows that as far as awareness regarding identification of LDs on the basis of IQ test and achievement tests are concerned, 74–90 percent of teachers identified students with problems used the above-mentioned discrepancy between ability and achievement. 1. Regarding listening and cognitive behaviors, 44–70 percent of teachers were found to be highly aware on different questions. Between 26 percent and 52 percent of teachers were moderately aware of identification of hearing and cognitive problems of students (Table 10.2a). Table 10.2(a) Listening and Cognition Behavior (in percentage) Areas General 1. 2. 3. 4. 5.

Students not following instructions Cannot understand class information Cannot remember oral information Cannot understand teacher’s instructions Cannot understand what the teacher is saying

Never Some- Always Total (%) times (%) (%) (%) 4 2 4 10

26 48 52 36

70 50 44 54

100 100 100 100

10

46

44

100

Source: Based on data computed by the authors.

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Dhananjai Yadav and Vidya Agarwal

2. Regarding oral language behavior, between 54 and 70 percent of teachers were found to be highly aware of children having pronunciation and oral communication problems, 26–44 percent of teachers were moderately aware whereas 2–10 percent of teachers never tried to identify these children (Table 10.2b). 3. Regarding written language problems, between 50 and 70 percent of teachers were found to be highly aware of children committing writing mistakes while 26–46 percent of teachers were moderately aware. Only 4–8 percent of teachers were not at all aware of written language problems (Table 10.2c). 4. As far as mathematical computation problems are concerned 50–70 percent of teachers were highly aware of dealing with children with mathematical computation problems, 26–42 percent of teachers were moderately aware, whereas 4–12 percent of teachers were found to be least aware and never involved themselves in identification and dealing with mathematical computation disability (Table 10.2d). Table 10.2(b) Oral Language Problems (in percentage) Areas General 1. 2. 3. 4. 5.

Never (%)

Cannot pronounce properly Cannot reuse the words Cannot narrate stories Cannot communicate properly Understands but cannot express

4 2 10 8 8

Some- Always times (%) (%) 26 44 30 30 30

70 54 60 62 62

Total (%) 100 100 100 100 100

Source: Based on data computed by the authors. Table 10.2(c) Written Language Problems (in percentage) Areas General 1. 2. 3. 4.

Cannot copy written matter Can speak but cannot write Reversals in writing numbers Illegible handwriting

Never (%) 8 4 6 4

Source: Based on data computed by the authors.

Some- Always times (%) (%) 30 46 34 26

62 50 60 70

Total (%) 100 100 100 100

231

A Base-line Study of Learning Disabilities Table 10.2(d) Mathematical Computation Problems (in percentage) Areas General 1. 2. 3. 4.

Never Some- Always (%) times (%) (%)

Confused with mathematical symbols Mistakes in reading & writing numbers Confused with mathematical operations Cannot identify geometrical figures

4 4 12 8

26 32 26 42

70 64 62 50

Total (%) 100 100 100 100

Source: Based on data computed by the authors.

5. Regarding behavior related problems of learning disabled students 30–64 percent of teachers were found to be highly aware of dealing with different types of behavioral problems. In some cases, for example, items 6, 7, and 8 (that is, identifying those children who cannot adjust in new situations; identifying those children who fail to perform their responsibilities; and identifying those who like to be lonely in the class) between 10 and 24 percent of teachers have been found to be not at all aware of having children behavioral disorders (Table 10.2e). 6. Regarding conduct and motor behavior problems of learningdisabled students, 32–86 percent of teachers were found to be highly aware of dealing with children having motor behavior problems. In case of items 3, 4, 6, 9, 10, and 11 (that is, identifying those children who always tell lies; identifying those children who cannot use new equipments; identifying those Table 10.2(e) Behavior Related Problems (in percentage) Areas General 1. 2. 3. 4. 5. 6. 7. 8.

Do not cooperate with peers Cannot follow instructions Do not participate in activities Cannot mix with other students Remain indifferent to others needs Cannot adjust in new situations Fail to carry out responsibilities Remain aloof from others in class

Never (%) 2 6 6 6 6 10 10 24

Source: Based on data computed by the authors.

Some- Always times (%) (%) 42 34 30 42 48 50 60 30

56 60 64 52 46 40 30 46

Total (%) 100 100 100 100 100 100 100 100

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Dhananjai Yadav and Vidya Agarwal

children who cannot maintain their body balance; identifying those children who are anxious; identifying those children who abstain from school; and identifying those children who have destructive tendencies.) between 10 and 16 percent teachers were not at all aware of dealing with children with conduct and motor disorders (Table 10.2f). The overall picture of Table 10.2 shows that item numbers 4 and 5 of listening and cognitive behavior (that is, identifying those students who fail to understand the words spoken by the teacher, and identifying those students who cannot understand the meaning of words spoken by the teacher); 3 of oral language behavior (that is, identifying those children who cannot narrate stories); 3 of mathematical computation behavior (identifying those children who cannot make practical use of basic mathematical operations); 6, 7, and 8 of general behavior (that is, identifying those children who cannot adjust to new situations, identifying those children who fail to perform their responsibilities, and identifying those who like to be lonely in the class); and 3, 4, 6, 9, 10, and 11 of motor behavior problems (that is, identifying those children who often Table 10.2(f) Conduct and Motor Behavior Problems (in percentage) Areas General 11. 12. 13. 14. 15. 16. 17. 18. 19. 10. 11. 12.

Shy in behavior and fails to respond Remains troubled and sad Always tell lies Cannot use new instruments Cannot hold pencils and books properly Poor physical balance Lazy and work slowly Always feels tired Always anxious Shows absenteeism from school Shows destructive tendency Shows hyperactive behavior

Never (%)

Some- Always times (%) (%)

Total (%)

8 8 12 10 6

20 60 30 38 40

72 32 58 52 54

100 100 100 100 100

12 4 6 16 10 10 4

38 36 64 24 38 20 10

50 60 40 60 52 70 86

100 100 110 100 100 100 100

Source: Based on data computed by the authors.

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tell lies, identifying those children who cannot use new equipments, identifying those children who cannot maintain their body balance, identifying those children who feel themselves terrified, identifying those children who abstain from school, and identifying those children who have destructive tendencies) need special attention because 10–24 percent of teachers perceive themselves to be least competent in identifying and dealing with children having LDs. Table 10.3 shows the status of classroom intervention practices followed by a teacher in order to deal with children having different kinds of LDs. These observations show an entirely different picture from that observed in Table 10.2. Regarding hearing and cognitive problems of LD student only 15–62 percent of teachers were found to perform average level activities to deal with children with learning disability. Between 10 and 23 percent of teachers were found to do nothing when dealing with hearing and cognitive. Table 10.3 Classroom Practices for Dealing with Learning Disability Hearing & Cognition 1. Repetition of instructions 2. Helping children individually in class 3. Helping children who cannot remember oral information 4. Intimating on blackboard or copies for those who cannot remember orally

Absent (%)

Below Average Average (%) (%)

Total (%)

15 12 23

23 57 62

62 31 15

100 100 100

10

60

30

100

Source: Based on data computed by the authors.

Regarding oral language behavior (Table 10.3a) only item number 1 (that is, identifying objects and telling their names) was being practiced in 63 percent of the classes observed whereas item number 2 (identifying pronunciation mistakes), item number 3 (identifying verbal orders) and item number 4 (identifying serial order in students ideas) were not being practiced at all in 40–60 percent of the classes observed. As far as classroom interventions to deal with written language disabilities were concerned, only 10–38 percent of classes were

234

Dhananjai Yadav and Vidya Agarwal Table 10.3(a) Classroom Practices for Dealing with Oral Language Problems (in percentage)

Oral Language

Absent (%)

1. Giving practice in identifying and telling names 2. Identifying pronunciation errors 3. Identification of world orders 4. Identifying serial order in thoughts

Below Average Average (%) (%)

Total (%)

10

27

63

100

51 40 65

45 58 30

4 2 5

100 100 100

Source: Based on data computed by the authors.

utilized to perform average level of activities whereas 40–75.5 of classes showed below average level of activities. In 15–27 percent of classes, no such activities concerned with dealing with written language disabilities were found (Table 10.3b). Regarding mathematical computation, the situation of classroom intervention practices was much alarming. Where only 3–31 percent of classes were having average level of interventions and 13–62 percent of classes had below average level of intervention practices and 13–80 percent of classes had almost no intervention practices. Table 10.3(b) Classroom Practices for Dealing with Written Language Problems (in percentage) Written Language

1. Correcting mistakes while copying written matter 2. Helping those who speak correct but cannot write 3. Correcting mistakes while reversing letters 4. Correcting dirty and illegible handwriting

Absent (%)

Below Average Average (%) (%)

Total (%)

21

62

17

100

15

75

10

100

27

62

11

100

22

40

38

100

Source: Based on data computed by the authors.

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In particular no efforts were made in item number 3 (to remove problems concerning basic mathematical operation) and item number 4 (confusion in identification of geometrical figures) in 70–80 percent classes the teachers were not providing interventions for children with a LD (Table 10.3c). In the area of general behavior, the status of classroom interventions was very poor. Only in 7–29 percent of classes teachers were showing average level of intervention practices in various dimensions. Thirteen–70 percent of classes fall in below average category whereas in 21–81 percent of classes, the status of intervention was found to be nil. For instance, no efforts were made on items number 4 (motivate students to work in cooperation) and 5 (encouraging shy students to participate in group games) (51–81 percent classes) (Table 10.3d). As far as conduct and motor problems are concerned, the status of classroom practices was alarming where only in 3–11 percent of classes, teachers were found to perform average level of intervention. A major chunk, (16–75 percent) of classes falls under the below average category; whereas, in 20–80 percent of classes no activities were performed. In case of items 5 and 6 (helping students who skip over leaving one activity incomplete and helping students who cannot stay calm, respectively) teachers in 79–80 percent classes were found to perform no activity at all to help learning disabled children (Table 10.3e). Table 10.3(c) Classroom Practices for Dealing with Mathematical Computation Problems (in percentage) Mathematical Computation 1. Helping those confused with mathematical signs 2. Correcting mistakes in reading or writing numbers 3. Correcting mistakes in mathematical operations 4. Correcting mistakes while identifying geometrical figures

Absent (%)

Below Average Average (%) (%)

Total (%)

13

56

31

100

22

62

16

100

70

27

3

100

80

13

7

100

Source: Based on data computed by the authors.

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Dhananjai Yadav and Vidya Agarwal Table 10.3(d) Classroom Practices for Dealing with General Behavior Problems (in percentage)

General Behavior

Absent Below Average Total (%) Average (%) (%) (%)

1. Identifying students who are distracted by irrelevant stimuli 2. Helping students to be familiar with others 3. Motivating students to participate in other school activities 4. Motivating students to cooperate with others 5. Accomodating shy students in games

21

50

29

100

23

70

7

100

31

57

12

10

51

40

9

100

81

13

6

100

Source: Based on data computed by the authors. Table 10.3(e) Classroom Practices for Dealing with Conduct and Motor Problems (in percentage) Conduct and Motor Problems

Absent Below Average (%) Average (%) (%)

1. Encouraging students to use new instruments 2. Helping students to hold pencils and books properly 3. Helping students to overcome anxiety and fear 4. Motivating students to become regular at school 5. Helping students who skip activities to complete thier forms 6. Helping students to remain calm and attentive

Total (%)

35

60

5

100

20

75

5

100

24

68

8

100

31

58

11

100

80

17

3

100

79

16

5

100

Source: Based on data computed by the authors.

Major Findings 01. Prevalence of learning disability in the age group of 8–10 years in children of parishadiya primary schools of Allahabad is found to be around 2.25 percent. 02. The prevalence of learning disability in males exceeds that in females (2.66 percent in males and 1.71 percent in females).

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237

03. The extent and prevalence of learning disability in writing skills is much higher as compared to oral skills in both boys and girls. 04. In oral learning disability, language learning disability is much more than attention disability. 05. Male students perform better on CPM than female students (M=27.16 and F=22.33) and the average disability level of males is higher than in females. 06. In the area of writing disability, up to 33.33 percent male students and 16.66 percent female students had severe problems and were unable to respond to any of the items. 07. Some cases like number 7, 5, and 1 need to be studied in depth to work out specific intervention practices to deal with their learning problems. 08. Regarding teacher’s awareness about identification and intervention practices for learning disability 30–90 percent perceived themselves to be highly aware. Ten–64 percent perceived them to be moderately aware whereas just up to 24 pecent of teachers perceived themselves to be unaware of students’ learning problems. 09. The classroom observation data about ongoing intervention practices depicts an entirely different picture where only 2– 63 percent of teachers were performing average level of activity, 13–75 percent below average and 10–81 percent do not perform any intervention activities to help students with learning problems. 10. Regarding mathematical computation, general behavior, and motor behavior disabilities, the status of intervention practices is very poor. Probably this leads to higher prevalence of learning problems in these areas. 11. A clear-cut discrepancy between teachers’ awareness as perceived by themselves and classroom intervention practices as observed by researchers justify the need for holding inservice teacher orientation programs on different dimensions of learning disabilities. i. In such programs, identification and remedial interventions for learning disabilities in writing skills need to be stressed more.

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ii. Behavioral aspect should be given more attention while designing any program for dealing with learning disability. iii. The identification and intervention of oral language problems need to be stressed more as 51 percent of teachers could not identify pronunciation errors and 65 percent of teachers could not identify errors in serial order in the thoughts expressed by the students. iv. The area of mathematical computation needs to be given more emphasis as 70 percent of teachers failed to correct mistakes in mathematical operations and 80 percent of teachers were found to correct the mistakes of students while identifying basic geometrical figures. v. The area of general behavioral problems also needs attention as 51 percent of teachers failed to motivate their students to cooperate with others and 81 percent of teachers failed to encourage shy students to participate in group games. The skills of motivation should be an integral part of such training programs. vi. As far as conduct and motor problems are concerned, teachers should be skilled in helping students who cannot stay calm or show hyperactive behavior and helping those who leave their work incomplete.

REFERENCES Clement, S. (1966). ‘Minimal Brain Dysfunction in Children’, NINDS Monograph No. 3, Public Health Service Bulletin No. 1415. Washington DC: Department of Health, Education and Welfare. Gibson, Janice T. (1976). Psychology for Classroom, New Jersey: Prentice Hall Inc. Katzen, K. (1980). ‘A Teacher’s View’, Exceptional Children, 48: 582. Public Law 94–142, The Education for all Handicapped Children Act of 1975 USA. Reddy, G.L., R. Ramar and A. Kusuma. (2000). Learning Disabilities (A practical guide to practitioners). New Delhi: Discovery Publishing House. Skinner, C.E. (1977). Educational Psychology (Fourth Edition). New Delhi: PrenticeHall of India Private Limited. Taylor, Ronald L. and L. Sternberg. (1989). Exceptional Children: Integrating Research and Teaching. New York: Springer Verlag. Warren, H.C. (1934). Dictionary of Psychology. Bosten: Houghton Mifflin Company.

11 A Theory-driven Approach to the Diagnosis and Remediation of Learning Problems in Children CAS and PREP * SUNITA PAGEDAR

AND JAGRUTI

SARNATH

C

hildren like to learn. They are happy when they are successful in doing worthwhile things, which suit their ability and temperament. Yet, there are students who fail to learn or achieve in academics. Since the consequences of low academic achievement of a child are manifold, there has been a growing concern regarding these children. When a student’s academic performance lags far behind his innate ability then it is a cause of concern not only for the child and his parents but also is a serious loss in terms of his contribution to the development of human resource of the country. A scientific effort to understand and unveil the factors associated with school success and failure can provide valuable clues to minimize this loss. * This paper is an amalgam of two papers presented in the conference. The first author, SP is using a training program which shares the theoretical bases of the assessment approach and the second author, JS, is dealing with an alternative approach to the diagnosis of learning problems in children. These papers were merged as they showcase the utility of a cognitive approach to both assessment and remediation.

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The enigma of the youngster who has difficulty in learning is, however, not new. Experts from various disciplines like medicine, psychology, language, and education have contributed to the study of the learning difficulties that children face. There is a general tendency amongst professionals to label the child facing learning difficulties. They claim that it helps to get special concessions for the child, and helps to plan instructions and the curriculum for them (Smith et al., 1993). However, professionals who support the non-categorical or generic classification system emphasize that many of the characteristics of students in several categorical groups overlap significantly, and thus instead of spending our efforts on labeling the child, we could diagnose the learning problems in such a way that the child’s strengths and weaknesses are emphasized and it provides appropriate guidelines for remediation. Generally, it is seen that there is a set of diagnostic tools on one hand and a medley of remediation tools on the other. There is not necessarily an association between the two. The diagnosis thus is useful only to label the child. However, what does the child or parent do with the labels like learning disability (LD), slow learner, autistic, attention-deficit hyperactivity disorder (ADHD), mental retardation (MR), and so on, given to the child by the traditional IQ tests? The framework for intellectual assessment has been constructed around the notion of intelligence as a static unitary concept (Das, 1988). Originally, these tests were devised to classify individuals according to their academic potential. Now tests are used for diagnostic purposes and to inform instructional needs to maximize each child’s potential. Thus there is a need to look for alternative approaches to assess and diagnose the learning problems of children. If psychometrics were to give a more accurate picture of the child’s learning problem there is a need to broaden the construct of intelligence. Moreover, a focus on how information is processed rather than how much or what information we possess is important. This approach to assessment is effectively captured by the PASS theory of intelligence. Building upon the groundwork of Luria (1966, 1973, and 1980), Das and his colleagues (Das et al., 1975; Naglieri and Das, 1990), have extensively researched the functional units of PASS and their role in cognition.

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There are four components that make up the central processing mechanisms and together make up the PASS: 1. 2. 3. 4.

Planning (P) Attention-arousal (A) Simultaneous (S), and Successive processing (S).

An important part in this theory is the knowledge, the base of past experiences, and learning, emotions and motivations. These provide the information to be processed. These processes are associated with different parts of the brain. Planning is broadly located in the frontal lobe (Luria, 1980). Planning processes are required when the individual makes some decisions about how to solve a problem, or carry out an activity. It is also needed to focus our attention, and to use simultaneous and successive processes when required. Arousal is a simple process that keeps us alert and awake; it is associated with activities in the brain stem and lower part of the cerebral cortex (Luria, 1973). But attention is more complex. One can be alerted by things that interest one in the environment just as one may fall asleep during a boring lecture. The frontal lobe and the lower part of the cortex decide as to what we are experiencing is boring or interesting. Simultaneous processing involves the integration of stimuli into groups by interrelating each aspect of the incoming information to all other elements of it (Naglieri and Das, 1989). A strong relational quality exists in simultaneous coding. Conversely, successive processing involves temporal sequencing such that the elements of information form a chain-like progression (Naglieri and Das, 1987). Although cognitive processing occurs in simultaneous or successive form, or a combination thereof, individual processing differences are evident. Such differences are influenced by sociocultural experience, existing knowledge base, and the demands of a given task. Simultaneous processes are broadly associated with the occipital and the parietal lobes while successive processes deal with the frontal-temporal lobes (Luria, 1966). The last component is the output or behavior. If a child is asked to memorize the definition of a word, he must use successive process. However, if he is asked to describe what the word is all about, he could use simultaneous

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processes. Thus, by changing the requirement of the answer, the output can change the processing. Therefore how we measure output becomes important in measuring intelligence. Each of these units has been operationalized in the Cognitive Assessment System (CAS). Designed by Naglieri and Das (1997) the CAS is a theory-based, norm-referenced measure of intelligence based on the PASS cognitive processing model. It is intended to predict academic achievement in children. The full-scale standard scores are the best overall predictors of achievement whereas individual PASS scales standard scores would relate to specific areas of academic performance. From inadequacies identified by the instrument, remediation consistent with the processing difficulties can be implemented. This may answer the “what now” questions often posed by concerned parents. Using the CAS with children with different types of learning difficulties and who had been variously diagnosed, the second author (JM) presents brief case studies of children in Mumbai who had already been diagnosed as ADHD, MR, and LD. A brief description of three case histories and interpretation of their CAS profiles would help one to understand the cognitive deficiency behind their learning and behavioral problems.

CASE 1 A 9-year-old boy of grade 4. He had problems with his spellings, writing, math, and difficulty in copying from the black board, was unable to concentrate, and forgot things very fast. His parents were in Surat. According to them, he was lazy and they thought admitting him in a hostel would make him perform better academically. His uncle and aunt got him to Mumbai instead. He seemed to be a very quiet child. He was compliant and rarely protested about anything. He used to suffer from enuresis up till the last six months.

CAS Interpretation His planning and attention scores were low while successive and simultaneous processing were average. A tentative diagnosis of

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Attention-Deficit Hyperactivity Disorder (ADHD-inattentive type) was made. ADHD involves problems with behavioral inhibition and self-control, which is associated with poor executive functions. It impairs goal-directed planned behavior. Thus, due to this specific learning difficulty (SLD) he is likely to face problems in his studies. It is also reflected in the inconsistency in his academic performance, and the lack of interest and disorientation that he exhibited.

CASE 2 A 10-year-old boy of grade 5. He was diagnosed with ADHD by the school psychologist. He was referred to the psychologist for behavioral problems, as he would hit other children, disturb the class, throw temper tantrums at home, and display stubbornness and great impatience. He had poor handwriting, but was good at reading familiar and unfamiliar words, and oral spellings but poor in written spellings. He displayed good observation abilities. His mother felt that he was performing much below his potential.

CAS Interpretation Although his hyperactivity, impulsivity, and non-compliance would be indicative of symptoms of ADHD, his CAS scores indicate that it may be a secondary symptom; LD in planning may be the primary problem. An ADHD individual would be expected to be deficient in several processes, with a marked deficiency in attention while the LD individual is more likely to be deficient in one of planning, simultaneous, or successive processes. His low planning scores may have influenced his attention scores. Superior scores in successive and average scores on simultaneous processing also indicate that the encoding of information was fairly normal. Although the reading scores were high, the comprehension scores were below the age and grade equivalent scores. This is correlated with problems in planning process as high proficiency in comprehension ought to involve some degree of planning.

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CASE 3 A 13-year-old girl of grade 7. She was mentally retarded, had low self-esteem, and did not maintain eye-contact. She was referred for guidance for future course of action.

CAS Interpretation The full score here is in the same range as that of WISC. The scores on planning, attention, and simultaneous processes were below average. However, successive processes score were in the average range. This was also reflected in her WRAT spelling score which was in the average category. Thus this child who was written off as a mentally retarded person, did after all have a cognitive strength that of successive processes. This indicated that both the perception of stimuli in sequence and the formation of sound and movements in order were fairly developed. This strength could be developed and it could help answer the what-now question not only for remediation but also for suggesting a future course of action. The second part of the chapter, which is authored by SP, highlights the use of a training program based on the same theoretical paradigm as the CAS. When the English tongue we speak Why is ‘break’ not rhymed with ‘freak’? Will you tell me why it’s true We say ‘sew’ but likewise ‘few’? Wherefore ‘done’ but ‘gone’ and ‘lone’, Is there any reason known? And, in short, it seems to me, Sounds and letters disagree! (Anonymous)

This poem illustrates how variable and inconsistent the English language is. Is it therefore, any surprise that many children face reading difficulties? This quirky language leads to many problems for

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those having SLD. While reviewing the literature on remediation of reading disabilities, one comes across a plethora of training programs, which are neither based on any sound theoretical background, nor do they have stated objectives of facilitating transfer to other situations. Most of these training programs rely heavily on rehearsal training. Common reading problems faced by children include errors of omissions; substitutions; mispronunciation; and slow, labored reading without comprehension. Remedial procedures like teaching phonics, word supply, sentence repetition, end of page review, emphasis on word meaning, and drill are generally used by remedial teachers to try and overcome these problems. Most of these programs are eclectic, not based on any well-researched theories and are extremely memory-specific in nature. In contrast, the PASS Reading Enhancement Programme (PREP) is a dynamic theory-driven reading remediation program for primary school-aged children who are experiencing difficulty with reading, spelling, and comprehension. It was developed as a cognitive remedial program based on the PASS model of cognitive functioning (Das et al., 1994). It aims at improving the information-processing strategies, specifically simultaneous and successive processing that underlie reading, while at the same time avoiding the direct teaching of word reading skills such as phoneme segmentation or blending. PREP is also founded on the premise that the transfer of principles is best facilitated through inductive, rather than deductive, inference (Das, 1998). The program is accordingly structured so that tacitly-acquired strategies are likely to be used in appropriate ways. A brief description of PREP follows. The ultimate purpose of PREP is to improve a specific academic skill, namely reading, of struggling readers. The emphasis up until now had been on removing word–decoding difficulties. The global process training provides children with the opportunity to internalize strategies in their own way, thus maximizing generalization and facilitating transfer. This remediation program also provides “bridges”, that is, training in strategies that have been shown to be relevant for academic skills of reading and spelling. These two parts of PREP encourage the application of the strategies to academic tasks through verbal mediation and internalization of processes.

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The tasks in this program are designed to provide remediation of successive and simultaneous processing deficiencies, but will also have small effects on other related processes, such as planning and attention. The criteria for the tasks are: 1. To provide a structure for the child, in which he/she is by design using the targeted process, either simultaneous or successive processing. 2. To provide a scaffolding network through a series of prompts which provides the child with only that amount of assistance which is necessary for the child to successfully complete the tasks, and yet ensures maximal success for the child. 3. To provide a monitoring system that is able to assess when the material is too difficult for the child, as well as when the child is able to progress successfully to a more difficult level.

THE STRUCTURE

AND

CONTENT

OF

PREP

The PREP program consists of 10 tasks, each of which involves a global training component and a curriculum-related bridging component. The global component includes structured, non-reading tasks that require the application of simultaneous or successive strategies. These tasks also provide children with the opportunity to internalize strategies in their own way, thus facilitating transfer. The bridging component involves the same cognitive demands as its matched global component, and provides training in simultaneous and successive processing strategies, which have been closely linked to reading and spelling. Besides, simultaneous and successive processing, attention, and planning are important aspects of tasks given in the program. Specifically, attention is required to perform each task, and planning skills are developed by encouraging children to discuss their strategies and solutions both during the task and following each task. The 10 tasks include: 1. Joining Shapes: The purpose of this task is to join a series of geometric shapes with a line in response to a series of

CAS and PREP

2.

3.

4.

5.

6.

7.

247

verbal instructions and a set of rules provided by the facilitator. The bridging task involves joining letters in a similar fashion to form meaningful words. Window Sequencing: The student has to reproduce a series of chips that vary in color and shape, in the same order in which they are presented using a Window Shield. The bridging activity involves the reproduction of a series of letters in the same order in which they are presented and say or write the word that is spelled by the letters. Connecting Letters: Students are required to follow a line to find which letter on the left side of a page is connected to which letter on the right side of the page. The matched bridging activity includes letters on both sides of the page with letter blends or single words along the way. Students have to visually track each line, mentally connect the series of letters, and say the word that is spelled out by the letters. Transportation Matrices: In this task, the student has to reproduce a series of transportation pictures in the order in which they are presented. The bridging component involves reproduction of a series of letters in the correct order as shown through the Window Shield and make the word using alphabets-set provided to them. Related Memory Sets: The student has to match the front half of an animal with its back half, completing the picture and also has to explain his reason for choosing it. In the bridging task, the student has to choose the proper front half of a word to match the back half and read the entire word. Tracking: Students are presented with a village map with numbered houses and trees and also tracking cards that illustrate a path from a starting point to either a numbered house or tree. The student has to survey each card and the map and then locate the number of the house or tree on the map. In the matched bridging activity, students are shown the map of a shopping mall. They are given cards with passages depicting different routes inside the mall. The student has to comprehend the entire passage and then trace out the route in the map. Shape Design: The student has to study a design that is presented to him for about 10 seconds and reproduce this design

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with the colored shapes provided to him. In the bridging activity, he has to read a phrase or a story from a card that describes how two or more animals are arranged in relationship to one another, visualize the scene, and arrange the animals suitably. 8. Shapes and Objects: Here, students have to match the picture of an object to an abstract shape, or match a colored chip to a geometric shape. The corresponding bridging activity has cards with phrases or sentences which have to be categorized on the basis of thematic similarity. 9. Matrices Numbers and Letters: Here, the student has to memorize a sequence of randomly chosen letters or numbers that are displayed within a five-cell matrix and reproduce them in same order. In the bridging component, he has to memorize and reproduce the position and sequence of a series of words presented on a cross–matrix. 10. Sentence Verification: The student is presented with a set of pictures which are thematically similar. Each set is accompanied by a printed passage which describes what is happening in only one of the pictures. The student has to select the picture that best illustrates the contents of the passage. In the paired bridging activity, the student is presented with a set comprising one picture and a few printed passages. He then has to select the passage that best matches the picture. An integral part of the structure of each task in PREP is to develop strategies such as rehearsal, categorization, monitoring of performance, prediction, revision of prediction, sounding, and sound blending. Children are encouraged to use these strategies through verbalization rather than being explicitly taught by the tutor. Growth in the ability to use strategies and be aware of appropriate opportunities for their use develops over the course of remediation. A system of prompts is also integrated into each global and bridging component. The series of prompts creates a scaffolding network that supports and guides the child to ensure that tasks are completed with a minimal amount of assistance and a maximal amount of success. A record of these prompts provides a monitoring system for teachers to determine which material is too difficult for a child or when a child is able to successfully progress to a more difficult level.

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A criterion of 80 percent correct responses is required before a child can proceed to the next level of difficulty. If this criterion is not met an alternate set of tasks, at the same difficulty level, is used to provide the additional training required.

WHO IS MOST LIKELY TO BENEFIT

FROM

PREP?

Research has revealed that two types of difficulties are present among children who have reading difficulties. This is true despite good motivation, family support, and emotional well-being. The larger group is the “garden variety” poor readers and a much smaller group is the dyslexic readers. Both groups are similar as neither is able to read at a level that would be expected for their particular grade. We use the word “read” to mean the ability to identify written words that most other children in the child’s grade group can identify. More specifically, when a word is unfamiliar (for example, “analogy”) or is a “made-up” word that has no meaning (for example, “pardet”), children with reading difficulties will be unable to read such words. The “garden variety” poor reader may also be poor in other subjects in school that do not require a great deal of reading, and he or she may perform poorly on various PASS assessment tasks. In contrast, the dyslexic has specific cognitive processing difficulties in successive tasks that are related to converting spelling to speech (phonological coding). This disability is well established in the majority of children with dyslexia by age nine, although it can be observed even at a younger age.

REVIEW

OF

RELATED LITERATURE

A review of related research in this area was done and three research studies were examined. 1. Das, Mishra, and Pool (1995) used PREP with a group of 51 fourth-grade students with reading disabilities in Edmonton, Alberta, Canada. The study involved students, aged 8 to 11 years, from four public schools. The students in the experimental

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group (31 students) were exposed to PREP whereas students in the control group (20 students) were not. The experimental group was divided into groups of four and PREP was administered approximately twice a week for a total of 15 sessions. The pre-test and post-test results of the PREP group were compared to the control group on word decoding as assessed by the Woodcock Reading Mastery Test–Revised (WRMT–R). The PREP group improved significantly more in word identification and word attack than the control group (who received no intervention), even though both groups experienced the same amount of additional instructional time. Therefore, the Das, Mishra, and Pool study also provides empirical support for the efficacy of PREP. 2. Carlson and Das (1997) used the PREP program for underachieving students in Hemet, California. In this study, students were instructed during two 50-minute sessions per week for three months. Both the PREP (22 students) and control (15 students) groups continued to participate in the regular program. The students who received PREP remediation gained significantly in word identification and word attack. This study provides strong support for the utility of PREP in improving word reading by teaching students to use appropriate processing strategies. 3. Boden and Kirby (1995), studied the effectiveness of a modified PREP for an older group. A group of fifth and sixth-grade students were randomly assigned to either a control or an experimental group. The control group received regular classroom instructions and the experimental group received PREP. The purpose of the study was to examine the effects of instruction in successive processing and phonological coding on reading. Poor readers were identified from the overall sample based on their average grade equivalent scores on the GatesMacGinitie Comprehension and Vocabulary tests. Two instructors taught the remediation program to the students. Half of the students received the program from one instructor and half from the other. Each group, which consisted of four students, received remediation for approximately three hours a week over about a seven-week period. This provided each student

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with an average of 14 hours of remediation. The results show differences between the control and PREP groups on the Word Identification and Word Attack subtests of the WRMT–R after treatment. In relation to the previous year’s reading scores, the PREP group performed significantly better than the control group. These results suggest that the poor readers had difficulty in applying successive processing to reading, and that the intervention program (PREP) provided instruction to address this problem. Boden and Kirby’s study provides evidence that the PREP instruction in phonological decoding and successive processing was effective for poor readers. In India, though, very few research studies on the efficacy of PREP have been conducted. This pilot study aims to assess the efficacy of PREP on a small target population.

METHODOLOGY PREP was administered to a group of students in the age group of seven to eleven years, who had been referred to the Maharashtra Dyslexia Association’s resource centers for amelioration of severe reading difficulties. They all had above average to superior IQ and no sensory deficits. There was a marked discrepancy between their verbal and performance scores on the WISC scores, which is an indicator of LD. They were also administered psycho–educational tests, one of which was the WRMT-R. Participants were first divided into two groups, one receiving PREP remediation and a second control group receiving remedial help, but no PREP. The PREP group received 24 sessions of training using PREP, apart from regular classroom activities and remedial sessions once a week. Children in the control group participated in regular classroom activities and also received remedial help like training in phonics, sight-reading, wholelanguage approach, and other general strategies after school for the same period. The Word Identification subtest (in which a list of meaningful words had to be read aloud) and the Word Attack subtest (in which a list of nonsense words had to be read out) of the WRMT–R

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were administered to both groups. After the intervention, both groups were tested again using the Word Identification and Word Attack subtests. The results obtained are presented in Table 11.1.

RESULTS Table 11.1 WRMT-R (Word Identification and Word Attack) Scores Following Remediation and PREP Children Administered PREP + Remediation WRMTR-Word Identification Scores

Child *A* Child *B* Child *C* Child *D* Child *E* Child *F*

Children Undergoing Remediation Only

WRMTR-Word Attack Scores

PreTest

PostTest

PreTest

PostTest

31 29 28

51 55 51

6 8 10

17 22 24

WRMTR-Word Identification Scores

WRMTR-Word Attack Scores

PreTest

PostTest

PreTest

PostTest

30 28 32

37 40 42

9 9 12

11 14 20

Source: Based on data computed by the authors.

DISCUSSION The results indicated that while both groups improved during the intervention period, there was a significant enhancement in the raw scores of the post-test, as compared to the pre-test on both, the Word Identification and Word Attack subtests of the WRMT-R in the group that had been administered PREP. Children with reading disabilities require a method of instruction that is based on specific elements of information integration that are fundamental to reading and constitute a main source of their reading difficulties. Unless the cognitive processes (simultaneous and successive processing)

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underlying reading are the focus of remediation, remediation will not be successful (Das et al., 1994). A remedial program based on repetitive performance of a number of identical items might teach near transfer, that is the learning of a specific strategy for a particular task. But the “inductive leap” needed for generalizing principles from particular experiences for far transfer does not take place effectively by only remedial training. Utilization of acquired strategies across a variety of situations is the ultimate aim of any remedial program. In other words, the teaching of basic phonetic skills or general strategies and tricks alone are inadequate for the remediation of children with reading disabilities.

CONCLUSION Content-specific remediation for a scholastic skill, such as reading, has an advantage over global remediation. Far transfer is more likely to occur here. Children with LD do have the skill for successive and simultaneous processing but do not utilize these effectively. Training in PREP makes them aware of the strategy to be used in new tasks and encourages their application to academic tasks through the use of verbal mediation and internalization processes. Thus, PREP can not only be used for reducing specific deficits in the older child’s cognitive functioning, but can also be used as a tool for cognitive stimulation and enrichment to reduce the chances of young children developing reading difficulties at a later stage.

REFERENCES Boden, C. and J.R. Kirby. (1995). ‘Successive Processing, Phonological Coding and the Remediation of Reading’, Journal of Cognitive Education, 4(2&3): 19–32. Carlson, J.S. and J.P. Das. (1997). ‘A Process Approach to Remediating WordDecoding Deficiencies in Chapter 1 Children’, Learning Disabilities Quarterly, 20: 93–102. Das, J.P. (1988). ‘Coding, Attention, and Planning: A Cap for Every Head’, in J.W. Berry, S.H. Irvine and E.B. Hunt (eds), Indigenious Cognition: Functioning in Cultural Context, pp. 39–56. NATO Series, Dordrecht: Nijhoff, The Netherlands.

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Das, J.P. (1998). Dyslexia and Reading Difficulties. Mumbai: Maharashtra Dyslexia Assoc. Das, J.P., J.A. Naglieri and J.R. Kirby. (1994). Assessment of Cognitive Processes: The PASS Theory of Intelligence. Boston: Allyn & Bacon. Das, J.P., J.R. Kirby and R.F. Jarman. (1975). ‘Simultaneous and Successive Synthesis: An Alternative Model’, Psychological Bulletin, 82(1): 87–103. Das, J.P., R.K. Mishra and J.E. Pool. (1995). ‘An Experiment in Cognitive Remediation of Word-Reading Difficulty’, Journal of Learning Disabilities, 28(2), 66–79. Luria, A.R. (1966). Higher Cortical Functions in Man. New York: Basic Books. ——————. (1973). The Working Brain: An Introduction to Neuropsychology. New York : Basic Books. ——————. (1980). Higher Cortical Functions in Man (2nd ed.). New York: Basic Books. Naglieri, J.A. and J.P. Das. (1987). ‘Construct and Criterion Related Validity of Planning, Simultaneous and Successive Cognitive Processing Tasks’, Journal of Psychoeducational Assessment, 5(4): 353–63. ——————. (1989). ‘A Cognitive Processing Theory for the Measurement of Intelligence’, Educational Psychologist, 24(2): 185–206. ——————. (1990). ‘Planning, Attention, Simultaneous and Successive Processes as a Model for Intelligence’, Journal of Psychoeducational Assessment, 8(3): 303– 37. ——————. (1997). Cognitive Assessment System. Interpretive Handbook. Itasca, IL: Riverside Publishing. Smith, E.C., D.M. Finn and C.A. Dowdy. (1993). Teaching Students with Mild Disabilities. New York: Harcourt Brace Jovanovich.

12 Scaffolding to Learn An Attempt DHARMISHTHA H. MEHTA

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tudies on the achievement of students with learning disabilities (LDs) have consistently demonstrated that they perform poorly on academic tasks and are poor at problem-solving. This has been attributed not to, low ability but to a lack of or an inappropriate use of learning strategies and poor monitoring of the process of learning (Chan and Cole, 1986; Hallahan et al., 1996; Larson and Gerber, 1987; Overalle and Metsenare, 1990). Learning strategies are systematic, deliberate planned activities used to gain and retain knowledge (Reid, 1980). They are processes that underlie performance on thinking tasks and are always purposeful and goal oriented. Strategies are the outcome of an efficient cognitive functioning and therefore those with a LD are generally unable to develop and use strategies for learning. Students with LDs fail to process information or apply knowledge effectively. They lack the self-regulation process, which is necessary for effective learning and problem-solving (Reddy et al., 2000; Torgesen 2001; Wong, 1992). As students with LDs are lacking in problem-solving skills, it is imperative to provide them opportunities for the acquisition of these skills. The importance of problem-solving in the process of learning has not received much attention as reading and math (Yan and Jitendra, 1999). Hence this study. Over the last 15 years or so the metaphor of scaffolding has played an important role in discussions of the teacher’s activity during effective instructional exchanges in

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the classroom (Wong, 1998). Central to the scaffolding metaphor are the two notions of support and relinquishment. Scaffolded instruction supports the child’s construction of new understanding but does so in a manner that allows for the eventual removal of that support. Such instruction has been seen as a powerful force in helping children to take ownership of new knowledge and procedures. Although the promise of scaffolded instruction for children with LDs is great, effective implementation is fraught with difficulties (Stone, 2002). The present study sought to study if adequate problem-solving skills could be developed among the learning disabled students by teaching them to use strategies. The following null hypothesis were proposed for this study: 1. Training in strategies will not have any significant effect on the post-test scores in the Test of Problem Solving (TPS). 2. The school examination marks and the post-test scores in TPS will not be positively and significantly related.

METHODOLOGY The study used a single group, pre-test post-test experimental (E) design. Using a purposive sampling technique the sample of N=60 was drawn (Table 12.1). Table 12.1 Description of the Sampling Process Sample Description

A B C D E

Students of Class 6 from govt. aided English-medium schools in the Northern suburb in Mumbai Students from Class 6 scoring M—1 SD on the class mean in the last examination Those scoring more than 30 on the Behavioral Checklist to screen LD (BCSLD) Those falling in the average to above average range on the intellectual functioning on the RPM Those scoring less than 50 on the Diagnostic Test of Learning Disability (DTLD) Those scoring less than 15 on the Test of Problem Solving (TPS)

Source: Based on data computed by the authors.

No. 380 120 102 98 92 60

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THE TOOLS The tools used for this study were as follows: 1. The Raven’s Progressive Matrices—a non-verbal test of intellectual functioning was used to identify subjects with average to above average intelligence. 2. The Behavioral Checklist to Screen the Learning Disabled, a standardized test, was used to screen learning disabled children primarily on grounds of behavior. It sought to uncover deficiencies in motor, cognitive, connative, and affective areas. 3. The Diagnostic Test of Learning (DTLD), a standardized test to identify the LD was used. It sought to assess the performance of students in 10 areas of psychological process of learners, since LDs would span a variety of abilities and disabilities. These areas covered both perceptual and cognitive areas. 4. The TPS was constructed by the researcher to identify deficits in process that led to a failure in problem-solving among the learning disabled children. The study was conducted in three stages: 1. the pre-test, 2. the treatment, and 3. the post-test.

THE PRE-TEST At this level, the subjects were administered the TPS.

THE EXPERIMENTAL TREATMENT The treatment was provided to the subjects selected. It was a 9-hour strategy training program that spanned over six sessions, one and a half hours each, in groups of six. The strategy used was S–SWEL and the following example will illustrate the underlying process. This exercise was given to students:

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In the rest-house, there were many extra thick rugs and bedsheets, but not mattresses to sleep on. We had just enough for our family. Suddenly, three guest from our hometown arrived, late in the night. Our problem now was providing them mattresses to sleep on. What shall we do? S = State the problem–providing mattresses to the guests, when there are no mattresses available. S = search for the possible solutions: 1. Shall tell the guests to stay somewhere else. 2. Go to the market and buy new ones. 3. We, family members, shall share the mattresses to provide for them. 4. Make them sleep on the mattresses and the two of us will sleep on the floor. 5. Make use of extra rugs and bedsheets to sleep. W =Work out a plan: Fold the rugs according to the size of the beds. Place them one above the other. Cover it with a bedsheet to give it a bed-like appearance. E = Execute the plan—do as planned. L = Link it to the problem—problem was that of providing mattresses to the guests; solution was by way of making a bed from the extra rugs. The students were trained in the use of strategy through a number of such exercises. Intensive practice to use the problem-solving strategy across the domains of arithmetic, figural, and social problem-solving was provided in sessions, each of one and a half hours. At the end of the training program, the subjects had mastered the strategy S-SWEL.

POST-TEST After a gap of 26 days, subjects of both Experimental (E) and Control (C) groups were evaluated on the previously used TPS.

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RESULTS Hypothesis 1 The strategy training S-SWEL will not have any significant effect on the post-test scores of the subjects in the TPS (Table 12.2). Table 12.2 Means, SDs and t-value of the Performance of the Subjects on Test of Problem Solving under Pre-test and Post-test Conditions Condition

Pre-test Post-test

Experimental Group N = 30 Mean

SD

t

df

Level of Significance

09.30 15.50

3.42 3.14

7.46

29

P > .01

Source: Based on data computed by the authors.

Table 12.2 shows that the difference between the means of the subjects on the Test of Problem Solving from pre-test to the post test is 6.2. At the post-test level, there is an increase of 6.2 in the mean performance of the students, that is, from 9.3 at the pre-test it has risen to 15.5. This could be attributed to the effect of the strategy-training program S-SWEL that was given to subjects. The “t” value of 7.46 indicates a true difference between the obtained score at the pre-test and is not because of chance factors. The difference is significant at and beyond .01 level of confidence.

Hypothesis 2 The school exam marks and the TPS scores of the subjects will not be positively and significantly related (Table 12.3). The correlation value of .30 in the pretest condition shows a nonsignificant positive relationship between the pre-test performance of the subjects on TPS and Scholastic Achievement to the extent of 30 percent. The correlation value of .40 in the post-test condition is indicative of higher degree of relationship between post-TPS scores and scholastic achievement as a result of the treatment. The results

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Dharmishtha H. Mehta Table 12.3 Co-efficient of Correlation between Pre- and Post-test Scores on TPS and Scholastic Achievement Obtained by the Subjects Experimental Group N = 30

Condition Pre-test performance on TPS and scholastic achievement Post-test performance on TPS and scholastic achievement

r

df

Level of Significance

.30

28

NS

.40

28

.05

Source: Based on data computed by the authors.

show that the treatment has shown a significant positive effect. It means that with formal training, students could be trained in the use of appropriate strategies which would improve their academic performances and problem solving abilities (Rottman and Cross, 1990).

DISCUSSION The mean performances of the subjects on the TPS as a result of training in strategy S-SWEL rose by 6.20. The efficacy of the strategy program has been thus established. The reason for their poor performance at pre-test could be attributed to their failure to perceive the available information in the correct perspective. To illustrate, the example from TPS could be taken where the problem was of making the design with the available material. Most learning disabled children’s immediate response was “will ask a friend to give the missing shape” or “will not make the design”—looking for an easy way out, rather than applying the mind to get the task done. They failed to realize that since an extra sheet was provided, the required shape could be cut from that to make the design. This response typifies the learning-disabled students. Being used to failure—often the effort to “think” is absent in them (Lerner 1988, Reid, 1980). The processes involved in adequate problem-solving are attention, concept organization, memory, cognitive mapping, conceptual clarity, and social cognition (Jitendra et al., 2002, Flavell, 1977). A problem in any of these lead to inadequate problemsolving. A failure to analyze data systematically and a tendency to overlook significant details too was observed in the sample studied.

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The present study concerned itself with the developing skills, through the use of strategies. The goal of training was to help pupils in their general comprehension corresponding to scholastic achievement. The pupil’s failure on academic tasks was traced primarily to a weakness at the comprehension level. Because of deficiencies in language and a lack of cognitive control over the learning process, these children failed miserably at academic work, despite normal intelligence. By the strategy training S-SWEL an attempt was made to help students check, control, and monitor their learning processes. The inability to focus attention on explicit and implicit facts in the passage, the failure to identify the appropriate strategy of learning and its usage were some of the characteristic behaviors of students at the start of the program. Training in problem-solving skills helped them plan, control, and monitor their learning process to the extent of transferring it to other areas, which helped them improve their study and learning skills, and thus affected a positive change on their academic achievement. Other empirical evidences in learning suggest that the long-term gains among those taught strategies were significantly higher than those who were not taught (Overalle and Metsenaere, 1990). Improved gains in the reading scores of subjects with severe reading disabilities and its internalization have also been recorded by the study of Torgesen et al. (2001) when reading skills were taught in flexible, small groups with clear reading instructions and explicit reading strategy instructions. Jitendra et al. (2002) too reiterate, through their 12-hour strategy training program to develop problem solving in math, that not only did the subjects substantially improve their performance in math but also generalized the strategy usage to novel problems. The internalization of the strategy usage was thus demonstrated. It was thus confirmed that cognitive training along with a package of self-control procedures tended to improve the academic performance of learningdisabled students. This enhancement was evident on those academic tasks on which the learning-disabled students generally faltered due to attentional deficits and a lack of cognitive control and organization. The educational implications of this study could be summarized as follows: 1. Knowledge acquisition should be secondary to skills in knowledge acquisition.

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2. The instructional material should be so developed that strategy instruction are incorporated within them. 3. Attention should be paid to the process of learning and not just the content, for if the process is correct it could be internalized to master more complex matter at a later stage. 4. Proper Remedial education corrects deficiencies in the learning process of LD children, and improves their learning effectiveness, thus decreasing the number of dropouts from schools.

REFERENCES Chan, L., and P.G. Cole. (1986). ‘The Effects of Comprehension Monitoring Training on the Reading Competence of Regular Class Students’, Remedial and Special Education, 4(1): 6–11. Flavell, J. (1977). Cognitive Development. Englewood Cliffs, N.J.: Prentice-Hall. Hallahan. D.P., J.F. Kauffman, and J.W. Llyod. (1996). Introduction to Learning Disabilities. Boston: Allyn & Bacon. Jitendra, A., M.C. Dipini and J.N. Person. (2002). ‘An Exploratory Study of Schema—Based Word Problem Solving Instruction for Middle-School Students with LD’, Journal of Special Education, 36(1): 23–38. Lerner, J.W. (1988). Learning Disabilities: Theories Diagnosis and Teaching Strategies (5th edition). Baston: Hougton Mifflin. Larson, K.A. and M.N. Gerber. (1987). ‘Effects of Social Meta Cognitive Training for Enhancing Overt Behaviour in Learning Disabled and Low Achieving Delinquents’, Journal of Learning Disabilities, 54 (3): 201–11. Overalle, M.V. and M. Metsenare. (1990). ‘The Effects of Attribution Based Intervention and Study Strategy’, The British Journal of Educational Psychology, 60(3): 229. Reddy, G.L., R. Ramar, and A. Kusuma. (2000). Learning Disabilities. New Delhi: Discovery Publishing House. Reid, K.D. (1980). A Cognitive Developmental Approach to Learning Disabilities. Boston: Allyn and Bacon. Rottman, J.R. and D.P. Cross. (1990). ‘Using Informed Strategies for Learning to Enhance Reading and Thinking Skills in Children with LD’, Journal of Learning Disabilities, 23(5): 270. Stone, C.A. (2002). ‘Promises and Pitfalls of Scaffolded Instruction for Students with Language Learning Disabilities’, in K.G. Butler and E.R. Silliman (eds), Speaking, Reading and Writing in Children with Language Learning Disabilities: New Paradigms in Research and Practice, pp. 175–98. Mahwah, NJ: Lawrence Erlbaum. Torgesen, J.K., A.W. Alexdander, R.K. Wagner, C.A. Rashotte, K.S.V. Voeller and V. Gross–Tusr. (2001). ‘Intensive Remedial Instruction for Children with

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Severe Reading Disabilities: Immediate and Long Term Outcomes from Two Instructional Approaches’, Journal of Learning Disabilities, 34(1): 33–58. Wong, B. (1992). ‘On Cognitive Process Based Instruction: An Introduction’, Journal of Learning Disabilities, 25(3): 150–52. Yan, P.X. and A.K. Jitendra. (1999). ‘Effects of Instruction in Mathematical Word Problem Solving for Students with L.D’, Journal of Learning Disabilities. 32(4): 207–24.

13 Detailed Assessment of Specific Learning Disability and Intervention in School Children MONICA MONGIA, RAJA SADHU, AND MANJU MEHTA INTRODUCTION

S

pecific learning disabilities (SLD) are characterized by deficits in specific academic, language, speech, and motor skills and are not caused by demonstrable physical or neurological disorders, a pervasive developmental disorder, mental retardation, or deficient educational opportunities (Kaufman and Kaufman, 2001). Specific learning disabilities prevent the growth and development of a child. Learning disabilities (LDs) become worse when associated with other co-morbid disorders such as attention-deficit hyperactivity disorder (ADHD), conduct disorder, oppositional defiant disorder, and so on (Greenhill, 2000). The mental, emotional, and behavioral trauma that results due to LD to the child as well as his family may be hard to bear (Lavin, 2001). It not only affects the academic performance but also the motivation and self-esteem of the child. Due to SLD, interpersonal relationships are impacted upon negatively, and so are parental expectations and peace of mind. Learning disabilities are one of the prime causes of poor scholastic achievements. According to studies conducted in different parts of the world, prevalence of specific reading disorder is 4 percent of

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school age population. The prevalence of specific spelling disorder is almost same as that of specific reading disorder, and the prevalence of specific disorder of arithmetic skills is 6 percent of the school age population (Sadock and Sadock, 2000). In India, very few focal studies have been conducted as far as the prevalence of SLD is concerned and the results are variable. In a multi-centric study on child psychiatric epidemiology funded by Indian Council for Medical Research, the prevalence, as reported by NIMHANS (2001), is 7.2 percent and the prevalence of specific reading disorder as reported by King George’s Medical College (KGMC) (under the same multi-centric study) is 0.52 percent. Considering that LDs are so prevalent, adequate, early, and exact assessment of the area of deficit holds promise for the development of early intervention programs. This is important as compensatory skills training for children can be attempted only if the exact nature of the problem is known. Assessment, which is the systematic process of collecting information about the child, examining levels of performance, strengths, and weaknesses in order to make educational decisions about the future them becomes imperative. Combining formal and informal methods of assessment would provide additional information for a comprehensive assessment. Formal assessment would involve using standardized tests while informal assessment would make use of non-standardized tests such as observation, interviews, and questionnaires (Sadock and Sadock, 2000). In almost all the cases, the student is being assessed because he has already experienced failure in some aspect of his school career (Jensen et al., 1993). It is important to be aware of what has gone wrong. This may involve evaluating the student’s early background and even considering the familys’ history including that of LDs. Adults are often prompted to seek an educational assessment either because of experiencing difficulty with work aspects, or because they are embarking on a course of further education and need an explanation for the learning barriers, which stem from their school career. In all situations, it is vital to gather as much background information as possible as this often provides useful insights into the options available to the individual and can help determine which interventions will be effective.

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This study was an attempt to outline the various strategies for assessment and intervention in SLD. Efforts have been made to use different assessment strategies for identifying children with SLD. These involved assessment of deficits in academic skills including reading, writing, attention and concentration, and non-academic skills such as social skills and motor co-ordination. Also, highlighted are the specific strategies for intervention used for improving upon the deficits in the areas of reading, writing, expression, and so on. The recommended interventions are based on the nature of the deficits shown by the students. In this way, specific intervention packages were used. To facilitate intervention, the assessment of soft neurological signs were also undertaken. Remedial measures have been proposed.

METHOD Study Group The participants were 42 children, 6–12 years of age who attended Child and Adolescent Psychiatry Clinic at the All India Institute of Medical Sciences (AIIMS), New Delhi, and were studying in classes 1–7 in schools in New Delhi. Fifteen children were clinically diagnosed as having SLD as per International Classification of Diseases: Classification of Mental and Behavioural Disorders, 10th Edition (WHO, 1992). The remaining 27 children had no disability or disorder. The children with SLD had deteriorating academic performance while the children in the control group showed average or above average performance. All children were from middle or upper/high socio-economic status.

PROCEDURE At the outset, two groups were constituted for comparison of SLD children with normal children. Fifteen children with a clinical diagnosis of SLD constituted the Experimental Group whereas 27 normal children formed the Control Group (Figure 13.1). Baseline

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Disability and Intervention in School Children Figure 13.1 Flowchart Showing Procedure Experimental group (n=15)

Control group (n=27)

Baseline Assessment IQ evaluation

ACADEMIC AREAS Reading

Writing

NON-ACADEMIC AREAS

Standard maintained by using NCERT books

Spelling

Social skills

Motor co-ordination Impulsivity

Arithmetic Attention and Concentration ANSERS Neurological soft signs assessment (PANESS)

Locating exact areas of difficulty in both groups

No intervention needed

Skill-based intervention session tailored as per each child’s need/area of defect Source: Based on data computed by the authors.

assessment of Intelligence was done using Malin’s Intelligence Scale for Indian Children for both the groups (Malin, 1970). Along with IQ, an assessment of academic areas like, reading, writing, spelling, arithmetic, attention, and concentration was done. In addition, assessment was done using the ANSERS scale (Levine, 1985). The

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ANSERS scale is useful for assessment of academic and related performances, problems in selective attention and activities, and behavioral problems of school children. The assessment of scholastic skills was also done using National Council of Educational Research and Training’s (NCERT) textbooks as a standard for a particular class. If a child could not perform up to his class level, books of a class lower to his were used. The initial assessment included assessment of reading, that is, some paragraphs from both language textbooks (English and Hindi) were read. The child reads a paragraph once overtly then covertly and finally the examiner reads out the paragraph to him. The comprehension on the part of the child was assessed each time a paragraph was read by the child and when read out by the examiner. Besides, reading speed, omissions, additions, and substitution errors committed by the child were recorded. Other significant aspects that were noted included recognition of discrimination between words, sequencing, recall, and so on. For assessing reading comprehension, Cloze Test (Mayer et al., 1999) was used, that is, every fifth or sixth word was removed from a sentence and the child was asked to fill in spaces. The Cloze Test is intended to assess a student’s skill in comprehending written directions for a language game. In determining which word fits in a blank, students must use strategies to comprehend verbal directions. The writing skills were assessed by making the child copy a paragraph, write a paragraph on a given topic, and write a paragraph while the examiner dictates it. The child’s choice of words, content of paragraph, organization, grammatical errors, spellings, and punctuations was analyzed by this method. Paragraphs were written by the child both in Hindi and in English. Spellings could be assessed from the paragraph writing as well as through writing of dictated words from the given texts. A note of errors made by the child (which letters or sounds were confused, whether letters were omitted or added to the word, and whether capital and small letters were used correctly or not) was done. Other things recorded were whether the child mixes order of words, takes long time in expressing. Writing also helped in knowing whether the child could plan and make the necessary movements to produce words and can recall the formation of a particular alphabet.

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Problems in arithmetic were assessed by the ability or inability to recognize symbols (+, –, x; problems in copying, carrying, counting, sequential procedures; difficulty with multiplication tables; understanding the statement problems in mathematics, and so on. The social skill deficits were also assessed, such as verbal expression, shyness, lack of confidence or self-esteem, and failure in social conduct. This was done using detailed interview with the child in question as well as with the parents. In addition, a report was sought from the school teacher on how the child relates to other children at school. The PANESS (Physical and Neurological Examination of Soft Signs) scale was administered to assess the presence of neurological soft signs. It was developed by the National Institute of Mental Health in 1976. It consists of two parts—the physical examination and the scored neurological examination for soft signs. The latter was being used in our study. The process and procedures used in assessment are presented in the form of a flow chart (Figure 13.1).

Intervention Specific Learning Disability cannot be cured or prevented, but the symptoms of SLD can be alleviated to some extent. Intervention was carried out for 15 children with SLD for both academic deficits as well as social skills deficits. For improvement in reading skills, training was carried out in two steps. The children were taught to associate single alphabets (graphemes) with their sounds (phonemes) in Step 1. In Step II, training was provided for words. Practice for the two steps was consistently done. In addition, adequate reinforcement was given for appropriate pronunciations. Consistently revising and practising regularly was recommended. The child was suggested to look at the word until he had spoken it, and then he was instructed to speak out carefully observing his oral kinesthetics. The child was instructed to look at the word and form a clear image of it before speaking it. Then while pronouncing the word, the movements of his facial muscles was observed (oral kinesthetics).

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Flash cards were used for spelling. The longer words were taught by breaking them into component parts, for example, ‘Hip/pot/a/mus. Similar strategies based on theoretical understanding of SLD were reinforced in children’s daily routine academics and for non-academic SLD aspects, that is, for improving clumsiness, coordination, sequential organization and attention. Behavioral problems in case of some children were also dealt with. Behavioral aspects were intervened with—including homework avoidance, cheating, aggression, controlling, quitting tasks, and disorganization. All the 15 children underwent around 10–12 weeks of skill-based training on a one-to-one basis depending on their unique needs and the extent of improvement in them was noted, thereafter. The scores obtained by the Experimental and central groups on sub-tests of intelligence are presented in Table 13.1.

Results Table 13.1 IQ Subtest Scores of Experimental and Control Groups Experimental Group

Control Group

Subtest

Mean

SD

Mean

SD

Information Comprehension Arithmetic Digit span

108.9 119.9 093.7 0 88.8

12.43 12.70 15.80 15.80

094.2 101.4 94. 90.6

11.46 09.77 08.32 09.44

Note: IQ Ranges: Dull average (80–89), above average intelligence (110 and above), Average–above average intelligence (90–109). Wide variation between mean subtest scores indicates partly towards the phenomenon of scatter in original subtest scores, which is indicative of SLD. Source: Based on data computed by the authors.

The problems faced by subjects as measured by the ANSERS scale (Table 13.2) and the PANESS scale (Table 13.3) are presented in the following tables. The nature of academic problems faced by both groups is presented in Table 13.4.

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Table 13.2 Problems Assessed by ANSERS Scale Experimental

Control

1. Performance delayed less or more than 1 year in more number of items 2. Problems in Selective attention activity 26% cases had mild problem 33% cases had moderate problem 41% cases had severe problem

1. Performance appropriate for age in more number of items

3. Behavioral Problems 33.3% cases had no problem 53.3% cases had mild problem 13.3% cases had moderate problem

2. Problems in selective attention activity 63% controls had no problem 18.5% controls had mild problem 18.5% controls had moderate problem 3. Behavioral Problems 81.5% controls had no problem 18.5% controls had mild problem

Note: Below average performance, more problems in selective attention activity and more behavioral problems were seen in experimental case group. Source: Based on data computed by the authors. Table 13.3 Abnormalities Found on Application of PANESS Scale on Experimental and Control Children Experimental Group

Control Group

Significantly more amount of abnormalities compared to the control group were seen in areas of : Graphaesthesia Maintenance of posture Motor Task Two point discrimination

No abnormality was found in significantly more amount in control group compared to the experimental group However, when optokinetic test was considered: 1 case showed Nystagmus on left side 1 case—broken pursuits bilaterally 1 case—nystagmus on right side

Normal aspects: Co-ordination Stereognosis Face hand/face noise Distal Extremity Rhythmic Movement

Comparable Comparable Comparable Comparable

Note: More neurological soft signs observed in experimental group. Source: Based on data computed by the authors.

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Experimental Group

Control Group

Reading Speed below expected level Missing words Adding/substituting words Disorganized Spelling—most affected Arithmetic—moderately affected Writing Expression—second most affected

Some distracted (2 Cases) 2 cases disorganized Minimal difficulties in spelling, arithmetic, and expression

Note: Results were analysed using descriptive statistics. Source: Based on data computed by the authors.

DISCUSSION This paper is a part of an ongoing Indian Council of Medical Research (ICMR) study called ‘Development and Dissemination of Intervention Strategies for Specific Learning Disability’ which began in October 2001. As the results have shown, differences were observed between the two groups. The number of participants in both groups was small as this paper represents the data collected till date for the study. A qualitative analysis of the results was carried out. ANSERS clearly showed that SLD impacts academic performance, selective attention, and behavior regulation. Below average performance was reported by parents of children with SLD on ANSERS while average performance was reported for normal children. This is in line with the general theoretical framework. Fortyone percent of SLD children have severe problems in selectively attending while only 18.5 percent of control children had moderate problem. This emphasizes that attention problems are present in both normal and SLD children but the extent to which both can manage to attend varies. Moderate behavioral problems too were reported in 13.3 percent SLD children while mild problems were reported in 18.5 percent of children in control group. Malin’s Intelligence Scale for Indian Children (MISIC), which is the Indian Adaptation of WISC, indicated that IQ scores ranged from dull average to above

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average intelligence category with very low scores on digit span and below average to average scores on arithmetic for most SLD children. The control group children had average to above average IQ scores. Greater scatter in between subtest scores of MISIC was observed for experimental group children. Higher scatter is indicative of specific learning disability. That is generally considered to be one of the most prominent indications toward LD and points toward the need for intervention specific to the area of deficit. Some control group children (one or two) seemed to be distractible and disorganized as they could not focus on the task for long, had difficulty comprehending instructions, and answered questions in an unsystematic manner. These children mostly belonged to the dull average intelligence category. Some also had hyperactive traits. However, these problems were more common in experimental group. Reading problems and deficit in spelling, arithmetic, and writing were found to be more in the SLD group. More neurological soft signs were found in the SLD group which is in consonance with the previous research, as it is assumed that SLD is due to an internal deficit and not environmental problems. Graphesthesia, maintenance of posture, motor task, two-point discrimination were the areas of problem in the SLD group while one case in control group showed nystagmus on left side and another case in this group showed nystagmus on right side on opto–kinetic tests. In other aspects, the two groups were comparable. It is suggested that early identification of the problem be done. We can help these children if we give them real push at the start (Foorman et al., 1997). Special training program is beneficial in the sense that these have given promising results and have helped children in making great progress, and the positive effect seems to persist as the children move up in the school (Wasik and Slavin, 1993). Multi-sensory approaches (Table 13.5), which have generally been used in these programs, aim to establish automatic responses to phonemes and graphemes, leaving more working memory available for higher thinking and writing skills. One of these modalities is likely to be weak in a child with SLD. By learning this way, he learns to use them in synchrony. This will make full use of his assets while awakening and integrating his weak areas in the process.

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Table 13.5 Four Modalities of the Multi-sensory Approach Auditory (Listening) Oral Kinesthetic Visual (Speaking) (Looking) Manual Kinesthetic (Writing) Source: (Walker and Brooks, 1996).

For promoting reading comprehension, it is important to thoroughly explain the meaning of words in context (Weisberg, 1988) and that background information for concepts and ideas is given through explicit instruction (Pearson and Leys, 1985). Reading cards are generally used to focus child’s attention on the target letter and its associated sound, and thus acts as a memory aid for example, carrot I k I. It requires awareness of sound, of writing a letter and rightly positioning his tongue, teeth, and lips to establish the graphemephoneme links. It is important, therefore, to articulate slowly and write simultaneously (Ball and Blachman, 1988). Phonological awareness training, therefore, becomes imperative (Blachman 1997; Brostrom and Elbro, 1997; Lie, 1991; Skjelfjord, 1977). Dowhower (1994) stressed the importance of repeated reading. Studies have also emphasized that cursive handwriting be stressed since early on. Posture is important—legs are to be planted on floor, sitting with straight back and shoulder, supporting the writing hand below the wrist from the table, and support from other hand to hold the paper in place. As far as arithmetic is concerned, considering the understanding and mastery of the language of mathematics are emphasized. Shortterm memory is as crucial when doing arithmetic as is the speed of information processing. Therefore, if easy concepts are taught first and tough ones later (Layton and Koenig, 1998) and a good learning environment (Scanlon and Vellutino, 1997) is created for a child with SLD, performance is expected to show drastic improvement. Mastery, over learning, and automatization help in improving the skills of SLD children. Patience, sensitivity, and understanding are needed; it is important to demonstrate that mastery can give pleasure and satisfaction, and it is important to awaken love of reading, to make the pupil believe in him/herself (Dougherty and Johnston, 1996).

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REFERENCES Ball, E. and B. Blachman. (1988). ‘Phoneme Segmentation Training: Effects on Reading Readiness’, Annals of Dyslexia, 38, 208–25. Blachman, B. (1984). ‘Relationship of Rapid Naming Ability and Language Analysis Skills to Kindergarten and First-grade Reading Achievement’, Journal of Educational Psychology, 76: 610–22. ——————. (1997). ‘Early Intervention and Phonological Awareness: A Cautionary Tale’, in B. Blachman (ed.), Foundations of Reading Acquisition and Dyslexia: Implications for Early Intervention. London: Lawrence Erlbaum Associates. Brostrom, I. and C. Elbro. (1997). ‘Prevention of Dyslexia in Kindergarten: Effects of Phonological Awareness Training’, in C. Hulme and M. Snowling (eds), Dyslexia: Biology, Cognition and Intervention. London: Whurr. Dougherty, K. and J. Johnston. (1996). Overlearning, Fluency and Automaticity. Behaviour Analyst, 19: 289–93. Dowhower, S. (1994). ‘Repeated Reading Revisited: Research into Practice’, Reading and Writing Quarterly: Overcoming Learning Difficulties, 19: 343–58. Foorman, B., D. Francis, S. Shaywitz, B. Shaywitz, and J. Fletcher. (1997). ‘The Case of Early Intervention’, in B. Blachman (eds), Foundations of Reading Acquisition and Dyslexi:. Implications for Early Intervention. London: Lawrence Erlbaum Associates. Greenhill L.L. (2000). Learning Disabilities: Implications for Psychiatric Treatment Volume 19, American Psychiatric Pub., Inc. Guy, W. (1976). Physical and Neurological Examination for Soft Signs (PANESS). ECDEU Assessment Manual for Psychopharmacology, Rockville, MD: NIMH. Jensen, P.S., M. Roper, P. Fisher, J. Piacentini, G. Canino, J. Richters, M. RubioStipec, M. Dulcan, S. Goodman, M. Davies. (1995). ‘Test-related Reliability of the Diagnostic Interview Schedule for Children (DISC 2–1); Parent, Child and Combined Algorithms, Archives of General Psychiatry, 52(1), 61–71. Jenson, W.R., S.M. Sheridan, D. Olympia and D. Andrews. (1994). ‘Homework and Students with Learning Disabilities and Behaviour Disorders: A Practical, Parent-based Approach’, Journal of Learning Disabilities, No. 27(9): 538–48. Kaufman, A.S. and N.L. Kaufman. (2001). Specific Learning Disabilities and Difficulties in Children and Adolescents: Psychological (eds), Cambridge University Press. Lavin, J.L. (2001). Special Kids Need Special Parents: A Resource for Parents of Children with Special Needs. New York: Berkley Books. Layton, C. and A. Koenig. (1998). ‘Increasing Reading Fluency in Elementary Students with Low Vision Through Repeated Readings’, Journal of Visual Impairment and Blindness, 92: 276–93. Levine, M.D. (1985). Aggregate Neurobehavioural Student Health and Educational Review (ANSER) system. USA: EPS. Lewis, M. (2002). Child and Adolescent Psychiatry—A Comprehensive Textbook, 3rd ed. NewYork: Lippincott.

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Lie, A. (1991). ‘Effects of a Training Program, for Stimulating Skills, in Word Analysis, in First-grade Children’, Reading Research Quarterly, 26: 234–50. Malin, F. (1970). Malins’ Intelligence Scale for Indian Children (MISIC) Shanti Niketan. Mayer, R.E., M. Schustack and W. Blanton. (1999). ‘What do Children Learn from Using Computers in an Informal Collaborative Environment?’, Educational Technology, 39: 215–27. Pearson, P. and M. Leys. (1985). ‘Teaching Comprehension’, in T. Harris and E. Cooper (eds), Reading, Thinking and Concept Development. New York: College Board Publications. Sadock, B.J. and V.A. Sadock. (2000). Comprehensive Textbook of Psychiatry. Vol. II, 7th ed. NY: Lippincott Williams and Wilkins. Scanlon, D. and F. Vellutino. (1997). Instructional Influences on Early Reading Success: Perspectives. The International Dyslexia Association, 23, 35–37. Skjelfjord, V. (1977). Metoden I den Forste Leseundervisningen. Oslo: Glydendal Norsk Forlag. Townend, J. and M. Turner. (2000). Dyslexia in Practice—A Guide for Teachers. NY: Plenum Press. Walker, J. and L. Brooks. (1996). Dyslexia Institute Literacy Programme. Staines: The Dyslexia Institute. Wasik, H. and R. Slavin. (1993). ‘Preventing Study Failure with One-to-one Tutoring. A Review of Five Programs’, Reading Research Quarterly, 28: 179–200. Weisberg P. (1988). ‘Direct Instruction in the Preschool’, Educational and Treatment of Children, 11: 249–363. World Health Organization (WHO). (1992). The ICD-10 Classification of Mental and Behavioural Disorders: Diagnostic Criteria for Research. Delhi: Oxford University Press.

14 Identifying Issues and Looking Ahead GEERDINA M. VAN

DER

AALSVOORT

T

he Introduction to this book clarified that a first Indian conference on learning disabilities (LDs) was organized to present the current scenario in India with respect to research in the field of LDs. We will first discuss a definition of LD that is widely used over the world. Then we will consider the views of the authors who presented their findings in this book.

DEFINING LEARNING DISABILITIES Learning disabilities as a concept is described in the Diagnostic Statistical Manual (DSM-IV-TR, 2000). The definition includes three parts—the child performs poorly in comparison to peers who have had comparable opportunities to education (lagging behind in the classroom for more than one year); second, the child performs poorly on norm-referenced tests (the child performs poorly compared to the normative group). The third characteristic is that special treatment consisting of individualized instructions and opportunities to practice does not lead to catching up: the child’s performance is resistant to treatment. The resistance to intervention reveals that neurological problems are the base of the problems with learning— LD refers to developmentally caused disability. The internationally accepted definition of LD implies that any child suffering from poor progress in academic skills can be identified with

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LD only after having met the three criteria mentioned before. There are children who show lags in academic progress, but they would improve their skills if only they would be provided with adequate instruction. The identification of LD thus always includes information about the schooling provided. The children mentioned before would most certainly profit from interventions at school level. This means offering schools opportunities to implement adequate teaching methods and offering guidance to the teachers when using the methods for a longer period of time.

THE MAIN ISSUES

OF THE

CHAPTERS

The question is how to proceed in India with respect to LD. The authors of the book claim that identification and awareness of teachers with respect to LD go together. Each author takes a position with respect to defining LD, refining assessment, and dealing with helping students identified with LD. Six chapters offered in this book relate to the definition. Another three contributions identify the role of teachers in screening LD, and four chapters deal with assessment and intervention. We will discuss the themes one after the other.

ISSUES RELATED

TO

DEFINITION

Where Kapur, Karanth, Verma, Van der Aalsvoort, and Gupta share the definition of LD described in the previous section, each of them approaches the definition differently. Kapur draws attention to children from rural areas where effective teaching is problematic, which suggests that the students attending rural schools are performing poorly. The data collected in rural communities clarifies that extrinsic variables are the reason for poor performance with respect to reading, writing, and arithmetic. She describes two issues of concern for India. The first one is socio-economic status (SES). Children from rural areas often come from poor families where making a living is the main issue and schooling is less important, and the children are expected to join the labor force in order to meet the family’s need on a daily basis. Moreover, in many of the rural schools the

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central syllabus is offered in the school, which may overburden the child’s understanding of the concepts offered. Kapur suggests that the assessment of LD should include issues such as SES and teaching content to be sure that children are not falsely diagnosed as learning disabled where external factors confound children’s abilities to learn. Karanth draws attention to another two issues concerning LD in India. The first one is the influence of language development on the development of LD. She discusses many findings related to comorbidity of LD and language disorders which should be taken into account when a child supposedly suffering from LD is assessed. The second variable that she describes in her chapter is the meaning of the first language with respect to learning to read and write effectively in English. There are many differences with respect to phonological awareness when English and Kannada or Hindi are involved. It cannot be assumed that LD in Indian children can be assessed in the same way as compared to children described in American and English studies. There are many questions that need to be answered first such as the relative meaning of the role of phonological skills to reading in the first and second languages. Verma follows the LD definition closely and tries to reveal the characteristics of LD with respect to the main academic skills. She sticks to child characteristics only but claims that the assessment at least should be carried our correctly. Gupta draws attention toward specific characteristics of Hindi to argue that Hindi-speaking children classified with LD suffer from comparable problems related to phonological awareness as their English-speaking peers classified as such. The contribution by Van der Aalsvoort aims at drawing attention to children who have not yet started formal education. Young children at-risk for LD may exhibit several behaviors that suggest LD, but it is only after having been offered formal teaching in reading and writing that LD can be detected. Therefore she suggests that offering time to play is a way to draw children’s attention to social skills that are needed to follow experiences in the school grounds as worthwhile and interesting. Shared play-time evokes pleasure in shared role-playing to get a grip upon realities of life. Pandey and Pant offer an insight into what they call the “marginalized Dalits”. They described problems with learning from a sociological and an anthropological perspective. Instead of

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describing school failure as a school- or teacher-related problem, they address the issue of children from a specific socio-economic background as one that refers to societal constraints of religion. They explain that Dalit children historically did not get the opportunity to go to school as they belonged to the lower castes. Moreover, even though governmental policy attempted to ensure education for all children in India, the parents of these children need the children’s contribution to make a living, which resulted in season-bound dropouts. Issues like these overrule questions about school failure as a child characteristic.

THE ROLE

OF

TEACHERS

IN IDENTIFYING

LD

All the three chapters related to the theme aimed at showing how identification of LD by teachers should be based upon learning progress with respect to reading and writing as well as observations of children’s behavior. Konantambigi and Shetty, however, perceive LD as a classification that should be carried out by teachers themselves to guarantee that the problems with learning to read and write are detected fast. They combined the findings of children identified with LD based on an interview with teachers, a screening checklist, and a test. The results revealed a moderate correlation between the measurements only. Therefore, Konantambigi and Shetty suggest that teachers are trained to become more competent in identifying LD. Tripathi and Kar draw comparable conclusions after having collected data about children’s learning progress with formal tests and teachers’ perception about these children. They suggest that programs to improve teachers’ awareness of LD would enable schools to meet the special educational needs of these students. Yadav and Agarwal also attempted to demonstrate that LD identification could be done by local and rural-based schools. They assessed children and asked teachers to complete the LD-Awareness Schedule. Moreover, they made observations in the classroom and showed a discrepancy between teachers’ awareness and actual LD. They suggest that teachers would need in-service programs to improve their sensitivity towards the learning disabled.

Identifying Issues and Looking Ahead

ASSESSMENT

281

AND INTERVENTION

Three contributions focus on a specific reading program that is based upon a cognitive theory named PASS or cognitive functioning based upon Planning, Attention-Arousal, and Simultaneous and Successive processing. Pagedar and Sarnath declare PASS as the base of reading stimulation with children who have made poor reading progress so far. Sarnath claims that the PASS Reading Enhancement Programme succeeds in making children with ADHD or LD better readers. Both Pagedar and Sarnath describe the content of the programs offered. Mehta offered strategy training to children classified with LD based on PASS and she showed that the children who had been offered the program outperformed their peers who had not been offered the intervention. Pagedar used the PASS reading programme (PREP) on an experimental group who differed with a control group only with respect to type of remediation. The experimental condition receiving PREP performed better after the intervention than the control group. The final chapter related to assessment and intervention is from Mongia, Sadhu, and Mehta. They describe a study that consists of two parts. The first part contains data about LD assessment related to reading and writing skills as well as strategy skills to apply when offered tasks. This information was used to carry out a multisensory intervention which they claimed as being successful.

DISCUSSION Specific Learning Disability: Discussing Definitions Bradley, et al. (2005) draw attention to the definition of LD. The operationalization as put forward in the Individual with Disabilities Education Act (IDEA), which is used to identify students who need an individualized education program, is not leading to appropriate identification or instructional improvements. However, strong converging evidence supports the concept of specific learning disability (SLD). Bradley et al. (2005, p. 485) describe SLD according to the following characteristics:

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1. the disorder significantly affects a relative narrow range of academic and performance outcomes; 2. IQ/achievement discrepancy is neither necessary nor sufficient for identifying individuals with SLD: IQ tests need not to be given in most evaluations of children with SLD; 3. response to quality intervention is the most promising method of alternative identification. Since the addition of response to instruction, Fuchs and Fuchs’ Response to Instruction Model (RTI) has gained increasing influence. Response to Instruction Model is seen as a means to promote inclusive education. Fuchs and Fuchs (1998) developed Response to Instruction Model as a model to determine whether the overall rate of responsiveness in the classroom indicates that instructional environment is sufficiently nurturing before claiming that individual students are poor learners. Response to Instruction Model supposedly tests effectiveness of instructional environment by offering the same opportunity to profit from instruction to all students in the classroom. Next, interpretation of academic progress is possible as RTI supplies evidence-based data with respect to students’ progress on systematic changes over time. The model consists of three tiers: 1. primary intervention consisting of general education program; 2. secondary intervention involving fixed duration, targeted evidence-based small group interventions; and 3. tertiary intervention involving individualized and intensive services that may be similar to traditional special education services. The validity of RTI is tested by Curriculum-Based Measurement (CBM). This method refers to a set of standardized procedures for collecting student data in the basic skill areas of reading, writing, mathematics computation, spelling, and written expression. Curriculum-Based Measurement is considered as a way of formative evaluation as it allows evaluation of the effectiveness of instructional programs so that teachers become more effective as they can trace the result of the students’ progress on a regular base (Fuchs et al., 2004). Kavale (2005) claims that the RTI model could be an appropriate, however, only first step in the SLD identification process.

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He developed a model that includes five levels in which each level is a necessary but not a sufficient condition. He seeks an approach that integrates concepts about SLD with theories about cognitive and academic functioning to generate a comprehensive and systematic assessment framework that provides an inherently practical method for SLD identification. Discussions like the one described in this section reveal that defining SLD is a matter that involves both theory and practice. Efforts from both sides are required to solve the problem that afflict many students who apparently profit from going to school but do not make progress in academic skills such as reading and writing. The authors who presented their views with regard to children with SLD all subscribe to this view.

Specific Learning Disability in India The country is struggling to meet the educational needs of its children. There is so much work to be done to reach all the children in every state of the country. Is identification of LD the first step to take? I suggest that the concept of LD is seen as a continuum that needs to be dealt with in schools. LD can be described as a concept that relates to degree of difficulties experienced with making progress in learning. Does the child experience problems in the classroom only or do his problems to deal effectively with academic tasks also hinder his social and emotional well-being? Learning disabilities may also be described as a continuum that connects to the type of help required. On the one side of the continuum, you will find that teachers successfully deal with problems that can be covered by temporary, intensive individual assistance, special tasks that allow more time to practice to develop skills with respect to reading, writing, and arithmetic, at the same time, taking care that the child completes classroom assignments just as his peers to prevent the child from being socially and emotionally excluded. On the other side of the continuum, teachers are aware of the LDs of the child and their expertise lies in instructing children by offering specific assistance to compensate for problems that the child can never deal with. Examples are allowing reading through audiotape

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assistance, writing with computers that offer spelling correction, extended time to complete tasks, and taking care that the child takes part in classroom assignments just as his peers to prevent the child from being socially and emotionally excluded. There will be researchers who feel compelled to clarify the number or degree of difficulties children experience when trying to become good readers and writers. These researchers will work with teachers who feel that others are aware of their struggle with students who fall behind. Efforts are made to equip these teachers with skills for early identification of problems. These teachers are instructed that part of the identification process includes the component of effective instruction by the teacher for a period of three to four months to ensure that poor performance is not related to poor teaching but to poor developmental abilities with respect to phonological awareness. There will also be researchers who feel that assessment is just a step away from intervention. They will assist teachers in documenting their efforts so that they can use to effective strategies in the classroom. Both types of research are required to stimulate effective teaching to Indian children. Using the RTI model may be of help to clarify educational quality before efforts related to more expensive and often not necessary individual assessments are collected to assist teachers’ efforts in instruction students to read and write. Finally, one last remark with respect to the contributions from Kapur, Karanth, Gupta, Pandey, and Pant. Learning Disability is a disability that is recognized all over the world but every cultural community has its own unique and specific perspective on its accurate identification. These authors drew attention to factors specific to the Indian context, which has a significant influence on the process of identification. Their chapters provide heuristic insights, which can facilitate the formulation of a research agenda and services for students with LDs in India.

REFERENCES American Psychiatric Association. 2000. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Test Revision (DSM-IV-TR) Washington, DC: American Psychiatric Association.

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Bradley, R., L. Danielson and J. Doolittle. (2005). ‘Response to Intervention’, Journal of Learning Disabilities, 38: 485–86. Fuchs, L.S. and D. Fuchs. (1998). ‘Treatment Validity. A Unifying Concept for Reconceptualizing the Identification of Learning Disabilities’, Learning Disabilities Research and Practice, 13: 204–219. Fuchs, D., L. Fuchs and D.L. Compton. (2004). ‘Identifying Reading Disabilities by Responsiveness-to-instruction: Specifying Measures and Criteria’, Learning Disability Quarterly, 27: 216–27. Kavale, K.A. (2005). ‘Identifying Specific Learning Disability: Is Responsiveness to Intervention the Answer?’, Journal of Learning Disabilities, 38(4): 553–62.

About the Editors and Contributors EDITORS Komilla Thapa is Professor at the Centre of Advanced Study, Department of Psychology, University of Allahabad. She trained as a clinical psychologist at the National Institute of Mental Health and Neurosciences, Bangalore. Her interests lie in mental health issues and childhood disorders. Geerdina M. van der Aalsvoort is Associate Professor at the Faculty of Social Science, Utrecht University, The Netherlands. Her expertise is in theory building with respect to development of children at-risk for learning difficulties, aged 4 to 8 years. Her current research activities include studying the relationship between social interaction during academic tasks and actual performance; role of emergent collaboration play and future academic performance, and application of learning potential tests. Janak Pandey is Professor, Department of Psychology and Coordinator for the Centre of Behavioural and Cognitive Sciences, University of Allahabad. He has headed various national and international associations of psychology and has received several awards and encomiums in his distinguished career. He has written extensively and has edited several prestigious volumes.

CONTRIBUTORS Vidya Agarwal is Professor in the Department of Education, University of Allahabad. She completed her M.Ed., M.Phil.(Edu), and Ph.D.(Edu) from Institution of Advanced Studies, Meerut University, Meerut. She has several books and many research papers to her credit. Her area of interest is educational administration and

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287

management. She is a member of various committees in a number of universities in India. Ashum Gupta is the Head of the Department of Psychology, University of Delhi. She is also the Director, Gandhi Bhawan, University of Delhi. A gold medalist from University of Delhi, she has 34 years of teaching, research, and consultancy experience. She has received several international and national awards. She has contributed to many national and international journals. Besides her academic pursuits, she has been very active in media being a columnist for a newspaper and a magazine, and has been participating in several programs on TV, FM radio, and the All India Radio. Malavika Kapur is an Honorary Professor at the National Institute of Advanced Studies, Bangalore. Previously she was a Professor of Clinical Psychology at the National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore. She has specialized in developmental psychopathology. For many years she has been conducting programs for sensitizing teachers toward the mental health problems of children. She has contributed numerous papers to national and international journals, and has edited books. Bhoomika R. Kar is a faculty member in the Centre of Behavioral and Cognitive Sciences. She did her Ph.D in Clinical Psychology from the NIMHANS Bangalore. Her research interests are cognitive development, bilingualism, dyslexia, reading acquisition, and cross linguistic transfer. She has contributed papers to journals and books, and has made numerous presentations at international and national conferences in India and abroad. Pratibha Karanth is Program Director, Com-DEALL Trust, Bangalore. She has degrees in Psychology, and Speech and Hearing, from the University of Mysore. She is a pioneer in the field of Speech Language Pathology in India and is known for her work on neurogenic communication disorders in children and adults. Dr Karanth has published extensively, and is the recipient of several grants and awards.

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Perspectives on Learning Disabilities in India

Rajani M. Konantambigi, a psychologist by training, is Associate Professor at the Centre for Human Ecology, School of Social Sciences, Tata Institute of Social Sciences, Mumbai. Her current research has been in the area of teaching learning problems in classroom, non-formal education of tribal children and outcome budgeting for Sarva Shiksha Abhiyan. She is also a member of the committee revising syllabi of the NCERT directed Regional Colleges of Education. Dharmishtha H. Mehta is Reader in the Centre of Special Education, S.N.D.T. Women’s University, Mumbai. She has worked extensively with children with learning disabilities. Manju Mehta is Professor of Clinical Psychology, Department of Psychiatry, All India Institute of Medical Sciences (AIIMS), New Delhi. She is Head of the Child and Adolescent Psychiatry Clinic at AIIMS. Monica Mongia has Ph.D in Clinical Psychology from the Department of Psychiatry, All India Institute of Medical Sciences (AIIMS), New Delhi, India. She is currently employed as Psychologist in the Ministry of Health and Family Welfare sponsored project on “Development of Cognitive Behavior Therapy Curriculum for PG Medical Students”. Her research areas include ADHD and SLD, parent training in ADHD, and impact of mental illness on caregivers. Sunita Pagedar is working on her doctoral degree in the area of Special Education at the State University of New York, Buffalo. Earlier she has worked as the Deputy Head, Research and Training at the Spastic Society of India, and has also been the Coordinator of the Maharashtra Dyslexia Association, Mumbai. S.K. Pant is a senior faculty at the G.B. Pant Social Science Institute, Allahabad. He has published many papers in national and international journals as well as books on education and social issues. He has completed many projects for prestigious organizations such as the Planning Commission, National Literacy Mission, Rajiv Gandhi Foundation, NCERT, and the State Project Directorate. His interest also lies in computer application programs for social scientists.

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Raja Sadhu is Senior Resident at the Department of Psychiatry, All India Institute of Medical Sciences (AIIMS), New Delhi. Jagruti Sarnath has done her Ph.D in counseling psychology from the University of Mumbai and is currently practicing in Bangalore. Mamatha Shetty is a practicing clinical psychologist and is associated with the Institute of Mental Health at Thane near Mumbai. She consults for a number of schools, and conducts workshops for parents and children on a wide variety of topics. Currently she is pursuing her Ph.D degree at the Tata Institute of Social Sciences, Mumbai. Nishi Tripathi is Assistant Professor at the College of Business Studies, Allahabad Agricultural Institute, Deemed University, Allahabad. She is also a Guest Faculty at the College of Education, Allahabad. She completed her Ph.D in Psychology from Allahabad University. She has worked in the area of disability, and its impact on cognitive and affective styles. She also worked in the area of cognitive disorders particularly learning disabilities. Preeti Verma is Reader in the Centre of Special Education, S.N.D.T. Women’s University, Mumbai. She has worked with children with specific learning disabilities. Dhananjai Yadav is Lecturer in the Department of Education at the University of Allahabad. He was awarded the UNESCO– PROAP AAOU Award–2001. He has completed several research projects, published a book, and a dozen of research papers in reputed national journals.

Author Index Aaron, P.G., 108 Agarwal, V., 280 Algozzine, B., 203 Al-Otaiba, S., 195 Armstrong, S.W., 206

Das, J.P., 164, 240, 241, 242, 245, 249, 250 Das, J.P. et al., 240, 245 Dougherty, K., 274 Dunn, L., 153, 155

Balasubrahmanyam, S.N., 39 Ball, E., 274 Bandura, A. et al., 196 Bartel, N.R., 206 Bashir, A.S. et al., 81 Bender, W.N., 183, 186 Bhola, P. et al., 178 Blachman, B., 274 Bley, N.S., 206 Boden, C., 250 Brostrom, I., 274 Bowers, P.G., 107 Bradley, R. et al., 281 Bright, W., 99 Bronfenbrenner, U., 52–53 Brooks, L., 274 Bryan, T., 161 Butler, K.G., 30

Education for All Handicapped Children Act, 201 Elbro, C., 274 Elliott, A., 48, 51

Carlson, J.S., 250 Ceci, S.J., 52–53 Chavan, M., 182 Clements, S., 224 Coles, G., 38 Coordinated Campaign for Learning Disabilities (CCLD), 202 Critchley, M., 154

Fawcett, A.J., 107 Feagans, L., 204 Fletcher, J.M. et al., 24, 30, 31, 33 Foorman, B. et al., 273 Fuchs, D., 282 Fuchs, D. et al., 282 Fuchs, L.S., 282 Garbarino, J., 35, 39 Gardner, H., 184, 197 Garg, A., 100, 111 Gaur, A., 100 Gee, J.P., 56 George, N., 90 Gerber, M.N., 255 Goswami, U., 84, 112 Graham, L., 184 Graham, S., 205 Gray, W.S., 155 Green, J.L., 56 Greenfield, D.B., 195 Greenhill, L.L., 264 Gupta, A., 92, 99, 100, 102, 111, 278, 284

291

Author Index Hall, N., 48, 51 Hallahan, D.P., 32, 147, 254 Hammill, D.D., 153, 157, 206, 216 Hanley, R., 85 Hannikainen, M., 60 Harms, T. et al., 62 Harris, K.R., 205 Harris, M., 84 Hatano, G., 84 Hecht, S.A., 195 Hiemenz, J.R., 41 Huang, H.S., 85 Hynd, G.W., 41 Individuals with Disabilities Education Act (IDEA), 28, 185, 281 Jain, S. et al., 118 Jensen, W.R. et al., 265 Jitendra, A.K., 254 Jitendra, A.K. et al., 260 John, A., 200, 203 Johnston, J., 274 Kapur, M., 173, 176, 178 Kapur, M. et al., 166, 173, 178, 278, 284 Kar, B.R., 280 Karanth, P., 39, 85, 86, 89, 91, 93, 141, 162, 163, 173, 202, 204, 213, 278, 279, 284 Katzen, K., 221 Kauffman, J.M., 147 Kaufman, A.S., 264 Kaufman, N.L., 264 Kavale, K.A., 24, 282 Kavale, K.A. et al., 145 Kirby, J.R., 250 Kirk, S.A., 200 Konantambigi, R.M., 182, 191, 280 Koppitz, E.M., 160, 174

Lall, A. et al., 178 Lambay, F., 182 Larsen, S.C., 157 Larson, K.A., 255 Lavin, J.L., 264 Leong, C.K., 85 Lerner, J.W., 24, 260 Leseman, P.P.M. et al., 60, 75 Levine, M.D., 267 Lie, A., 274 Lindamood, P., 83 Luria, A.R., 240 Lyon, G.R., 24, 28, 30, 32, 33, 36 Lyon, G.R. et al., 26, 29, 42 Majumdar, M., 118 Malin, A.J., 173, 267 Mammen, A., 90 Mani, M.N.G., 117 Markwardt, F.C., 155 Mastropieri, M.A., 207 Mayer, R.E. et al., 268 Mc Kinney, J.D., 204 Mc Leod, T.M., 206 McClelland, J.L., 108 McNutt, G., 216 Mehta, D.H., 164, 189, 190 Mehta, M., 281 Meijer, C.J.W., 50 Mercer, A.R., 213, 214 Mercer, C.D., 213, 214 Metsenare, M., 255 Mishra, R.K., 249 Misra, G., 140 Mongia, M., 281 Morais, J.P. et al., 86 Mukerjee, S. et al., 178 Mukhopadhyaya, S., 117 Murphy, L.A. et al., 87

292

Perspectives on Learning Disabilities in India

Naglieri, J.A., 164, 240, 241, 242 National Joint Commission on Learning Disabilities (NJCLD), 223 Nehru, R., 40, 100, 111 Newcomer, P.L., 153 Nicolson, R.L., 107 Orton, S., 80 Overalle, M.V., 255, 261 Pagedar, S., 281 Panda, K.C., 140 Pande, N., 141 Pandey, J., 279, 284 Pandey, J. et al., 123 Pant, S.K., 279, 284 Papola, T.S., 116 Perfetti, C.A., 107, 109 Peters, D.J., 206 Pijl, S.J., 50 Pool, J.E., 249 Porteus, S.D., 160 Prakash, P., 85, 86, 93, 213 Prema, K.S., 85, 163 Raven, J.C., 63, 102 Reddy, G.L. et al., 223, 255 Reid, K.D., 255, 260 Rekha, B., 86 Reynolds, C.R., 31 Robinson, H.M., 155 Rock, D. et al., 187 Rozario, J., 162, 163, 173, 174 Rozario, J. et al., 174 Rutter, M., 31 Sadhu, R., 281 Sadock, B.J., 265 Sadock, V.A., 265 Sankaranarayanan, A., 162 Sarnath, J., 281

Scanlon, D., 274 Sebastian, S., 26, 202 Seidenberg, M.S., 108 Siegel, L.S., 101, 111 Semel, E.M., 153 Share, D.L., 85 Sharma, M., 89 Sharma, R., 140 Shaywitz, B.A. et al., 40 Shaywitz, S.E. et al., 40 Shetty, M., 280 Sideridis, G.D. et al., 184 Sigafoos, J.D. et al., 74 Silliman, E.R., 30 Silliman, E.R. et al., 30 Singh, A.K., 118 Skjelfjord, V., 274 Skotten, B.C., 197 Slavin, R., 273 Smith, E.C. et al., 240 Snow C.E., 39 Snowling, M., 107 Specce, D.L., 204 Srikanth, N., 163 Srinath, S., 175 Stanovich, K.E., 25, 30 Stone, A.S., 54, 55 Stone, C.A., 37, 256 Sujatha, K., 117 Suresh, P.A., 26, 202 Swarup, S., 160, 164, 189, 190 Tal, N.F., 101, 111 Thorat, S., 118 Tonnessen, F.E., 197 Torgesen, J.K. et al., 261 Torgeson, J.K., 25, 27, 28, 206, 255 Trawick-Smith, J., 65 Tripathi, N., 280 Tripathi, R.C., 140 Uma, H., 176

293

Author Index Uma, H. et al., 174 UNICEF, 182 Vaid, J., 99, 100, 111 Vaidyanathan, A., 118 Van daal, V.H.P., 97, 113 Van Der Aalsvoort, G.M., 50, 52, 277, 278 Van der Leij, A., 97, 108, 113 Van Kleeck, A., 82, 88 Van Kuijk, J.J., 62 Vellutino, F., 274 Verba, M., 58 Verma, P., 160, 164, 278, 279 Vygotsky, L.S., 54 Wagner, R. K., 206 Walker, J., 274 Warren, H.C., 222

Wasik, H., 273 Weiner, M., 182 Weisberg, P., 274 Wiig, E.H., 153 Wimmer, H., 98 Wolf, M., 87, 107 Wong, B.Y.L., 25, 159, 160, 172, 184, 201, 255, 256 Wood, D. et al., 54–55 Wood, M.H., 157 Woodcock, R.W., 155 Woodward, D.W., 206 Yadav, D., 280 Yan, P.X., 255 Ysseldyke, J.E., 203 Ysseldyke, J.E. et al., 145 Zera, D.A., 197 Zoccolotti, P. et al., 98

Subject Index alphabetic script, 84, 85, 91, 92 alphasyllabary, 84, 86 Assessment of LDs: attention, 159, 207; behavior, 213–14, 215, 229; cognition, 158–59, 228; conduct and motor problems, 231, 232 236; formal, 263; Indian tests, 162–65; informal, 263; language, 151–52, 210, 214, 226, 229, 235; math, 156–58, 176, 205, 213, 226, 229, 230, 236, 266; meta-cognition, 59; pre-academic skills, 173; reading, 88, 152–55, 175, 205, 212–13; reasoning and problemsolving, 158, 256; social skills, 159–61, 266; writing; 155–56, 175, 214, 212, 214, 226, 229, 235, 236, 265 at-risk students, 48, 49, 51, 53–54, 56–59, 73, 146 Attention-deficit Hyperactivity Disorder (ADHD), 203, 240, 243, 264 auditory processing disorder, 81 automatization, 97, 98, 107, 274 bilingual, 93, 103 bio-ecological model, 52–53

Hindi: orthography, 99–102, reading difficulties, 101–02, reading errors, 105–06, 110 ideographic scripts, 85 interventions, 35–38; arithmetic, 273; behavioral problems, 268; multi-sensory approaches, 273; reading, 268, 272; spelling, 268 language acquisition/learning, 81, 91 language learning deficits/disabilities, 80, 81, 90, 147 learning Disabilities (LD)/Specific learning disabilities (SLD), 24–27, 170, 182, 220, 221–23, 239, 254, 262; concept, 142–43, 170–71; contextual factors, 38–40, 135–36, 162, 171, 177–78, 282; definitions, 27–30, 143–45, 171, 184, 199–200, 275–77, 279–80; developmental/life span, 33–35, 205–06; diagnosis, 147–49; exclusion criteria, 31–32, 185; in India, 26, 203, 265, 283; inclusion criteria, 185; neuroimaging, 40–42; prevalence/ epidemiology, 201–02, 225, 226–27, 235, 265 lexical retrieval, 87

co-morbid, 147, 264 developmental dyslexia, 87, 92, 97–99, 146, 154 discourse analysis, 52, 56, 57, 61, 70 dysnomia, 87 grapheme–phoneme correspondence/ conversion, 97, 98, 101, 215, 273

measures/tests, ANSERS scale, 267, 268, 270; Aston Index, 189, 190; Behavioral Checklist for Screening the Learning Disabled (BCSLD), 189, 190, 256; Cloze Test, 268; Cognitive Assessment System (CAS), 242; Coloured Progressive Matrices, 63, 225, 247; Curriculum

Subject Index Based Measurement, 282–83; Diagnostic Test of Learning Disabilities (DTLD), 189, 190, 257, 256; Early Childhood Environment Rating Scales (ECERS), 62; Hindi Reading Test, 102; Learning Disabilities Scale (LDS), 225; Learning Disabilities Awareness Schedule (LDAS), 225; Linguistic Profile Test (LPT), 89, 90, 91; Malin’s Intelligence Scale for Children (MISIC), 173, 267, 272; NIMHANS INDEX for SLDs, 173, 174; Physical and Neurological Examination of Soft Signs (PANESS) Scale, 269, 270; Problem Checklist Forms A, B, 208–09; Raven’s Progressive Matrices, 257; Teacher Behavior Observation Schedule (TBOS), 226; Test of Problem-Solving (TPS), 256, 257, 258, 259; Wechsler Intelligence Scale for Children (WISC), 243; Wide Range Achievement Test (WRAT), 244; Woodcock Reading Mastery Test-Revised (WRMT-R), 250, 251 meta-cognitive abilities, 183–84, 203 metalinguistics, 82, 88, 89, 91, 92 metaplay, 61, 65, 70 microgenetic approach, 57, 59, 75 multi-method approach, 48, 52, 57 National Policy on Education, 117; monitoring agencies, 134, 135; Sarva Siksha Abhiyan, 141, 221; school enrollment, 127 non-alphabetic scripts, 84, 91 non-literal language, 88 oddity tasks, 85, 86 orthographic transparency, 84 orthography, 85, 86, 98, 211, 215

295 PASS Reading Enhancement Programme (PREP), 245–49, 250 PASS theory, 240–43, 281 Perceptual deficit theory, 183 phoneme deletion, 86, 87 phonemic/phonological awareness, 83, 84, 85, 86, 87, 92, 93 proximal processes, 53–54 Response to Instruction Model (RTI), 282 rhyme recognition, 85, 86 scaffolding, 37, 55, 255 Scheduled Castes and Tribes (SC, ST), drop-out, 118; literacy rate, 123; occupational pattern, 118–19; poverty, 118 Schools, types: central syllabus, 176; english-medium, 209, 255; middle class, 174, 209; municipal, 188; parishadiya primary, 221–22; private, 187; state syllabus, 175 segmentation, 86 semantics, 87, 91, 93 special school, 49–50, 58, 74, speech disorders, 80, 81 Strategy Training (S-SWEL), 257, 258 syllable deletion, 85, 86 syllable segmentation, 85 syntax, 88, 90, 91, 93 teachers: awareness of LDs, 223, 230, 237; identification of LDs, 182, 188, 191, 210, 215, 221, 278; classroom practices, 222, 233–35 transactional theory of child development, 52 verbal analogical reasoning, 88 villages (sample): children assisting in agriculture, 131–33; community support, 137–39; drop-outs, 128–31,

296

Perspectives on Learning Disabilities in India

138; primary schools, 123; quality of schools, 133–34; school enrollment, 127–28; social infrastructure, 126; teachers, 140

word fluency and retrieval, 87 zone of proximal development (ZPD), 54