Current issues and trends in special education = Identification, assessment and instruction 9781848556683, 1848556683, 9781848556690, 1848556691

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CURRENT ISSUES AND TRENDS IN SPECIAL EDUCATION: IDENTIFICATION, ASSESSMENT AND INSTRUCTION

ADVANCES IN SPECIAL EDUCATION Series Editor: Anthony F. Rotatori Recent Volumes: Volume 11: Issues, Practices and Concerns in Special Education – Edited by Anthony F. Rotatori, John O. Schwenn and Sandra Burkhardt Volume 12: Multicultural Education for Learners with Exceptionalities – Edited by Festus E. Obiakor, John O. Schwenn, and Anthony F. Rotatori Volume 13: Intervention Techniques for Individuals with Exceptionalities in Inclusive Settings – Edited by Festus E. Obiakor, Sandra Burkhardt, Anthony F. Rotatori and Tim Wahlberg Volume 14: Autistic Spectrum Disorders: Educational and Clinical Interventions – Edited by Tim Wahlberg, Festus E. Obiakor, Sandra Burkhardt and Anthony F. Rotatori Volume 15: Effective Education for Learners with Exceptionalities – Edited by Anthony F. Rotatori, Festus E. Obiakor and Cheryl A. Utley Volume 16: Current Perspectives on Learning Disabilities – Edited by Sandra Burkhardt, Festus E. Obiakor and Anthony F. Rotatori Volume 17: Current Perspectives in Special Education Administration – Edited by Festus E. Obiakor, Anthony F. Rotatori and Sandra Burkhardt Volume 18: Autism and Developmental Disabilities: Current Practices and Issues – Edited by Anthony F. Rotatori, Festus E. Obiakor and Sandra Burkhardt

ADVANCES IN SPECIAL EDUCATION VOLUME 19

CURRENT ISSUES AND TRENDS IN SPECIAL EDUCATION: IDENTIFICATION, ASSESSMENT AND INSTRUCTION EDITED BY

FESTUS E. OBIAKOR University of Wisconsin-Milwaukee, Milwaukee, WI, USA

JEFFREY P. BAKKEN Illinois State University, Normal, IL, USA

ANTHONY F. ROTATORI Saint Xavier University, Chicago, IL, USA

United Kingdom – North America – Japan India – Malaysia – China

Emerald Group Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2010 Copyright r 2010 Emerald Group Publishing Limited Reprints and permission service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. No responsibility is accepted for the accuracy of information contained in the text, illustrations or advertisements. The opinions expressed in these chapters are not necessarily those of the Editor or the publisher. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-84855-668-3 ISSN: 0270-4013 (Series)

Awarded in recognition of Emerald’s production department’s adherence to quality systems and processes when preparing scholarly journals for print

CONTENTS LIST OF CONTRIBUTORS

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PREFACE

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PART I: IDENTIFICATION OF STUDENTS CHAPTER 1 EARLY IDENTIFICATION/ INTERVENTION: THE EARLIER THE BETTER FOR STUDENTS WITH DISABILITIES Yi-Juin Liu CHAPTER 2 EARLY IDENTIFICATION/ INTERVENTION: CAN MISIDENTIFICATION/ MISINTERVENTION IMPACT STUDENTS, TEACHERS, AND FAMILIES? Barbara Metzger, Cynthia G. Simpson and Jeffrey P. Bakken

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PART II: UNDER-IDENTIFICATION AND OVER-IDENTIFICATION IN SPECIAL EDUCATION CHAPTER 3 CAN UNDERIDENTIFICATION AFFECT EXCEPTIONAL LEARNERS? Rhonda S. Black

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CHAPTER 4 DISPROPORTIONATE REPRESENTATION IN SPECIAL EDUCATION: OVERREPRESENTATION OF SELECTED SUBGROUPS Tina Taylor Dyches and Mary Anne Prater

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CONTENTS

PART III: ASSESSMENT AND ACCOUNTABILITY IN EDUCATION CHAPTER 5 STANDARDIZED TESTING/ ACCOUNTABILITY: IS NCLB FAIR FOR STUDENTS WITH DISABILITIES? Tes Mehring

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CHAPTER 6 CURRICULUM-BASED ASSESSMENT: THE MOST EFFECTIVE WAY TO ASSESS STUDENTS WITH DISABILITIES Sunday Obi

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PART IV: LABELING AND CATEGORIZATION CHAPTER 7 LABELING OF STUDENTS WITH DISABILITIES: NEEDED FOR STUDENTS TO GET THEIR NEEDS MET Gathogo M. Mukuria and Jeffrey P. Bakken

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CHAPTER 8 LABELING OF STUDENTS WITH DISABILITIES: UNWANTED AND NOT NEEDED Craig Blum and Jeffrey P. Bakken

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PART V: PLACEMENT AND INCLUSION OF STUDENTS CHAPTER 9 THE GENERAL EDUCATION CLASSROOM: THIS IS NOT WHERE STUDENTS WITH DISABILITIES SHOULD BE PLACED Jeffrey P. Bakken CHAPTER 10 BEYOND TRADITIONAL PLACEMENT: MAKING INCLUSION WORK IN THE GENERAL EDUCATION CLASSROOM Festus E. Obiakor, Mateba K. Harris, Anthony F. Rotatori and Bob Algozzine

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PART VI: INSTRUCTIONAL METHODS FOR STUDENTS WITH DISABILITIES CHAPTER 11 BEHAVIORISM WORKS IN SPECIAL EDUCATION Darlene H. Anderson, Michelle Marchant and Nancy Y. Somarriba CHAPTER 12 OTHER INNOVATIVE TECHNIQUES: POSITIVE BEHAVIOR SUPPORTS AND RESPONSE TO INTERVENTION John J. Wheeler and Michael R. Mayton

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PART VII: INTERVENTION METHODS CHAPTER 13 SCIENTIFICALLY SUPPORTED INTERVENTIONS Martha L. Thurlow, Courtney Foster and Christopher M. Rogers CHAPTER 14 SCIENTIFICALLY UNSUPPORTED TREATMENTS FOR STUDENTS WITH SPECIAL NEEDS Julie A. Deisinger

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LIST OF CONTRIBUTORS Bob Algozzine

Department of Educational Leadership, University of North Carolina at Charlotte, Charlotte, NC, USA

Darlene H. Anderson

Department of Counseling Psychology and Special Education, Brigham Young University, Provo, UT, USA

Jeffrey P. Bakken

Department of Special Education, Illinois State University, Normal, IL, USA

Rhonda S. Black

Department of Special Education, University of Hawaii at Manoa, Honolulu, HI, USA

Craig Blum

Department of Special Education, Illinois State University, Normal, IL, USA

Julie A. Deisinger

Department of Psychology, Saint Xavier University, Chicago, IL, USA

Tina Taylor Dyches

Department of Counseling Psychology and Special Education, Brigham Young University, Provo, UT, USA

Courtney Foster

SupportedED Educational Consulting, Columbia, SC, USA

Mateba K. Harris

Department of Exceptional Education, University of Wisconsin-Milwaukee, Milwaukee, WI, USA

Yi-Juin Liu

Department of Exceptional Education, University of Wisconsin-Milwaukee, Milwaukee, WI, USA ix

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LIST OF CONTRIBUTORS

Michelle Marchant

Department of Counseling Psychology and Special Education, Brigham Young University, Provo, UT, USA

Michael R. Mayton

Department of Special Education, West Virginia University, Morgantown, WV, USA

Tes Mehring

Provost/Vice President, Emporia State University, Emporia, KS, USA

Barbara Metzger

Department of Language, Literacy, and Special Populations, Sam Houston State University, Huntsville, TX, USA

Gathogo M. Mukuria

Department of Special Education, Slippery Rock University, Slippery Rock, PA, USA

Sunday Obi

Special Education Department, Kentucky State University, Frankfort, KY, USA

Festus E. Obiakor

Department of Exceptional Education, University of Wisconsin-Milwaukee, Milwaukee, WI, USA

Mary Anne Prater

Department of Counseling Psychology and Special Education, Brigham Young University, Provo, UT, USA

Christopher M. Rogers

Institute on Community Integration, University of Minnesota, Minneapolis, MN, USA

Anthony F. Rotatori

Department of Psychology, St. Xavier University, Chicago, IL, USA

Cynthia G. Simpson

Department of Language, Literacy, and Special Populations, Sam Houston State University, Huntsville, TX, USA

Nancy Y. Somarriba

Department of Counseling Psychology and Special Education, Brigham Young University, Provo, UT, USA

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List of Contributors

Martha L. Thurlow

National Center on Educational Outcomes, University of Minnesota, Minneapolis, MN, USA

John J. Wheeler

College of Education, Tennessee Tech University, Cookeville, TN, USA

PREFACE Current Issues and Trends in Special Education is divided into two volumes; Volume 19, Identification, Assessment and Instruction; and Volume 20, Research, Technology, and Teacher Preparation. The field of special education constantly changes as a result of legislation, new instructional formats, and current research investigations. It can be difficult for general and special educators, school counselors and psychologists, administrators, and practicing clinicians to keep up with these changes and be current in all areas relating to special education. The special education literature knowledge base should reflect these changes; however, there is no current resource that effectively and comprehensively does this. The purpose of Current Issues and Trends in Special Education is to fulfill this void. Volumes 19 and 20 address the top issues and trends in special education by providing chapters written by active researchers and practitioners in their respective areas. Volume 19 first delineates traditional topics such as identification, assessment, and labeling by reviewing historical aspects and then discussing current concerns. Then this volume addresses newer innovations and issues related to placement and inclusion, scientifically supported and unsupported interventions, instructional methods such as response to intervention and positive behavioral supports, and programming students with challenging conditions such as attention deficit hyperactivity and autism spectrum disorders. Volume 20 addresses issues that impact all teachers, such as preparation of teachers; multicultural considerations for instruction; the use of assistive technology with special needs students; transition planning, preparation and implementation; language, communication, and education; and quantitative and qualitative research endeavors. The layout of Current Issues and Trends in Special Education follows the special education process, namely, identification, placement, instruction, and transitional programming. This process allows readers to progress through the chapters in a sequential manner that builds and enhances their knowledge base. Volumes 19 and 20 provide the reader with a comprehensive resource

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for general and special educators. As such, individual chapters from each volume can be read separately in any order as each chapter has the breath and depth to stand on its own. Festus E. Obiakor Jeffrey P. Bakken Anthony F. Rotatori Editors

PART I IDENTIFICATION OF STUDENTS

CHAPTER 1 EARLY IDENTIFICATION/ INTERVENTION: THE EARLIER THE BETTER FOR STUDENTS WITH DISABILITIES Yi-Juin Liu ‘‘Prevention and early identification-early intervention reduce the prevalence and severity of significant achievement and behavior problems’’ (Reschly, 2007, p. 3). Early intervention programs have been designed to provide services, resources, and support to meet the unique needs of children with delays or disabilities. The goal is to foster the children’s development and ultimately reduce the costs to society, through minimizing the need for special education. Furthermore, programs strive to enhance the capacity of families to meet the needs of their children, while maximizing the potential for children with disabilities to later live independently (Individuals with Disabilities Education Improvement Act [IDEIA], 2004). Researchers and policymakers have long recognized the value of providing early intervention services to children who have or may be at risk for developing a disability (Guralnick, 1997; Vanderveen, Bassler, Robertson, & Kirpalani, 2009). Concerns for the welfare of young children, regardless of income and disability, have been at the forefront of domestic policies since the creation of the Children’s Bureau in 1912. The Bureau was charged with investigating ‘‘all matters pertaining to the welfare of children

Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 3–16 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019004

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and child life among all classes of our people’’ (United States Social Security Administration, n.d.). Since the early 1900s, federal and state policies have centered on protecting the welfare of America’s children through research and the provision of intervening services. For example, in the mid-1950s, government grants were used to implement preventive health services for the care of premature infants (Bradbury & Eliot, 1956). Within a decade, services were extended to include ‘‘helping parents with early social and emotional difficulties in their children in order to prevent more serious problems later’’ (Bradbury & Eliot, 1956, p. 70). Interdisciplinary teams, consisting of health care professionals, social workers, therapists, teachers, and any other relevant personnel, were also formed to provide intervention services to children who were physically impaired. Furthermore, funds were allotted to address the increased demand for the care and education of children with intellectual disabilities (Bradbury & Eliot, 1956). Researchers and policymakers have sustained the mission of the Children’s Bureau, through continued research, development, and implementation of early intervention programs that address the needs of the nation’s children and their wellbeing. One primary reason may be the benefits associated with the provision of early intervention services. Studies have shown that quality early intervention leads to less special education placement, higher graduation rates, higher salary income and employment rate, and less dependency on welfare support as adults (Bryant & Maxwell, 1997; Karoly et al., 1998; Nores, Belfield, Barnett, & Schweinhart, 2005; Reynolds, Temple, Robertson, & Mann, 2001). Furthermore, researchers found that for every dollar invested in an early intervention program, society saw returns up to $16.14 (Nores et al., 2005). It was not until 1986, however, when the federal government, under the Education of Handicapped Act Amendments (later renamed as the Individuals with Disabilities Education Improvement Act of 2004 or IDEIA), mandated the provision of early intervention services for young children (3–5 years of age) with disabilities or delays. Subsequently, it was not until the early 1990s when Congress acknowledged a need to: Enhance the development of infants and toddlers with disabilities [to] minimize their potential for developmental delay, y [minimize] the need for special education and related services after [they] reach school age, and y enhance the capacity of families to meet the special needs of their infants and toddlers with disabilities. (IDEIA, 2004)

As a result, Public Law 102-119 was passed in 1991 to provide federal assistance to states who wanted to create early intervention services for infants and toddlers at-risk of or who have disabilities. This was in response

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to the fact that significant brain development occurs within the first few years of life (IDEIA, 2004). Since the 1990s, the concept of early intervention services has shifted from focusing primarily on early childhood children with disabilities to early elementary students who may be at risk for having a disability (i.e., learning disability (LD)). This was due to the finding that traditional methods of identifying children as having LD were ineffective, because by the time many of the children were assessed, they had already experienced years of academic failure (Wagner, Francis, & Morris, 2005). In recognition of this issue, Part B of IDEIA (2004) was amended so that schools could use up to 15% of their special education funding to implement early intervening services for students at risk of being identified as having LD. Such services include (a) educational evaluations, services, and supports; (b) evidencebased literacy instruction; and (c) professional development to assist teachers in the implementation of academic interventions (IDEIA, 2004). These early intervening services allow teachers to gauge student’s progress toward the intended academic outcomes. This chapter provides an overview of current early intervention practices provided in early childhood (i.e., from birth to 3 years) and early elementary classrooms. For the early childhood interventions (ECI), primary features of ECI are presented within the context of family-centered services for infants and toddlers with disabilities. With regard to the early elementary classroom interventions, the response to intervention (RTI) approach targeting children’s learning delays is examined.

APPROACHES TO EARLY INTERVENTION Early Childhood In an attempt to minimize the need for subsequent special education and related services, the federal government provides financial assistance to states to develop and implement quality ECI services to infants and toddlers with disabilities or developmental delays (IDEIA, 2004). Under Part C of IDEIA (2004), states, which receive federal assistance, are mandated to create a statewide, comprehensive, coordinated interagency council (also known as the state interagency coordinating council or SICC) that ensures qualified infants and toddlers, and their families are identified and provided with early intervention services. The SICC is composed of parents, ECI service

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providers, and other agencies that work with children with disabilities (e.g., Head Start, preschool, and child care providers; Blasco, 2001).

Early Identification Infants and toddlers are identified for ECI services through a comprehensive child find system. Public awareness programs are implemented to disseminate information on early intervention services to parents of premature infants, children with disabilities or delays, or children who have risk factors associated with learning or developmental complications (IDEIA, 2004). Parents are contacted through primary referral sources, such as local hospitals and physicians. Infants and toddlers eligible for ECI services must be under 3 years of age and have a disability or a developmental delay in one of the following areas: physical development, cognitive development, adaptive development, social/emotional development, or communication development. At the state’s discretion, early intervention services may also be provided to children who are identified as at-risk. This is because risk factors, such as (a) prenatal conditions (e.g., low birth weight or preterm birth) and (b) family and environmental conditions (e.g., family history of spoken or written language problems, low maternal education, limited language exposure, poverty, and exposure to environmental toxins), have been associated with later learning difficulties and school failure (Gutman, Sameroff, & Cole, 2003; National Joint Committee on Learning Disabilities [NJCLD], 2007). For example, in a longitudinal study of 152 families, Gutman et al. (2003) found that students who were exposed to a greater number of risks as infants and toddlers experienced lower grades and greater number of absences by 13 years of age. The risk factors included (a) parental occupation identified as laborers, semiskilled, or unemployed; (b) low maternal education; (c) families with four or more children living at home; (d) stressful or negative life events; (e) high maternal anxiety; (f ) poor maternal mental health; and (g) negative mother–child interaction. Recognizing the impact that prenatal, familial, and environmental risk factors have on later academic success, the federal government requires that interventions for infants and toddlers are implemented within the context of family-centered services. Families are recognized as an integral part of children’s development (Young & Hauser-Cram, 2006). Early childhood services are typically home-based programs and are guided by intervention plans (individualized family service plan) that identify and meet the unique

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needs of individual families. ECI services may include speech therapy, occupational/physical therapy, parent training on how to care for their children, family counseling, psychological services, and health services.

Early Childhood Interventions ECI programs have been found to be effective in empowering parents to meet the needs of their infants and toddlers with disabilities, as well as reducing the biological and environment risks that affect child development (Bailey et al., 2005; Guralnick, 1997). For example, Vanderveen et al. (2009) found that early interventions, which focused on training parents and enhancing their care giving skills, produced positive effects on premature infants’ neurodevelopment. The interventions, which worked with 3,509 low birth weight and very low birth weight premature infants, were implemented within the first 12 months of the infants’ lives and the effects were visible up to 36 months following the intervention. Similarly, Teti et al. (2009) found that training parents on how to care for and respond to extremely low birth weight (W1,000 grams) infants’ needs produced a significant effect on the infants’ mental development (as measured by Mental Development Index of the Bayley Scales of Infant Development – II; Black & Matula, 1999). Parents were provided with training on how to interpret their infants’ behaviors, assess their infants’ development, and administer gentle tactile and kinesthetic stimulations (i.e., infant massage). At the end of the 20-week session, the infants in the intervention group scored almost 10 points higher than the control group. Furthermore, in a survey of 2,586 families, 59% of the parents felt that they were more competent as caretakers and more confident in advocating for services and supports as a result of having participated in ECI services (Bailey et al., 2005). Primary components of ECI programs consist of (a) resource supports, (b) social supports, and (c) information and services (Guralnick, 1997). Resource supports include awareness of and access to ECI services, financial assistance, and respite care, while social supports include parent support groups, family counseling, and community networks. The information and services category is composed of the formal implementation of ECI services (home or center-based), individual therapy, and parent– professional partnerships (Guralnick, 1997). Within these components, researchers contend that effective interventions are dependent on seven critical elements – intensity, timing, types of services (direct or indirect),

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maintenance of gains, comprehensiveness, provision of individualized services, and cultural sensitivity (Blair & Ramey, 1997; Bryant & Maxwell, 1997). The intensity refers to how often the services are provided and the quality of the services. Generally, increased frequency and duration of the interventions lead to more positive outcomes (Blair & Ramey, 1997). For example, Bryant and Maxwell (1997) reported that children, who participated in the Carolina Abecedarian Project from birth to 5 years of age, scored higher than the control group on cognitive assessments. They also found that the effects remained through the end of second grade. Furthermore, interventions implemented within the first 12 months of life (timing) tend to be more effective than the ones implemented later in life (Vanderveen et al., 2009). These interventions also showed that the positive effects of quality intensive programs were able to be sustained over time. With regard to the types of services implemented, services provided directly to children, as well as services provided to parents that indirectly affect children, were found to be equally effective (Blair & Ramey, 1997; Teti et al., 2009). Intervention programs that focus on comprehensive care (i.e., multiple services are provided to families and their children) were found to be more effective than interventions that focused on a targeting a single factor in child development (Blair & Ramey, 1997; Pakula & Palmer, 1997). For example, children of families who received comprehensive services including pediatric follow-up, home visits, support groups, and educational programs had significantly higher intellectual ability (IQ) scores at 36 months of age (Pakula & Palmer, 1997). On the contrary, interventions that focused on a specific skill (e.g., motor development) were found to produce little benefit (Pakula & Palmer, 1997). Finally, provision of individualized services is a fundamental principle of IDEIA’s (2004) Part C. This is in recognition that all children are different and have differing individual and familial needs. As a result, individualized interventions should also incorporate culturally sensitive practices that respect the differing values and priorities families may place on intervention services. Quality ECI are critical to children’s overall development. Given the association between risk factors and later academic achievement, interventions need to be implemented through identifying and meeting the unique needs of the family. Effective ECI programs consist of comprehensive, individualized, and intensive supports; however, these characteristics are not unique to ECI. The next section examines how comprehensive, individualized, and intensive interventions are provided in the early elementary classrooms for students experiencing learning delays.

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EARLY ELEMENTARY PROGRAMS: RESPONSE TO INTERVENTION Before the amendments of IDEIA (2004), students were identified as having a LD only if they exhibited a significant discrepancy between their IQ and academic achievement. Unfortunately, it typically takes several years before the psychometric criterion is visible (Wagner et al., 2005). Therefore, even though academic difficulties may be evident in the early grades, struggling students were often not identified and provided with special education services until the second or third grade, when the discrepancy could be documented. By then, students already have experienced years of academic failure.

Early Identification In response to the traditional ‘‘wait to fail’’ approach, researchers have sought to identify and implement effective early intervening services for atrisk students. They found that with appropriate early interventions (e.g., RTI), majority of struggling readers in the early grades were able to become, at the minimum, average readers (Kamps et al., 2008; Vellutino, Scanlon, Zhang, & Schatschneider, 2008). This was because early reading difficulties experienced by the majority of beginning readers were found to be due to a lack of appropriate experiential and instructional opportunities rather than actual reading-related disabilities (Vellutino et al., 2008). Valid identification of students who are at-risk of academic difficulties is a requisite for determining what type of intervention should be implemented. Screening measures allow teachers to identify students who may be experiencing difficulty in the classroom and thus need further evaluation. An example of a screening tool is the curriculum-based measurement (CBM). CBMs allow for efficient and reliable assessment of student’s abilities (e.g., reading) at a particular point in time as well as student progress across time (Fuchs, Fuchs, & Compton, 2004b). CBMs have actually been accepted as one of the most accurate ways of identifying struggling students (Good, Simmons, & Smith, 1998).

Response to Intervention Once the students who are experiencing learning difficulties have been identified, teachers need to ensure that appropriate intervention services

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(e.g., RTI) are available to meet the needs of those students. IDEIA (2004) has, in fact, mandated that states must allow schools to use RTI as a method of identifying a student for LD. One common RTI approach is the multi-tier model. The multi-tier model generally consists of three levels or tiers (Vaughn & Roberts, 2009). The first tier (Tier 1) provides universal screening and evidence-based instruction for all students, within a classroom, as part of the primary prevention against academic failure. In other words, Tier 1 instruction is the typical classroom instruction that all students receive. Tier 2, the secondary intervention, is for students who are not successful in Tier 1 (as identified through progress monitoring and standardized assessments) and thus need additional instruction in a targeted area (Vaughn & Roberts, 2009). For example, assessment findings may reveal that 10 students are achieving below benchmark in phonemic awareness despite having participated in Tier 1 instruction. The teacher or interventionist would then provide additional instruction focusing on phonemic awareness for those 10 students (generally in small, homogenous groups of four or five students per group). In addition to the Tier 2 intervention, biweekly progress monitoring would be conducted to determine the efficacy of the Tier 2 instruction and the student progress made toward meeting the benchmarks. Students generally receive Tier 2 instruction in addition to Tier 1 intervention. Students who do not respond to Tier 2, or for whom Tier 2 would be inappropriate (due to the severity of the students’ difficulties), would be placed into Tier 3. Tier 3, the tertiary intervention, provides even more intensive instruction with more frequent progress monitoring (e.g., weekly) to assess students’ acquisition of the targeted skill(s) (e.g., phonemic awareness). Intensity of instruction is generally measured by the number of students in an intervention group (the more intensive the intervention, the fewer number of students within the group), the duration of the intervention (the amount of time increases with intensity), and the frequency of the intervention sessions (three sessions per week versus five) and progress monitoring (weekly versus biweekly). Students who receive Tier 3 instruction experience greater difficulties in meeting the identified benchmarks when compared to the Tier 2 students. Similar to the students in Tier 2, Tier 3 students often receive the intensive intervention along with the primary intervention provided to all students. Some educators also consider Tier 3 as a special education placement (Fuchs, Compton, Fuchs, Bryant, & Davis, 2008). Approximately 20% of the students within a class typically require some form of additional intervention (Vaughn & Roberts, 2009). Efficacy of the multi-tiered system is dependent on the provision of

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systematic and explicit instruction, intensity of the intervention, use of evidence-based curriculum, ongoing monitoring of student progress, adjustment of instruction based on individual needs, and flexible grouping. Fuchs et al. (2008) assessed the efficacy of small group tutoring (Tier 2) for first graders who did not respond to evidence-based classroom reading instruction (Tier 1). Nonresponders were students whose performance level and growth rate were measured at 0.75 standard deviations or more below all study participants (n ¼ 783; Fuchs et al., 2008). All of the classroom teachers used the district’s basal text for their Tier 1 instruction, while half also used the peer-assisted learning strategies. The students who participated in the Tier 2 intervention were provided with small group tutoring (grouping ranged from one to four students per group) four times per week for 45 minutes each session. Of the initial 84 students who received primary intervention in the fall, 40 students needed secondary intervention in the spring. Pretest analysis of the 40 students indicated that the students performed at about 2/3 of a standard deviation below the local average for word identification fluency (WIF; Fuchs, Fuchs, & Compton, 2004a) and 0.75–1.0 standard deviation below the national average on unspecified IQ, oral vocabulary, and phonological processing measures. By the end of the spring semester, the intervention group made greater growth on the WIF when compared to the matched control (Fuchs et al., 2008). Brown and Felton (1990) implemented two Tier 1 interventions for first graders at-risk of reading disabilities – one focused on explicit and systematic, code-based phonics instruction, whereas the other emphasized the use of context for identifying words. Code-based phonics instruction focused on teaching students letter/sound correspondence, how to decode and blend phonetically regular words, and sight word recognition. The students were expected to achieve proficiency on one task (e.g., decoding phonetically regular words) before moving on to a more difficult task (e.g., recognizing irregular spelling of words). On the contrary, the contextbased approach centered on teaching students to identify unknown words by using the context cues. The unknown words were then decoded to determine if the correct words were chosen; however, students were not taught how to blend the phonemes. The interventions were provided for 2 years (i.e., students received the same instructional intervention as first and second graders). At the end of first grade, students who received code-based instruction scored significantly higher on the Woodcock Reading Mastery Test-Form A (WRMT; Woodcock, 1973) and the Test of Written Spelling-2 (TWS; Larsen & Hammill, 1986) than those who received context-based instruction.

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Furthermore, a majority of the code-based students (61%) performed, at the minimum, on a second grade level (grade levels ranged from 2.0 to 7.0) for WRMT’s word attack subtest at the end of first grade, whereas only 23% of the context-based students performed on the second grade level for word attack. On the word identification subtest of WRMT, majority of both groups were achieving within a first grade level. The positive outcomes of the study maintained through second grade, with the systematic code-based intervention group outperforming the context-based group (Brown & Felton, 1990). By the end of second grade, 25% of students from both groups were still performing at the first grade level on the word attack subtest. However, 47% of the code-based group performed at or above third grade, compared to approximately 26% of the context-based students. On the word identification subtest, 35% of the context-based students were still at the first grade level by the end of second grade, compared to 5% of the code-based students. The remaining students performed at or above grade level. Kamps et al. (2008) examined the efficacy of a RTI approach for working with kindergarteners identified as being at the intensive level of risk for reading failure. The intensive level was defined according to the Dynamic Indicators of Basic Early Literacy Skills measure (DIBELS; Kaminski & Good, 1998) – the ability to identify no more than seven sounds on the nonsense word fluency and no more than eight sounds on the initial sound fluency. Eighty three students from 11 elementary schools were provided with tiered interventions from kindergarten through second grade. Schools were randomly assigned to either the experimental group or the control group. Students in the experimental condition participated in small group instruction (consisting of three to six students per group) focusing on explicit phonemic awareness and phonics-based instruction. The curricula used for the experimental group were consistent with the Direct Instruction program. Students were assigned to the appropriate tiers depending on their performance on the DIBELS assessment, which was given three times each year. The students in the comparison group, on the contrary, did not participate in RTI. They did, however, receive small group instruction (3–12 students per group), with groupings based on teacher recommendations, rather than assessment data. The instruction for the comparison groups focused on phonemic awareness, with less attention on phonics instruction and structured lessons (Kamps et al., 2008). Findings from Kamps et al. (2008) revealed that students who participated in RTI and received explicit and systematic instruction using the Direct Instruction curricula (experimental group) outperformed the control group on the Woodcock Reading

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Mastery Test-Revised (Woodcock, 1998) and the DIBELS (Kaminski & Good, 1998). Furthermore, a greater percentage of the students who participated in Direct Instruction performed at benchmark at the end of first and second grade when compared to the control group. The RTI studies substantiate the importance of implementing the multitiered approach for students with learning delays, given that interventions targeting individual needs, through the provision of differing levels of instruction and ongoing assessments, have been found to be effective in preventing future difficulties. As a result, it is imperative that schools allocate the necessary resources to ensure that proper identification of struggling students are conducted as early as possible, so that they can be provided with the intensive, evidence-based interventions needed for academic success.

CONCLUSION Although interventions may vary greatly between early childhood and early elementary (family-focused versus child-focused), key elements of effective interventions are evident across all ages. For example, as evidenced in Fuchs et al. (2008) study, the intensity of the intervention is positively associated with child outcomes. Timing of the intervention, as well as the maintenance of its effects, is essential to ensuring positive outcomes of the intervention. For example, Vanderveen et al. (2009) found that the positive effects associated with interventions implemented within the first 12 months of a child’s life were visible up to 36 months. Furthermore, Brown and Felton (1990) revealed that systematic interventions provided in first grade produced positive outcomes that sustained through second grade, and by the end of the second grade year, majority of the students were achieving at or above grade level. In fact, experts contend that if services were delayed until students were 9 years of age, when they are traditionally identified as having LD, approximately 75% of those students will continue to experience reading difficulties in later years (Lyon, 1998). Early identification and intervention services for children have long been recognized as being critical to the prevention of later disabilities or academic failure. From the creation of the Children’s Bureau to the amendments of IDEIA (2004), researchers have sought to identify and implement effective interventions that would meet the needs of children with delays or disabilities. Researchers can now predict, with 80–90% accuracy, who will later experience reading difficulties (Lyon, 1998). Researchers have also

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identified the risk factors (e.g., preterm or low birth weight) that may lead to later delays (Lyon, 1998). Given the existing knowledge on child development and evidence-based strategies and programs, it is imperative that educators and service providers take advantage of that knowledge and provide eligible children with the needed intervention services. Concerns with finding the necessary resources and funding to implement evidencebased interventions, though, are not without warrant. However, the costbenefits of early intervention are undeniable, and policymakers need to focus on ensuring that funds are available to provide the appropriate services. Administrators need to streamline their resources so that what is available could be used efficiently and effectively. If the goal of the government is truly to maximize young children’s ability to live independently when they become adults, and thereby reduce the costs to society, then evidence-based interventions indeed need to be provided to eligible children as early as possible. As the NJCLD (2007) stated, ‘‘It is not in the best interest to ‘wait and see’ or hope that the child will ‘grow out of ’ his or her problems (p. 65).

REFERENCES Bailey, D. B., Hebbeler, K., Spiker, D., Scarborough, A., Mallik, S., & Nelson, L. (2005). Thirty-six-month outcomes for families of children who have disabilities and participated in early intervention. Pediatrics, 116, 1346–1352. Black, M. M., & Matula, K. (1999). Bayley scales of infant development – II. New York: Wiley. Blair, C., & Ramey, C. T. (1997). Early intervention for low-birth-weight infants and the path to second-generation research. In: M. J. Guralnick (Ed.), The effectiveness of early intervention (pp. 77–97). Baltimore, MD: Brookes Publishing Co. Blasco, P. M. (2001). Early intervention services for infants, toddlers, and their families. Needham, MA: Allyn and Bacon. Bradbury, D. E., & Eliot, M. M. (1956). Four decades of action for children: A short history of the Children’s Bureau (Available at http://www.ssa.gov/history/childb1.html. Retrieved on May 12, 2009.). Washington, DC: U.S. Government Printing Office. Brown, I. S., & Felton, R. H. (1990). Effects of instruction on beginning reading skills in children at risk for reading disability. Reading and Writing: An Interdisciplinary Journal, 2, 223–241. Bryant, D., & Maxwell, K. (1997). The effectiveness of early intervention for disadvantaged children. In: M. J. Guralnick (Ed.), The effectiveness of early intervention (pp. 23–46). Baltimore, MD: Brookes Publishing Co. Fuchs, D., Compton, D. L., Fuchs, L. S., Bryant, J., & Davis, G. N. (2008). Making ‘‘secondary intervention’’ work in a three-tier responsiveness to intervention model: Findings from the first grade longitudinal reading study of the National Research Center on Learning Disabilities. Reading and Writing, 21, 413–436.

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Fuchs, D., Fuchs, L. S., & Compton, D. L. (2004a). Identifying reading disability by responsiveness-to-instruction: Specifying measures and criteria. Learning Disability Quarterly, 27(4), 216–227. Fuchs, D., Fuchs, L. S., & Compton, D. L. (2004b). Monitoring early reading development in first grade: Word identification fluency versus nonsense word fluency. Exceptional Children, 71, 7–21. Good, R. H., Simmons, D. C., & Smith, S. B. (1998). Effective academic interventions in the United States: Evaluating and enhancing the acquisition of early reading skills. The School Psychology Review, 27, 45–56. Guralnick, M. J. (1997). Second-generation research in the field of early intervention. In: M.J. Guralnick (Ed.), The effectiveness of early intervention (pp. 3–20). Baltimore, MD: Brookes Publishing Co. Gutman, L. M., Sameroff, A. J., & Cole, R. (2003). Academic growth curve trajectories from 1st grade to 12th grade: Effects of multiple social risk factors and preschool child factors. Developmental Psychology, 39, 777–790. Individuals with Disabilities Education Improvement Act. (2004). 20 U.S.C. y 1400 et seq. Kaminski, R., & Good, R. H., III. (1998). Assessing early literacy skills in a problem-solving model: Dynamic indicators of basic early literacy skills. In: M. R. Smith (Ed.), Advanced applications of curriculum-based measurement (pp. 30–41). New York, NY: Guilford. Kamps, D., Abbott, M., Greenwood, C., Wills, H., Veerkamp, M., & Kaufman, J. (2008). Effects of small-group reading instruction and curriculum differences for students most at risk in kindergarten: Two-year results fro secondary- and tertiary-level interventions. Journal of Learning Disabilities, 41, 101–114. Karoly, L. A., Greenwood, P. W., Everingham, S. S., Hoube, J., Kilburn, M. R., Rydell, C. P., Sanders, M., & Chiesa, J. (1998). Investing in our children: What we know and don’t know about the costs and benefits of early childhood interventions. Santa Monica, CA: RAND Distribution Services. Larsen, S. C., & Hammill, D. D. (1986). Test of written spelling-2. Austin, TX: Pro-Ed. Lyon, G. R. (1998). Overview of reading and literacy initiatives. Washington, DC: National Institute of Child Health and Human Development. National Joint Committee on Learning Disabilities (2007). Learning disabilities and young children: Identification and intervention. Learning Disabilities Quarterly, 30, 63–72. Nores, M., Belfield, C. R., Barnett, W. S., & Schweinhart, L. (2005). Updating the economic impacts of the High/Scope Perry Preschool Program. Educational Evaluation and Policy Analysis, 27, 245–261. Pakula, A. L., & Palmer, F. B. (1997). Early intervention for children at risk for neuromotor problems. In: M. J. Guralnick (Ed.), The effectiveness of early intervention (pp. 99–107). Baltimore, MD: Brookes Publishing Co. Reschly, D. J. (2007). Overview document: Teacher quality for multitiered interventions. Washington, DC: National Comprehensive Center for Teacher Quality. Reynolds, A. J., Temple, J. A., Robertson, D. L., & Mann, E. A. (2001). Long-term effects of an early childhood intervention on educational achievement and juvenile arrest: A 15-year follow-up of low-income children in public schools. Journal of the American Medical Association, 285, 2339–2346. Teti, D. M., Black, M. M., Viscardi, R., Glass, P., O’Connell, M. A., Baker, L., & Cusson, R. (2009). Intervention with African American premature infants: Four-month results of an early intervention program. Journal of Early Intervention, 31, 146–166.

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United States Social Security Administration. (n.d.). The creation of the Children’s Bureau. Available at http://www.socialsecurity.gov/history/childb1.html Vanderveen, J. A., Bassler, D., Robertson, C. M. T., & Kirpalani, H. (2009). Early interventions involving parents to improve neurodevelopmental outcomes of premature infants: A meta-analysis. Journal of Perinatology, 29, 343–351. Vaughn, S., & Roberts, G. (2009). Secondary interventions in reading. Teaching Exceptional Children, 39, 40–46. Vellutino, F. R., Scanlon, D. M., Zhang, H., & Schatschneider, C. (2008). Using response to kindergarten and first grade intervention to identify children at-risk for long-term reading difficulties. Reading and Writing, 21, 437–480. Wagner, R. K., Francis, D. J., & Morris, R. D. (2005). Identifying English language learners with learning disabilities: Key challenges and possible approaches. Learning Disabilities Research & Practice, 20(1), 6–15. Woodcock, R. (1998). Woodcock reading mastery tests-Revised. Circle Pines, MN: American Guidance Service. Woodcock, R. W. (1973). Woodcock reading mastery tests. Circle Pines, MN: American Guidance Service. Young, J. M., & Hauser-Cram, P. (2006). Mother-child interaction as a predictor of mastery motivation in children with disabilities. Journal of Early Intervention, 28, 252–263.

CHAPTER 2 EARLY IDENTIFICATION/ INTERVENTION: CAN MISIDENTIFICATION/ MISINTERVENTION IMPACT STUDENTS, TEACHERS, AND FAMILIES? Barbara Metzger, Cynthia G. Simpson and Jeffrey P. Bakken A student must be identified as having a specific disability in order for him or her to receive special education services. The Education for All Handicapped Children Act (PL-142) mandated that only students who are identified as handicapped and whose handicap prevents them from benefiting from regular education instruction can be placed in a special education setting (Christensen, Gerber, & Everhart, 1986). Since the passing of this Act, the field of special education is sometimes so focused on the legal process that the quality of special education services is overlooked. In addition, much controversy has existed regarding the identification and placement of students into special education programs. For example, the reauthorization of the Individuals with Disabilities Education Improvement Act (IDEIA, 2004) has refueled the debate of the identification process of Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 17–34 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019005

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students with learning disabilities. The frequently used discrepancy model (Deisinger, 2004) is being replaced by a response to intervention (RtI) model (Mellard & Johnson, 2008; Shores & Chester, 2009). Although there is no one RtI model, in general it refers to a multistep model of interventions for students who are struggling in the regular education classroom (National Education Association, 2007). However, critics argue that the implementation of this model may lead to misidentification or underidentification of individuals needing services for special education. As professionals who believe passionately that each child with special needs deserves high-quality special education services and who believe that educators are presented with the difficult task of becoming effective teachers in today’s schools, we find ourselves examining those areas in special education that have stirred a debate among special educators, advocates, and parents of individuals with disabilities. To overcome obstacles that hinder the proper identification of children with special needs and the subsequent evidence-based interventions, it is necessary to acknowledge and examine problems found within each of these areas as a first step to developing solutions. Ideally, a child receives early assessment, accurate diagnosis, appropriate placement, and subsequently appropriate services. When the process works well, there can be many benefits for both the child and the family. Unfortunately, the process does not always work well when the ideal meets the social and institutional reality of schools, and this impacts students, families, and teachers in many capacities (Christensen et al., 1986). In this chapter, we first address the misidentification of students and then address problems with which can stem from misintervention. Finally, we reflect on the impact of how problems in special education affect all those involved.

MISIDENTIFICATION Misidentification of students with disabilities is a widely publicized aspect of the shortcomings of our special education programs. Many factors can contribute to misidentification. In the Congressional Research Service (CRS) Report for Congress (Apling, 2001), three issues were specifically identified as reasons for possible misidentification. ‘‘Misidentification can result from failing to identify those with disabilities, from identifying children with disabilities they do not have, and from delaying identifying children with disabilities’’ (p. 2). In addition to the aforementioned concerns, an overrepresentation of minorities in special education programs has been a focal point for critics of special education programs and

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eligibility criteria for decades (see Harry & Klinger, 2006). Biases in assessment often lay the foundation for overrepresentation of minorities. Others express serious concerns regarding misidentification due to a direct result of the referral (or lack of effective prereferral) and evaluation practices used in many states (Ysseldyke, Algozzine, Richey, & Graden, 1982). Last, misidentification due to the changing eligibility criteria and differences in eligibility criteria across states has been added to the concerns in the field of special education.

Referral, Evaluation, and Eligibility Criteria Referral Practices Effective use of prereferral intervention strategies is the foundation that is needed to correctly identify those children who need to be referred to determine whether they meet the eligibility criteria for special education services. Many times, ineffective development of prereferral teams and inaccurate selection and implementation of prereferral strategies lead to a false need for referral. Conversely, this same situation could lead to a child not being referred for further assessment. For example, a regular education teacher may prematurely refer a child to special education because he or she recognizes that the child needs extra help and think it is the only option available (National Education Association, 2007). Other concerns regarding the referral and evaluation practices revolve around the use of formalized assessment measures for eligibility purposes, specifically, learning disabilities. Teachers need to be trained to make the best educational decisions as possible based on current available data. Identification of students with learning disabilities has created a strong debate over identification processes. Identifying specific disabilities based on less subjective measures such as a vision and hearing impairment, however, fuel less debate. Identification of learning disabilities, autism, and emotional disturbance requires a level of subjective measures. The use of such subjective measures (e.g., parent questionnaires, teacher referrals and diagnostic professional judgment) provides the foundation for more frequent errors in the identification process. Although IDEIA 2004 permits the use of an alternate method of determining eligibility for special education services as learning disabled, some states have continued to use the discrepancy/achievement model. In this model a severe discrepancy must exist between achievement and IQ for a child to receive services for special education under the learning disability

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category. Those states not using a discrepancy model have moved to the RtI model as a means of determining eligibility. Although both methods can be utilized (per federal law), each methods draws skeptics to question the processes and the implications they have on students needing special education services. For instance, one of the possible side effects of the RtI process is that it may result in an unwritten policy or subtle pressure to use the assessment procedure as a way to reduce referrals to special education. Or, the RtI process may lead to sluggishness in starting the referral process. School staff may misunderstand the RtI process and believe that they cannot make a referral even when they have a strong suspicion that the student has a disability (Weatherly, 2008). Others indicate that although prereferral systems have been implemented, they serve only as a formality in the referral process. Unfortunately, the system is often inaccurately used or used before the actual attempt to remediate within the general education setting. In the RTI model, prereferral strategies are documented as the child progresses through the specified tiers of instructional support. There is the general assumption that only those students who have received proper documented prereferral interventions are considered for special education services, but the entrance of misinformation into the RTI process could occur leading to an improper identification, lack of identification, or misidentification of a specific disability. The process for referring a child for special education can be convoluted with assessment personnel and classroom teachers being forced to make decisions that have lifelong implications for students. This alone causes concerns, but the reality is that all individuals make errors, and ethical decision making is being brought to the forefront. Defining a disability is not straightforward, and the categories of disability change over time. In addition, many children with an identified disability in one state would not meet eligibility criteria in another state. For example, a child displaying characteristics of emotional disturbance in Texas may move to an adjoining state where he or she is identified as having a learning disability or possibly no disability at all. Evaluation Practices It is possible that students may be identified as needing special education services when the reality is that the identification of a specific disability category was a direct result of errors in the assessment process. Few would argue that assessment instruments are subjective in nature, including many standardized, formal assessment instruments. In addition to errors that can be made during assessment administration procedures (e.g., failure to follow

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standardization techniques), often errors can be made while scoring the responses and/or converting raw scores to scaled scores. Even if the assessment is administered correctly, assessment personnel often misinterpret the considerable amount of information accumulated from testing (Christensen et al., 1986). These errors often directly impact the overall fullscale IQ. For example, in the discrepancy model, the IQ score is fundamental in determining eligibility. Technical competence in administering assessment is a necessity in correctly identifying a student. Lack of competency to select appropriate tests and to administer and score the selected instruments could lead to misidentification or lack of identification. Not only does the ability of the assessment personnel come into question when determining eligibility, but the way the assessment data are used can create controversy as well. Depending on the regulations of the state and the specific school districts within a state, there can be inconsistencies in the label a child receives. These differences reflect new laws, policies, personnel and funding opportunities more so than any real changes in the student population (Nelson, 1983). As previously addressed, the 2004 IDEIA regulations allow states to select from three different options in diagnosing a learning disability: (a) the discrepancy model, (b) RtI, or (c) other research-based procedures (Zirkel & Krohn, 2008). One state may select the discrepancy model, whereas another state may select an absolute low achievement model, and thus, a child may be found eligible for special education services in one state, but not in the other. This inconsistency in diagnosis shows that the type of identification model used may impact the outcome of the eligibility determination. Additionally, specific characteristics and eligibility areas have changed across time. For example, autism was not recognized by the US Department of Education as a special education diagnostic category until 1990 (Morrier, Hess, & Heflin, 2008). Identification categories change over time in response to philosophical fashions, politics, and research (Nelson, 1983). For example, autism as a spectrum disorder and the broadening of the disability characteristics may have contributed to the increasing incidence. These changes may have a direct link to a decrease or increase of the number of children being identified under a specific category. When the process of assigning the label is inconsistently and/or inaccurately applied, it leads to questioning the label as well as the subsequent placement and services (Christensen et al., 1986). It may be surprising to some outside of the identification process that there is not consensus among professionals in defining some categories of disabilities. For example, there are several definitions of emotional/ behavioral disorder as well as learning disabled (Christensen et al., 1986).

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Identification of students based on behavioral deficits, excesses, or patterns depends on the clinical experience and judgment of school personal; and sometimes professionals disagree. There are categories of identified disabilities, such as autism, that have no markers other than behavioral ones. Yet, behaviors that are attributed to children with autism are shared by children identified as mentally retarded, multiple handicapped, and emotional/behavior disordered. Behaviors that are attributed to children with learning disabilities are exhibited by those who are identified as mentally retarded or emotional/behavior disordered as well as those without any special education label (Christensen et al., 1986). When behaviors of students are neither specific to that population nor universal within it, and yet are the primary markers for identification, there is potential for misidentification. The Politics of Eligibility Categories What is the function of identifying a student with a specific eligibly category as needing special education services? Legally, categorizing a student is necessary to receive needed services. Practically, identifying students with a specific disability can facilitate educational programming. Economically, labeling a child may have nothing to do with the child and his or her educational needs. For example, identifying a child with a specific disability sometimes is not in the school district’s best interests. For example, school districts with fewer financial resources are less likely to identify a child as needing special education services (Nelson, 1983). A child’s identifying eligibility category may be a function of other practical considerations such as the availability of programs and personnel, or how many other children have been identified with the same disability. Identifying fewer students as needing special education services or implementing an inclusion only model that ignores the child’s specific disability are methods to reduce costs (Nelson, 1983). For example, in the state of Texas, students with the label of autism qualify for additional services such as in-home, parent training. Thus, some school districts may serve the child under the general category of developmental disability and delay identifying the child with autism to avoid the costs of the additional services. Conversely, it can be argued that labeling a child is very appealing to educators and parents when deficits inherent in the child are due to poor instructional practices or parenting (Cassidy & Jackson, 2005). ‘‘Learning disability is particularly appealing in that no conscious act on the part of the child is considered responsible for the problemy’’ (Christensen et al., 1986, p. 327). In most cases, a child must be identified as needing special education before receiving additional services. The secondary level of RtI, as previously

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addressed in the earlier section on referral, however, provides a failing student with additional instructional support without the necessity of a specific disability (Brown-Chidsey, 2007). Providing students with intervention before considering them for special education has the effect of reducing the number of children in special education (Brown-Chidsey) and leads to the question of how necessary is any label?

Disproportionality Social aspects of the referral and assessment process may also contribute to misidentification. As early as the 1960s, the overrepresentation of minorities being identified as special needs students has been a target of criticism in the field of special education. The rate of referral for special education services for ethnically diverse students is higher than that for Caucasian students. The percent of black and other racial minorities found to be eligible for special education is much higher than expected given the percent of racial minorities in the US population (Brown-Chidsey, 2007). For example, disproportionate numbers of minority students are identified as having a learning disability (Christensen et al., 1986), emotional/behavior disorder, mental retardation (National Education Association, 2007) as well as autism (Morrier et al., 2008). Why is disproportionality a large, national concern? The list of reasons is long but a prime one is that identifying students as disabled when they really are not leads to inappropriate services for the mislabeled students as well as fewer resources for those who actually need services. Also, once students start to receive special education services, they tend to remain in special education (Harry & Klinger, 2006). In addition, once students are found eligible for services, those with diverse ethnic backgrounds are more likely to be placed in a self-contained special education classroom than in the general education classroom (Fierros & Conroy, 2002) where they will be more likely to experience a less rigorous curriculum which in turn can lead to diminished academic and post-secondary opportunities (Harry & Klinger, 2006). This bias toward more restrictive placement for minority students covers various eligibility categories such as mild mental retardation, specific learning disability, as well as emotional/behavior disorder (de Valenzuela, Copeland, Huaqing Qi, & Park, 2006; Hosp & Reschly, 2003; Skiba, PoloniStaudinger, Gallini, Simmons, & Feggins-Azziz, 2006). Disproportionality can also contribute to racial separation (Harry & Klinger, 2006) as well as social stigma.

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Determining the reason for the disproportionate number of minority students being identified as students with disabilities is not an easy task. Various possible causes have been bought to the forefront, but no single cause has been identified. Test bias and the predominance of white, middle-class culture in the field of education are contributors (Maheady, Towne, Algozzine, Mercer, & Ysseldyke, 1990). But the issue is complex. For example, when a student has limited English skills, it can be difficult for educators to determine the cause of poor academic performance and whether or not special education services are warranted. It is estimated that by 2010 the number of students who speak a language other than English will increase to more than 30% of students (National Association for the Education of Young Children, 2005). This increase in English language learners (ELLs) will most likely result in an increase in special education referrals and placements. Children who are ELLs are between 1.42 and 2.43 times more likely to be labeled as learning disabled and language impaired than children who are English speakers (Artiles, Rueda, Salazar, & Higareda, 2005). As part of the special education process, school district personnel must determine whether a child’s poor academic performance is actually a case of limited English proficiency masking a disability, or whether low test scores are an artifact of assessment, or whether poor academic progress is a reflection of the instruction the child has received (Wagnor, Francis, & Morris, 2005). It may be the problem of over-referral to special education is not in the referral and assessment system per se, but in the nature of the regular education programs that are offered to language minority students. For example, when school personnel are ethically diverse, children from ethnically diverse backgrounds are less likely to be referred to special education (Serwatka, Deering, & Grants, 1995), suggesting that factors such as the culture of the school staff and the student’s culture can also influence referral rates in special education. Although race and ethnicity dispropotionality in special education has dominated the field recently (Harry & Klinger, 2006; Morrier et al., 2008), there is also an issue of gender in that there is a long-standing underrepresentation of female students. Boys are 1.33 times as likely as girls to be identified under the mental retardation eligibility category, twice as likely to be identified as learning disabled, and almost 3.5 times as likely to be identified as having emotional/behavior disorder (Coutinho & Oswald, 2005). These data suggest that girls with disabilities are not being appropriately identified and thus may not be receiving effective intervention (Coutinho & Oswald, 2005). As with minority students, it is hypothesized that bias in the referral and identification process is a likely cause the underrepresentation of

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girls. For example, criteria for emotional/behavior disorder may not capture behaviors more prevalent in girls such as depression or suicidal ideation (Coutinho & Oswald, 2005). In addition to concerns with misidentification, concerns also exist with misintervention and the impact this can have on students and their teachers and families.

MISINTERVENTION There is an assumption that a correct diagnosis leads to a prescription of educational treatment (Christensen et al., 1986). A child may be identified early as well as identified accurately, but if the services provided are not appropriate, then there is little benefit. As previously noted, RtI is an alternative approach to determine a student’s eligibility for special education as well as a method of instruction (Brown-Chidsey, 2007). Although RtI has many positive aspects, the success of this model rests upon the assumption that all students progressing through the designated tiers of instruction are being taught using research-based, effective teaching methodologies. Unfortunately, this is not the case in many classrooms. The lack of research-based teaching methodologies during the RtI process demonstrates how misidentification could occur. Looking only at programming after identification, services provided often are inappropriate due to these same ineffective, not research-based teaching methodologies. According to Heward (2005, p. 317), ‘‘observational studies of classroom practice consistently report that the education received by many U.S. students does not take advantage of existing knowledge about effective instruction.’’ Although not best practice, sometimes the reality is that a specific eligibility criterion determines not only the amount and type of services provided but also the student’s placement, and this can lead to inappropriate intervention. For example, students identified with autism may be automatically placed in classrooms designed for children with autism. Although this practice may benefit some students, this placement may not be appropriate for all children on the autism spectrum. The practice of a label determining placement may lead to a child with conversational language being placed in a classroom in which he or she is the only child with functional language. This placement does not benefit the child without peer language models and another type of classroom may be more academically and socially appropriate, but it can be difficult to go against the standard operating procedure to do what is best for a child. In addition, if the child’s category determines placement, an incorrect diagnosis can lead to a mismatch between the child’s needs and the services.

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For example, a child incorrectly diagnosed with autism placed in a program designed specifically for children on the spectrum may not be receiving appropriate intervention. The question of the quality of services must be addressed. Who is to blame when a student does not learn? Within the field of education, it is often the child or the parents. Indeed, there are environmental events beyond the educator’s ability to control such as socioeconomic, cultural, or familiar factors that can play a causal role in a special education student failing to learn. However, a common self-delusion in the education field is that schools provide equal educational opportunity and that the distribution of knowledge and skills is unbiased and well done. Thus, when a student does not learn the instructional process is not attributed the blame. Rather, the failure is assumed to be a result of individual student’s deficits (Christensen et al., 1986; Heward, 2005). Although the field of special education still has a lot to learn about how to effectively teach all children with disabilities, we do know that if a student is not learning, then something needs to change about how he or she is being taught (Heward, 2005). A scientific view of education ‘‘places the responsibility for student learning on teachers and schools’’ (Heward, 2005, p. 324). We agree with Harper, Maheady, and Mallette (2005, p. 140) that ‘‘change in pupil performance as a function of teacher instruction’’ is the bottom line. Special education students have been especially denied effective instruction due to ineffective interventions, fads, and miracle treatments (Jacobson, Foxx, & Mulick, 2006). Some disabilities such as autism are a magnet for treatments that either have not been subjected to the rigors of science or, when studied, have not been supported as effective (Mukuria & Obiakor, 2008). Thus, quality of instruction remains a problem for the field of special education. Another element that addresses misintervention is the actual curriculum being implemented. Services may be inappropriate due to curriculum that is not covering the skills needed for the student to be successful in his or her next placement or function in his or her everyday environment. Current practices of modifying the curriculum used for the general education students may be appropriate for children with mild disabilities, but can be a farce for children with severe disabilities. Smith (as cited in Christensen et al., 1986) found that school personnel involved in special education placement decisions severely sanctioned attempts to explain a child’s behavior as a result of teaching methods or curriculum. Yet, unlike most professions in which practitioners’ tools are thoroughly tested to ensure that they are reliable, education has a long history of adopting new curricula with minimal to no evidence of effectiveness (Spear-Swerling & Sternberg, 2001).

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Although, many are quick to identify the inability of teachers to perform accurate research-based instruction as a sole determent in lack of student progress, it must be noted that improper data collection may be the underlying issue in determining the type of instruction to be utilized. Although special education teachers are required by law to use data for instructional decisions and 75% of them in one survey agreed that is ‘‘important’’ to do so, 85% reported that they ‘‘never’’ or ‘‘seldom’’ collected data and instead reported that they used anecdotal and subjective measures to determine student progress on IEP objectives (Cooke, Heward, Test, Spooner, & Courson, 1991). If teachers do not collect direct and frequent measurement of student performance, how can they verify the effectiveness of their instruction? Ineffective instruction will continue unless the teacher collects relevant data and correctly interprets it. Conversely, effective instruction could be discontinued if the teacher is not collecting data that shows small, gradual improvement in student performance (Heward, 2005).

THE SOCIAL CONTEXT OF MISIDENTIFICATION AND MISINTERVENTION Impact on Students When school personnel determine a child needs special education services and assign a child an eligibility category, we are assigning a label to the child. There can be unintended negative consequence of the labeling process for the student. Some individuals with disabilities are aware that others evaluate those with disabilities negatively, that there is a social stigma associated with their difference (Green, Davis, Karshmer, Marsh, & Straight, 2005). Link and Phelan (2001) call labeling, a recognition of difference, one of the five components of stigma. Once a label is given, it tends to become attached to the child, and not his or her behavior (Cassidy & Jackson, 2005). For example, a student becomes known as ‘‘violent’’ rather than a student who occasionally exhibits difficult behaviors. Also, once a label is assigned, it tends to follow the child by both reputation and the student’s file (Cassidy & Jackson, 2005). Factors such as a child’s physical appearance, race, ethnicity, and socio-economic class can all influence a teacher’s expectations for a student’s academic achievement; so to does the student’s eligibility category label (Rist & Harrell, 1982). A negative, self-fulfilling prophecy occurs when erroneous teacher expectations for a student’s achievement lead to

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differential teacher behavior, which subsequently leads to a student performing consistently with those expectations. The self-fulfilling effects of teacher expectations are small, however, because teacher expectations of student achievement are generally accurate. The self-fulfilling effects of teachers’ negative expectations, however, are higher when the teacher’s expectations of student achievement are not accurate (Jussim & Harber, 2005). Thus, when a child has been misidentified, there is the possibility of a negative, self-fulfilling prophecy. Also, there is limited research to support that students who belong to a stigmatized group, such as most eligibility categories, may be especially susceptible to a negative, self-fulfilling prophecy (Jussim & Harber, 2005). On the contrary, if a child is not identified early, he or she may not be given services during a critical time of development. Especially for children with milder disabilities, ideally early intervention will help them exit services when they are still in elementary school. For example, if a child with limited English ability who actually has a problem in learning language that is not identified until the third grade, the child may be so far behind at that point that remediation is not possible. Children achieving less than they could have if they had been given effective, intensive intervention is the normative culture in special education; especially for students with more severe disabilities. Yet poor student achievement is so common in special education that many in the field are no longer offended by it. It is so common that IEDA 2004 acknowledges that the quality compared to nondisabled peers remains a barrier in many local schools (Kozleski et al., 2008). The impact of ineffective instruction is ubiquitous: it affects every aspect of the child’s daily life as well as limiting future possibilities. For a child to not meet his or her individual potential because of poor quality instruction is a tragedy.

Impact on Teachers Most special educators are people who went into the field because they love children and want to make a significant difference in the lives of those with disabilities. When a child learns a skill because of our efforts, teaching is wonderful and joyful. One of the foundation beliefs of the field of special education is the importance of each individual. Just because a student is different does not equate into being of less worth. There is juxtaposition, however, of the practical reality of the poor outcome of special education and the beliefs of special educators. Unfortunately, a good special education

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teacher is too often functionally defined as one who keeps students quiet and who does not refer students to the office for disciplinary reasons, not as one who provides quality instruction that make a difference. When a child is not receiving appropriate services as a result of an incorrect eligibility category or inappropriate intervention, the teacher is much less likely to be effective. Most teachers are not going to stay professionally or personally motivated when their efforts do not impact students. Although there is some debate regarding the rate of teacher attrition in special education and its multitude of causes, not making a difference is a contributing factor to burnout and leaving the field (Billingsley, 2004). Even worse is the teacher who knows what he or she is not helping students, but continues to go through the motions, marking time to retirement. Teacher retention consists of more than a person on the job, it also consists of engagement in teaching (Gold, 1996). Thus, there is an interdependent relationship between student and teacher in that quality instruction and subsequent student achievement have both immediate and long-term impact for both.

Impact on Families In general, families that include children with disabilities face many challenges and experience higher stress levels than families whose children do not have disabilities (Glidden, 1993). For example, children with disabilities may have behavior problems and require extensive supervision. There may also be additional expenses related to child-care, additional therapies or medical care. Some family members may be affected by the stigma associated with a special needs child (Green et al., 2005). In addition, there may be social constraints on the families’ leisure activities. Even though these families face many challenges, some research suggests that many families are able to adjust and that having a child with special needs does not automatically cause maladjustment and family dysfunction (Dodd, Zabriskie, Widmer, & Eggett, 2009; Dyson, 1996; Ferguson, 2002) An important challenge to families of children with disabilities is becoming an advocate for their child in the special education process. As professional educators, we have some insight into how institutional practices can be difficult for families to navigate as they work to get educational services for their children; but we cannot really know what it is like unless we are a parent, sibling, or grandparent who has sat alone in an IEP meeting surrounded by a large number of professionals and bombarded

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by a plethora of forms and special education slang. The relationship between school personnel and families is often defined by the professionals; we are the experts and the family is the recipient of our advice. This view of the family as recipients may lead to the families’ view and requests being subordinated to the professionals as their views are assumed to be better and more accurate (Kozleski et al., 2008). Additionally, there is a professional distance between the school personnel and the family and the family members are supposed to respect us as knowledgeable professionals and to trust us that we will do what is best for the child (Nelson, Summers, & Turnbull, 2004). And often this relationship does work and perhaps with minimal negotiating, the child receives needed services. Unfortunately, the relationship between school personnel and families does not always work. The institutional practices for identification, placement and intervention decisions in American special education assumes families having ‘‘specific patterns of communication, an understanding of school practices and rules, access to information from a variety of sources, and the cultural and social capital necessary to participate in decision making with professionalsy’’ (Kozleski et al., 2008, p. 28) and in the case of conflict, access to advocates and/or lawyers knowledgeable in special education. Kozleski et al. (2008, p. 32) give a potent example of what can go wrong when school personnel fail to make the process and the reasons for it transparent The school sent me somewhere to have some assessments done with my son, but I don’t know what kind of assessments or what they were for. I took him, but I don’t know why, and I never heard anything about the results. [translated from Spanish]

Kozleski et al. reported that many families feel coerced to accept the professionals’ assessment results as well as advice regarding placement and intervention. The American special education process demands a lot from parents and professionals, and thus, it is not surprising that sometimes the relationship between parents and school personnel can be difficult. One of the vital elements of the relationship between the family and school district personnel is trust and when school district personnel make mistakes, it can erode or even destroy trust. The family is depending on school personnel to determine that the child needs special education services, what type and how much, and who will deliver those services competently. When a child does not receive appropriate services, there can be profound and far-reaching impact on the daily life of the family. For example, if a child without verbal communication skills is not taught functional communication skills to appropriately express his or her needs and wants,

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the child is more likely to engage in self-injury or aggression toward family members. This in turn could possibly limit the family’s ability to participate in the community or cause family members to live in fear. In addition to affecting everyday family life, misintervention can also have future implications. For example, if a child with behavioral problems is not taught self-management and appropriate methods of getting his/her needs met, this can severely restrict his/her future choices in terms of living arrangements. It may force family members to make a more restrictive residential placement decision because the child can no longer live at home or the child may not be accepted into an attractive group home placement. A child with learning disabilities who is a marginal reader and is not taught to read fluently may be limited in his/her future career options. Also, his/her family member may be in a difficult position of financially supporting or assisting the individual because he/she is unemployed or under-employed. A child with autism who has poor social skills who is not taught to interpret body language and respond accordingly may have difficulty making and maintaining adult friendships as well as adult relationships. This may lead to the child’s family being his/her only source of social interaction. The depth and the breath of the reverberations of misidentification and especially misintervention on the family are a reminder of the sobering responsibility of those of us in the special education field.

CONCLUSIONS The system of special education does not always work the way it should; unfortunately the issues related to misidentification and misintervention presented in this chapter are not new. Although the federal law mandates the rights of students with special needs, there is a gap between best practices for identifying and educating our students that are present in the literature and the policy and practice of schools (Liu, Ortiz, Wilkinson, Robertson, & Kushner, 2009). At times it seems an overwhelming challenge to fight and change the system of special education and get best practices as the part of the normative culture. However, when one starts to look at the wide-reaching ramifications of misidentification and misintervention, it is a reminder of how important education is to all involved. Teachers, family members and students are intertwined and thus it is imperative that we acknowledge problems and work diligently to continue to improve special education policies, guidelines, and procedures.

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REFERENCES Apling, R. N. (2001). Individuals with disabilities act (IDEA): Identification and misidentification of children with disabilities. Congressional Research Service Library of Congress. Available at: https://www.policyarchive.org/bitstream/handle/10207/1301/RL31189_ 20011120.pdf?sequence=1 Artiles, A. J., Rueda, R., Salazar, J., & Higareda, I. (2005). Within-group diversity in minority disproportionate representation: English language learners in urban school districts. Exceptional Children, 71, 283–300. Billingsley, B. S. (2004). Special education teacher retention and attrition: A critical analysis of the research literature. The Journal of Special Education, 38(1), 39–55. Brown-Chidsey, R. (2007). No more ‘‘waiting to fail’’. Educational Leadership, 65(2), 40–46. Cassidy, W., & Jackson, M. (2005). The need for equality in education: An intersectionality examination of labeling and zero tolerance factors. McGill Journal of Education, 40(3), 445–466. Christensen, C. A., Gerber, M., & Everhart, R. (1986). Toward a sociological perspective on learning disabilities. Educational Theory, 36(4), 317–331. Cooke, N., Heward, W., Test, D., Spooner, F., & Courson, F. (1991). Student performance data in the special education classroom: Measurement and evaluation of student progress. Teacher Education and Special Education, 14(3), 155–161. Coutinho, M. J., & Oswald, D. P. (2005). State variation in gender disproportionality in special education. Remedial and Special Education, 26(1), 7–15. Deisinger, J. (2004). Conceptualizations of learning disabilities: Beyond the ability-achievement discrepancy. In: S. Burkhardt, F. E. Obiakor & A. F. Rotatori (Eds), Current practices on learning disabilities (pp. 1–20). London: Elsevier Press. de Valenzuela, J. S., Copeland, S. R., Huaqing Qi, C., & Park, M. (2006). Examining educational equity: Revisiting the disproportionate representation of minority students in special education. Exceptional Children, 72(4), 425–441. Dodd, D. C. H., Zabriskie, R. B., Widmer, M. A., & Eggett, D. (2009). Contributions of family leisure to family functioning among families that include children with developmental disabilities. Journal of Leisure Research, 41(2), 261–286. Dyson, L. L. (1996). The experience of families of children with learning disabilities: Parental stress, family functioning, and sibling self-concept. Journal of Learning Disabilities, 29(3), 280–286. Ferguson, P. M. (2002). A place in the family: An interpretation of research on parental reactions to having a child with a disability. Journal of Special Education, 36(3), 124–130, 147. Fierros, E. G., & Conroy, J. W. (2002). Double jeopardy: An exploration of restrictiveness and race in special education. In: D. J. Losen & G. Orfield (Eds), Racial inequity in special education (pp. 39–70). Cambridge, MA: Harvard Education Press. Glidden, L. M. (1993). What we do not know about families with children who have developmental disabilities: Questionnaire on resources and stress as a case study. American Journal of Mental Retardation, 5, 481–495. Gold, Y. (1996). Beginning teacher support: Attrition, mentoring, and induction. In: J. Sikula, T. J. Buttery & E. Guyton (Eds), Handbook of research on teacher education (2nd ed., pp. 548–595). New York: Simon & Schuster.

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Green, S., Davis, C., Karshmer, E., Marsh, P., & Straight, B. (2005). Living stigma: The impact of labeling, stereotyping, separation, status loss, and discrimination in the lives of individuals with disabilities and their families. Sociological Inquiry, 75(2), 197–215. Harper, G., Maheady, L., & Mallette, B. (2005). Developing, implementing, and maintaining a responsive educator program for preservice general education teachers. In: W. L. Heward, N. A. Neff & S. M. Peterson (Eds), Focus on behavior analysis in education achievements, challenges, and opportunities (pp. 139–153). Upper Saddle River, NJ: Pearson Prentice Hall. Harry, B., & Klinger, J. (2006). Why are so many minority students in special education?: Understanding race and disability in schools. New York: Teachers College Press, Columbia University. Heward, W. (2005). Reasons applied behavior analysis is good for education and why those reasons have been insufficient. In: W. L. Heward, N. A. Neff & S. M. Peterson (Eds), Focus on behavior analysis in education achievements, challenges, and opportunities (pp. 316–340). Upper Saddle River, NJ: Pearson Prentice Hall. Hosp, J. L., & Reschly, D. J. (2003). Referral rates for intervention or assessment: A metaanalysis of racial differences. The Journal of Special Education, 37(2), 67–80. Individuals with Disabilities Education Improvement Act (IDEIA). (2004). Public Law No. 108–446. Jacobson, J. W., Foxx, R. M., & Mulick, J. A. (Eds). (2006). Controversial therapies for developmental disabilities: Fad, fashion, and science in professional practice. Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Jussim, L., & Harber, K. D. (2005). Teacher expectations and self-fulfilling prophecies: Knowns and unknowns, resolved and unresolved controversies. Personality and Social Psychology Review, 9(2), 131–155. Kozleski, E. B., Engelbrecht, P., Hess, R., Swat, E., Eloff, I., & Oswald, M. (2008). Where differences matter: A cross-cultural analysis of family voice in special education. Journal of Special Education, 42(1), 26–35. Link, B. G., & Phelan, J. C. (2001). Conceptualizing stigma. Annual Review of Sociology, 27(1), 363–385. Liu, Y., Ortiz, A. A., Wilkinson, C. Y., Robertson, P., & Kushner, M. I. (2009). From early childhood special education to special education resource rooms: Identification, assessment, and eligibility determinations for English language learners with readingrelated disabilities. Assessment for Effective Intervention, 33(3), 177–187. Maheady, L., Towne, R., Algozzine, B., Mercer, J., & Ysseldyke, J. E. (1990). Minority overrepresentation: A case for alternative practices prior to referral. In: S. B. Sigmon (Ed.), Critical voices on special education (pp. 89–102). New York: State University of New York Press. Mellard, D. F., & Johnson, E. (2008). RTI: A practitioner’s guide to implementing response to intervention. Thousand Oaks, CA: Corwin. Morrier, M. J., Hess, K. L., & Heflin, L. J. (2008). Ethnic disproportionality in students with autism spectrum disorders. Multicultural Education, 16(1), 31–38. Mukuria, G. M., & Obiakor, F. E. (2008). Curriculum innovation to educate students with autism. In: A. F. Rotatori, F. E. Obiakor & S. Burkhardt (Eds), Autism and developmental disabilities: Current practices and issues (pp. 25–40). Bingley, UK: Emerald Group Publishing Group Limited.

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National Association for the Education of Young Children. (2005). Screening and assessment of young English-language learners: Supplement to the NAEYC and NAECS/SDE joint position statement on early childhood curriculum, assessment, and program Evaluation. Washington, DC: Author. Available at: http://www.naeyc.org/about/positions/ELL_ Supplement.asp. Retrieved on June 1, 2009. National Education Association. (2007). Truth in labeling: Disproportionality in special education. Washington, DC: Author. Nelson, F. H. (1983). School district response to labeling, cost, and programmatic incentives in special education. Journal of Education Finance, 8(3), 380–398. Nelson, L. G., Summers, J. A., & Turnbull, A. P. (2004). Boundaries in family-professional relationships: Implications for special educatoin. Remedial & Special Education, 25(3), 153–165. Rist, R. C., & Harrell, J. E. (1982). Labeling the learning disabled child: The social ecology of educational practice. American Journal of Orthopsychiatry, 52(1), 146–160. Serwatka, T. S., Deering, S., & Grants, P. (1995). Disproportionate representation of AfricanAmericans in emotionally handicapped classes. Journal of Black Studies, 25(4), 492–506. Shores, C., & Chester, K. (2009). Using RTI for school improvement: Raising every student’s achievement scores. Thousand Oaks, CA: Corwin Press. Skiba, R. J., Poloni-Staudinger, L., Gallini, S., Simmons, A. B., & Feggins-Azziz, R. (2006). Disparate Access: The disproportionality of African American students with disabilities across educational environments. Exceptional Children, 72(4), 411–424. Spear-Swerling, L., & Sternberg, R. J. (2001). What science offers teachers of reading. Learning Disabilities: Research & Practice, 16(1), 51–57. Wagnor, R. K., Francis, D. J., & Morris, R. D. (2005). Identifying English language learners with learning disabilities: Key challenges and possible approaches. Learning Disabilities Research & Practice, 20(1), 6–15. Weatherly, J. (2008). Districts must ensure that RtI isn’t used to block special edition referrals. District Administration, 44(7), 5. Ysseldyke, J. E., Algozzine, B., Richey, L., & Graden, J. (1982). Declaring students eligible for learning disabilities services: Why bother with the data? Learning Disabilities Quarterly, 5(1), 37–44. Zirkel, P. A., & Krohn, N. (2008). RtI after IDEA. Teaching Exceptional Children, 40(3), 71–73.

PART II UNDER-IDENTIFICATION AND OVER-IDENTIFICATION IN SPECIAL EDUCATION

CHAPTER 3 CAN UNDERIDENTIFICATION AFFECT EXCEPTIONAL LEARNERS? Rhonda S. Black It has been proposed that the ‘‘percentage of children in any subpopulation (e.g., group identified by gender, ethnicity, of SES) who are identified as exceptional (by reason of disability or hyperability) should be precisely proportional to the percentage of the general population comprising their subgroup’’ (Kaufman, Hallahan, & Ford, 1998, p. 3). To the extent that this does not occur, we have disproportionality, and it is assumed that disproportion is due to discrimination (MacMillan & Reschly, 1998). According to Bateman (1994, p. 515), ‘‘disproportion may or may not be discriminatory, but ignoring it probably is.’’ If large numbers of minority students are overrepresented in special education, we might assume this is discriminatory based on (a) the stigma and deficit perspective associated with special education labels, (b) lowered expectations, (c) the right to an education with same age, (d) being placed in dead-end programs from which they might not exit, and (e) limiting equal opportunities such as certain postsecondary education options and more desirable forms of employment. On the contrary, if a child is struggling in a general education system that does not meet his or her needs, the child is denied a fair and just education that could be offered in the form of extra help from special education services. Labeling a student for special services focuses on the child’s

Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 37–51 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019006

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differences, which may increase risk of stigma and discrimination. However, not labeling the student and thereby not providing services also increases the risk of stigma and discrimination (Hallahan & Kauffman, 1994). Overrepresentation occurs when the percentage of a group of students in special education programs is greater than in the school population as a whole (Guiberson, 2009). Underrepresentation occurs when students with disabilities are not identified and do not receive appropriate services (Guiberson, 2009). For the past four decades, much has been written about overrepresentation of minority children in special education. Two seminal articles in the field of special education focused on overrepresentation. The first, Lloyd Dunn’s (1968) Special Education for the Mildly Retarded: Is Much of it Justifiable, spoke about overrepresentation of children from ethnically diverse and economically disadvantaged homes in segregated special education classes. Although Dunn’s article has been criticized for using numbers that are not empirically based, the basic premise of overrepresentation of minority students is not disputed. As Dunn stated: In my best judgement, about 60 to 80 percent of the pupils taught [in special day classes for students with mental retardation] are children from low status backgrounds – including Afro-Americans, American Indians, Mexicans, and Puerto Rican Americans; those from nonstandard English speaking, broken, disorganized, and inadequate homes; and children from other nonmiddle class environments. This expensive proliferation of self-contained special schools and classes raises serious educational and civil rights issues. (p. 6)

The second pivotal work was The President’s Committee on Mental Retardation 1969 Report, The Six-Hour Retarded Child. This work spoke of ‘‘culturally disadvantaged’’ children who were classified as mentally retarded during the six hours in school, but who functioned adequately outside of school. Both of these significant works questioned the appropriateness of large numbers of minority children being (a) given the diagnostic label of mild mental retardation and (b) placed in segregated special education classrooms. There will always be students who fall behind academically in general education (Bateman, 1994). General education is geared toward ‘‘the group.’’ Accordingly, there are and always will be those who are at the top and at the bottom of ‘‘the group.’’ Because education is not a one-size-fitsall venture, there will always be students who require more individualization than a ‘‘group’’ model can provide. In advocating for differentiated curricula, some educators have stated that an equal education is not a fair

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education (Wormeli, 2006). Equality refers to providing the same treatment, whereas equity refers to fairness, which may require different treatment for some persons or groups (Kranich, 2001). We know that students across the United States do not have equal opportunities to experience success in the educational system. Many of the students who have been excluded from the ‘‘American Dream’’ are culturally, linguistically, or economically different from the majority culture (of Western European ancestry, middle income, and for whom English is their first language). To promote equity, educators have sought to address these diversities to ensure (a) access to quality learning experiences, and (b) success for students who have traditionally been marginalized. Hence, when should providing different treatment and different levels of educational support cause concern? And, when does providing additional services for marginalized children become discriminatory? These are difficult questions to address. We hear a great deal about overrepresentation of minority children in special education programs. However, overrepresentation of these children in Head Start programs has not been met with the same kind of criticism and legal battles (MacMillan & Reschly, 1998). Head Start programs have been likened to leveling the playing field and giving children who have less the extra help they need to become successful in school. Why is special education not viewed through this same lens? Requests for increased social services spending focus on the conditions of underserved children with respect to medical care and family support programs. Why is it then, that if those same children receive MORE services in the form of special education, this is somehow harmful and discriminatory? Education and political leaders speak of ‘‘the casualties of instruction,’’ which implies that large numbers of children are being underserved. Is it better to be overlooked and underserved than to receive special education services? As educators, we rarely, if ever, hear criticism about ‘‘overserving’’ children in our educational system. However, we do hear a great deal about children ‘‘falling through the cracks’’ and being underserved by our educational and social services systems. Underrepresentation of students from certain groups in special education seems to be of minor concern. It is ironic that disproportionality is of more concern when too many individuals in a group receive services than when too few members of this same group receive services. If disproportionality is only a problem when it involves overrepresentation, do we assume underrepresentation is beneficial? This chapter focuses on problems associated with underidentification of exceptional learners in special education.

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ASSUMPTIONS UNDERLYING DISCUSSIONS OF UNDER- AND OVER-REPRESENTATION In reviewing the special education professional literature using ‘‘disproportionality’’ as a descriptor, most of the articles addressed overrepresentation (Salend, Duhaney, & Montgomery, 2002). An Educational Resources Information Center (ERIC) Digest was titled Reducing the Disproportionate Representation of Minority Students in Special Education (Burnette, 1998) yet it focused on ‘‘what can be done to reduce over-representation.’’ Apparently, underrepresentation/underserving students is not an issue of great importance. A recent article in one of special education’s premiere journals, Exceptional Children, used the term disproportionality as synonymous with overrepresentation (Skiba et al., 2008). The article did not mention underrepresentation as part of the disproportionality puzzle. In the view of these authors, overrepresentation of minority students in special education is the only part of the disproportionality equation that merits consideration. When education professionals view overrepresentation as a more serious issue than underrepresentation or underidentification, what message is this sending? Does this imply that serving children in special education is inherently harmful? According to Reschly (1997), none of the overrepresentation lawsuits would have happened if special education was doing something truly remarkable. Given the reduced student to teacher ratio, the focus on individualization, and significantly more per pupil expenditures, would every parent not want his or her child to receive special education? If special education was viewed as a positive thing, would more of the research literature focus on how we are not reaching enough children, rather than serving fewer of them? In understanding issues surrounding disproportionality, we need to examine current assumptions about special education. The first assumption is that special education is undesirable and to be avoided. Much of the professional literature has shined a spotlight on data indicating that there are higher percentages of certain groups of minority children in special education than there are in the general school population. Apparently, this has been a source of shame for our profession. The implicit assumptions, then, are that special education programs are ineffective, stigmatizing, and educationally inferior (Reschly, 1997). But, is there another side to this disproportionality puzzle?

UNDERIDENTIFICATION OF STUDENTS WITH EMOTIONAL AND BEHAVIORAL DISORDERS Much of the overidentification literature focuses on learning disabilities (LD) and mild mental retardation. In contrast, students with emotional and

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behavioral disorders (EBD) appear to be underrepresented/underidentified. This is especially true for children who are compliant and nonaggressive but suffer from problems such as depression, anxiety, school phobia, or social isolation (Walker et al., 1990, 1994). Procedures for identifying students who may need special education services vary from district to district, state to state, but these procedures almost always begin with teacher-initiated referrals. The best predictor of whether a teacher will refer a specific student is the presence of behavioral problems or misbehavior in addition to low academic achievement (Abidin & Robinson, 2002). Students are far more likely to be referred for externalizing problems such as acting out than for internalizing problems such as shyness, social withdrawal, anxiety disorders, or depression (Walker et al., 1994). For example, if a teacher is stressed by the behavior of a particular child, he or she may become biased in judgments about the severity of this child’s behavior (Abidin & Robinson, 2002). One possible explanation for the underidentification of children with internalizing emotional problems may be that these children do not disrupt class activities, instructional routines, or cause teachers extra stress. In addition, teachers may underestimate the impact of internalizing problems on students’ long-term functioning (Abidin & Robinson, 2002). Yet, these children are greatly at-risk for a host of difficulties both in school and in the community. Students with EBD are among the most underidentified and underserved students with disabilities (Bazelton Center on Mental Health Law, n.d.). The national rate of students receiving special education services under this diagnostic category is approximately 1% (Walker, Nishioka, Zeller, Severson, & Feil, 2000), whereas the U.S. Surgeon General estimated that between 5% and 11% of all school-age children have mental health disorders (Bazelton Center on Mental Health Law, n.d.). Therefore, only a fraction of those who need intervention for EBD are actually identified and served under Individuals with Disabilities Education Act (IDEA) (Landrum, Tankersley, & Kauffman, 2003). Even when schools correctly identify students as having EBD, the identification is typically delayed (Bazelton Center on Mental Health Law, n.d.; Landrum et al., 2003). The rates of identification peak in the 14- to 15-year age range well after the point where early intervention would have a substantial positive impact (Walker et al., 2000). According to Forness et al. (2000, pp. 327–328): Significant delays in identification are common.y Thus, emotional or behavioral problems become much more severe before they are identified, and the occurrence of secondary disorders becomes much more likely. This lack of appreciation regarding the progressive nature of many emotional or behavioral problems and the absence of genuinely preventive programs remain as serious obstacles to the development of a comprehensive continuum of care for students with emotional or behavioral disorders.

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When identification is delayed, students’ maladaptive behaviors increase to exceed tolerance levels and accommodation capacities of teachers. The risk trajectories for these students ‘‘will accelerate and may ultimately cause them to be pushed out of school due to the aversive nature of their behavior patterns’’ (Walker et al., 2000, p. 29). Effective prevention of school failure depends crucially on early recognition and provision of services for troubled children. Delayed identification results in children’s requiring more intensive IDEA services once they are identified. For example, these children are disproportionately placed in the most restrictive settings and are far less often mainstreamed than children with other disabilities (Forness & Kavale, 2000; Skiba & Grizzle, 1991). Kauffman (1999) explained the phenomenon very well in an article aptly named, How We Prevent the Prevention of Emotional and Behavioral Disorders. He stated that: It is abundantly clear that far less than half of the population of youngsters with such disorders [EBD] have been identified for special education and that students with these disorders are typically identified for special education only after several years of very serious difficulties y Prevention in an underserved population demands that more individuals be identified, not fewer or the same number. (p. 457)

Underidentification of Girls According to Bateman (1994), special education serves at least two boys for every girl. These disproportionate numbers indicate that girls are obviously underrepresented in special education. If disproportionality is a problem, then the underrepresentation of girls in special education needs to be addressed (Bateman, 1994). The Centers for Disease Control (2008) noted that boys were more than twice as likely as girls to have attention deficit hyperactivity disorder (ADHD), twice as likely to have LD, and twice as likely to have both ADHD and LD. Low prevalence rates for girls with EBD have also been reported (Miller, Trapani, Fejes-Mendoza, Eggleston, & Dwiggins, 1992). ‘‘Boys tend to be referred more frequently for clinical treatment of ADHD symptoms than girls because boys tend to exhibit more externalizing and disruptive behaviors than girls, or at least they are perceived as displaying more of these types of behaviors’’ (Dietz & Montague, 2006, p. 26). Interestingly, medication for adults with ADHD is dispensed equally to men and women (Adams, 2007). If adults are experiencing ADHD in equal numbers, children might too. Are too many young girls being overlooked by

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our schools and not getting the help they need? Adams (2007) reported that as many as 50–75% of girls with ADHD may be missed. When they are identified, girls with ADHD are diagnosed on average five years later than boys – boys at age 7, girls at age 12 (Adams, 2007). Girls are more likely to have attention deficit disorder (ADD), whereas ADHD is more common in boys (Women’sHealth.org, n.d.). Because a girl does not act out in the classroom, her behavior causes fewer problems for the teacher. Girls are less likely to display hyperactive or impulsive behaviors. Instead, they may just appear spacey, unfocused, or inattentive (Adams, 2007). In girls, the disorganization and distraction often results in lack of activity rather than excessive activity. They are too confused to get things started, so they drift from one task to another without completing any of the tasks. The true problems, the inability to concentrate and execute goals, are likely to be overlooked (Women’sHealth.org, n.d.). The symptoms of ADD in girls overlap with the symptoms of depression. Both conditions include disorganization, trouble concentrating, and difficulty with social relationships. Even more confusing, the unrecognized ADD can lead to major coping problems, which in turn lead to actual depression on top of the ADD. Without intervention, behaviors associated with in attention, hyperactivity, and disruptive behavior may be exacerbated over time, placing these girls at risk for poor school and social–personal outcomes (Dietz & Montague, 2006). Similarly, girls with EBD often withdraw, become anxious and depressed, and internalize their feelings. Their emotional problems may be overlooked or minimized in an academic setting (Dietz & Montague, 2006; Miller et al., 1992). Females with EBD often exhibit dependency, conformity, and passivity, which all contribute to low academic functioning. Wehmeyer and Schwartz (2001) analyzed student admissions to special education to determine the degree to which referral, admission, and placement services are provided in an equitable manner. They found that contrary to most literature focusing on male overrepresentation, ‘‘the present system may be inequitable, not because more boys are being served than girls, but because girls who have equivalent educational needs are not provided access to supports and services that might address these needs’’ (p. 42). They suggested that boys outnumber girls 2 to 1 in special education due to a combination of behavioral issues and biases based on gender. The underrepresentation of girls receiving services was not because fewer girls need special educational assistance, or because the boys who did receive services did not have needs or challenges that deserved to be addressed. They concluded that females with disabilities may be underrepresented in receiving special education services because of different behavior expectations of boys

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and girls. Abidin and Robinson (2002) similarly reported that a gender effect has been found in studies in which teachers report their actual referral experiences. When girls are undiagnosed and untreated for ADD or EBD, they are greatly at risk of truancy, teen pregnancy, criminality, and suicide (Miller et al., 1992; Women’sHealth.org, n.d.). As these girls hit their teen years, the increased organizational demands of middle and high school may become overwhelming. They may become tired and disheartened by poor school performance. Their impulsivity may lead to self-medication with drugs or alcohol. Or, they may throw themselves into social relationships to compensate and may begin to engage in risky sexual behaviors. They may be described as boy-crazy or party girls (Women’sHealth.org, n.d.). Undiagnosed adult women with ADD or ADHD have been found to have everything from general underachievement to depression, from low selfesteem to substance abuse (Women’sHealth.org, n.d.).

Underidentification and Asperger’s Syndrome The recognition of Asperger’s Syndrome also illustrates underidentification and underserving the needs of a group of individuals who needed more assistance. Beginning in the late 1960s, researchers began to notice children who had specific difficulties with social-emotional functioning, but were not delayed in language (Atwood, 1998; Stewart, 2002). These individuals were in need of assistance but were not eligible for services under any of the disabilities defined by special education laws or by the Diagnostic and Statistics Manual of Mental Disorders-Revised (DSM-IV) of the American Psychiatric Association (APA, 2000). In 1994, Asperger’s Syndrome was made official in the DSM-IV. Before that time, the lack of a consistent agreed-upon definition led to a great deal of confusion. Researchers could not interpret other researchers’ findings, clinicians used labels based on their own interpretations, and parents were often faced with a diagnosis that nobody appeared to understand or know what to do about (Klin & Volkmar, 2007). School districts were not aware of the condition, and there was no published information regarding what forms of treatment and interventions were warranted (Klin & Volkmar, 2007). These children were not receiving special education services because their academic achievement was not severely affected by the disability (Atwood, 1998; Stewart, 2002). However, the social characteristics of these individuals indicated a need for some additional support to enable these individuals to be included in school and in their communities (Atwood, 1998).

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According to Safran (2008), although the prevalence of autistic spectrum disorders (ASD) in the general population has risen dramatically, the incidence of students with autism receiving special education under the 1990 IDEA has not kept pace. This is in large part due to underidentification of youngsters on the higher functioning end of the spectrum. Individuals with Asperger’s Syndrome are either identified at a later age or not at all. Their symptoms – interpersonal skills deficits, unusual mannerisms, rigidity, and lack of empathy – may be wrongly interpreted as rude and inappropriate. These symptoms are often masked by their intellectual functioning, academic achievement, and language abilities. Although their academic performance is not adversely affected, due to their social difficulties, these individuals are in need of intervention. ‘‘It is with this group of children that future special education identification resources must be focused’’ (Safran, 2008, p. 94). Thus, Asperger’s was ‘‘born’’ from the issue of underidentification.

Underidentification of English Language Learners In the past, a number of lawsuits and court orders, such as Diana v. Board of Education, focused on issue of overidentification of English language learners (ELLs) for special education services. Artiles, Rueda, Salazar, and Higareda (2005) stated that in some cases, there may be a reluctance to qualify Hispanic children for special education partly because of fears of Office of Civil Rights complaints or district, state, or national audits. Thus, the overidentification trend is now shifting as the fear of litigation has driven many school districts to underidentify language minority students for special education (Gertsen & Woodward, 1994; Olson, 1991). Today, students of all ethnicities from second language backgrounds are, in general, underrepresented in special education programs (Watkins, 2009). Artiles et al. (2005) studied students from 11 urban districts in California to determine the effects of language proficiency on special education placement. More than 90% of the participants were Hispanic. They separated the participants into the following two categories: still acquiring English (i.e., ELL) or English proficient (EP; i.e., they had acquired sufficient language competency to function in the classroom with native English speakers). Results revealed that ELL students were underrepresented in special education in Grades K–5 and overrepresented in Grades 6–12, whereas EP students were underrepresented at the secondary level. This may indicate that elementary grade students with limited English language skills are not receiving needed services. In turn, these students fall

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farther and farther behind and then qualify for services at the secondary level. Gertsen and Woodward (1994) noted similar concerns regarding the underrepresentation of language minority students. They stated that these students who struggle in general education classrooms benefit little from conventional instruction and need specialized assistance. Thus, underidentification in the early years seems to be detrimental to these students. ‘‘In no way are increased referral rates into pullout special education programs a remedy. However, we are concerned about a large number of students from language-minority groups who are falling through the cracks’’ (Gertsen & Woodward, 1994, p. 313).

Underidentification and Intervention Issues Professionals can freely discuss issues surrounding underidentifying students in need of services or interventions. Yet, advocating for serving more students ‘‘in’’ special education is met with resistance. Perhaps the objectionable issue is not the identification of kids who need extra help, but rather the segregation of children when providing these services? MacMillan, Semmel, and Gerber (1994) stated that much of the overepresentation debate centers on where services are delivered. However, they reported that efforts to address the disproportionality of minority students simply moved the site of overrepresentation from the special education classroom to the remedial education classroom. Both settings enrolled a ‘‘homogeneous grouped population with low academic achievement including a disproportionate number of ethnic minority students’’ (MacMillan et al., 1994, p. 474). The only true difference was that in the remedial education classes, students were not required to have a label or diagnosis. It appears then that the label may have been the stigmatizing factor. Is there a way to provide services without a label? The Response to Intervention (RTI) movement was fueled by arguments regarding both under- and over-identification of students for special education services. RTI addresses overrepresentation by focusing on a series of targeted interventions before special education referrals are made. Underrepresentation is addressed by implementing universal screening to identify all struggling learners and intervene BEFORE these children fall behind. RTI aims to serve more children earlier with a primary goal of reaching those kids who have been overlooked and underserved. RTI was created to replace the discrepancy model, which has been called a ‘‘wait to fail’’ model. Five of six states in the Southeast Region reported that

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reducing disproportionality was a primary reason for their interest in RTI (Sawyer, Holland, & Detgen, 2008). These states believed adopting RTI would reduce overidentification and underidentification of students from minority subgroups for special education by relying more on data to make placement decisions. Many children are not achieving academic success despite their apparent ability to do so. They are not being adequately served by their current educational services. Therefore, they need some educational supports and a different kind of service provision. They need academic accommodations and instruction in specific strategies to help them succeed. RTI may be a way to address skill and strategy instruction without requiring formal diagnosis. Some individuals are diagnosed as having an LD for the first time in adulthood. Many of these individuals struggled throughout their school years and are relieved to have an explanation for their difficulties (Bogod, n.d.). The diagnosis can offer a measure of freedom from their self-doubt and lowered self-esteem due to lifelong accusations of being lazy or unmotivated. Many individuals have written about their experiences on internet discussion groups, blogs, or books, stating that it was liberating to learn that, ‘‘I’m not lazy, dumb, or unmotivated, I just learn differently.’’ They wished they had been given intervention rather than criticism while they were in school. The Learning Disabilities Association of America (LDA, n.d.) discussed those individuals with undiagnosed LD who never received appropriate treatment or instructional assistance. LDA claims that many of these individuals, frustrated by school failures, dropped out of high school. A very high proportion of these girls became pregnant at a young age. The men, if they were lucky, found entry level and dead-end jobs. They all got on with their lives as best they could with low literacy skills. Perhaps RTI holds promise for identifying reading difficulties and intervening so that our next generation will experience better adult outcomes.

CONCLUSIONS The biggest question is, is underrepresentation positive or negative? Many times, well meaning professionals do not identify children as in need of special education to avoid labeling and stigmatization. The unintended result of this lack of identification (or delayed identification) is to prevent effective prevention (Kauffman, 1999; Walker et al., 2000). ‘‘The rub for prevention is this: Disproportional identification of some groups for special education can be used as a rationale for non-identification, nonintervention,

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waiting to take action out of fear that action will merely exacerbate the disproportion of the group to which the student belongs’’ (Kauffman, 1999, p. 459). Although special education may be perceived as a last resort for students, ‘‘general education is and always will be a dead end for some students if their educational needs are not identified and served appropriately’’ (Kauffman & Hallahan, 2005, pp. 2–3). As professionals we must weigh the relative merits of over- and underidentification: Which is a worse mistake in the matter of identifying (or not) an exceptionality: (a) a false positive or (b) a false negative? (A false positive means identifying an exceptionality that does not really exist; a false negative means not identifying an exceptionality that does exist.) An absolutely foolproof, error-free system of identification is not possible. The question really is: Which type of mistake is worse? (Kauffman & Hallahan, 2005, p. 8).

False negatives have far-reaching consequences. For example, it appears that underidentifying students with EBD is extremely detrimental to those students as their behaviors become increasingly more maladaptive and more difficult to treat. Underidentifying girls also puts them at greater risk for negative adult outcomes. And identifying and addressing reading difficulties early can actually prevent years of struggling with academic content. In these cases, then, a false negative can truly impact a lifetime for the individuals not identified. The profession needs to continually examine what constitutes unfair treatment in school. We, as special education professionals, should focus our energies on providing services that enhance quality of life and offer students better and more satisfying future opportunities. This seems the most direct route to redirect concerns related to overrepresentation and address underrepresentation to ensure that all students who need extra assistance receive that assistance in the most professional and life-enhancing manner possible.

REFERENCES Abidin, R., & Robinson, L. (2002). Stress, biases, or professionalism: What drives teachers’ referral judgments of students with challenging behaviors? Journal of Emotional & Behavioral Disorders, 10(4), 204–212. Retrieved on May 30, 2009, from Academic Search Premier database. Adams, C. (2007). Girls and ADHD: Are you missing the signs? Instructor, 116(6), 31–35. (ERIC Document Reproduction Service No. EJ792934) Retrieved on May 25, 2009, from ERIC database.

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American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders: DSM-IV (4th ed., text revision). Washington, DC: American Psychiatric Association. Artiles, A., Rueda, R., Salazar, J., & Higareda, I. (2005). Within-group diversity in minority disproportionate representation: English language learners in urban school districts. Exceptional Children, 71(3), 283–300. Atwood, T. (1998). Asperger’s syndrome: A guide for parents and professionals. London: Jessica Kingsley Publishers. Bateman, B. D. (1994). Who, how and where: Special education’s issues in perpetuity. Journal of Special Education, 27(4), 509–520. Bazelton Center on Mental Health Law. (n.d.). Failing to qualify: IDEA identification rates. Available at http://www.bazelon.org/issues/education/publications/failingtoqualify/ identification.htm. Retrieved on May 30, 2009. Bogod, L. (n. d.). Top 5 emotional difficulties of people with learning disabilities. Available at http://www.ldpride.net/emotions.htm. Retrieved on June 25, 2009. Burnette, J. (1998). Reducing the disproportionate representation of minority students in special education (ERIC Document Reproduction Service ED 417 501). Reston, VA: ERIC Clearinghouse on Disabilities and Gifted Education. Centers for Disease Control and Prevention (2008). Diagnosed attention deficit hyperactivity disorder and learning disability: United States, 2004–2006. Hyattsville, MD: U.S. Department of Health and Human Services, National Center for Health Statistics. Dietz, S., & Montague, M. (2006). Attention deficit hyperactivity disorder comorbid with emotional and behavioral disorders and learning disabilities in adolescents. Exceptionality, 14(1), 19–33. (ERIC Document Reproduction Service No. EJ733729) Retrieved on May 26, 2009, from ERIC database. Dunn, L. M. (1968). Special education for the mildly retarded: Is much of it justifiable? Exceptional Children, 35, 5–22. Forness, S., Serna, L., Nielsen, E., Lambros, K., Hale, M., & Kavale, K. (2000). A model for early detection and primary prevention of emotional or behavioral disorders. Education and Treatment of Children, 23(3), 325–345. (ERIC Document Reproduction Service No. EJ618006) Retrieved on May 29, 2009, from ERIC database. Forness, S. R., & Kavale, K. A. (2000). Emotional or behavioral disorders. Background and current status of the EBD terminology and definition. Behavioral Disorders, 25, 205–210. Gertsen, R., & Woodward, J. (1994). The language-minority student and special education: Issues, trends, and paradoxes. Exceptional Children, 60, 310–322. Guiberson, M. (2009). Hispanic representation in special education: Patterns and implications. Preventing School Failure, 53(3), 167–176. (ERIC Document Reproduction Service No. EJ832469) Retrieved on May 28, 2009, from ERIC database. Hallahan, D. P., & Kauffman, J. M. (1994). Toward a culture of disability in the aftermath of Deno and Dunn. The Journal of Special Education, 27, 496–508. Kauffman, J. M. (1999). How we prevent the prevention of emotional and behavioral disorders. Exceptional Children, 65, 448–468. Kauffman, J. M., & Hallahan, D. P. (2005). Special education: What it is and why we need it. Boston: Pearson Education. Kaufman, J. M., Hallahan, D. P., & Ford, D. Y. (1998). Introduction to special section. Journal of Special Education, 32(1), 3. Klin, A., & Volkmar, F. R. (2007). History of Asperger’s disorder. Psych Central. Available at http://psychcentral.com/lib/2007/history-of-aspergers-disorder/. Retrieved on June 3, 2009.

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Kranich, N.C. (2001). Libraries and democracy: The cornerstones of liberty. Chicago: American Library Association. Landrum, T., Tankersley, M., & Kauffman, J. (2003). What is special about special education for students with emotional or behavioral disorders? Journal of Special Education, 37(3), 148–156. Learning Disabilities Association of America. (n.d.). Adults with learning disabilities: An overview. Available at http://www.ldanatl.org/aboutld/adults/special_pop/adult_ld.asp. Retrieved on June 6, 2009. MacMillan, D. L., & Reschly, D. J. (1998). Overrepresentation of minority students: The case for greater specificity of reconsideration of the variables examined. Journal of Special Education, 32(1), 15–24. MacMillan, D. L., Semmel, M. I., & Gerber, M. M. (1994). The social context of Dunn: Then and now. The Journal of Special Education, 27, 466–480. Miller, D., Trapani, C., Fejes-Mendoza, K., Eggleston, C., & Dwiggins, E. (1992). Females with emotional and behavioral disorders: Unique considerations. Paper presented at the Annual Conference of Teacher Educators of Children with Behavioral Disorders, Phoenix, AZ. (ERIC Document Reproduction Service No. ED361971) Retrieved on May 29, 2009, from ERIC database. Olson, P. (1991). Referring language minority students to special education. ERIC Digest. ERIC Clearinghouse on Language and Linguistic. (ERIC Document Reproduction Service No. ED329131) Retrived June 15, 2009, from ERIC database. President’s Committee on Mental Retardation, Washington, DC. (1969). The six-hour retarded child. A Report on a conference on problems of education of children in the inner city (Warrentown, Virginia, August 10–12, 1969). (ERIC Document Reproduction Service No. ED038827) Retrieved on May 28, 2009, from ERIC database. Reschly, D. J. (1997). Disproportionate minority representation in general and special education: Patterns, issues, and alternatives (ERIC Document Reproduction Service No. ED415632) Retrieved on June 26, 2009, from ERIC database. Mountain Plains Regional Resource Center: Des Moines, IA; Iowa State Department of Education. Bureau of Special Education, Drake University, Des Moines, IA. Safran, S. P. (2008). Why youngsters with autistic spectrum disorders remain underrepresented in special education. Remedial and Special Education, 29(2), 90–95. Salend, S., Duhaney, L., & Montgomery, W. (2002). A comprehensive approach to identifying and addressing issues of disproportionate representation. Remedial and Special Education, 23(5), 289–299. (ERIC Document Reproduction Service No. EJ655439) Retrieved on May 21, 2009, from ERIC database. Sawyer, R., Holland, D., & Detgen, A. (2008). State policies and procedures and selected local implementation practices in Response to Intervention in the six Southeast Region states (Available at http://ies.ed.gov/ncee/edlabs. Retrieved on May 20, 2009.). (Issues & Answers Report, REL 2008, No. 063). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Southeast. Skiba, R., & Grizzle, K. (1991). The social maladjustment exclusion: Issues of definition and assessment. School Psychology Review, 20, 577–595. Skiba, R., Simmons, A., Ritter, S., Gibb, A., Rausch, M., Cuadrado, J., et al. (2008). Achieving equity in special education: History, status, and current challenges. Exceptional Children, 74(3), 264–288.

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Stewart, K. (2002). Helping a child with nonverbal learning disorder or Asperger’s syndrome. Oakland, CA: New Harbinger Publications. Walker, H., Severson, H., Todis, B., Block-Pedego, A., Williams, G., Haring, N., & Barckley, M. (1990). Systematic screening for behavior disorders (SSBD): Further validation, replication, and normative data. Remedial and Special Education, 11(2), 32–46. Walker, H. M., Nishioka, V. M., Zeller, R., Severson, H. H., & Feil, E. G. (2000). Causal factors and potential solutions for the persistent underidentification of students having emotional or behavioral disorders in the context of schooling. Assessment for Effective Intervention, 26(1), 29–39. Walker, H. M., Severson, H. H., Nicholson, F., Kehle, T., Jenson, W. R., & Clark, E. (1994). Replication of the systematic screening for behavior disorders (SSBD) procedure for the identification of at-risk children. Journal of Emotional and Behavioral Disorders, 2(2), 66–77. (ERIC Document Reproduction Service No. EJ484998) Retrieved on May 28, 2009, from ERIC database. Watkins, E. (2009). Bridging systems to address under-representation of English language learners (ELLs) in special education. AccELLerate: The Quarterly Newsletter of the National Clearinghouse for English Language Acquisition, 1(3), 15–17. Retrieved on December 5, 2009, from http://www.ncela.gwu.edu/accellerate/edition/5/ Wehmeyer, M., & Schwartz, M. (2001). Disproportionate representation of males in special education services: Biology, behavior, or bias? Education and Treatment of Children, 24(1), 28–45. (ERIC Document Reproduction Service No. EJ635093) Retrieved on June 28, 2009, from ERIC database. Women’sHealth.org. (n.d.). Why girls with attention deficit disorder go undiagnosed. Available at http://www.womenshealth.org/a/attention_deficit_disorder_girls.htm. Retrieved on May 28, 2009. Wormeli, R. (2006). Fair isn’t always equal: Assessing and grading in the differentiated classroom. Portland, ME: Stenhouse Publishers.

CHAPTER 4 DISPROPORTIONATE REPRESENTATION IN SPECIAL EDUCATION: OVERREPRESENTATION OF SELECTED SUBGROUPS Tina Taylor Dyches and Mary Anne Prater The U.S. Commissioner of Education, James E. Allen, stated in 1969 that ‘‘it can only be through a concern for the value of life for all men that we will finally evolve a true equality of education and a true equal society’’ (President’s Committee on Mental Retardation, 1969, p. 3). These concerns expressed more than 40 years ago are still relevant to education today. The professional literature is replete with research and discussions on overidentification of students with disabilities (e.g., Diller, 2006; Greene, 2007), inaccurate classification of disabilities (e.g., Coo et al., 2008; Kavale & Flanagan, 2007), and the overrepresentation of disability groups by students from ethnically/racially diverse backgrounds (e.g., Artiles & Bal, 2008; Blanchett, 2006; Coutinho & Oswald, 2006; Dyches, Wilder, Sudweeks, Obiakor, & Algozzine, 2004; Obiakor, 2009; Skiba et al., 2008). The argument presented focuses on overrepresentation across disabilities, as well as disproportionate representation by racial/ethnic groups across disability classifications, educational environments, expulsions/suspensions,

Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 53–71 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019007

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reasons for exiting school, and early intervention services. The structure of this chapter focuses on three main issues, which include (a) too many students are being identified with disabilities, (b) too many students are being identified with the wrong disability, and (c) racially/ethnically diverse students are overrepresented and inappropriately served in special education. Within each section, factual information will be presented, followed by opinion supported with facts, but first, important terminology including methods of measuring disproportionality will be explained.

TERMINOLOGY AND METHODS OF MEASURING DISPROPORTIONALITY Misidentification has two meanings. First, it refers to the identification of a student with a disability when in fact he or she does not have a disability. This is also referred to as a false positive. Misidentification can also mean a student has been identified with the wrong disability (e.g., specific learning disability (SLD) instead of mental retardation (MR)). Disproportionality includes both overrepresentation and underrepresentation. Overrepresentation is identifying more students with disabilities than would be expected based on proportions within a defined population. Conversely, underrepresentation refers to identifying fewer students with disabilities than their prevalence in a population. Disproportionality is measured by calculating a composition index, risk index, or risk ratio. The composition index answers the question, ‘‘What percentage of students receiving special education and related services either for a particular disability or in a particular educational environment are from a specific racial/ethnic group?’’ (Westat, 2003, p. 4). The composition index is calculated by dividing the number of students from a racial group in a disability category by the total number of students in the disability category, then multiplying the result by 100 to provide a percentage. For example, in 2004, 555,524 students were identified as having MR, 185,883 of whom were Black (33%). When compared to their representation in the school-age population (15.6%), this index shows that Black students are overrepresented in the composition of students with MR (U.S. Department of Education, Office of Special Education Programs, 2008a). The use of the composition index has been criticized for several reasons including not being useful to detect when a discrepancy is

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meaningful, although using a 10–20% confidence interval around the target population has been suggested (Coutinho & Oswald, 2006; Skiba et al., 2008). Another way of calculating disproportionality is to use a risk index. This index answers the question, ‘‘What percentage of students from a specific racial/ethnic group receive special education and related services for a particular disability?’’ (Westat, 2003, p. 8). The risk index is calculated by dividing the number of students from a racial group in a disability category by the total number of students from that racial group, then multiplying the result by 100. For example, in 2004, 185,883 Black students aged 6–21 years were classified as having MR; the total number of Black students in this age group equals 1,252,218. Thus, 14.84% of all Black students aged 6–21 years were classified as having MR (U.S. Department of Education, Office of Special Education Programs, 2008a). The risk index is not particularly meaningful until it is used to compare groups (Skiba et al., 2008). This is done by using a risk ratio. This ratio answers the question, ‘‘What is a specific racial/ethnic group’s risk of receiving special education and related services for a particular disability as compared to the risk for all other students?’’ (Westat, 2003, p. 11). Risk ratios are calculated by dividing the risk index for the specific group by the risk index for a comparison group, often including all other groups combined. Exact proportionality is represented by a risk ratio of 1.0, whereas overrepresentation has ratios above 1.0 and underrepresentation has ratios below 1.0. For example, the risk ratio of 2.83 for Black students with MR aged 6–21 years indicates that they are 2.83 times more likely to receive special education services compared to the proportion of students with MR receiving services in all other racial/ethnic groups combined (U.S. Department of Education, Office of Special Education Programs, 2008a). While measuring disproportionality is a complex process, some guidance has been provided by the U.S. Department of Education. The Office of Special Education Programs has recommended the use of a risk ratio for monitoring disproportionality, and both risk ratios and risk indexes are calculated in the most recent Annual Report to Congress (U.S. Department of Education, Office of Special Education Programs, 2008a). However, they have not provided cutoff points to indicate when disproportionate representation is significant or meaningful. This is left to the interpretation of policymakers and individual state education agencies or by using an arbitrarily selected cutoff point (e.g., risk ratio of 1.5) (Bollmer, Bethel, Garrison-Mogren, & Brauen, 2007; Coutinho & Oswald, 2006; Westat, 2003).

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TOO MANY STUDENTS ARE BEING IDENTIFIED WITH DISABILITIES In 1970, U.S. schools educated only 20% of the nation’s children and youth with disabilities, excluding approximately 1 million students from schools and an additional 3.5 million from receiving appropriate educational services due to exclusionary policies (National Council on Disability, 2000). With the passage of the Education of All Handicapped Children’s Act in 1975, state education agents, as recipients of federal monies, were legally mandated to aggressively undertake the task of identifying and evaluating all children with disabilities and to provide a free and appropriate education to eligible students. Thus, the increase of students with disabilities served in U.S. schools emerged. In 1976, 8.3% of U.S. students were identified as having disabilities, rising 30 years later to 13.6% (U.S. Department of Education, Office of Special Education Programs, 2008a). Given the rise in the number of students identified with disabilities, one could infer that many more students with disabilities exist today than 30 years ago. However, several alternative explanations can be made for these increases, including improved understanding and diagnosis of disabilities, decreased stigmatization of some disabilities, parents seeking accommodations for their children, and schools avoiding responsibility for educating lowachieving students. Another alternative explanation is the so-called bounty system. That is, government policies reward schools for classifying students regardless of whether they truly have disabilities to receive more financial support (Greene, 2007). The increased percentages of students identified with disabilities could also be attributed to the changing definitions and categories of disabilities in the Individuals with Disabilities Education Act (IDEA) of 1990. When this law was first passed in 1975, only nine disability categories were included. Today, IDEA lists 13 categories of disabilities, adding to the potential for increased numbers of students identified and served under the Act. In addition, some of the definitions of disabilities outlined in IDEA have not been updated based on the professional knowledge base (Forness & Kavale, 2000; Prater, 2007; Wehmeyer, 2003). See Figs. 1 and 2 for a comparison of the composition of students identified between 1976 and 2006. Another possible explanation for the increase of students with disabilities over time is the belief of some teachers that certain students need help and the best way to receive that help is through special education. They refer them for special education services, not because they have a disability, but to get them additional support. Such misidentification results in false

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Disproportionate Representation in Special Education

Hearing impairments Other health 2% impairments 4%

Orthopedic Impairments 2%

Emotional Disturbance 8%

Visual Impairments 1%

Speech or language impairment 35%

Specific Learning Disabilities 22%

Mental Retardation 26%

Fig. 1.

Note. Percentages not available for the categories of Multiple Disabilities, Deaf-Blindness, Autism, Traumatic Brain Injury, and Developmental Delay.

Percentages of Children with Disabilities Served under IDEA in 1976.

positives – students identified as having a disability when indeed they do not have a disability that qualifies them for services. This may be evidenced in the dramatic increases of students classified as having SLD or other health impairments (OHI) such as attention deficit hyperactivity disorder (ADHD). As the proportion of boys compared to girls who have a disability is almost two to one (Arms, Bickett, & Graf, 2008), it is possible that boys are being overidentified as having a disability whereas girls are being underidentified. Thus, the overrepresentation of students as having a disability may be due, in large part, to overidentification of boys. We agree that students in general, and boys in particular, are overidentified with disabilities. Greene (2007) expressed it well by stating that identifying one in eight students as having a disability stretches the meaning of disability ‘‘beyond its common usage and certainly beyond what the authors of the original legislation imagined’’ (p. 705). Several explanations

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TINA TAYLOR DYCHES AND MARY ANNE PRATER Hearing impairments 1%

Multiple Disabilities 2%

Orthopedic Impairments 1%

Visual Impairments 1%

Traumatic Brain Injury 0% Deaf-blindness 0%

Autism 4%

Emotional Disturbance 7%

Developmental Delay 5%

Specific Learning Disabilities 40% Mental Retardation 8%

Other health impairments 9%

Fig. 2.

Speech or language impairment 22%

Distribution of Children with Disabilities Served under IDEA in 2006.

for these increases were discussed previously including the notion that IDEA has not moved forward with more progressive definitions of disabilities as advocated in the professional community. As such, school personnel continue to use outdated definitions with vague descriptors to determine who qualifies for special education, increasing the numbers of students identified with disabilities. We also believe that being misidentified as having a disability is hurtful to students. When students are inappropriately identified, they often carry a label throughout their educational career, rarely exiting the special education program. Such misidentification results in low expectations for achievement by teachers, administrators, and even family members (National Alliance of Black School Educators [NABSE] & ILLIAD Project, 2002). We are hopeful that the recent inclusion of the response to intervention (RTI) option for identifying students with SLD will accomplish the intended outcome of helping school personnel identify only those students with true SLD (rather than incorrectly identifying those who have been poorly instructed).

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Apart from the impact on students regarding overrepresentation in special education, a strong impact is made on the educational system at large. First, it is more expensive to educate students with disabilities who need support from special education teachers, paraeducators, and related service providers. The failure of some general education teachers to provide effective research-based instruction to all students results in the inappropriate overidentification of students who require specialized instruction to meet their individual needs. Second, when teachers abdicate their responsibility to effectively teach students with diverse abilities, the responsibility is often not shared, but shifted to specialists. Students who are misidentified and served are also likely to have poor post-school outcomes. They often have low graduation rates, social-emotional problems, low earning power after graduation, low rates of post-secondary education, and low enrollment in higher education institutions (NABSE & ILLIAD Project, 2002; Snyder, Dillow, & Hoffman, 2009).

TOO MANY STUDENTS ARE BEING IDENTIFIED WITH THE WRONG DISABILITY Not only have more students been identified as having disabilities in the past 30 years, but proportionately more students with SLD, OHI, autism, and traumatic brain injuries (TBI) have been identified. For example, in the 1976–1977 school year, 21.5% of the students served in special education had SLD, compared to 39.9% in 2006–2007. Likewise, the proportion of students with OHI has increased over 30 years almost threefold (from 3.8 to 9.1%). While students with autism and students with TBI are considered to be lowincidence disabilities, their identification has increased dramatically since the 1995–1996 school year (from 0.5 to 3.9% for autism and from 0.2 to 0.4% for TBI) (Snyder et al., 2009). See Fig. 3 for a comparison of the composition of students served with the most prevalent disabilities over time. Conversely, the identification of students with other disabilities has been decreasing over the past 30 years. Most notably, students with MR once represented 26% of all students in special education (aged 3–21 years), whereas in 2006, they represented only 8% of that population. The proportion of students with speech and language impairments (SLI) also decreased from 35.2 to 22.1% in that same period of time. Only slight declines are found in children with orthopedic impairments (OI), visual impairments (VI), hearing impairments (HI), and emotional disturbance (ED) (Snyder et al., 2009).

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Fig. 3.

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Percentage of Children Served under IDEA within Disability Categories over Time.

At least two hypotheses exist regarding the variable trends of identifying students with various disabilities in U.S. schools in what has been called a ‘‘category shift’’ or ‘‘diagnostic substitution.’’ First, as we mentioned earlier, autism and TBI were not included in IDEA definitions as separate disability categories until 1990. That same year, ADHD was included as one of many OHI. The increase of students identified as having OHI is primarily due to the dramatic increase in the number of students identified with ADHD (Diller, 2006). The rapid increase from 1990 (1.2%) to 2006 (9.1%) moves OHI from being a low-incidence disability to the third most common disability category after SLD and SLI (Snyder et al., 2009) (see Fig. 3). A second hypothesis regarding variable trends within categories is the effectiveness of early intervention services for students. This hypothesis can particularly help explain the declining proportion of students served as having SLD within the past decade. As mentioned previously, we believe school personnel need to improve their identification, evaluation, and classification procedures to ensure that

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only students who truly have disabilities are identified. One may question whether it is just as important that the correct disability be identified. We know that students with physiological characteristics attributed to disabilities that are medically diagnosed or classified with hard diagnostic criteria (e.g., sensory impairments and OI) are more likely to be properly classified than those in the ‘‘soft’’ disability categories requiring professional judgment (e.g., SLD and MR) (Harry & Klingner, 2006; Skiba et al., 2008). This is evidenced in the data indicating that for certain disabilities such as HI, VI, OI, and developmental delays, the classification rates have been relatively stable over the past two decades. The field has moved to a cross-categorical approach to educating students in the ‘‘soft’’ disability categories recognizing they have more in common than they have differences. With the ‘‘soft’’ disabilities, if special education services are implemented properly, disability labels should not dictate the type or amount of services. If a child needs certain services, she/he should receive them regardless of label. At the same time, teachers and parents are more accepting of certain disability labels. Some parents and educators lobby for more desirable classifications such as SLD rather than MR, which may account for some of the shift between those two categories. It was previously argued that several of the IDEA definitions of disability are outdated and need to be adjusted based on the current knowledge base. It is also possible that the profession has matured over the past 30 years leading to more accurate educational classifications in certain disability categories (e.g., autism, TBI).

RACIALLY/ETHNICALLY DIVERSE STUDENTS ARE OVERREPRESENTED AND INAPPROPRIATELY SERVED IN SPECIAL EDUCATION In the wake of the U.S. Civil Rights Movement of the 1950s came concern about the separate and unequal practices of identifying and placing racially and ethnically diverse students, particularly African Americans, in separate special education classes for students with MR. This concern of misidentification was articulated by Dunn (1968) in his historic critique of the field, and highlighted by the President’s Committee on Mental Retardation in their conference report, The Six-Hour Retarded Child (1969). Many of these students were African Americans living in poverty and labeled ‘‘functionally retarded’’ because they were performing poorly

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during the 6 hours in school, yet were functioning adaptively in their home and community environments. Given this contradiction, scholars and educators began to ask important questions regarding discriminatory practices in education for students with special needs. Why were there proportionately more African American students and those living in poverty identified as having MR and how should they best be served? The argument has been extended to other disability groups and these discriminatory practices continue today (Skiba et al., 2008). Surprisingly, systematic efforts to collect and analyze data regarding the disparities in educational access and progress among students from different races and ethnicities were not mandated until the reauthorization of IDEA in 1997. Annually, the U.S. Office of Special Education Programs presents a report to Congress on the implementation of the Individuals with Disabilities Education Act. In this report, data represent how students are being identified and served by special education and related services. Beginning in 1998, these data also include information regarding race/ethnicity of students with special education needs using the following categories: (a) American Indian or Alaska Native, (b) Asian/Pacific Islander (A/PI), (c) Black or African American (not Hispanic), (d) Hispanic or Latino, and (e) White (not Hispanic). These data are only as accurate as the reporting system allows. For example, race/ethnicity data may be based on data sampled from school districts rather than actual counts, and race/ethnicities for some students who have an unknown race/ethnicity or multiple races/ethnicities are estimated by education professionals. Also, only one race/ethnicity category may be reported for each student, unlike the current U.S. Census data collection system, which allows for multiple racial categories for each citizen. Furthermore, special education data are distinctly different from epidemiological data based on medical records and should not be used to report prevalence or incidence of any given disability in a population; it provides only information about the students identified by school multidisciplinary teams as having a disability and thereby requiring special education. The 2004 reauthorization of IDEA focuses on efforts to prevent the misidentification and high dropout rates of racially/ethnically diverse students with disabilities and requires state education agencies to (a) establish policies and procedures to prevent disproportionate representation, (b) collect and examine disproportionality data, (c) review and evaluate policies, procedures, and practices, (d) disaggregate data regarding suspension and expulsion, and (e) monitor local education agencies’ rates of disproportionality (U.S. Department of Education, Office of Special Education Programs, 2008b). Furthermore, it requires schools with significant disproportionality to provide

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early intervening services, such as tutoring, to students who are struggling to learn (Skiba et al., 2008). The data collected and reported annually to Congress validate what the Office of Civil Rights, the National Academy of Science, and researchers have previously reported, that students from racial/ethnic subgroups are disproportionately represented in several disability categories. Generally speaking, groups overidentified include African American, Hispanic, and American Indian/Alaska Native (AI/AN) students identified as having MR, ED, SLD, and SLI (Harry & Klingner, 2006; National Research Council, 2002). Data from the most recent Annual Report to Congress (2008a) indicate an overrepresentation of students from various ethnic/racial backgrounds in many areas related to special education. This section presents recent data related to the overrepresentation of each reported racial category, noting when a confidence interval of 10% is exceeded for one racial/ethnic category over another or several others (Skiba et al., 2008). See Tables 1, 2, and 3 for racial/ethnic groups that have the highest overrepresentation in each category.

American Indian/Alaska Native Students Infants and toddlers who are AI/AN represent a higher proportion of children who receive audiology, health, medical, nutrition, specialized instruction, vision, and other early intervention services than children from other races. They also are more likely than those of other races/ethnicities to be served in programs for typically developing children (7.2% compared to the lowest group 2.6% of Hispanic). AI/AN infants and toddlers are proportionally more likely to be eligible for early intervention services than those of other races (74% of AI/AN qualify, compared to the group with the lowest eligibility rates – 51% of A/PI). Children aged 3–5 years in this racial category are 1.5 times more likely to be served in special education than all other races combined, and they are more likely to be served in early childhood settings (48.2%) (rather than early childhood special education or other settings) than preschoolers from other backgrounds. The group of AI/ AN students with disabilities aged 6–21 years has (a) a risk ratio higher than 1.0 for special education eligibility, as well as all disability categories except for OI and autism; (b) the highest risk ratio for being eligible for special education services than all other races combined (1.52); (c) a higher risk ratio than all other races combined for the following disabilities – SLD, SLI, HI, VI, deaf-blindness (DB), and TBI (1.79, 1.33, 1.31, 1.27, 1.73, 1.46,

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Table 1.

Highest Levels of Overrepresentation in Identification and Services for Infants and Toddlers with Disabilities. American Indian/ Alaska Native

Eligible for early intervention Served in home Served in programs for typically developing children Assistive technology services Audiology services Family training, counseling, home visits Health services Medical services Nursing services Nutrition services Occupational therapy services Physical therapy services Psychological services Respite care services Social work services Specialized instruction Speech/language therapy services Transportation services Vision services Other early intervention services

Table 2.

Asian/Pacific Islander

Black (Not Hispanic)

Hispanic

White (Not Hispanic)

x x x x x x x x x x x x x x x x x x x x

Highest Levels of Overrepresentation in Identification and Services for Preschoolers with Disabilities. American Indian/Alaska Native

Eligible for early childhood special education Not eligible for early childhood special education Served in early childhood settings Served in early childhood special education settings

Asian/ Pacific Islander

Black (Not Hispanic)

Hispanic

White (Not Hispanic)

x x x x

respectively); (d) the greatest percentage of students who drop out of school (44.6% compared to the lowest group – 22% of A/PI); (e) the highest percentage of students who spend 21–60% of the day outside of the general education environment (33% compared to the lowest group – 22.5 of A/PI);

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Table 3.

Highest Levels of Overrepresentation in Identification and Services for School-Aged Students with Disabilities. American Asian/ Black Hispanic White Indian/Alaska Pacific (Not (Not Hispanic) Native Islander Hispanic)

Eligible for special education Specific learning disability Speech or language impairments Mental retardation Emotional disturbance Multiple disabilities Hearing impairments Orthopedic impairments Other health impairments Visual Impairments Autism Deaf-blindness Traumatic brain injury Dropout Graduate with regular diploma Educated less than 21% of day outside of general classrooms Educated 21–60% of day outside of general classrooms Educated at least 60% of day outside of general classrooms Educated in separate environments Removed to interim alternative educational setting due to guns or weapons Suspended or expelled, more than 10 days

x x x x x x x x x x x x x x x x x x x x

x

and (f) the highest percentage of students who are removed to an interim alternative educational setting due to possession of guns or weapons (0.65% compared to the lowest group – .09 A/PI). Asian/Pacific Islander Students The largest proportion of infants and toddlers who receive early intervention services in their home are A/PI (83.4%) compared to only 75.5% of Black children (the group with the lowest proportion served in

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home). They also have a higher percentage than other races of infants and toddlers who receive nursing services; psychological services; social work services; and family training, counseling, and home visits. This group has the highest percentage among the other races who were determined to be not eligible for special education (51%) and exited early intervention services to other programs (31.9%). A/PI preschoolers were served in early childhood special education settings at a higher percentage than other races (44.8%). The group of A/PI students with disabilities aged 6–21 years is overrepresented in only two areas; this group has (a) a risk ratio greater than 1.0 for HI, autism, and DB; and (b) a higher percentage of students graduating with a diploma than all other races (63.5%). Black (Not Hispanic) Students Infants and toddlers who are Black are as likely as children in all other race/ ethnicity groups to receive early intervention, with a risk ratio of 1.0. These infants and toddlers have a higher percentage of children who receive transportation services than other races (7.6% compared to the lowest group – 3.8% of A/PI). The group of Black students with disabilities aged 6–21 years has (a) a risk ratio higher than 1.0 for special education eligibility, as well as each disability category except OI and DB; (b) the highest risk ratio than all other races combined for MR, ED, and multiple disabilities (MD) (2.83, 2.24, 1.50, respectively); (c) the highest percentage of students who are taught at least 60% of the time outside of the general class (26.2% compared to the lowest group – 13.2% of AI/AN); (d) the highest percentage of students who are suspended or expelled for more than 10 days (2.38%) or for multiple days exceeding 10 (2%); and (e) the highest percentage of students educated in separate environments (5.5%, compared to the lowest group – 2.8% of AI/AN). Hispanic Students Infants, toddlers, and preschoolers with disabilities who are Hispanic are not overrepresented in the service they receive from early intervention or early childhood special education. However, there is a higher percentage of infants and toddlers who receive respite care than other races (5.1%, compared to the lowest group – 2.9% of White). Also, there is some overrepresentation in the 6- to 21-year age group; specifically, this group of Hispanic students with disabilities has (a) a risk ratio higher than 1.0 for

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SLD, HI, OI, and DB; and (b) the highest risk ratio than all other races combined for students with OI (1.08). White (Not Hispanic) Students Some overrepresentation exists for White infants and toddlers in terms of receiving services such as assistive technology (3.4%), occupational therapy (34.3%), physical therapy (34.8%), and speech/language pathology (53%). White preschoolers are overrepresented in terms of being eligible for preschool services (risk ratio ¼ 1.3). Also, some overrepresentation occurs for schoolaged students. The group of White students with disabilities aged 6–21 years has (a) a risk ratio greater than 1.0 for SLI, MD, OHI, autism, and TBI; (b) a higher risk ratio than all other races combined for students with OHI (1.52 times more likely than other races) and autism (1.3 times more likely than other races); and (c) a higher percentage of students who are enrolled less than 21% of the day outside of general education settings than students from other races (56.8% compared to the lowest group – 41% of Black students). According to Skiba et al. (2008), the problem of overrepresentation in special education of racially/ethnically diverse students continues to be ‘‘among the most critical and enduring problems in the field’’ (p. 264). Even when mitigating variables (e.g., poverty) are accounted for, racially/ethnically diverse students continue to be overrepresented with stigmatizing disabilities (e.g., MR and ED) and underrepresented in more socially acceptable categories such as giftedness (De Valenzuela, Copeland, Qi, & Park, 2006). Unfortunately, racially/ethnically diverse students with disabilities are particularly prone to being ‘‘misidentified, misassessesd, miscategorized, misplaced, and misinstructed’’ (Obiakor, 2009, p. 100). Disproportionality compromises even the principles upon which special education law is based. As Boone and King-Berry (2007, p. 341) state, Research data are growing confirming the existence of educational disparities that adversely impact African American and other culturally or linguistically diverse students with disabilities. In particular, disproportionality regarding disability classifications, placement, service delivery, and ultimately, educational outcomes indicate that for African American and other minority children, major principles of IDEA y are being severely compromised.

Two principles of IDEA compromised by disproportionality include equal access and least restrictive environment. In more restrictive environments (e.g., segregated classrooms), students are removed from the general classroom and are more likely to not have access to the general education

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curriculum. As described in the previous statistics, 33% of AI/AN students with disabilities spend 21–60% of their school day outside of the general education classroom, whereas, 26.2% of Black students with disabilities are taught outside of the general class at least 60% of the school day (U.S. Department of Education, Office of Special Education Programs, 2008a). These data support other research with similar findings. For example, De Valenzuela et al. (2006) found that African American, Hispanic, and Native American students received special education services in more segregated settings than White and A/PI students. Students who are misidentified are likely to be denied appropriate access to the general curriculum as they receive their education in separate environments with a separate curriculum (Salend, Duhaney, & Montgomery, 2002). Although IDEA mandates access to the general curriculum for all students with disabilities, in practice, levels of access may vary immensely, and students therefore do not receive services that fit need their needs, resulting in inequitable educational opportunities (NABSE & ILLIAD Project, 2002). Disproportionality may extend beyond compromising the basic principles of IDEA. Professionals have argued that it legalizes segregation and racism. For example, Blanchett (2006, p. 25) writes, For many African American and some poor students, special education has become a form of segregation from the mainstream y In fact, special education has become a mechanism for keeping many African American students from receiving an equitable education in the general education environment y As a result, some scholars y have referred to special education as a new legalized form of structural segregation and racism.

Disproportionality in special education based on race/ethnicity can compromise the tenets of IDEA and promote segregation based on race/ ethnicity in the schools. It should be noted that the ‘‘policies, procedures, and practices that may result in unequal, unfair treatment of students from different racial/ethnic groups’’ (Coutinho & Oswald, 2006, p. 8) should be examined and rectified.

CONCLUSION No single factor can explain the complexity of overrepresentation and disproportionality in special education. Factors that do contribute include social factors such as vague definitions of socially constructed disability categories and misinterpretation of culturally based behaviors. Systemic

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factors include schools having limited access to resources; school personnel failing to collect data and recognize disproportionality exists; teachers using culturally unresponsive tests, curriculum, and pedagogy; lack of teacher diversity in the field; and inadequate teacher preparation (Blanchett, 2006; National Research Council, 2002; Salend et al., 2002). In addition to these social and systemic factors, individual factors include biological, social, and contextual contributors to children’s early development. When disproportionality results in inappropriate general education programs, discriminatory assessment practices, or ineffective special education practices, then such disproportionality is harmful to students (Coutinho & Oswald, 2006). It is incumbent upon education professionals and policymakers to address the underlying problems that lead to disproportionality so that schools will meet the 40-year-old charge of the U.S. Commissioner of Education for a ‘‘true equality of education’’ for all students (President’s Committee on Mental Retardation, 1969, p. 3).

REFERENCES Arms, E., Bickett, J., & Graf, V. (2008). Gender bias and imbalance: Girls in US special education programmes. Gender and Education, 20, 348–359. Artiles, A. J., & Bal, A. (2008). The next generation of disproportionality research: Toward a comparative model in the study of equity in ability differences. The Journal of Special Education, 42(1), 4–14. Blanchett, W. J. (2006). Disproportionate representation of African American students in special education: Acknowledging the role of white privilege and racism. Educational Research, 35(6), 24–28. Bollmer, J., Bethel, J., Garrison-Mogren, R., & Brauen, M. (2007). Using the risk ratio to assess racial/ethnic disproportionality in special education at the school-district level. The Journal of Special Education, 41, 186–198. Boone, R. S., & King-Berry, A. (2007). African American students with disabilities: Beneficiaries of the legacy? The Journal of Negro Education, 76, 334–345. Coo, H., Ouellette-Kuntz, H., Lloyd, J. E. V., Kasmara, L., Holden, J. J. A., & Lewis, M. E. (2008). Trends in autism prevalence: Diagnostic substitution revisited. Journal of Autism and Developmental Disorders, 38, 1036–1046. Coutinho, M. J., & Oswald, D. P. (2006). Disproportionate representation of culturally and linguistically diverse students in special education: Measuring the problem. Tempe, AZ: National Center for Culturally Responsive Educational Systems. De Valenzuela, J. S., Copeland, S. R., Qi, C. H., & Park, M. (2006). Examining educational equity: Revisiting the disproportionate representation of minority students in special education. Exceptional Children, 72, 425–441.

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Diller, L. H. (2006). The last normal child: Essays on the intersection of kids, culture, and psychiatric drugs. Westport, CT: Praeger. Dunn, L. M. (1968). Special education for the mildly retarded – Is much of it justifiable? Exceptional Children, 23, 5–21. Dyches, T. T., Wilder, L. K., Sudweeks, R. R., Obiakor, F. E., & Algozzine, B. (2004). Multicultural issues in autism. Journal of Autism and Developmental Disorders, 34, 211–222. Forness, S. R., & Kavale, K. A. (2000). Emotional or behavioral disorders: Background and current status of the E/BD terminology and definition. Behavioral Disorders, 25, 264–269. Greene, J. P. (2007). Fixing special education. Peabody Journal of Education, 82, 703–723. Harry, B., & Klingner, J. (2006). Why are so many minority students in special education? Understanding race and disability in schools. New York: Teachers College. Kavale, K. A., & Flanagan, D. P. (2007). Ability-achievement discrepancy, response to intervention, and assessment of cognitive abilities/processes in specific learning disability identification: Toward a contemporary operational definition. In: K. A. Kavale (Ed.), Handbook of response to intervention: The science and practice of assessment and intervention (pp. 46–63). New York: U.S. Springer Science. National Alliance of Black School Educators (NABSE), & ILLIAD Project. (2002). Addressing over-representation of African American students in special education: The pre-referral intervention process – An administrator’s guide. Council for Exceptional Children, Arlington, VA, and National Alliance of Black School Educators, Washington, DC. National Council on Disability. (2000). Back to school on civil rights. National Council on Disability, Washington, DC, January 25. Available at www.ncd.gov/newsroom/ publications/2000/backtoschool_1.htm. Retrieved on June 15, 2009. National Research Council. (2002). Minority students in special and gifted education. In: M. S. Donovan & C. T. Cross (Eds), Washington, DC: National Academy Press. Obiakor, F. E. (2009). Demographic changes on public education for culturally diverse exceptional learners: Making teacher preparation programs accountable. Multicultural Learning and Teaching, 4, 90–110. Prater, M. A. (2007). Teaching strategies for students with mild to moderate disabilities. Boston: Allyn & Bacon. President’s Committee on Mental Retardation. (1969). The six-hour retarded child: A report on a conference on problems of education of children in the inner city. Washington, DC: Office of Education, Bureau of Education for the Handicapped. Salend, S. J., Duhaney, L. M. G., & Montgomery, W. (2002). A comprehensive approach to identifying and addressing issues of disproportionate representation. Remedial and Special Education, 23, 289–299. Skiba, R. J., Simmons, A. B., Ritter, S., Gibb, A. C., Rausch, M. K., Cuadrado, J., & Chung, C. (2008). Achieving equity in special education: History, status, and current challenges. Exceptional Children, 74, 264–288. Snyder, T. D., Dillow, S. A., & Hoffman, C. M. (2009). Digest of education statistics 2008 (NCES 2009-020). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education, Washington, DC. Available at http:// nces.ed.gov/pubs2009/2009020.pdf. Retrieved on June 15, 2009. U.S. Department of Education, Office of Special Education Programs (2008a). Twenty-eighth annual report to Congress on the implementation of the individuals with Disabilities Education Act, 2006. Washington, DC: Westat.

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U.S. Department of Education, Office of Special Education Programs. (2008b). Disproportionality and overidentification. Available at: http://www.ideapartnership.org/index.php?option =com_content&view=article&id=841&oseppage=1. Retrieved on December 7, 2009. Wehmeyer, M. L. (2003). Defining mental retardation and ensuring access to the general curriculum. Education and Training in Developmental Disabilities, 38, 271–282. Westat. (2003). Methods for assessing racial/ethnic disproportionality in special education: A technical assistance guide. Available at http://www.ideadata.org/docs/Disproportionality %20Technical%20Assistance%20Guide.pdf. Retrieved on July 21, 2009.

PART III ASSESSMENT AND ACCOUNTABILITY IN EDUCATION

CHAPTER 5 STANDARDIZED TESTING/ ACCOUNTABILITY: IS NCLB FAIR FOR STUDENTS WITH DISABILITIES? Tes Mehring Beginning in the mid-1980s, various national reports strongly criticized the American educational system (Goodlad, 1984; National Commission on Excellence in Education, 1983). Major areas of concern included the declining academic achievement of US students in comparison to youths from other industrialized nations, adult illiteracy, dropout rates, and readiness for school (Goodlad, 1984). These concerns were initially addressed in 1989 by the nation’s governors, meeting at the first-ever Education Summit. Several broad national goals emerged from this historic conference that helped establish a blueprint for educational progress. In March 1994, for example, the US Congress enacted Goals 2000: Educate America Act (P.L. 103-227), which translated these reform efforts into law. Similarly, in 2001, the US Congress reauthorized the Elementary and Secondary Education Act, popularly known as the No Child Left Behind (NCLB) Act of 2001 (PL 107-110) (Gargiulo, 2009, p. 37). The central mandates of NCLB (2001) require states to (a) ensure that highly qualified teachers are in every classroom; (b) use research-based

Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 75–85 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019008

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practices as the foundation of instruction; (c) develop tests to assess students so that data-driven decisions become an integral part of the educational system; and (d) hold schools accountable for the performance of all students (Cohen, 2002). To measure academic progress, NCLB requires that states administer tests to all public school students. The states set proficiency standards, called adequate yearly progress (AYP), that progressively increase the percentage of students in a district that must meet the proficiency standard. If a school district does not meet these proficiency levels, the law mandates that sanctions and corrective actions be applied. All pupils, including those in special education, are expected to demonstrate proficiency in mathematics and reading. Annual testing of children in math and reading is required in grades 3–8, with students in grades 10 through 12 assessed at least once (Gargiulo, 2009). Beginning in 2007, all students in grades 3 through 8 were also required to be tested in science. Schools are expected to show AYP toward the goal of 100% proficiency by 2014. For improved school accountability, NCLB and the Individuals with Disabilities Education Improvement Act (IDEIA) of 2004 require all students to participate in their school district’s accountability system. Almost all (some 95%) of those with disabilities take the same statewide or districtwide assessments as their classmates without disabilities (U.S. Department of Education, 2007). A small percentage of students are excused from these tests when their Individualized Education Program (IEP) provides for an exemption. Students who are excused have their yearly growth evaluated through different means. Because this law is concerned with the achievement of all students, test scores must be disaggregated according to the pupil’s disability, socioeconomic status, race, ethnicity, and English language proficiency. The anticipated benefit of this requirement is that assessment results will directly translate into instructional accommodations for students that lead to a unified delivery system (Salend, 2008). NCLB required a major shift in the ways that teachers, administrators, and state department of education personnel think about public schooling. It is a very controversial law because educators are pressured to increase achievement of all students, narrow the test score gap between different groups of students, and ensure that all teachers are highly qualified (Anthes, 2002). Furthermore, educators are held responsible for bringing about these changes. The achievement and test score accountability provisions have generated much discussion regarding standard-based assessment, the value of high-stakes group testing, and alternate testing considerations (Stodden, Galloway, & Stodden, 2003).

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ACCOMMODATIONS In 2007, the U.S. Department of Education released new regulations for both NCLB and IDEA 2004 that increased the percentage of students who could demonstrate their annual learning through alternate means. These regulations resulted in three groups:  Students who demonstrate grade-level proficiency by taking large-scale assessments (without accommodation because they do not need them or with the accommodations called out in their IEPs) along with their classmates without disabilities.  Students with disabilities who participate in the general education, but whose achievement standards have been significantly modified (about 2% of all school children).  Students with disabilities who do not participate in the general education curriculum but participate in alternate assessment that reflect their IEP objectives (about 1% of all schoolchildren) (Smith & Tyler, in press). Although NCLB and IDEA 2004 require that all students participate in state and district assessments, special arrangements can and should be provided for students who have special needs or circumstances. NCLB requires that school districts provide students with disabilities access to appropriate accommodations if necessary to take the statewide assessment. Students with disabilities are to be held to the standards for the grade in which the student is enrolled, although in some situations, accommodations or modifications may be needed to get a true picture of a student’s achievement. To receive accommodations or modifications, students with disabilities must be eligible for special education services under the IDEA or Section 504 of the Rehabilitation Act. Each student’s IEP or 504 planning team must determine if a student can take the statewide assessment without accommodations or modifications, with appropriate accommodations and modifications, or if they will take an alternate assessment. Scores on the statewide assessment, with or without accommodations, or scores on the alternate assessment must be included in all statewide assessment reports. School districts also have to report the percentage of students taking an alternate assessment. The National Center for Educational Outcomes (NCEO, 2007) stresses that the purpose of these accommodations is to give students with disabilities an opportunity to demonstrate their knowledge and skills, rather than emphasizing their disabilities or lack of English fluency. How do educators decide which accommodations students with disabilities should be provided in testing situations? One guideline is that any

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accommodations made for instruction should also be provided during testing (Baca & Cervantes, 2004; Thurlow & Liu, 2001). Thus, if a student is allowed extra time to complete assignments, then allowing extra time would be a proper accommodation during an assessment. Examples of accommodations include taking a test individually or in small group instead of a large group; taking more frequent breaks during testing; having an extended time to take the test; taking a Braille edition of the test; and marking directly in a response booklet rather than bubbling in answers on a test sheet. The presentation format may be modified (e.g., the student may be presented with different directions or be given assistive devices for help in understanding the questions). The format for responding to questions may also be changed (e.g., providing an oral response to a scribe who then transfers them to corresponding ‘‘bubbles’’ on a computer-scored answer sheet). Accommodations vary greatly from state to state and are not explicitly determined by research evidence. Rather, school officials make recommendations for how particular students should be accommodated during standardized testing, as required by law. The need for accommodations should be stated in the students’ IEP. The accommodations used for highstakes assessment should be used in daily instruction of the student. Situations exist when a student with disabilities is unable to participate in the state assessment. When a student cannot participate, even with accommodations, an alternate assessment may be used to gather information needed to measure and document the student’s AYP (Thurlow, Elliott, & Ysseldyke, 2003). Students with more severe intellectual disabilities are excused from the required annual statewide and districtwide assessments (U.S. Department of Education, 2006, 2007). These students (approximately 1% of all students) have their AYP progress evaluated through alternate assessments (e.g., portfolios, direct measures of a skill or specific instructional target, or checklists). Typically, these students’ IEP goals do not reflect the complete general education curriculum or are they working toward a regular high school diploma but rather are participating in a functional or life skills curriculum (Smith & Tyler, in press). The IEPs of these students clearly identify both an alternate curriculum and the means for alternate assessments (Smith & Tyler, in press).

ADEQUATE YEARLY PROGRESS AYP are the overall results from individual’s schools that are used to ‘‘grade’’ school’s effectiveness, affect student promotion, and sometimes

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impact the school’s funding. These yearly assessments are often referred to as high-stakes testing. The ultimate expectation is that all students will achieve proficiency in reading and math, along with mastery of the content presented through the general education curriculum. When students’ test scores do not reach proficiency levels, the school they attend experiences significant disincentives (penalties). The possibility of penalties due to deficient test scores is a significant source of pressure for school districts. In addition, there is significant controversy surrounding the use of high-stakes tests for students with disabilities. While some say that participation by students with disabilities increases expectations, others say the tests are not fair to them (Bowie, 2007). Others go as far as stating that recent increases in the dropout rate of students with disabilities are due to the stress that these high-stakes tests create (Williams, 2007a). Furthermore, Williams (2007b) suggested the stakes are so high that many suspect that incidents of ‘‘teacher-assisted cheating’’ are on the rise. A school is labeled ‘‘in need of improvement’’ when a particular subgroup fails to meet AYP goals after 2 years, or if a subgroup does not meet the 95% participation rate (Kim & Sunderman, 2005). Schools in need of improvement are required to develop a plan for instructional improvement. The schools are provided technical and financial assistance to carry out the improvement plan. Students who attend Title I schools, which receive federal funding due to high enrollment of students from low-income families, may transfer to a better public school within the school district if the school fails to meet AYP for 2 consecutive years. The school district must provide transportation to the new school using a portion of Title I funds. If AYP goals are not met after 3 years, the label ‘‘in need of improvement’’ remains, and funding is provided to assist low-income students with supplemental educational services such as tutoring, after school classes, and summer programs (Council for Exceptional Children, 2003). Also, parents of children in ‘‘failing’’ schools will be given the opportunity to transfer their children to private and parochial schools. If AYP goals are not met after 4 years, corrective actions are required, such as replacing staff and creating a new curriculum. When AYP goals are not met after 5 years, a school can be restructured, taken over by the state or a private contractor, converted to a charter school, or reconstituted with new staff (Kim & Sunderman, 2005). Student consequences of using standardized test scores to assess AYP can be quite serious. For example, students who are required to repeat a grade due to failing a standardized test are more likely to drop out of school (Thomas, 2005). Also, a large number of students who fail a standardized

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test but meet all other school requirements for graduation are denied a high school diploma (Thomas, 2005).

POSITIVE OUTCOMES OF NCLB The accountability measures in NCLB have brought attention to the educational needs of students with disabilities. This accountability has encouraged school district administrators to budget additional educational resources that can assist students in their educational achievement. Furthermore, NCLB has lead to the early instructional intervention of students with learning problems. Also, NCLB has created an atmosphere of high expectations for all students, including those with disabilities. Lastly, monitoring every school’s overall improvement in academic achievement has encouraged all school personnel to attend to how well their students are mastering the general education curriculum’s goals, objectives, and benchmarks of achievement.

CONCERNS When considering the assessment-to-instruction connection, it is important to examine whether adaptations to the testing materials in presentation and response modes affect the performance of students with possible disabilities. For example, if a student has a reading difficulty and he/she is being assessed in math, does his/her reading difficulty interfere with his/her math performance (Kritikos, in press)? If it does, there is a validity issue regarding the assessment of that content area. Another concern is whether to assess students with disabilities using group or individual standardized achievement tests. Cohen and Spenciner (2007) report the advantages and disadvantages of group tests involving achievement. They note that consistency of administration, scoring, and interpretation is an advantage for group tests. In contrast, group test requirements related to writing, reading, time limits, and the complexity of transferring answers to answer sheets are disadvantages for students with disabilities (Cohen & Spenciner, 2003). Furthermore, individual achievement tests are more ideal than group tests for students with disabilities because the examiner can provide additional direction and clarification on test tasks (McLoughlin & Lewis, 2005). Lastly, individual tests allow the tester to motivate and encourage the student on the more difficult test items. These latter aspects can result in a more optimal test performance for students with disabilities.

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Although IDEA and Section 504 of the Americans with Disabilities Act allow for assessment accommodations, they are not used sometimes (Gagnon & McLoughlin, 2004). In fact, Hollenbeck, Tindal, and Almond (1998) found that only 21% of the general education and special education teachers they surveyed reported using accommodations specified statewide testing manuals. Furthermore, only 55% of the teachers surveyed reported knowledge of allowable accommodations on statewide tests (Gagnon & McLoughlin, 2004). All 50 states have guidelines or policies in place concerning the use of testing accommodations. However, the guidelines differ widely from state to state (Thurlow, 2007). For example, in a large-scale assessment study by the NCEO (2007), it was reported that many different accommodations are used across the states to help students with disabilities demonstrate how well they have learned. Furthermore, some states allow a common accommodation (e.g., read the test directions aloud) that is banned by others (Crawford, 2007). High-stakes testing can lead to many negative outcomes for students, teachers, and schools. One of the most severe outcomes is test score pollution. It occurs when test scores are systematically increased or decreased due to factors unrelated to what the test is intended to measure. When this occurs, the increase or decrease in test scores over time is not a true increase or decrease in student learning but rather the result of other factors, including unethical actions by teachers and administrators under pressure to meet legislated standards. Negative outcomes of high-stakes testing can show up in several ways, including ‘‘teaching to the test,’’ using unethical test preparation approaches (e.g., providing students with actual test questions before the standardized testing session), extending time limits, allowing students to respond directly on test booklets rather than on the computerscored answer sheets, or systematically excluding students from testing because they are likely to have low scores (Haladyna, 2002). Educators have also been found to increase test scores by reading answers to students and erasing student answers to insert the correct answer after completion of the test (Haladyna, 2002). Lastly, educators have used excessive motivation practices (e.g., promises of parties or recognition of students by the school for high scores) to increase student test scores (Haladyna, 2002).

NCLB AND STUDENTS WITH DISABILITIES Although many professionals laud the provisions of NCLB, the law is notably silent as far as addressing students with disabilities. In fact, there is

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genuine concern in some educational circles that with more rigorous standards of academic competency and stringent evaluation requirements, students with disabilities may be shortchanged in their drive toward obtaining a high school diploma. In response to NCLB, several states have instituted higher graduation standards and there is a growing national trend toward greater teacher accountability for student performance. This push poses some interesting challenges for both general and special educators because many students with disabilities experience difficulty fulfilling current academic expectations, let alone the newer performance guidelines. IDEA (PL 105-17) contains several requirements that speak to the overall intent of NCLB. For instance, each pupil’s IEP must now contain a statement that addresses the extent to which the student will be involved in and progress through the general education curriculum. An implication of this standard is that general educators will be held increasingly accountable for the performance of students with disabilities and other impairments. The 2004 version of IDEA also requires the inclusion of children with disabilities in statewide and districtwide assessments (using appropriate accommodations) in an attempt to gauge their educational progress. Previously, these students were routinely excluded from testing programs most likely because their anticipated weak performance would reflect poorly on the school in ratings or rankings relative to other schools. Accountability is the buzzword in NCLB. This law stresses outcomes, as measured by academic achievement, for all learners, including pupils with disabilities. High-stakes testing is now commonplace for students, teachers, and administrators. However, NCLB raises significant questions for students with disabilities who fail to meet performance standards. Will we see an increase in referrals for special education services? Are we destined to have more children identified as learning disabled as schools continue to focus on high standards and accountability (Brooks, 2002)? Will IEP goals become more closely aligned with the content standards of the general education curriculum? Will students with disabilities simply drop out of school as a result of the growing emphasis on accountability and academic performance? These questions will be addressed in time but presently there are no answers.

CONCLUSION The current educational reform movement, with its clarion call for greater accountability and higher academic standards, will certainly affect students with disabilities and general and special educators who instruct them.

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Judging the success of this reform movement may center on answering the following questions: How competently will students with disabilities perform on high-stakes assessments; How effective will instructional intervention be? Obviously, NCLB emphasizes academic achievement as measured by student performance on standardized tests. Furthermore, NCLB has an expectation that effective instructional strategies can compensate for a student’s disability. The enactment of NCLB has ushered in an era of what is commonly referred to as ‘‘high-stakes testing.’’ Unfortunately, high-stakes testing may be problematic for students with disabilities due to the stress that it causes. Positively, NCLB has placed greater emphasis on ensuring that students with disabilities are exposed to the general education curriculum that should be beneficial to their educational development. One can also anticipate that due to NCLB, greater attention will be focused on aligning the IEP goals of students with disabilities with the content standards of the general education curriculum (Council for Exceptional Children, 2003). Because of NCLB, general and special education teachers will play a proactive role in improving the educational achievement of students with disabilities. In ending, teachers cannot afford simply to bury their heads in the sand and hope that all will turn out well for students with disabilities. Teachers must understand the political, educational, and assessment context in which NCLB works. Such understanding will allow them to be effective advocates for best practices in education for students with disabilities, both in the classroom and in a larger political and social context (O’Donnell, Reeve, & Smith, 2009).

REFERENCES Anthes, K. (2002). No child left behind policy brief: School and district leadership. Denver: Education Commission of the States. Available at http://www.ecs.org/clearinghouse/32/ 37/3237.doc Baca, L. M., & Cervantes, H. T. (Eds). (2004). The bilingual special education interface (4th ed.). Upper Saddle River, NJ: Merrill/Pearson Education. Bowie, L. (2007). Special ed is drawn into exam debate. Baltimore Sun, October 22. Available at http://www.baltimoresun.com. Retrieved on October 22, 2007. Brooks, M. (2002). A look at current practice. In: R. Bradley, L. Danielson & D. Hallahan (Eds), Identification of learning disabilities: Research to practice (pp. 335–340). Mahwah, NJ: Erlbaum. Cohen, L., & Spenciner, L. (2003). Assessment of children and youth (2nd ed.). New York: Longman. Cohen, L., & Spenciner, L. (2007). Assessment of children and youth (3rd ed.). New York: Longman.

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Cohen, M. (2002). Assessment and accountability: Lessons from the past, challenges for the future, February. Paper presented at a conference sponsored by the Thomas B. Fordham Foundation, No Child Left Behind: What will it take? Council for Exceptional Children. (2003). No Child Left Behind Act of 2001: Reauthorization of the Elementary and Secondary Education Act (technical assistance resource). Arlington, VA: Author. Crawford, L. (2007). State testing accommodations: A look at their value and validity. New York: National Center for Learning Disabilities. Gagnon, J. C., & McLoughlin, M. J. (2004). Curriculum, assessment, and accountability in day treatment and residential schools. Exceptional Children, 70(3), 262–283. Gargiulo, R. M. (2009). Special education in contemporary society. Los Angeles, CA: Sage. Goodlad, J. (1984). A place called school. New York: McGraw-Hill. Haladyna, T. M. (2002). Essentials of standardized achievement testing: Validity and accountability. Boston: Pearson. Hollenbeck, K., Tindal, G., & Almond, P. (1998). Teachers’ knowledge of accommodations as validity issue in high-stakes testing. The Journal of Special Education, 32(3), 175–183. Kim, J. S., & Sunderman, G. L. (2005). Measuring academic proficiency under the No Child Left Behind Act: Implications for educational equity. Educational Researcher, 34(8), 3–13. Kritikos, E. (in press). Special education assessment: Issues and strategies affecting today’s classrooms. Upper Saddle River, NJ: Merrill. McLoughlin, J., & Lewis, R. (2005). Assessing students with special needs (6th ed.). Upper Saddle River, NJ: Merrill/Pearson Education. National Center for Educational Outcomes. (2007). Online accommodations bibliography. Available at http://www.nceo.org. Retrieved on December 22, 2007. National Commission on Excellence in Education. (1983). A nation at risk: The imperative for educational reform. Washington, DC: Author. O’Donnell, A. M., Reeve, J., & Smith, J. K. (2009). Educational psychology: Reflection for action (2nd ed.). Hoboken, NJ: Wiley. Salend, S. (2008). Creating inclusive classrooms (6th ed.). Upper Saddle River, NJ: Pearson Education. Smith, D. D., & Tyler, N. C. (in press). Introduction to special education: Making a difference (7th ed.), Upper Saddle River, NJ: Merrill. Stodden, R. A., Galloway, L. M., & Stodden, N. J. (2003). Secondary school curricula/issues: Impact on postsecondary students with disabilities. Exceptional Children, 70, 9–25. Thomas, R. M. (2005). High stakes testing: Coping with collateral damage. Mahwah, NJ: Erlbaum. Thurlow, M. L. (2007). Research impact on the state accommodation policies for students with disabilities. Paper presented as part of a research symposium entitled ‘‘Research Influences Decisions for Assessing English Language Learners and Students with Disabilities’’ at the American Education Research Association, Chicago. Thurlow, M. L., Elliott, J. L., & Ysseldyke, J. E. (2003). Testing students with disabilities: Practical strategies for complying with district and state requirements. Thousand Oaks, CA: Corwin Press. Thurlow, M. L., & Liu, K. K. (2001). Can ‘‘all’’ really mean students with disabilities who have limited English proficiency? Journal of Special Education, 14(November), 63–71.

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U.S. Department of Education. (2006). 34 CFR parts 300 and 301, Assistance to States for the Education of Children with Disabilities and Preschool Grants for Children with Disabilities: Final rule. Federal Register, 1263–1264, Washington, DC, August 14. U.S. Department of Education. (2007). Measuring the achievement of students with disabilities: What families and schools need to know about modified academic achievement standards. Washington, DC: Author. Williams, J. (2007a). California exit exam boosts dropout numbers. Associated Press, November 8. Available at http://ap.google.com. Retrieved on November 8, 2007. Williams, J. (2007b). Cheating can tempt test givers. Baltimore Sun, March 21. Available at http://www.baltimoresun.com. Retrieved on March 26, 2007.

CHAPTER 6 CURRICULUM-BASED ASSESSMENT: THE MOST EFFECTIVE WAY TO ASSESS STUDENTS WITH DISABILITIES Sunday Obi Assessment is used to describe the process of gathering information to make judgments about how well someone has performed, how much progress has been made, and how much potential someone has. In other words, gathering information and forming judgments are both indispensable to good teaching. In recent years, the rules of the testing game have been dramatically altered. Educational tests that, only a short while ago, were fairly innocuous and low-impact assessment tools are now being used to produce the key evidence that both high-level policymakers and run-of-themill citizens rely on to decide whether schooling is effective. Newspapers now annually report test results of schools and school districts. Parents can see how well their children’s schools stack up against schools elsewhere. Local school boards can determine whether the performance of their district’s teachers and administrators, as reflected by a district’s relative performance on such tests, is marvelous or miserable. Indeed, pupils’ performances or tests serve as the single most significant indicator of a school system’s success (Kirk, Galloway, Anastasiow, & Coleman, 2006).

Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 87–97 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019009

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Throughout the history of education, there has always been the concern that classroom evaluations may not be fair. Our standardized tests are often biased, our teacher-made tests are not very reliable, and our assessment strategies are artificial. Although these concerns are often valid, they do not deter excessive reliance on tests and grades. Teachers will always be involved in making judgments and decisions; and to pretend that we do not evaluate when we teach, is not only dishonest, but also creates a situation that allows unfair practices to go unnoticed and unchecked (Cooper & TenBriak, 2003). In this chapter, I advocate curriculum-based assessment (CBA) strategies to evaluate meaningful knowledge and skills in the particular curriculum in use in schools.

CURRICULUM-BASED ASSESSMENT: HOW RELEVANT TO INSTRUCTION? There has been a grass roots movement among parents and educators requiring answers to precise questions about students’ academic learning behaviors in relation to actual classroom instruction – a movement that is requiring the very character of educational assessment to assume a more direct role in determining the instructional needs of students. Both parents and teachers want their children to receive a good education and to be successful in school relative to their developmental skills. To achieve this, there is no better or more immediate way than through assessing how well children function in relation to the daily instruction they are receiving within their classroom assignments. Clearly, the curriculum establishes itself as the relevant medium for assessing both students’ needs and the directions to be taken by teachers in meeting those needs (McLaughlin & Lewis, 2001). Progress monitoring has of late been on the agenda of educational policy decision makers and administrators. With standard-based reform and school accountability at the forefront of educational policy (e.g., No Child Left Behind Act of 2001), it has become clear that if all students are to meet rigorous academic standards, assessment tools are needed to track student progress toward those standards and to quickly and accurately identify students at risk for failing to read them. Moreover, some have suggested the use of progress monitoring as part of a nondiscriminatory, response-tointervention approach for special education referral and identification (Fuchs & Fuchs, 2006; Speece, Case, & Molloy, 2003). For students receiving special education services, progress monitoring is viewed as a way to uphold major tenets of the Individuals with Disabilities Education

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Improvement Act (IDEIA, 2004) by aligning goals and objectives on Individualized Education Programs with performance and progress in the general curriculum (Nolet & McLaughlin, 2000). Of late, educators and administrators have focused increasing attention on assessment instruments that can precisely assess students’ knowledge of curriculum contents (Hunt & Marshall, 2006). This increased attention is, in part, in response to reports of lack of reliability and validity of standardized instruments. Technically, sound measures of curriculum knowledge and skills are needed to ensure that students are progressing toward curriculum standards, to identify those who struggle, and to inform instruction aimed at improving students’ knowledge and skills. One of the most extensively researched progress monitoring approaches is CBA, a formative evaluation method designed to evaluate performance in the particular curriculum to which students are exposed (Ysseldyke, Salvia, & Bolt, 2009). It usually involves giving students a small sample of items from the curriculum in use in their schools. CBA has received widespread attention in the area of special education – its concept is certainly not new and has been employed in schools for a number of years. The interest in CBA developed as a means of coping with low-achieving and special needs learners who were mainstreamed into regular education (Smith, Palloway, Patton, & Dowdy, 2001). Clearly, the CBA model fits nicely into a noncategorical model in which the emphasis is on testing curricular-based skills instead of testing for labeling purposes. CBA involves the measurement of the level of a student in terms of the expected curricula outcomes of the school (Tucker, 1985). In other words, the assessment instrument is based on the content of the student’s curriculum (Smith et al., 2001). CBA actually refers to various different procedures – some types are relatively informal whereas others are more formal and standardized (Stecker & Fuchs, 2000). In fact, there has been some confusion as to what professionals are talking about when they refer to the term CBA. The early professional literature regarding CBA procedures delineated four models (Deno & Fuchs, 1987). The first was CBA for instructional design in which the determination of instructional needs is based on students’ continuous performance in the existing curriculum. The second, curriculum-based evaluation, is characterized by the measurement of specific subcomponents of a curricular task. The other two – criterionreferenced CBA and curriculum-based measurement (CBM) – are the most widely researched and used. Teachers make various decisions during the course of a year. The arrival of each new class marks the beginning of a decision-making cycle that involves placing students into curriculum materials and determining the logistics of

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forming instructional groups. As the year progresses, performance must be continuously monitored to evaluate pupil progress and to make necessary instructional modifications. Throughout the year, teachers are called upon to discuss pupils’ academic performance at parent–teacher conferences and in meetings such as those held to determine a student’s eligibility to receive special education services. To perform any of these functions, teachers need to link assessment results with curriculum and instruction. Reliance on achievement test data alone precludes the possibility of making the necessary linkage. The disadvantages of basing instruction on the results of achievement tests are well known, the principal drawbacks being that measurement is infrequent and there is no assurance that the items on the test reflect the skills contained in the curriculum used in the classroom (Ysseldyke et al., 2009). In recent years, interest has intensified in developing other, more reliable methods of assessing academic performance. The most promising alternative to emerge is CBA, a criterion-referenced test that is teacher constructed and designed to reflect curriculum content. CBAs are intended for teachers to use in determining students’ skills in various curricula taught in the classroom. The primary strength of a CBA is that, as teachers develop it, they also formulate the important goals and objectives of the school program. Goalsetting is a natural artifact of this process; as teachers organize the assessment tool, they are also organizing and prioritizing the scope and sequence of the curriculum. Thus, they not only develop an assessment instrument that reflects what is being taught, but they also glean a clearer and better organized perspective of what will be achieved in the program. As indicated, the concept of CBA was developed as a solution to certain problems in our educational society, most of which have to do with educating low-achieving and special needs learners in inclusive settings. As special education monies and those earmarked for the education of students who experience cultural disadvantage have been made available to schools, the need to assess problem learners’ skills became apparent. This resulted in the construction and selling of a huge array of testing instruments. Many of these instruments have been used for assigning categorical labels to children to qualify them to receive supplementary educational assistance (Idol, Nevin, & Paolucci-Whitcomb, 1999). A general discontent with such labeling practices (Gordon, 1995) gave way to a continuing line of research to verify the utility and efficacy of CBA (Howell & Evans, 1995; Morison, White, & Feuer, 1996). It became evident that categorical labeling created certain problems. As a result, a solution to the labeling problem was to establish noncategorical programs for students with mild disabilities (IdolMaestas, 1981). The category of mild disability included students who had

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previously been labeled as having learning disabilities, mild mental retardation, or mild behavior disorders. CBA emerged as a testing methodology that suits well with noncategorical special education because the emphasis is on testing curricular-based skills, as opposed to attempting to define a special education exceptionality such as mental retardation, attention deficit disorder, or behavior problem (Idol et al., 1999). Because standardized tests do not always test the same skills or reflect curriculum content, they sometimes serve as weak predictors of how well a student might perform in the classroom. The use of CBA is a solution to this problem, because teachers construct CBAs to test mastery of the very skills that are taught and required in the classroom. More specifically, CBA is a natural, reality-based form of classroom assessment test. It is viewed as a reasonable solution to the social ills that can occur with the use of standardized tests, categorical labeling, and inadequate matches between tests and curricular. CBA has been recommended by many people involved in the reform of assessment practices in general (Bernauer & Cress, 1997; Lewis, 1997; Thompson, Beckmann, & Senk, 1997; Van Zant & Brown, 1997) as well as reform of assessment practices in mathematics (Graue & Smith, 1996; Wilcox & Zielinski, 1997), language arts (Wixson, Peters, & Porter, 1996), and Science (Pallrand, 1996). One of the most researched models of CBA is CBM, which was developed by Deno and Fuchs (1987) at the University of Minnesota. Although CBA is a more generic term that usually refers to informal and nonstandardized assessment, CBM is a set of standardized and specific measurement procedures that can be used to quantify student performance in the basic academic skill areas of reading, spelling, mathematics computation, and written expression. As a variant of CBA, CBM uses the general education curriculum as the basis for test development and is designed primarily as a measurement and evaluation system that school psychologists and teachers can routinely use to monitor individual student progress and instructional effectiveness. Strong research support exists for the reliability and criterion-related validity of CBM (Marston, 1989).

EFFECTIVE WAY TO ASSESS STUDENTS WITH DISABILITIES It is clear from the literature that CBAs have become viable alternatives to other assessment practices. For example, CBAs have been applied to better assess various populations such as students with mental retardation

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(Umbreit, 1996), students with learning disabilities (Stecker & Fuchs, 2000), students with attention deficit disorder (Stoner, Carey, & Ikeda, 1994; Umbreit, 1995, 1996), students with severe disabilities and medical challenges (Skakun, 1988; Thousand & Villa, 1990), students with emotional or behavioral problems (Algozine, Ruhl, & Ramsey, 1991; Delfino, 1994), students with speech impairments (Nelson, 1989), students at risk for school failure (Rydell, 1990), students in bilingual special education settings (Baker & Good, 1994; Ortiz & Wilkinson, 1991), and reading in English proficiency for bilingual students (Cline & Frederickson, 1996). CBA has been validated for assessing children and youth of various ages. At the preschool level, several researchers have studied the application of CBAs (Bondurant-Utz & Luciano, 1994; Notari & Drinkwater, 1991). At the elementary level, several researchers and practitioners have contributed important additional data showing the efficacy for this population (e.g., Guernsey, 1990; Hintze, Shapiro, & Lutz, 1994; Norris, Fuchs, & Fuchs, 1994). Efficacy of CBA for students at the secondary level has been investigated by Bol and Strage (1996), Espin and Deno (1995), Espin and Foegen (1996), Delfino (1994), Pallrand (1996), Russell (1995), Tindal and Nolet (1995), Seidenberg (1986, 1987), Tindal and Nolet (1995). In addition to comprehensive literature reviews by Algozine et al. (1991) and Mehrens and Clarizio (1993), researchers have reported the use of CBA with various academic content areas. Several researchers (Casteel, Roop, & Schiller, 1996; Ellliott & Fuchs, 1997; Fuchs & Fuchs, 1995; Gable, Arllen, & Evans, 1997; Hintze et al., 1994; King-Sears, 1997; Lewis, 1997; Roberts & Shapiro, 1996; Wixson et al., 1996) reported the applications of CBA for reading and language arts acquisition in elementary school children. Cawley, Miller, and Carr (1990) examined the reading performance of students with mild educational disabilities or learning disabilities through a combination of norm-referenced and CBA. Baker and Good (1995) used CBAs for reading in English to validate CBA sensitivity and reliability for bilingual (Spanish/ English) readers. Mathes, Fuchs, and Fuchs (1995) used CBAs in reading to validate improved reading performance of students with disabilities. Shinn, Powell-Smith, and Good (1997) used CBAs in reading to verify the positive effects of reintegrating students who had been previously removed from the general education classroom. Many researchers have expanded CBA research to include the area of mathematics (Fuchs, Fuchs, & Karns, 1995; Fuchs, Fuchs, & Phillips, 1995; Parke & Lane, 1996; Parker & Picard, 1997). Gable, Enright, and Hendrickson (1991) reported the applications of arithmetic CBAs for elementary school children. Espin and Foegen (1996) established the validity of three CBA measures (oral reading, maze, and

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vocabulary) on comprehension, acquisition, and retention of content-area material for 184 urban middle school students including 13 with mild disabilities. Finally, Pallrand (1996) recommended the use of sequential CBA activities for high school science to emphasize how secondary students can use knowledge to explain phenomena that build upon what they previously learned. CBA has been extended to other areas of the curriculum. Parke and Lane (1996) described a CBA system for mathematical problem solving, reasoning, and communication skills that was implemented successfully by teachers in six schools. Tindal and Nolet (1995) presented examples of CBA for critical thinking skills for middle and high school students. Frey (1995) recommended using CBA as part of portfolio assessment procedures for adult education and job training curriculum. The research support for CBA procedures has been very positive. The strengths of CBA that have been noted are its ability to lead to student improvement (Galagan, 1985) and its use as an effective communication tool with parents (Marston & Magnusson, 1985). Clearly, its primary advantage is in allowing increased instructional decision-making (Howell & Morehead, 1987). In other words, reformers, researchers, and practitioners are in agreement that CBAs are a viable alternative to more traditional psychoeducational assessment techniques. There is strong encouragement by educators and researchers to continue the development, implementation, evaluation, and refinement of CBAs in more areas of the curriculum (Idol et al., 1999). Moreover, teachers who use CBA to evaluate students’ skill areas often find that instruction becomes more streamlined; students can be offered instruction for unmastered areas without receiving repetitive instruction in previously mastered areas. Also, CBA can be developed collaboratively with other teachers who use the same curriculum; and they can be used with groups of students or with individuals. CBA allows ineffective adaptations to be more quickly redesigned.

CONCLUSION CBA is a new term for a teaching practice that is as old as education itself: a methodology used to determine the instructional needs of students based upon their performances within existing course content. More specifically, CBA uses the material to be learned as the basis for assessing the degree to which it has been learned. CBA data provide useful information at three stages in the teaching process: before instruction, immediately following

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instruction, and periodically throughout the year to assess long-term retention. Although CBA data are useful for planning instruction for all students, the method is especially appropriate for use with students with special needs. CBA results focus attention on classroom-relevant skills students need to learn. These data are reliable and are valid with respect to other accepted measures of academic achievement. Importantly, the student performance data collected for one decision (e.g., screening) are related to the data used to make other decisions (e.g., IEP planning and monitoring academic progress). As a result, data collection and decision-making are a more continuous process than in traditional assessment and decisionmaking practice.

REFERENCES Algozine, R., Ruhl, K., & Ramsey, R. (1991). Behaviorally disordered? Assessment for identification and instruction: Working with behavioral disorders. Reston, VA: Council for Exceptional Children. Baker, S., & Good, R. (1994, April). Curriculum-based measurement reading with bilingual Hispanic students: A validation study with second-grade students. Paper presented at the Annual Meeting of the Council for Exceptional Children/National Training Program for Gifted Education, Denver, CO. Baker, S., & Good, R. (1995). Curriculum-based measurement of English reading with bilingual Hispanic students: A validation study with second grade students. The School Psychology Review, 23(4), 561–578. Bernauer, J., & Cress, K. (1997). How school communities can help redefine accountability assessment. Phi Delta Kappan, 79, 71–75. Bol, L., & Strage, A. (1996). The contradiction between teachers’ instructional goals and their assessment practices in high school biology courses. Science Education, 80, 45–163. Bondurant-Utz, J., & Luciano, L. (1994). A practical guide to infant and preschool assessment in special education. Needham Heights, MA: Allyn & Bacon. Casteel, J., Roop, L., & Schiller, L. (1996). ‘‘No such thing as an expert’’: Learning to live with standards in the classroom. Language Arts, 73(1), 30–36. Cawley, J. F., Miller, J., & Carr, S. (1990). An examination of the reading performance of students with mild educational handicaps or learning disabilities. Journal of Learning Disabilities, 23, 284–290. Cline, T., & Frederickson, N. (Eds). (1996). Curriculum related assessment and bilingual children. Bristol, PA: Multilingual Matters. Cooper, J. M., & TenBriak, T. (2003). An educator’s guide to classroom assessment. New York: Houghton. Delfino, L. (1994, November). Curriculum-based assessment for adjudicated youth. Paper presented at the Annual Conference of Children with Behavioral Disorders, Tempe, AZ. Deno, S., & Fuchs, L. (1987). Developing curriculum-based measurement systems for data based special education problem solving. Focus on Exceptional Children, 19, 1–16.

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Ellliott, S., & Fuchs, L. (1997). The utility of curriculum-based measurement and performance assessment as alternatives to traditional intelligence and achievement tests. The School Psychology Review, 26(2), 224–233. Espin, D., & Deno, S. (1995). Curriculum-based measures for secondary students: Utility and task specificity of text-based reading and vocabulary measures for predicting performance on content-area tasks. Diagnostique, 20(1-4), 121–142. Espin, D., & Foegen, A. (1996). Validity of general outcome measures for predicting secondary students’ performance on content-area tasks. Exceptional Children, 62, 497–514. Frey, B. (1995). Portfolio assessment. Monograph. Lewistown, PA: Adult Education and Job Training Center. (ERIC Document Reproduction Service No. ED404503.) Fuchs, D., & Fuchs, L. (1995). What’s ‘special’ about special education? Phi Delta Kappan, 76, 522–530. Fuchs, D., & Fuchs, L. S. (2006). Introduction to responsiveness-to-intervention: What, why, and how valid is it? Reading Research Quarterly, 41, 92–99. Fuchs, L., Fuchs, D., & Karns, K. (1995). General educators’ specialized adaptation for students with learning disabilities. Exceptional Children, 61(5), 440–459. Fuchs, L., Fuchs, D., & Phillips, N. H. (1995). Acquisition and transfer effects of classwide peer-assisted learning strategies in mathematics for students with varying learning histories. The School Psychology Review, 24(4), 604–620. Gable, R., Arllen, N., & Evans, W. (1997). Strategies for evaluating collaborative mainstream insurrection: ‘‘Let the data be our guide’’. Preventing School Failure, 41, 153–158. Gable, R. A., Enright, B., & Hendrickson, J. (1991). A practical model for curriculum-based assessment and instruction in arithmetic. Teaching Exceptional Children, 24(1), 6–9. Galagan, J. (1985). Psychoeducational testing: Turn out the light the party’s over. Exceptional Children, 52, 288–299. Gordon, E. (1995). Toward an equitable system of educational assessment. The Journal of Negro Education, 64, 360–372. Graue, M., & Smith, S. (1996). Parents and mathematics education reform: Voicing the authority of assessment. Urban Education, 30, 395–421. Guernsey, M. A. (1990). Curriculum-based assessment and the regular classroom teacher. Illinois Schools Journal, 69(2), 15–19. Hintze, J., Shapiro, E., & Lutz, G. (1994). The effects of curriculum on the sensitivity of curriculum-based measurement in reading. Journal of Special Education, 28, 188–202. Howell, K., & Evans, D. (1995). A comment on ‘‘Must instructionally useful performance assessment be based in the curriculum?’’ Exceptional Children, 61, 394–396. Howell, K., & Morehead, M. (1987). Curriculum-based evaluation for special and remedial education. Columbus, OH: Charles E. Merrill. Hunt, N., & Marshall, K. (2006). Exceptional children and youth (4th ed.). New York: Houghton Mifflin Company. Idol, L., Nevin, A., & Paolucci-Whitcomb, P. (1999). Models of curriculum-based assessment. Rockville, MD: Aspen Publishers. Idol-Maestas, L. (1981). A teacher training model: The resource/consulting teacher. Behavioral Disorders, 16, 108–121. Individuals with Disabilities Education Improvement Act of 2004, 20 U.S.C. & 1400 et seq. (2004) (reauthorization of the Individuals with Disabilities Education Act of 1990). King-Sears, M. (1997). Best academic practices for inclusive classrooms. Focus on Exceptional Children, 29(7), 1–22.

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Kirk, S. M., Galloway, J. J., Anastasiow, N. J., & Coleman, M. R. (2006). Educating exceptional children (11th ed.). New York: Houghton Mifflin Company. Lewis, A. (1997). Changing assessment, changing curriculum. Education Digest, 62(7), 13–15. Marston, D., & Magnusson, D. (1985). Implementing curriculum-based assessment: Considerations for pupil appraisal professionals. Exceptional Children, 52, 266–276. Marston, D. B. (1989). A curriculum-based measurement approach to assessing academic performance: What it is and why we do it. In: M. R. Shinn (Ed.), Curriculum-based measurement: Assessing special children (pp. 18–78). New York: Guilford Press. Mathes, P., Fuchs, D., & Fuchs, L. (1995). Accommodating diversity through Peabody classwide peer tutoring. Intervention in School and Clinic, 31, 46–50. McLaughlin, J. A., & Lewis, R. B. (2001). Assessing students with special needs (5th ed.). Upper Saddle River, NJ: Prentice-Hall, Inc. Mehrens, W. A., & Clarizio, H. F. (1993). Curriculum-based measurement: Conceptual and psychometric considerations. Psychology in the Schools, 30, 241–254. Morison, P., White, S., & Feuer, M. (Eds). (1996). The use of IQ tests in special education decision making and planning. Washington, DC: Board on Testing and Assessment, National Research Council. (ERIC Document Reproduction Service No. ED393261.) Nelson, N. W. (1989). Curriculum-based language assessment and intervention. Language, Speech, and Hearing Services in Schools, 20(2), 170–184. No Child Left Behind Act of 2001, 20 U.S.C. 70 & 6301 et seq. (2002). Nolet, V., & McLaughlin, M. J. (2000). Accessing the general curriculum: Including students with disabilities in standards-based reform. Thousand Oaks, CA: Corwin Press. Norris, P., Fuchs, L., & Fuchs, D. (1994). Effects of classwide curriculum-based measurement and peer tutoring: A collaborative researcher-practitioner interview study. Journal of Learning Disabilities, 27, 420–434. Notari, A. R., & Drinkwater, S. S. (1991). Best practices for writing child outcomes: An evaluation of two methods. Topics in Early Childhood Special Education, 11(3), 92–106. Ortiz, A. A., & Wilkinson, C. Y. (1991). Assessment and intervention model for the bilingual exceptional student (AIM for the Best). Teacher Education and Special Education, 14, 35–42. Pallrand, G. (1996). The relationship of assessment to knowledge development in science education. Phi Deta Kappan, 78(4), 315–318. Parke, C., & Lane, S. (1996). Learning from performance assessments in math. Educational Leadership, 54(4), 26–29. Parker, D., & Picard, A. (1997). Portraits of Susie: Matching curriculum instruction, and assessment. Teaching Children Mathematics, 3(7), 376–377. Roberts, M., & Shapiro, E. (1996). Effects of instructional ratios on students’ reading performance in a regular education program. Journal of School Psychology, 34, 73–91. Russell, D. (1995). Collaborative portfolio assessment in the English secondary school system. The Clearing House, 68, 244–247. Rydell, L. (1990). The least biased assessment: Implications for special education (Crosscultural Special Education Series, Vol. 4). Sacramento, CA: Resources in Special Education. Seidenberg, P. L. (1986). Curriculum-based assessment procedures for secondary learning disabled students: Student centered and programmatic implications. Brooklyn, NY: Long Island University. Seidenberg, P. L. (1987). The unrealized potential: College preparation for secondary learning disabled students. A guide for secondary school administrators, faculty, and parents. Brooklyn, NY: Long Island University.

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Shinn, M. R., Powell-Smith, K., & Good, R. (1997). The effects of reintegration into general education reading insurrection for students with mild disabilities. Exceptional Children, 64, 59–79. Skakun, V. (1988). Integration-how can we make it work? In: D. Baine, D. Sobsey, L. Wilgosh & G. Kysela (Eds), Alternative futures for education of students with severe disabilities (pp. 30–42). Edmonton, Alberta, Canada: University of Alberta, Department of Educational Psychology. Smith, T. E., Palloway, E. A., Patton, J. R., & Dowdy, C. (2001). Teaching students with special needs in inclusive settings. Boston: Allyn and Bacon. Speece, D. L., Case, L. P., & Molloy, D. E. (2003). Responsiveness to general education instruction as the first gate to learning disabilities identification. Learning Disabilities Research & Practice, 18, 147–156. Stecker, P. M., & Fuchs, L. S. (2000). Effecting superior achievement using curriculum based measurement: The importance of individual progress monitoring. Learning Disabilities Research and Practice, 15, 128–134. Stoner, G., Carey, S., & Ikeda, M. (1994). The utility of curriculum-based measurement for evaluating the effects of methylphenidate on academic performance. Journal of Applied Behavior Analysis, 27, 101–113. Thompson, D., Beckmann, C., & Senk, S. (1997). Improving classroom tests as a means of improving assessment. Mathematics Teacher, 90(1), 58–64. Thousand, J. W., & Villa, R. A. (1990). Strategies for educating learners with severe disabilities within their local home schools and communities. Focus on Exceptional Children, 23(3), 1–24. Tindal, G., & Nolet, V. (1995). Curriculum-based measurement in middle and high schools: Critical thinking skills in content areas. Focus on Exceptional Children, 27, 1–22. Tucker, J. (1985). Curriculum-based assessment: A special issue. Exceptional Children, 52, 199–204. Umbreit, J. (1995). Functional assessment and intervention in a regular classroom setting for the disruptive behavior of a student with attention deficit hyperactivity disorders. Behavioral Disorders, 20(4), 267–278. Umbreit, J. (1996). Functional analysis of disruptive behavior in an inclusive classroom. Journal of Early Intervention, 20(1), 18–29. Van Zant, S., & Brown, S. (1997). Evaluating student success. Thrust for Educational Leadership, 26, 18–20. Wilcox, S., & Zielinski, R. (1997). Using the assessment of students’ learning to reshape teaching. Mathematics Teacher, 90(3), 223–227. Wixson, K., Peters, C., & Porter, S. (1996). The case for integrated standards in English language arts. Language Arts, 73(1), 20–30. Ysseldyke, J. E., Salvia, J., & Bolt, S. (2009). Assessment. Belmont, CA: Wadsworth Publishing Company.

PART IV LABELING AND CATEGORIZATION

CHAPTER 7 LABELING OF STUDENTS WITH DISABILITIES: NEEDED FOR STUDENTS TO GET THEIR NEEDS MET Gathogo M. Mukuria and Jeffrey P. Bakken DEBATE ON LABELS: PAST AND PRESENT Centuries ago labeling and classification of people was insignificant; survival was the major concern. Individuals with disabilities were prevented from full participation in activities necessary for survival, were left out on their own to perish, and, in some instances, were even killed (Berkson, 2004). In later years, derogatory labels such as imbecile, stupid, and retarded were used to describe individuals who did not conform to the societal norms. Clearly, regardless of the terms used, their function was geared to exclude people with disabilities from facilities, and activities enjoyed by people without disabilities. Unfortunately, this resulted in alienation, isolation, and institutionalization of individuals with disabilities (Hallahan, Kauffman, & Pullen, 2009). Labeling remains a controversial issue in special education (Norwich, 1999). In the past three decades, educators have been embroiled in a debate regarding pros and cons of labeling and categorization of students with disabilities (Hallahan et al., 2009). The proponents of labeling have suggested Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 101–114 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019010

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that labeling may communicate a child’s strengths and weaknesses, establish a diagnosis, suggest interventions, be used to raise financial support, and provide foundation for research on etiology and prevention (Ysseldyke & Algozzine, 1990). In addition, they posit that labeling is imbedded in the law, recognizes meaningful differences in learning, leads to a proactive response, provides common language for researchers and professionals, helps in fundraising for research and other programs, enables disability-specific advocacy to promote programs and spur legislative action, and helps make exceptional children’s needs more visible to policy makers members of public (Hallahan et al., 2009). The opponents of labeling argue that giving labels to children with disabilities should be stopped because it stigmatizes and impacts negatively on those children (Danforth & Rhodes, 1997; Gartner & Lipsky, 1989; Kliewer & Biklen, 1996; Reschly, 1996; Stainback & Stainback, 1986; Wang & Walberg, 1988). While proponents and opponents of labeling of individuals with disabilities voice differing opinions, some groups of people with disabilities dislike being too closely integrated into nondisabled society. For example, some people who are deaf, because of their difficulty in communicating with the hearing world, prefer associating with other people who are deaf. For them, normalization does not translate into integration into the larger community. Students who are deaf feel more socially and emotionally secure if they have other students who are deaf with whom they can communicate (Stinson & Whitmire, 1992, 2000). For them, they consider deafness to be a distinct culture of the American society that needs to be respected. Although the pros and cons of using disability labels have been widely debated for several years, conceptual argument and research findings from either side on the effects of labeling have produced inconclusive and often contradictory results due to methodological weakness (Mostert, 1991; Weisel & Tur-Kaspa, 2002). This should not be surprising because each side looks at the labeling through different lenses which clouds judgment, research, and opinions. Consequently, each side advocates its own agenda based on personal bias and philosophy rather than science.

LABELING CATEGORIZATION IS EMBEDDED IN THE LAW In the United States, special education and the law are intertwined in an intricate way and cannot be separated. Right from its conception, special

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education as a discipline has been shaped and influenced by the legal process (Turnbull, Stowe, & Huerta, 2007). The current gains, including educating students with disabilities in inclusive settings, have been won through legal battles. In 1975, the Education of All Handicapped Children’s Act (P.L. 94-142) was passed with the following fundamental ingredients: (a) education for students from 3 to 21 years of age, (b) free and appropriate public education, (c) identification of students, (d) nondiscriminatory assessments, (e) placement in the least restrictive environment (LRE), (f) confidentiality of information, (g) due process procedural safeguards, and (h) development of Individualized Education Program (IEP). In 1986, P.L. 94-142 was amended to accommodate young children from birth to 3 years of age. This law was enacted to provide not just IEPs for children but also Individual Family Support Plans (IFSP) for parents and guardians in accordance to P.L. 99-457 that focuses on intervention in early childhood. In 1990, P.L. 94-142 was renamed as the Individuals with Disabilities Education Act (IDEA; P.L.101-476). IDEA involved funding for states to provide educational services to students from birth to 21 years of age and ensured procedural safeguards that guarantee meaningful participation in the evaluation process for parents (Heward, 2006). Clearly, labeling is stipulated under the current law as a critical ingredient for eligibility for special education services, and it cannot be evaded for practical purposes. A student must be identified as having a disability and, in most cases, be further classified in one of the state’s categories, such as learning disabilities or emotional behavior disorders (McLaughlin & Lewis, 2008) to be eligible for special education services. Therefore, it is imperative to realize that a student becomes eligible for special education services because of being a member of a given category. Labeling becomes inevitable because it is the only way through which educators, states, service providers, and local agencies can know the students for whom they have to provide services. The only exception IDEA makes is for children of aged 3–7 years who are identified as developmentally delayed and receive special education services without the use of a specific disability label being attached.

LABELING AS A NECESSARY STEP IN RESPONDING RESPONSIBLY TO DIFFERENCES Inevitably, labeling recognizes meaningful differences in learning or behavior and is a first and necessary step in responding responsibly to individual

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differences. While universal interventions can be applied to all learners, labels are critical because they enable educators to adequately address specific needs of individual children. In other words, instruction comes after labels have been assigned. It would be practically impossible for teachers to help an individual student unless he/she first knows and clearly understands the kind of problems that the student exhibits. Labeling should be assigned professionally, cautiously, and with common sense so that it does not become an end to itself. If labels have erroneously been attached to a certain category, instruction and placement that will follow cannot be correct. This means that the individual can never maximize his or her highest potential (Mukuria & Obiakor, 2004). Refusal to recognize an individual student’s disability by avoiding labeling is a denial of the student’s limitations (Mostert, 1991). A problem does not disappear simply because people refrain to address or talk about it! The truth of the matter is that even before children with disabilities are officially labeled, their peers and community members notice those differences. It is erroneous and misleading to assume that if children with disabilities are not labeled, they would behave and be treated differently by their peers, teachers and the community at large, as well as by their counterparts without disabilities. Differences are observed and categorized informally even before children start school. On the contrary, if the category of the disability could be ascertained early, professionals could recognize meaningful behavior and are more likely to act responsibly to those differences. Labeling a problem is the first step in dealing with it productively (Kauffman, 1990). Inevitably, parents of students with disabilities are deeply concerned to know and understand the condition of their child. Logically, when one is aware of the problem, it is easier to learn how to cope or deal with it. The argument that labeling students with disabilities will stigmatize them and have other negative impacts is a pretence that disabilities are make-believe, a figment of others imaginations, and of little consequences in educational and learning settings (Mostert, 1991). This notion is indeed far from reality (Mostert, 1991).

UNDERSTANDING PARENTS’ PSYCHOLOGICAL AND EMOTIONAL STRESS It is critical for professionals to understand the emotional and psychological stress parents of children who have disabilities go through (Ferguson, 2003). Many parents have great concern and anxiety to know the disability of their

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child. Studies conducted on the emotional responses and adjustments of parents after the realization that their child has disabilities indicate that there is symbolic death of the child that was to be (e.g., Blacher, 2001; Ferguson, 2003; Frey, Fewell, & Vadasy, 1989). This research has indicated that most parents go through an adjustment process that may include anger, sadness, and bitterness as they work through their emotions. Some parents go from one professional to another trying to find out the condition of their child. Eventually, when they ascertain the category of the disability of their child, hard as it may be to accept, they seem to adjust to face the inevitable. They seem to find relief when they learn the exactness of the disability of their child and eventually learn to adjust to the situation. Knowing the label of the condition is crucial and seems to bring relief for many parents (Hallahan et al., 2009). It is common knowledge that physicians cannot prescribe medication to a patient until they have diagnosed a problem. In the same way, unless a teacher knows the problem he/she is dealing with, it is impossible to know how to address it. It is imperative to first identify and categorize the problem the child is experiencing before devising a way of dealing with it. Labeling is essential before any other steps are taken. Professionals should refrain from being drifted into rhetoric of political correctness and refrain from being swayed by the public but instead perform their work professionally and avoid unnecessary labels. What are critical are not the labels assigned to individuals but what we do with them. Moreover, in real life, we use labels all the time. For example, in schools, students are categorized in grades, first, second, third, and fourth. Teachers are assigned to each grade, and whether we like it or not, instructions for each grade are differentiated in one way or another. During teacher preparation, students are prepared to teach in specialized areas at different grade levels. We contend that labels are inevitable in real life and cannot be perceived as if they are only restricted to students with disabilities. For example, at high school and college levels, instructors specialize in certain areas of their disciplines and are commonly labeled according to the subject they teach. For instance, Mr. Smith the mathematics teacher, or Mrs. Joe the biology teacher. It would be uncharacteristic for a biology teacher to effectively teach history or geography. Interestingly, even students in their grades understand their limitations. For instance, a third grader is aware that there are some chores or tasks that are beyond his or her limitations until later in life. Evidently, labeling has been assigned on what students in each grade can do or what each individual child can accomplish in each stage of their developmental milestones.

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Some educators believe that labeling is used to identify exceptional children and stigmatize and deny them the opportunity for inclusion (Kauffman, 1999) and that reducing the stigma associated with the disability requires honest recognition of the condition by using ‘‘a less stigmatizing term’’ that minimizes and deviates the individual’s situation and needs for supports. This is blatant denial that is far from reality (Kauffman, 2003).

LABELS ARE NECESSARY FOR SELF-APPRECIATION It is critical for individuals to understand themselves. All people should appreciate who they are. It is the understanding of an individual’s strengths and weaknesses that enable people to set high but realistic goals. We do not want individuals to live in a world of self-hate but instead want them to know and understand their strengths and limitations. Labeling may help students with disabilities understand themselves and recognize that there are individuals out there who are like themselves. That realization does not only remove them from isolation but may help them get some consolation, create a better self-image, help them appreciate themselves, and develop better selfesteem. The argument that individuals with disabilities will not know that they are different if they are not labeled or categorized does not hold water. Clearly, to call a ‘‘broken bone broken’’ does not widen a fracture. As was mentioned earlier, children begin to know their gender differences even before they begin kindergarten. Students with disabilities begin to realize that they are different and have limitations early in life. Their nondisabled counterparts know it as well.

LABELING AS A PROTECTIVE RESPONSE THAT MAY LEAD TO ACCEPTANCE It is important to realize that people cannot live in a world of hate. People need to know what and who they are to appreciate themselves and develop a good self-concept. People need to know who they are before they reach their highest potential. Individuals need to know what they can and cannot do. That realization is critical in assisting individuals to develop personal goals, self-evaluation, and a sense of personal worth. The purpose of an IEP is to help individual students maximize their highest potential. Understanding

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what an individual can or cannot achieve enables one to gain self-knowledge that enhances confidence. Professionals should also realize that people with disabilities need affiliation with others who go through similar experiences and interests (Hall, 2002). Individuals with the same labels can have much in common and may find strength and consolation by sharing the common challenges they encounter daily. Sharing common experiences and challenges these students encounter daily helps them realize that they are not alone in their struggles and provides them some consolation that they are not alone in their struggles. In addition, labeling may lead to a protective response in which adults and children without disabilities become more accepting of atypical behavior of an individual with disabilities than a child without a disability who exhibits the same behavior.

LABELING HELPS PROFESSIONALS AND RESEARCHERS COMMUNICATE MORE EFFECTIVELY Special education is a multifaceted discipline and communication is critical when professionals from different disciplines work together. Labeling enhances common language for professionals and researchers by minimizing confusion regarding terminology. This is imperative because different disciplines may have different labels and terminologies, and unless professionals come to consensus on labels acceptable to all, confusion may ensue. Special education is a dynamic field in which new disorders materialize frequently. Therefore, the field is constantly involved in identifying etiology and treatment solutions for these new disorders. Such an undertaking requires a common language of communicating to ease any confusion. Labeling provides a common language, fosters clarity and understanding, and offers an avenue of communication through the use of shared language and concepts which allows professionals and researchers to work harmoniously and efficiently (Lauchlan & Boyle, 2007).

LABELS ARE NECESSARY FOR FUNDING Labels are critical for raising funds for special education programs and research. These funds enable special educators, researchers, and related professionals to keep track of information about emerging and known

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categories of disabilities. This information is critical for planning education, treatment, and research endeavors at national, state, and local levels. While the federal government does not directly get involved in educational, treatment, and research matters related to individuals with disabilities directly, it does so indirectly through the provision of categorical monetary grants (Turnbull et al., 2007). When grants are given to state and local governmental agencies and private organizations, the federal government requires an accounting of the funds distributed by specific disability categories. Therefore, labeling and categorization of disabilities become inevitable in this endeavor. Financial resources are critical in special education for starting new programs and also for research. Inevitably, funding and resources for research in institutions of higher education and other programs are often based on specific categories of exceptionality. It would be impossible for the fund-raisers to look for money without having a specific label or category in mind making labels very necessary. It is naı¨ ve to assume that labeling is bad by itself. What is bad is what is done with those labels. When labels are used to ostracize, discriminate, and deny deserving students the necessary services they need to succeed, it will foster failure. However, if labels are used to provide services and instruction to correctly identify a student’s disability category, then the use of labels is validated. Clearly, labeling by itself is not bad. What is evil is how labels may be used. It is well known that medicine has revolutionized our lives by curing diseases that previously killed many people. We cannot say that medicine is bad because some people misuse it. The truth of the matter is that the invention of medicine has saved many lives that could have perished many years ago! Anything good can be subject to abuse! In the same vein, labels are not bad; it is how they are used that may be either good or bad.

LABELS CAN ASSIST ADVOCACY GROUPS Individuals and ideas have played critical roles in shaping the history of special education. Much of the progress that has been made over the years in special education has been achieved primarily by the collective efforts of parents and professionals. Since the inception of special education, parent organizations have played pivotal roles in furthering the progressive education and treatment of individuals with disabilities. A good example is what happened in 1972 in the class action case Pennsylvania Association for the Retarded Children (PARC) v. Commonwealth of Pennsylvania. In this case, the parents of children with mental retardation brought suit

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against the state of Pennsylvania because they could no longer accept the status quo of schools excluding their sons/daughters with intellectual disabilities from certain programs. The court ruled in favor of the parents (Heward, 2006). Parents’ organizations have typically served three functions: (1) providing informal groups for parents to discuss common problems and needs and help one another to deal with anxiety and frustrations; (2) disseminating information pertinent and potential services for their children; and (3) providing the structure for obtaining salient services for their children. Organizations such as The Learning Disabilities Association, The Autism Society of America, and The Association for Retarded Citizens are a few examples that came about as a result of parents’ efforts. The passage of P.L. 94-142 reveals what can be achieved when citizens and parents of children with disabilities unite for a common purpose, namely, the public education for all handicapped children. The history of special education litigation and legislation demonstrates emphatically how parents with disabilities, special education professionals, and concerned citizens working together can improve the quality of education and treatment of children with disabilities. Parent and professional advocacy groups are formidable forces for pressing federal and state governments to give more funds programs for children with special education needs. Success of advocacy groups is enhanced when individuals with disabilities are advocates for themselves. There can never be a stronger force than when people with disabilities speak for themselves. Labeling is important for enabling disability-specific advocacy groups to promote specific programs and spur legislative action. This is critical because from the inception of special education, advocacy groups have played a critical role in furthering the course of special education.

ASSESSMENT IN SPECIAL EDUCATION Assessment in special education is a multifaceted process that takes place in a number of contexts and serves a number of purposes (Obiakor, 2001). It refers to the systematic process of gathering educationally relevant information for legal and instructional decisions (McLaughlin & Lewis, 2008). In the past four decades, educators have decried the disproportionate overrepresentation of minority students in special education programs (Artiles & Trent, 1994; Hallahan et al., 2009) and have stressed that assessment may be partially responsible for this overrepresentation (Obiakor & Schwenn, 1996). For example, there is a plethora of evidence to show that

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traditional assessment processes are biased against students from culturally and linguistically diverse backgrounds (Obiakor & Schwenn, 1996). There is a popular African adage that ‘‘one does not start to climb a tree from the top but from the bottom.’’ A logical extension is that the critical steps of identification of students greatly influence how special education is practiced and perceived in schools. Ideally, when identification and referral are poorly and prejudicially done, the other processes of assessment, categorization, labeling, placement, and instruction usually produce prejudicial results (Mukuria & Obiakor, 2004). To curtail inappropriate referrals, many schools have now implemented Response to Intervention (RTI) (Fuchs & Fuchs, 2006). Through RTI, teachers try to meet all student needs in the general education classroom. When a student is not learning like other students, the classroom teacher may seek assistance from an RTI team. This team helps the teacher make a data-based decision on what intervention to incorporate in her classroom to help the student having difficulty. During this helping phase, the classroom teacher collects data to see if the intervention is effective or whether a more restrictive process is needed. If he/she does, the student receives additional small group instruction with different evidence-based strategies. Throughout this period, the classroom teacher collects performance data that is communicated to the RTI team. If the student does not progress with the small group instruction, one-to-one instruction is implemented. When a student does not progress with one-toone instruction, he/she is referred to special education for a multidisciplinary evaluation that entails the administration of a comprehensive battery of formal and informal assessments. This team would then collect assessment data for the purpose of deciding if the student is eligible for special education services and which services would be most appropriate for this particular learner. If she/he is eligible, then the IEP is initiated. The multidisciplinary team is then responsible for making recommendations regarding services on the IEP (Lerner & Beverly, 2009). Although the law mandates that assessment be administered to ensure individuals with special needs receive free appropriate education, cases of miscategorization are not unusual (McLaughlin & Lewis, 2008; Mukuria & Obiakor, 2004; Obiakor, 2001). For example, African Americans and other children from culturally and linguistically diverse backgrounds are often inappropriately placed in restrictive services (Artiles & Trent, 1994). Furthermore, African Americans have been and continue to be disproportionately overrepresented in classes for students with behavioral and emotional disorders and also in programs for individuals with intellectual disabilities. When that happens, inevitably, their educational needs cannot

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be met. It is therefore imperative for the evaluation and assessment processes to be administered carefully and professionally so that unwarranted placements do not become the end product. Incorrect identification of learners leads to improper placement, which may impair service providers’ effectiveness due to the incongruity between the student’s educational needs and their placement.

MINIMIZING UNWARRANTED LABELS CATEGORIZATION As was mentioned earlier, labels cannot be separated from the assessment process. Proper identification, referral, and assessment are all critical ingredients of good instruction and intervention. In other words, if identification, referral, and assessment are not completed properly, they may lead to incorrect labeling, inevitably resulting in misplacement and impacting the provision and intervention. Clearly, there is a ripple effect in the whole process if one step in not administered properly. Erroneous misidentification leads to miscategorization, misplacement, and misinstruction (Obiakor, 2001; Obiakor & Utley, 2004). For example, if a student with autism is categorized and placed in a classroom for students with learning disabilities, he/she cannot maximize his/her potential because his/her educational needs cannot be met in that environment. The goal of special education is to tailor instruction to meet the needs of an individual student. The content, the pace of instruction, and the environment must be modified to meet the unique need of the student. This cannot be attained unless labeling and the entire assessment are done correctly. It is important for all professionals involved in the assessment process to work with ultimate care to avoid unwarranted identification, categories, and labels. In addition, they should be given training on multicultural issues to minimize the overrepresentation of minorities in special education programs. Special education is a multidisciplinary discipline where professionals from different academic preparations work together. For them to work harmoniously, collaboration, consultation, and cooperation are critical. More importantly, mutual respect, trust, openness, and proper communication must be established. In addition, professional jealousy, superiority complexes, and discipline rivalry must be set aside. Just putting professionals from different disciplines together does not guarantee that they will work together effectively. Training professionals on communication and sharing of

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information is essential. In addition, training them on how to use multiple assessment tools especially on assessing students from diverse background would greatly enhance their work and lead to minimizing overrepresentation of students from culturally, linguistically, and ethnically diverse background in special education programs (Obiakor & Utley, 2004).

CONCLUSION While the debate on labeling continues, the positive benefits of labels outweigh the negative impact they may have on children with disabilities. The use of labels in special education is justified because of the educational, research, monetary funding and personal benefits labels it provides as well as federal law that requires it. Anything can be used for good or for evil depending on how it is used and for what purpose. The argument that professionals should try to use more favorable terms so as to minimize stigmatization of students with disabilities does not take the disability away. What is true is that labels, like anything else, can be misused. Greater emphasis should be placed on training assessors so that unwarranted labels and categories are not assigned to students. In addition, rather than spending time debating minor categorization, professionals should focus on developing valid and reliable multidimensional assessment tools. Labeling is critical for helping professionals and researchers communicate more effectively through the use of a common language. In addition, labeling is critical for fund-raisers. It is imperative for lobbyists to have a specific label when approaching congress and other organizations in an attempt to raise awareness and grant funds for individuals in a particular category. Lastly, labeling helps students with disabilities to understand and appreciate themselves. Ideally, all people appreciate who they are. It is the understanding of an individual’s strengths and weaknesses that enable people to set high but realistic goals, develop better self-esteem, and build selfconfidence. Overall, labeling is a good idea when used responsibly and solely to the benefit of the child’s education. Clearly, the benefits of labeling outweigh the negative effects.

REFERENCES Artiles, A. J., & Trent, S. C. (1994). Over representation of minority students in special education: A continuing debate. Journal of Special Education, 27(4), 410–428.

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Berkson, G. (2004). Intellectual and physical disabilities in prehistory and early civilization. Mental Retardation, 42, 195–208. Blacher, J. (2001). Transition to adulthood: Mental retardation, families, and culture. American Journal of Mental Retardation, 106, 173–188. Danforth, S., & Rhodes, W. C. (1997). On what basis hope? Modern progress and postmodern possibilities. Remedial and Special Education, 25, 357–366. Ferguson, P. M. (2003). A place in family: A historical interpretation of research on parental reaction to having a child with a disability. Journal of Special Education, 36, 124–130. Frey, S. K., Fewell, R. R., & Vadasy, P. F. (1989). Parental adjustment and changes in child outcomes among families of young handicapped children. Topics in Early Childhood Special Education, 8(4), 38–57. Fuchs, L., & Fuchs, D. (2006). Identifying learning disabilities with RTI: Perspectives. The International Dyslexia Association, 32(1), 39–43. Gartner, A. L., & Lipsky, D. K. (1989). Beyond special education: Toward quality system for all students. Harvard Educational Review, 57, 305–326. Hall, J. P. (2002). Narrowing the breach: Can disability culture and full inclusion be reconciled? Journal of Disability Policy Studies, 13, 144–152. Hallahan, D. P., Kauffman, J. M., & Pullen, P. C. (2009). Exceptional learners (7th ed.). Boston: Pearson. Heward, W. L. (2006). Exceptional children: An introduction to special education (8th ed.). Upper Saddle River, NJ: Merrill/Prentice Hall. Kauffman, J. M. (1990). Special education and process of change: Victim of master of education reform? Exceptional Children, 57(2), 109–115. Kauffman, J. M. (1999). How to prevent the prevention of emotional and behavior disorders. Behavioral Disorders, 65, 448–468. Kauffman, J. M. (2003). Appearance, stigma, appearance and prevention. Remedial and Special Education, 24, 195–198. Kliewer, C., & Biklen, D. (1996). Labeling who wants to be retarded? In: W. Stainback & S. Stainback (Eds), Conversational issues confronting special education: Divergent prospective (pp. 83–95). Boston: Allyn & Bacon. Lauchlan, F., & Boyle, C. (2007). Is the use of labels in special education useful? Support for Learning, 22(1), 36–42. Lerner, J., & Beverly, J. (2009). Learning disabilities and related mild disabilities. Boston: Houghton Mifflin Company. McLaughlin, J. A., & Lewis, R. R. (2008). Assessing students with special needs (7th ed.). Upper Saddle River, NJ: Merrill/Prentice Hall. Mostert, M. P. (1991). The regular education initiative: Strategy for teaching handicap and the perpetuation of differences. Disability, Handicap & Society, 6(2), 91–101. Mukuria, G., & Obiakor, F. (2004). Special education issues and the African diaspora. Journal of International Special Needs Education, 7, 12–17. Norwich, B. (1999). The connotation of special education labels for professionals in the field. British Journal of Special Education, 26(4), 179–183. Obiakor, F. (2001). It even happens in good schools: Responding to cultural diversity today’s classrooms. Thousand Oaks, CA: Corwin Press. Obiakor, F. E., & Schwenn, J. O. (1996). Assessment of culturally diverse students with behavioral disorders. In: A. F. Rotatori, J. O. Schwenn & S. Burkhardt (Eds), Issues, practices and concerns in special education (pp. 37–57). Greenwich, CT: JAI Press.

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Obiakor, F. E., & Utley, C. A. (2004). Creating successful learning environments for African American learners with exceptionalities. Thousand Oaks, CA: Corwin Press. Reschly, D. J. (1996). Identification and assessment of students with disabilities. Future of Children, 6(1), 53–60. Stainback, W., & Stainback, S. (1986). A rationale for the merger of special and regular education. Exceptional Children, 52, 102–111. Stinson, M., & Whitmire, K. (2000). Adolescents who are deaf or hard of hearing: A communication perspective on educational placement. Topics in Language Disorders, 20(2), 58–72. Stinson, M. S., & Whitmire, K. (1992). Students’ views of their social relationships. In: T. N. Kluwin, D. F. Moors & M. G. Gaustad (Eds), Towards effective public school programs for deaf students: Context, process and outcomes (pp. 149–174). New York: Teachers College Press. Turnbull, H. R., Stowe, M., & Huerta, N. E. (2007). Free appropriate public education: The law and the children with disabilities (7th ed.). Denver, CO: Love Publishing Company. Wang, M. C., & Walberg, H. J. (1988). Four fallacies of segregations. Exceptional Children, 55, 128–137. Weisel, A., & Tur-Kaspa, N. (2002). Effects of labels and personal contact on teacher’s attitude towards students with disabilities. Exceptionality, 10, 1–10. Ysseldyke, J. E., & Algozzine, B. (1990). Introduction to special education (2nd ed.). Boston: Houghton Mifflin.

CHAPTER 8 LABELING OF STUDENTS WITH DISABILITIES: UNWANTED AND NOT NEEDED Craig Blum and Jeffrey P. Bakken Labeling of things and people has been around for centuries. It is a way to categorize things by similarities or differences (e.g., large, expensive, and valuable), a way to highlight status (e.g., upper class, middle class, and lower class), and a way to categorize for a specific reason of providing services or guidance (e.g., learning disability [LD], gifted, and autistic). Labels are ways people have of thinking of others and can help them comprehend certain qualities and help in their communication with each other. More specifically, labeling of students with disabilities by category is necessary to provide the financial resources needed for special programs and related services (Cullinan, 2004). In the United States, federal funds are only provided to public schools when a student’s particular disability has been identified. Therefore, if there were no categories for students with disabilities, there would be a lack of funding for programs to help them. The use of disability labels, however, by professionals in various fields associated with special education and rehabilitation highlight an individual’s supposed weaknesses, or assumed defects. These labels are often associated with what students cannot do and the negative versus what they can do and the positive. Often, this hides the complexity and uniqueness of the person labeled (Kliewer & Biklen, 1996). Assignment of a label plays a major role in

Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 115–125 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019011

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decisions to intervene and can profoundly shape a person’s future. People associate strong images with specific diagnostic labels and tend to act upon these images. For example, if a student is identified as having LD, the teacher would immediately know that the student needed some type of academic supports to be successful. They also might treat the student in a certain way because of the labels they have. Sometimes the labels are useful generalizations; sometimes they are harmful stereotypes. Because of the potential harm caused by diagnostic classifications, the practice of labeling individuals with disabilities is widely criticized (Gallagher, 1955; Higgins, Raskind, Goldberg, & Herman, 2002; Szasz, 1960). Those who study diagnostic classifications are especially concerned about the role labeling plays in segregating individuals with physical, cognitive, social, and emotional differences – including a disproportionate number from ethnically diverse groups (Adelman, 1996). The point we need to make very clear is that disability labels are ideas not facts. When we create or construct them, we do so within particular cultural contexts. That is, someone observes particular behaviors or how people act and respond and then describes these as a classification with a label. The problems with being labeled have to do with the place of disability within the culture. Typically, a disability label is not a neutral term. In most cultures, it is not a valued status and often looked upon negatively. Disability labels have developed and transformed from being a benefit to help individuals with disabilities to being used for stereotyping and discriminating against them (Kliewer & Biklen, 1996). A disability label applied to an individual can have a profound effect on how we understand that person. Although we may recognize people without disabilities as complex and multifaceted, labeling persons as disabled becomes central to our understanding of who they are and predetermines how we think they may perform. For instance, instead of understanding someone with a behavior disorder (BD) as having varied interests and passions, strengths and areas of proficiency and being capable of success, we may dismiss and ignore these qualities and view the person with BD in terms of negative stereotypes and social roles associated with a BD label (Lemay, 2006; Wolfensberger, 2000). Unfortunately, people with disabilities sometimes find themselves excluded from activities due to their disability label (Lauchlan & Boyle, 2007). For example, a student with a writing LD may be excluded from an academic project or activity (e.g., serving on the high school newspaper) because it is perceived by others that he/she is not competent enough to be successful in writing an article about the recent governance student election. In reality, the student does not even get the opportunity to attempt the

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activity even though he/she may be fully competent and have the necessary skills to write such an article. Labels also block the essential agenda of good teaching, namely inquiry through dialogue and interaction between the teacher and the student (Kliewer & Biklen, 1996). If teachers have preconceived notions of what disability-labeled students can and cannot do, they may not involve them in typical classroom activities like students without such labels. Assigning a disability label to a student also raises the concern about negative consequences (e.g., harmful stereotyping and stigmatization, undermining self-esteem, generating negative expectations, misidentification, and misprescription) (Adelman, 1996). It is a common knowledge that stereotypes are often embedded deep in our culture and have a tremendous influence over how we react to stereotyped people (Kliewer & Biklen, 1996). Unfortunately, negative stereotypes (e.g., impulsive, self-centered, paranoid) associated with a student’s disability label can adversely impact how a teacher interacts with that student label. The teacher’s adverse reaction may cause other students to react in a similar manner. This occurs because teachers are modeling appropriate and inappropriate behaviors every day in their classroom. Therefore, if teachers treat students with disabilities differently and provide them less access and opportunities, other students in the class may learn to treat and interact with these students in the same way. Other disadvantages of disability labeling appear in Table 1. We also know that disability label is always permanent. Personal experience as well as research studies, theoretical commentaries, and definition manuals suggests that the very definitions of disabilities are always in flux, constantly being redefined or modified, and certainly not static, objective, natural, or a given (Lauchlan & Boyle, 2007). For example, over time, the term mental retardation (MR) has come to be considered something real within our culture. This occurred after the term was applied to real people, defined as describing particular characteristics and behavior identified through testing, and addressed in state and federal laws. Yet, even though MR is thought to be real, the term MR keeps changing over time. For instance, the term MR has been redefined in every decade since its creation (Kliewer & Biklen, 1996). Typically, the redefining of the term MR has been in response to educational and societal changes in ideas about education, learning, development, testing bias, and negative social consequences of disability labeling (Kliewer & Biklen, 1996). Despite constant redefining and inconstancies in disability labels, people often come to believe that disability labels are true. When society members believe disability labels to be true, such labels can result in unintended

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Table 1. Disadvantages of Labeling. 1. Labels inform teachers and shape their expectations. On the basis of a label, a teacher may have different expectation of what the student can and cannot do before they even meet. Studies on teacher expectations have demonstrated that what teachers believe about student capability is directly related to student achievement. 2. All children have some difficulties and challenges regarding behavior. Labels can exaggerate a student’s actions in the eyes of a teacher, and they may overreact to behavior of a child who is labeled that would be tolerated in another. 3. Labels send a clear message that students have something wrong with them (the learning problem is student-centered). Labels can influence instruction and obscure the essence of teaching and learning as a transactional process (a back and forth process between teacher and student). 4. Labels perpetuate the notion that students with mild disabilities are qualitatively different from other children that are not labeled. This is a fallacy as students with mild disabilities go through the same developmental stages as their peers, although sometimes at a slower rate. 5. Teachers may confuse the student with the label. Labels reflect categories of disabilities, and categories are abstract concepts that are general enough to incorporate many different individuals. When a student is placed in a category, a teacher who knows some of the characteristics of a category may attribute all known characteristics to each labeled child. This is stereotyping and can harm students when teachers rationalize low achievement by citing characteristics of the label. 6. Students, under law, cannot receive special education services until they are labeled. In many instances, by the time there is an intervention implemented valuable time is lost. The need to label students before help arrives undermines the teaching oath of educating all learners to the best extent possible. 7. Diagnostic labels are unreliable, and the educational evaluation process is filled with many little differences. Many states use different descriptive criteria for the same categories. 8. Labels often inadvertently blame the parents for the student’s problems. Source: Adapted from Henley, Ramsey, and Algozzine (2009, para 1–8).

negative consequences for persons with disabilities. Some scholars have observed that labels legitimize oppression and the isolation of individuals with disabilities (Cockerham, 2002; Szasz, 1960), whereas others (Pfuhl, 1980) have identified the harsh social consequences of labeling that lead to individuals with disability being marginalized and/or identified as deviants. Even when educational disability labels are meant to be transient markers so that remedial services can be delivered, the label can often endure, fostering prejudices of peers and adults in and out of school. For example, students with BD do not care for their label and experience lower educational and behavioral expectations by teachers and parents (Cullinan, 2004). Because of these lowered expectation, the BD label becomes a self-fulfilling prophecy for these students to engage in antisocial behavior and poor academic

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achievement. A similar affect of labels on teacher expectations for students with LD and MR is reported in the literature (Rolison & Medway, 1985).

PROBLEMS WITH LEGAL LABELS AND TRADITIONAL ELIGIBILITY To identify a student with LD, many school districts use a discrepancy model of achievement and cognition model (Mercer, Jordan, Allsop, & Mercer, 1996). Using this model, a school psychologist administers intelligence and achievement tests to see whether a large score discrepancy exists between the two. When a large score discrepancy occurs, the student is diagnosed as having an LD (this is true only when other possibilities have been ruled out). Although well intended, this model has had several flaws and has lead to a 200% increase in the incidence of LD (Vaughn, LinanThompson, & Hickman, 2003). Also, this model does not consider whether remedial instructional strategies appropriate for children at-risk for LD were employed. Furthermore, even if a child at-risk for LD was receiving remedial instruction, there is no mechanism to determine whether that instruction was appropriate. Last, rather than preventing learning problems, the discrepancy approach leads to a ‘‘wait-to-fail’’ school culture that encourages an ill-guided attempt to insure students receive services (Berkely, Bender, Peaster, & Saunders, 2009). Similar problems have been identified in the labeling and eligibility requirements of students with emotional disturbance (ED). According to the Individuals with Disabilities Education Improvement Act (IDEIA, 2004), a student must meet the following eligibility criteria, which specify that one or more of the following student characteristics need to be present and affect educational performance adversely over an extended period of time for a student to be labeled ED: ‘‘(1) Criteria A – An in ability to learn that cannot be explained by intellectual, sensory, or health factors, (2) Criteria B – An inability to build or maintain satisfactory interpersonal relationships with peers and teachers, (3) Criteria C – Inappropriate types of behavior or feelings under normal circumstances, (4) Criteria D – A general pervasive mood of unhappiness or depression, (5) Criteria E – A tendency to develop physical symptoms or fears associated with personal or school problems’’ [Code of Federal Regulation, Title 34, Section 300.7(c)(4)(ii)]. However, ‘‘socially maladjusted’’ children (e.g., children who do not act within society’s norms) and conduct disordered children are excluded from eligibility because such children have behavior that is not considered a disability under the law.

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There is no evidence to suggest that this is scientific or accurate assertion and appears to be more of a policy of convenience rather than a policy designed to help meet the mental and behavioral health needs of socially maladjusted and conduct disordered children and adolescents in schools today (Gresham, 2006). Finally, Gresham (2006) further points out that the ED definition itself is problematic due to the contradictions and tautological confounds contained in the definition as listed below: (a) (b) (c) (d) (e)

Criterion A could apply to specific LD as well. Criterion B implies that social skill deficits are central. Criteria C and D emphasize internalizing disorders. Criterion E implies that externalizing disorders cannot be excluded. Criterion B is in contradiction to the social maladjustment exclusion because an inability to build or maintain satisfactory interpersonal relationships with peers and teachers is a form of ‘‘social maladjustment.’’

This illustrates an inane and confusing eligibility and labeling system, which results in a chaotic application of the IDEIA, which may result in the under or over serving of children with ED who it is intended to help. Unfortunately, disability labels often are designed to serve the interest of those who do not have them rather than support the individuals who do. For example, it is more expedient and viewed as cheaper to label some individuals with ED as criminals rather than labeled ED because it is easier for our society to use current mechanisms, such as prison and juvenile detention centers to support them rather than build new specially designed educational systems. In essence, disability labeling relies on a system of classification that justifies treating the individual as an object that can be sorted into an existing social system. Furthermore, in educational disability labeling, we wait until the underlying educational challenge is so severe that we can justify exclusion from the broader educational process, while providing limited prevention or early intervention. Hence, the disability label itself often gets in the way of the most effective educational practice.

RESPONSE TO INTERVENTION AS AN EDUCATIONAL APPROACH TO ELIGIBILITY Although new to most educators and families of children with disabilities, response to intervention (RtI) models have been around since the 1960s and

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1970s (Berkely et al., 2009). RtI evolved to address concerns that families, educators, and policy makers had with the identification of children with LD and BD (Bender & Shores, 2007). More specifically, RtI was designed to deal with over- and under-representation issues by re-centering eligibility and identification aspects to a core set of educational practices that are scientifically based. Although models vary, the RtI components that have emerged across a number for RtI approaches (Bradely, Danielson, & Doolittle, 2007; Fuchs & Fuchs, 2007; Mellard & Johnson, 2008; Shores & Chester, 2009) include the following: (a) Use of scientifically based intervention(s) matched to student need. (b) Continuous progress monitoring that is systematically collected and monitored. (c) Adequate opportunity for students to respond to intervention. (d) Monitoring of instructional fidelity to insure quality and interventions are provided as intended. (e) Prevention focus and use of a problem-solving model. (f ) Use of a prevention logic model (Fig. 1): if a student fails to respond to the core intervention (i.e., universal intervention), a more intensive intervention is applied (i.e., secondary intervention), and if a student fails to respond to the secondary prevention the most intensive intervention is applied (i.e., tertiary prevention). These components have conceptual validity and some technical adequacy that support their use when compared to the discrepancy model of achievement and cognition (Ardoin, Witt, Connell, & Koeing, 2005; Burns, Appleton, & Stehouwer, 2005; Mellard & Johnson, 2008; VanDerHeyden, Witt, & Barnette, 2005). Rather than having a ‘‘refer-test-place’’ model that is often irrelevant to the actual practice of teaching, RtI uses instruction in context to obtain treatment validity. Treatment validity is both a powerful concept and central to any RtI model’s success. Using treatment validity as a unifying construct for eligibility in special education means that a student is not only measured against their peers, but also their rate of educational growth in the context of instruction (Fuchs, Fuchs, & Speece, 2002). The discrepancy of both growth rate and level is referred to as a ‘‘dual discrepancy’’ model. In other words, to be identified for special education students must fail to respond to intervention. Fuchs et al. (2002) have outlined a four-phase model to establish special education eligibility. Phase I: Assessment is used to determine whether the classroom and school environment have quality and are nurturing. For this assessment, mean growth rates need to be established against national and district

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Tier III: Tertiary Prevention: Specialized intervention uniquely designed to provide support for students with the most intensive educational problems that have failed to respond to Tier I and II or students identified as needing intensive support immediately-5%-10% of students in the school. Tier II: Secondary Prevention: Targeted interventions to children at-risk of developing intensive problems in specific instructional domain-10%-15% of children in the school.

Tier I: Universal core instructional strategies available to all children-most students respond (75%-80%).

Fig. 1.

RtI Logic Model and Continuum of Supports in a School.

growth rates. Poor quality environments lead to intervention that strengthens the instructional setting. Phase II: Assessment is used to identify individual students with dual discrepancies. Phase III: Remedial intervention is targeted to meet the needs of students in general education. If a student fails to respond to this enhanced instructional method, they become eligible for special education. Phase IV: The effectiveness of special education is evaluated. Like any new system, the use of RtI to replace the educational disability labeling system is not without challenges. RtI was initially conceptualized to address broad disability categories that are historically problematic such as LD and ED. Unique to these disabilities is the possibility that they may be preventable or their disabling challenges substantially mitigated through educational remedial. In contrast, prevention of MR, a sensory disability or a physical disability is not considered a possibility through educational intervention as we know it. On the surface, it may seem impossible to rectify

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this conundrum making RtI a less than useful framework for these latter types of disabilities. This is unfortunate because disability labels such as MR have become a means to demean, marginalize, and excommunicate individuals with MR from being active participants in our society (Kliewer & Biklen, 1996). To address social injustices and segregation caused by a disability label such as MR, ecological models of curricular development have been created to help individuals with MR develop competency and participate meaningfully in civil society (Browder, 2001). Although the discrepancy model of achievement and cognition has proved itself largely useless and often damaging for many individuals with disability, an alternate assessment model (e.g., RtI) that is education oriented and embedded in natural context can be used instead (Brown, Snell, & Leher, 2006). In such a model, alternate assessment tools that are practical and fit within an ecological framework can be developed (Westling & Fox, 2009). These tools can then be used by educators to (1) determine meaningful and functional needs of a student with a disability and (2) guide teachers in decision making about the student’s responsiveness to intervention.

CONCLUSION In this chapter, the authors argue that disability labels have outlived their educational usefulness. Furthermore, most educators and scholars, even those who support disability labeling, are aware of the damaging social effects of labeling a student with a disability. Instead of using a disability labeling approach, the authors recommend that RtI and alternate assessments that provide an ecological framework to guide educators in the identification of students with disabilities be adopted. Although the origin of disability labels is connected to the medical model of identification and treatment, they are not educational relevant. Certainly, diagnostic medical disability criteria are useful in medicine and psychiatry; however, they have little meaningful instructional application in education, despite the persistent use of them in the general and special education. To effectively teach a student with a disability, general and special educators need to use educational practice based assessment and instruction to guide their decision making related to a student’s responsiveness to their instruction. The goal of special education has always been about opening doors for a student with a disability by enhancing his/her capabilities and minimizing his/her weaknesses. General and special educators should not endorse a system of

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labeling and classification no matter how expedient it may appear because such a system makes it difficult for an individual with a disability to become self-empowered. The central tenet of this chapter is to have general and special educators focus instructional intervention on what it does effectively. The RtI model and alternate assessment can assist general and special educators in meeting the above focus because these practices were specially designed to assess instructional intervention, which can maximize the selfempowerment of a student with a disability. Adopting these advancements can free special education instruction of the shackles imposed by an antiquated disability labeling system.

REFERENCES Adelman, H. S. (1996). Appreciating the classification dilemma. In: W. Stainback & S. Stainback (Eds), Controversial issues confronting special education: Divergent perspectives (pp. 96–111). Needham Heights, MA: Allyn & Bacon. Ardoin, S. P., Witt, J. C., Connell, J. E., & Koeing, J. L. (2005). Application of a three-tiered response to intervention model for instructional planning, decision making, and the identification of children needing services. Journal of Psychoeducational Assessment, 23, 362–380. Bender, W. N., & Shores, C. (2007). Response to intervention: A practical guide for every teacher. Thousand Oaks, CA: Corwin Press. Berkely, S., Bender, W. N., Peaster, L. G., & Saunders, L. (2009). Implementation of response to intervention: A snapshot of progress. Journal of Learning Disabilities, 42, 85–95. Bradely, R., Danielson, L., & Doolittle, J. (2007). Response to intervention: 1997–2007. Teaching Exceptional Children, 39, 8–12. Browder, D. (2001). Curriculum and assessment for students with moderate and severe disabilities. New York: Guilford Press. Brown, F., Snell, M. E., & Leher, D. (2006). Meaningful assessment. In: M. E. Snell & F. Brown (Eds), Instructing students with severe disabilities (pp. 67–110). Upper Saddle River, NJ: Pearson Education, Inc. Burns, M., Appleton, J. J., & Stehouwer, J. D. (2005). Meta-analytic review of responsivenessto-intervention research: Examining field-based and research-implemented models. Journal of Psychoeducational Assessment, 23, 381–394. Cockerham, W. C. (2002). Sociology of mental disorder (5th ed.). Upper Saddle River, NJ: Merril/Prentice Hall. Cullinan, D. (2004). Classification and definition of emotional and behavior disorders. In: R. B. Rutherford, Jr., M. M. Quinn & S. R. Mather (Eds), Handbook of research in emotional and behavior disorders (pp. 32–53). New York: The Guilford Press. Fuchs, L. S., & Fuchs, D. (2007). A model for implementing responsiveness to intervention. Teaching Exceptional Children, 39, 14–20. Fuchs, L. S., Fuchs, D., & Speece, D. L. (2002). Treatment validity as a unifying construct for identifying learning disabilities. Learning Disabilities Quarterly, 25, 33–46. Gallagher, B. J. (1995). The sociology of mental illness (3rd ed.). Englewood Cliffs, NJ: Prentice Hall.

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Gresham, F. M. (2006). Response to intervention and emotional and behavioral disorders: Best practices in assessment for intervention. Assessment for Effective Intervention, 32, 214–222. Henley, M., Ramsey, R. S., & Algozzine, R. F. (2009). Labeling and disadvantages of labeling. Available at: http://www.education.com/reference/article/advantages-disadvantageslabeling/?page ¼ 2. Retrieved on August 4, 2009. Higgins, E. L., Raskind, M. H., Goldberg, R. J., & Herman, K. L. (2002). Stages of acceptance of the impact of a learning disability: The impact of labeling. Learning Disability Quarterly, 25, 3–18. Individuals with Disabilities Education Improvement Act of 2004, 20 U.S.C. 1400 et seq. (2004). Reauthorization of the Individuals with Disabilities Education Act of 1990. Kliewer, C., & Biklen, D. (1996). Labeling: Who wants to be called retarded? In: W. Stainback & S. Stainback (Eds), Controversial issues confronting special education: Divergent perspectives (pp. 83–95). Needham Heights, MA: Allyn & Bacon. Lauchlan, F., & Boyle, C. (2007). Is the use of labels in special education helpful? Support for Learning, 22, 36–42. Lemay, R. (2006). Social role valorization insights into the social integration conundrum. Mental Retardation: A Journal of Practices, Policy and Perspectives, 44, 1–12. Mellard, D. F., & Johnson, E. (2008). RTI: A practitioner’s guide to implementing response to intervention. Thousand Oaks, CA: Corwin Press. Mercer, C., Jordan, L., Allsop, D. H., & Mercer, A. R. (1996). Learning disabilities definitions and criteria used by state education departments. Learning Disability Quarterly, 19, 217–232. Pfuhl, E. H. (1980). The deviance process. New York: D. Van Nostrand Company. Rolison, M. A., & Medway, F. J. (1985). Teachers’ expectations and attributions for student achievement: Effects of label, performance pattern, and special education intervention. American Educational Research Journal, 22, 561–573. Shores, C., & Chester, K. (2009). Using RTI for school improvement: Raising every student’s achievement scores. Thousand Oaks, CA: Corwin Press. Szasz, T. S. (1960). The myth of mental illness. American Psychologist, 15, 113–118. VanDerHeyden, A. M., Witt, J. C., & Barnette, D. W. (2005). The emergence and possible futures of response to intervention. Journal of Psychoeducational Assessment, 23, 339–361. Vaughn, S., Linan-Thompson, S., & Hickman, P. (2003). Response to treatment as means of identifying students with reading/learning disabilities. Exceptional Children, 69, 391–409. Westling, D., & Fox, L. (2009). Teaching students with severe disabilities. Upper Saddle River, NL: Pearson. Wolfensberger, W. (2000). A brief overview of social role valorization. Mental Retardation, 38, 105–123.

PART V PLACEMENT AND INCLUSION OF STUDENTS

CHAPTER 9 THE GENERAL EDUCATION CLASSROOM: THIS IS NOT WHERE STUDENTS WITH DISABILITIES SHOULD BE PLACED Jeffrey P. Bakken Inclusion is a topic within the field of special education that has caused much debate, stirred emotions, and has received great attention. While discussing issues related to supporting the continuum of educational placements as opposed to full inclusion of learners with special and diverse needs, a fundamental perspective to this discourse is that access to a highquality, effective, individualized educational environment is far more valuable and socially significant than mere placement and proximity to typically developing peers. The critical question for educators and families should be, ‘‘Will the general education environment result in meaningful gains and achievement for learners with diverse needs and disabilities?’’ The purpose of this chapter then is to present a perspective that supports the need for a continuum of educational placements for learners with special and diverse needs; this perspective is starkly contrasted with the absolute full inclusion of learners with special needs in the general educational classroom.

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EXPLAINING RELEVANT CONSTRUCTS IN THE PLACEMENT ISSUE Before discussing educational placement issues related to learners with special needs, definitions related to inclusion need to be presented. It is important to note there is no universally accepted definition of inclusion; thus, this term holds different meanings to different individuals (Fuchs & Fuchs, 1994). Furthermore, the terminology has also changed over the decades (McLeskey, 2007). During the 1960s through the early 1980s, the term mainstreaming was used. The terms of integration and regular education initiative were used throughout the 1980s. From the late 1980s through the present, the preferable term has been inclusion. Schwartz (2005) optimistically stated that an inclusive program is ‘‘one that provides educational intervention to students with and without disabilities in a common setting and provides appropriate levels of instruction and support to meet the needs of all students’’ (p. 240). Others have defined inclusion ‘‘as the practice of educating students with disabilities in the general education classroom setting’’ (Zinkil & Gilbert, 2000, p. 225). The meaning of inclusion has been defined differently from the term mainstreaming, which has been defined as ‘‘when students y earn their way into the general educational classroom y with minimal, if any, special education assistance’’ (Zinkil & Gilbert, 2000, p. 225). For the purposes of this chapter, the definition of inclusion provided by Zinkil and Gilbert (2000) will be used. With the passing of the Education for All Handicapped Children Act in 1975, the course of public education was forever changed (Heward, 2009). It has been revised five times since its passing; in 1990, it was renamed the Individuals with Disabilities Educational Act (IDEA). This enactment fundamentally impacted how learners with special needs were educated. Although there are six major principles of IDEA, only one directly speaks to the educational placement of learners with special needs, the principle of Least Restrictive Environment (LRE). (For a detailed discussion of IDEA, please see Manasevit, Plagata-Neubauer, Winters, & Martin, 2008.) The principle of LRE federally mandates that learners with disabilities be educated with learners without disabilities to the maximum extent possible. When this is not possible, a continuum of alternative educational placements must be provided (Heward, 2009). The continuum of alternative placements can be conceptualized along an increasing continuum of least (i.e., the general educational classroom) to most restrictive (i.e., hospital or home program). In addition, as the continuum of alternative educational placements transitions from least to most restrictive, the number of students

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being educated across those environments transitions from the most number of students (i.e., in the general educational environment) to the least number of students (i.e., in a hospital or home program). As the educational environments transition from least to most restrictive, the intensity of instructional support also increases. There are many reasons that the need for an educational continuum must be maintained. First, the concept of LRE is a guiding principle set forth and mandated by IDEA. Given that there are eight educational environments suggested by the LRE, then all learners should have the right to access an environment across this continuum that is suitable to their educational needs. The alternative educational placement should be determined at the level of the individual and not dictated by the category of disability (Heward, 2009). Second, school environments are not static environments (Krantz & McClannahan, 1999). With every new school year, there are countless new challenges that the learner with special needs faces. These new challenges can include novel teachers, peers, classrooms, rules, behavioral expectations, curriculum, and instruction. Consequently, as the school environment is fluid and is influx, placement is not expected to be static as well. It is illogical to expect that the learner will academically progress at the same pace and rate within changing environments. Typically, educational placement is to be determined based on input from the multidisciplinary team comprosed of school personnel and the family of the student (Friend & Bursuck, 2009). Members of the multidisciplinary team typically consist of a general educator, a special educator, a school administrator, a speech pathologist, and even when appropriate, a school counselor. Across the team and family, discussion of educational placement begins by identifying the LRE. The general educational classroom is the least restrictive educational environment even across diverse learners. Then, depending on the level of support required for the learner to make progress, placement is determined from across the educational continuum. In deciding the appropriate placement, there is no concrete or method deemed best-practice to deciding placement. Ultimately, the least restrictive educational placement is decided by the team and family. At least annually, the educational placement should be reviewed; however, placement can be altered as many times as deemed necessary with the parent’s permission. Typically, a change in educational placement is sought as a result of disciplinary action or to place the learner in a more restrictive environment to better manage behavior. Although this is to be a group decision where input is received across family and school personnel, public policy may also exert influence over educational placement of learners with special and diverse needs

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(Duffrin, 2002b; Soltman & Moore, 2000). For example, in 1992, a school reform group coupled with Northwestern University Legal Clinic sued the Chicago Public Schools (CPH) and the State of Illinois for violating the IDEA on behalf of nearly 40,000 CPS students. Specifically, the lawsuit was raised for the violation of the LRE principle. It was found that nearly half of CPS learners with special needs spent the majority of their school day in the general educational environment. This figure was behind the national average of 70%. In 1998, the Chicago School board had settled the lawsuit. As a result of the settlement, learners with special needs are now to be placed in the general educational environment unless placement in a more restrictive environment can be fully justified. It has also been found that this has resulted in co-teaching across special and general educators (Duffrin, 2002b). However, there have been numerous challenges identified complying with the settlement (Duffrin, 2002a).

BARRIERS TO FULL INCLUSION There are several barriers to full inclusion of students with disabilities in the general education classroom. First, inclusion requires collaboration between the special educator and the general educator. As identified by first-year special educators, one challenging endeavor identified was working collaboratively within an inclusive environment (Mastropieri, 2001). While working within an inclusive environment, first-year special educators identified difficulties including learners with special needs in general education activities. Other barriers to inclusion pertain to the general educator’s perception of successfully educating an entire classroom with a range of diverse needs (Mastropieri, 2001; Scruggs & Mastropieri, 1996). Concerns raised by general educators include the potential disruptive nature of learners with special needs in the general education learning environment and concerns about adequately addressing the lower performers. An additional concern pertains to the ability to maintain a high academic level despite the diverse range of learners. Some general educators are adamant that placing learners in an environment where they cannot academically compete is detrimental to both general education students and special needs students (Anderson, 2002). Given that the current climate of public education is heavily influenced by high-stakes testing, this factor may exert greater influence over time. Results of a research synthesis conducted by Scruggs and Mastropieri (1996) identified needs of general educators to support learners with special

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needs in the general education classroom. As a result of their research, it was found that nearly one-third of teachers surveyed reported that they lacked the time, the skills, the training, the personnel, and the material resources needed for successful inclusion. In addition to the general educator’s perceptions, another challenge is the misconception that exposure to the general education learning environment is sufficient for skill acquisition for the learner with special needs (Leaf, Parker, & McEachin, 2008; Schwartz, 2005). It is illogical to assume that learners with special needs will acquire skills as a result of proximity to and duration with typically developing peers. Without specific support, placing learners with greatly varying abilities in proximity results in two learners who have a range of abilities being in proximity without explicit instruction and support. If mere exposure or proximity to developing peers was sufficient for skill acquisition, then perhaps behavioral deficits would not be present nor would a specific diagnosis be warranted (Leaf et al., 2008). Besides the misconception of exposure, an additional obstacle with inclusive classrooms centers on the heterogeneity of inclusive programs (Hines, 2001). Across and even within school districts, inclusive programs greatly differ in regard to the definitions employed that outline a program or specific components of programs. Consequently, given that there is a range of inclusive programs by definitions and components, it is expected that learners with diverse needs must hurdle through the range of programs and adapt to the changing environments. Because consistency has been identified as a pillar of special educational services (Heward, 2009), it is incomprehensible that learners are expected to conform to the different learning environments. Although placement in the general education environment may be federally mandated, districts have difficulty implementing and abiding by the federal law (Duffrin, 2002a). This has been especially difficult at the high school level. One challenge is due to the inflexibility of high school educators’ schedule to permit collaboration across special and general education. The lack of planning time to discuss learning and behavior problems for a particular student was particularly challenging for educators. Furthermore, as monitoring across 20 Chicago Public High Schools (CPHS) revealed, general high school educators identified reoccurring challenges serving learners with special needs in general education classrooms. Challenges identified included the lack of (a) instructional supports, (b) successful implementation of behavior management plans, (c) implementation of an appropriate grading system, (d) tracking of student progress, and (e) collaborative communication with parents. As found at CPHS, appropriate academic support for learners with special needs was inadequately provided by general educators Duffrin, 2002a).

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Furthermore, another challenge to successful inclusion regarding placement in the LRE is the lack of insight gathered by educators and school personnel of parents of typically developing learners (Bricker, 2000). This means that parents who have children without disabilities are not consulted or surveyed when considering placement of learners with special and diverse needs in the general education classroom. These parents have little or no choice about placement and they may have legitimate concerns over the impact on the general educational environment due to the inclusion of learners with special and diverse needs. If the supporting educational staff cannot calm concerns of parents of typically developing learners, this may negatively impact the tone of the inclusion debate within the general educational classroom.

WHY THE GENERAL EDUCATION ENVIRONMENT MAY BE INAPPROPRIATE FOR LEARNERS WITH SPECIAL NEEDS There are several related issues that educators and parents should consider when evaluating whether the general education classroom is an appropriate learning environment for a student with diverse needs. First, by definition, although perhaps redundant and trite, special education is ‘‘special.’’ By definition, special education requires an education that is individualized, requires that progress is closely monitored and evaluated, and requires modified and adapted curriculum, all of which is to be implemented and coordinated by a special educator. Ultimately, special education requires specialized training and specialized instruction. Given the specialized and intensive instruction to be provided to a learner whose academic achievement level has previously been documented to lag behind his/her typically developing peers, it seems absolutely ludicrous to expect the same intensity of instruction to be provided in the general education environment. Second, for learners who have deficits within the repertoire that warrant special education, time is important. Precious time has already been consumed documenting deficits, assessing deficits, and determining whether a learner qualifies for special education. To risk their educational progress and academic achievement and to limit their trajectory and progress are unjust and the cumulative ramifications of which cannot be measured. Third, the present educational climate does not suggest how responsibility across special and general educators is determined. This seems especially relevant for monitoring the individualized educational plan (IEP) for the

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student receiving special education. Not only does the IEP specify how the student will access the general education curriculum, it also ensures that the learner is provided with ample learning opportunities and accommodations to support his/her success in achieving educational goals (Pierangelo & Giuliani, 2007). Ensuring that the IEP is being addressed takes initiative and effort on behalf of the educator. This also requires progress monitoring and documentation. Consequently, this division of labor and role sharing can certainly interfere with the classroom. Fourth, simply because a learner is placed within an inclusive educational setting does not mean that inclusion is functioning successfully (Leaf et al., 2008). If a random classroom visitor can identify the learner included, then the success of inclusion should be questioned. Disruptive behavior and the presence of a paraprofessional can cue the bystander to identify the learner with special needs. In addition, if the learner can only be successful when a paraprofessional is able to repeat classroom instructions provided by the general educator or the learner needs full assistance provided for by the paraprofessional to meaningfully participate, then the success of inclusion should be examined. This also results in an increase of dependence on the paraprofessional and stifles independence. Other factors that impede the success of inclusion relate to the types of academic tasks provided to the learner with special needs, the presence of the instructional supports, and the intensity of accommodations needed to result in successful integration in the general educational environment (Bricker, 2000; Leaf et al., 2008). If the learner with special needs is provided with academic tasks that are greatly dissimilar to the academic tasks that are provided to the majority of the classroom, then the functionality of inclusion needs to be questioned (Leaf et al., 2008). Given that a separate task is provided to the learner with special needs, then the engagement and completion of the separate tasks directly impedes the interaction with the typically developing learners in an indirect fashion, the learner can be isolated in the general education class. In addition, the mere presence of instructional supports can hamper inclusion (Bricker, 2000). For example, providing a learner with an aide can be stigmatizing and can increase the isolation of the learner. If the learner with special needs requires intensive modifications to successfully complete the academic task provided to the majority, the necessary modifications may hamper the independence and success over time for the learner (Leaf et al., 2008). Examples of modifications and accommodations typically provided to learners with special and diverse needs in inclusive environments include changing classroom rules and expectations, quantity and quality of academic work,

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and the organization demonstrated by the student. By dramatically altering behavior and academic expectations, the success and independence of the learner may ultimately be hampered. Lastly, regardless of ability, learners have a right to effective education (Barrett et al., 1991). The position taken by Barrett et al. (1991) outlines essential components of an effective education and describes the conditions of an effective education which students are entitled. An effective education supports and maintains academic achievement and academic progress. Educators or school personnel behaviors that undermine the development and maintenance of academic progress should not be supported. Effective education should be evident across (a) curriculum and instructional objectives, (b) assessment and student placement, and (c) instructional methods. Curriculum and instructional objectives should be empirically validated and based on measurable criteria of performance. Furthermore, instructional objectives should target both short-term and long-term success through the level of the individual and in regard to vocation. Criterionreferenced assessments should be utilized to inform decision-making based on actual skill level versus decision-making based on a categorical level. In addition, placement within a curriculum should be based on entry and prerequisite skills. Instructional methods should allow learners to progress at their own pace, provide frequent opportunities to master skills, provide corrective feedback, and be able to adjust and modify instruction when progress is not being made. Consequently, if it is found that a particular learner is not progressing within group instruction, then the learner is entitled to instruction delivered at the individual level to improve the educational outcome. Given these details outlined by Barrett and colleagues regarding a student’s entitlement to an effective education, one can only ask, ‘‘Is this the current landscape in most general education classrooms and can this be possible within an inclusive classroom?’’

UNDER WHAT CIRCUMSTANCE SHOULD LEARNERS BE TRANSITIONED TO THE GENERAL EDUCATION ENVIRONMENT? To maximize educational opportunities and achievement, transition to the general educational environment should only be considered when the learner demonstrates skills that will result in contacting natural communities of reinforcement (i.e., reinforcement that is freely available in the classroom

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and occurs as a result of a natural consequence of a behavior). The importance of a learner contacting natural communities of reinforcement in the general educational environment is to promote and maintain independence, sustained engagement on academic tasks, and classroom participation. Although it seems challenging to determine whether the learner’s repertoire and skill set will lead to a successful transition, direct observation and data collection can certainly inform this decision. Specific observable, measurable behaviors have been identified as important to successful inclusion (Krantz & McClannahan, 1999; Leaf et al., 2008; Sundberg, 2008). To experience success in the general education environment, observable and quantifiable skills must be identified as being crucial to the learner’s success (Krantz & McClannahan, 1999; Leaf et al., 2008; Sundberg, 2008). For instance, Krantz and McClannahan (1999) suggested six behavioral measures that have been identified as meaningful for successful integration. The various behavioral measures include on-going attention and engagement to both individuals and tasks within the classroom, the ability to follow written and oral instructions regardless if presented to the group or presented individually, and the ability to be sensitive to remote consequences for behavior. Other skills important for successful inclusion include generalized language skills (i.e., emitting novel and untrained verbal utterances) and the generalization of skills across novel environments. In addition, the successful inclusion of learners with special and diverse needs must show the low occurrence of problem and disruptive behavior, the ability to learn skills from observation, the ability to demonstrate preference for peers, and socialization with peers. To a large measure, learners must demonstrate some basic proficiency of social skills (Leaf et al., 2008). Although special and general educators can certainly make use of direct observation and data collection procedures to inform the placement decision of a student, a recent assessment can certainly aid in this process. The Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP) is a comprehensive criterion-referenced assessment for learners with autism and related disabilities (Sundberg, 2008). In addition to including a skills assessment and recommendations for program development based on the outcome of an individual’s assessment, the VB-MAPP also provides a means to quantify skill excesses and deficits that may form potential barriers to a child’s educational progress, irrespective of the child’s learning environment (Sundberg, 2008). In addition, the VB-MAPP also includes a transition assessment to aid educators and parents in the decision-making process of appropriate placement. As denoted in the barriers assessment, there are 24 different language and learning barriers that have been

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identified. Although not an exhaustive list, examples of identified barriers include engagement in tantrum behavior, dependency on prompts to emit the appropriate target behavior, deficient attending skills, obsessivecompulsive behaviors, and hyperactivity. The transition assessment of the VB-MAPP can guide the decision-making process of identifying the least restrictive education environment for a learner. Within this assessment, there are 18 skills grouped across three categories. The first category addresses language, social skills, and behavioral skills. The second category within the transition assessment evaluates the learner’s ability to acquire information in a less intense teaching environment. In doing so, it closely examines his/her ability to generalize skills, rate of skill acquisition, and the ability to maintain skills over time. The third category assesses the learner’s self-help skills, spontaneity of behavior, and selfdirection. As cautioned by Sundberg (2008), the author of the VB-MAPP, this category of self-help ‘‘should not bear as directly on placement, but often is does y’’ (p. 129). This means that the learner’s proficiency of daily living skills should not be used to determine educational placement of the learner; instead, educational placement should take into account the learner’s ability to academically progress when placed within a given environment. In some measure, the VB-MAPP provides some valuable information to educators and parents to permit them to make a more informed decision.

CONCLUSION Although special education laws specifically mandate educational placements of learners with special needs across a continuum, educators, administrators, parents, and the like need to critically evaluate whether the general education environment is the appropriate place for learners with diverse needs at all. This chapter raised issues related to this position of inclusion. In doing so, it discussed the need for a continuum of educational environments and discussed factors related to educational placement. Finally, it exposed the fallacy that mere exposure to the general education environment will be sufficient to the acquisition of appropriate skills.

REFERENCES Anderson, V. (2002). Balancing the scales for special education. Catalysts: Voices of Chicago School Reform, 14, 2.

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Barrett, B. H., Beck, R., Binder, C., Cook, D. A., Engelmann, S., & Greer, R. D. (1991). The right to effective education. The Behavior Analyst, 14, 79–82. Bricker, D. (2000). Inclusion: How the scene has changed. Topics in Early Childhood Special Education, 20, 14–19. Duffrin, E. (2002a). Schools struggle with federal law. Catalyst: Voices of Chicago School Reform, 14, 2. Duffrin, E. (2002b). Who is Corey H.? Catalyst: Voices of Chicago School Reform, 14, 2. Friend, M., & Bursuck, W. D. (2009). Including students with special needs: A practical guide for teachers (5th ed.). Upper Saddle River, NJ: Allyn & Bacon. Fuchs, D., & Fuchs, L. (1994). Inclusive schools movement and the radicalization of special education reform. Exceptional Children, 60, 294–309. Heward, W. L. (2009). Exceptional children: An introduction to special education (9th ed.). Upper Saddle River, NJ: Pearson Education. Hines, R. A. (2001). Inclusion in middle schools. Champaign, IL: Office of Educational Research and Improvement (OERI). (ERIC document Reproduction Service No. ED 459 000). Krantz, P. J., & McClannahan, L. E. (1999). Strategies for integration: Building repertoires that support transitions to public schools. In: P. M. Ghezzi, W. L. Williams & J. E. Carr (Eds), Autism: Behavior analytic perspectives (pp. 221–231). Reno, NV: Context Press. Leaf, R., Parker, T., & McEachin, J. (2008). Inclusion-sense and nonsense. In: R. Leaf, J. McEachin & M. Taubman (Eds), Sense and nonsense in the behavioral treatment of autism: It has to be said (pp. 221–253). New York: DRL Books. Manasevit, L. M., Plagata-Neubauer, C., Winters, T., & Martin, C. (2008). IDEA: New expectations for schools and students (4th ed.). Washington, DC: Thompson Publishing Group. Mastropieri, M. A. (2001). Is the glass half full or half empty? Challenges encountered by firstyear special education teachers. The Journal of Special Education, 35, 66–74. McLeskey, J. (2007). Reflection on inclusion: Classical articles that shape our thinking. Arlington, VA: Council for Exceptional Children. Pierangelo, R., & Giuliani, G. (2007). 100 frequently asked questions about the special education process: A step-by-step process guide for educators. Thousands Oaks, CA: Corwin Press. Schwartz, I. S. (2005). Inclusion and applied behavior analysis: Mending fences and building bridges. In: W. L. Heward, T. E. Heron, N. A. Neef, S. M. Peterson, D. M. Sainato, G. Cartledge, R. Gardner, III, L. D. Peterson, S. B. Hersh & J. C. Dardig (Eds), Focus on behavior analysis in education: Achievements, challenges, and opportunities (pp. 239–250). Upper Saddle River, NJ: Merrill/Prentice Hall. Scruggs, T. E., & Mastropieri, M. A. (1996). Teacher perceptions of mainstreaming/inclusion, 1958–1995: A research synthesis. Exceptional Children, 63, 59–74. Soltman, S. W., & Moore, D. R. (2000). Ending illegal segregation of Chicago’s students with disabilities: Strategy, implementation, and implications of the Corey H. lawsuit, November. Paper presented at the Conference on Minority Issues in Special Education, the Civil Rights Project of Harvard University, Cambridge, MA. Sundberg, M. L. (2008). Verbal behavior milestones assessment and placement program guide. Concord, CA: AVB Press. Zinkil, S. S., & Gilbert, T. S. (2000). Parents’ view: What to consider when contemplating inclusion. Intervention in School and Clinic, 35, 224–227.

CHAPTER 10 BEYOND TRADITIONAL PLACEMENT: MAKING INCLUSION WORK IN THE GENERAL EDUCATION CLASSROOM Festus E. Obiakor, Mateba K. Harris, Anthony F. Rotatori and Bob Algozzine The inclusion of students with disabilities into general education classrooms has continued to stimulate debates in education. ‘‘Inclusive education means that all students within a school regardless of their strengths or weaknesses, or disabilities in any area become part of the school community’’ (King, 2003, p. 152). Students attend the same schools as siblings and neighbors and are members in the general education classroom, being provided with the support needed to learn within that environment and from the general curriculum (King, 2003). Inclusion is built on the principle that all students should be valued for their exceptional abilities and included as important members of the school community (Causton-Theoharis & Theoharis, 2008). Clearly, it is a matter of entitlement, an issue of belonging within an educational community on equal terms (Hall, Collins, Benjamin, Nind, & Sheehy, 2004). Social justice is a central ingredient of inclusion since it is in opposition to exclusion. In addition, social justice is centered on the ideas of challenging Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 141–153 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019013

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the arrangements that promote the continuation of marginalization and exclusionary practices; and it supports a foundational process of respect, care, recognition, and empathy (Theoharris, 2007). Earlier, Fullan (2003) discussed these same proponents as essential characteristics in building an ethical school. Within ethical schools, social justice is a major component of the belief systems of educators. Activities support achieving and maintaining environments where students are provided with an equitable education. Frattura and Capper (2007) explained that the inclusion of students in the general education curriculum and environment is an issue of equity and social justice. They contended that to develop an inclusive school where all students feel as a part of the school’s community, school officials must engage in reflections about the current state of the school as it relates to social justice for students with disabilities, what they need to do to get there, and how they are going to do it. With inclusion, students with disabilities are able to achieve academic success and emotional success while learning aside their nondisabled peers (Hall et al., 2004). Inclusion in schools is not far removed from the social justice reform movement in education. In fact, it is an issue of social justice since it cannot and will not be a reality in schools where students are segregated from their nondisabled peers to be given instruction from a curriculum and instruction that is separate from their nondisabled peers (Theoharris, 2007). Students with disabilities have historically been excluded from learning aside their nondisabled peers, denied access to the general education curriculum, and educated within programs where there was little to zero accountability (Artiles, Harris-Murri, & Rostenberg, 2006). Owing to this lack of accountability, students with disabilities were frequently subjected to receive an education that does not prepare them to live, and function within a society where at least the basic skills sets of reading, writing, and mathematics are essential. Clearly, we do not live in homogenous society, nor do we live in a separatist society. Therefore, our students with disabilities should not and must not be educated in separate classrooms or facilities. The 1954 Brown v. Board of Education case opened the doors for parents and educators to argue for equal accessibility to schooling for students with disabilities. In 1994, the world conference on special needs education concluded that ‘‘regular schools with [an] inclusive orientation are the most effective means of combating discriminatory attitudes, creating welcoming communities, building an inclusive society and achieving education for all’’ (Foreman & Arthur-Kelly, 2008, p. 110). Within inclusive classrooms, students feel connected to their peers and have access to meaningful, rigorous general education curricula (Causton-Theoharis & Theoharis,

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2008). Approximately 70% of students with disabilities are serviced with the general education classroom among their nondisabled peers (King, 2003); however, some students with exceptionalities are educated in separate facilities from their non-disabled peers. As Katsiyannis, Yell, and Bradley (2001) observed, more than 1.75 million students with exceptionalities failed to receive educational services, forcing families to seek costly educational services outside of the public sphere. Special education must be an avenue through which children with disabilities are guaranteed to receive specifically designed instruction to assist them in maximizing their highest potential. Special education is a necessary component of public education that provides services to students with exceptionalities; and it includes effective methods of specially designed instruction for students who require specific, controlled, monitored, and intensive content (Hockenbury, 1999). Special education provides students with exceptionalities an education that achieves meaningful outcomes while simultaneously experiencing learning as valued members of general classes and schools (Ford, Davern, & Schnorr, 2001). Clearly, special education involves individualizing instruction with the aim of helping students with special needs to gain access to the general curriculum (Shealey, Lue, Brooks, & McCray, 2005). Historical exclusionary practices such as educating students with disabilities within separate facilities and outside of the general education are contradictory to the goals of special education. This chapter focuses on how we can go beyond the traditional placement to include learners with disabilities in the general education classroom.

PLACEMENT PRACTICES WITHIN THE LEAST RESTRICTIVE ENVIRONMENT The process of placing students into special education programming often begins with the teacher being able to identify appropriate educational placements (Rizza & Morrison, 2003). It is important that educators know how decisions regarding placement will impact the daily lives of students including their social interactions with peers and the curriculum used to service students. The least restrictive environment (LRE) mandate of the Education of All Handicapped Children’s Act of 1975, later reauthorized as the Individuals with Disabilities Education Act (IDEA) of 1990 stated that students with disabilities must be educated with non disabled peers to the

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‘‘maximum extent appropriate,’’ ‘‘and that they may be removed from the general education environment only if they cannot be satisfactorily educated with the use of supplementary aides and services’’ (Hosp & Reschly, 2003, p. 68). Furthermore, the LRE ensures that students with disabilities must have access to the general curriculum and be taught with their nondisabled peers (Turnbull, 2003). As a result, fully integrated applications of learning strategies designed originally for students with disabilities are implemented, and scores on No Child Left Behind (NCLB) have increased, and sanctioned accountability measures for all students have increased (Sailor & Roger, 2005). Placement decisions can cause ‘‘unrealistic expectations, prejudicial generalizations, illusory conclusions, and deceptive self-aggrandizement’’ (Obiakor, 2001, p. 84). There are different placement options for students with disabilities such as inclusion, where students are serviced within the general education environment with their nondisabled peers, from the general education curriculum; resource where students are pulled out of the regular education environment and serviced outside of the regular environment, usually in the special education classroom; self-contained or most restrictive placements (MRP) where students, with moderate to profound needs, remain in a special education classroom for the majority of their school day, alternative placements where students are serviced outside of the general public school, and the institution where services are provided to children in a day or residential treatment center or the like. Conversations about placement have been ongoing. Researchers such as Pugach and Warger (2001) stated that the general education environment is optimal for the greatest success in education. Furthermore, many parents and professionals of students with disabilities agree that most students with disabilities should receive the greatest portion of their education within the general education classroom with their nondisabled peers (Cardona, 2009). More importantly, students both with and without disabilities want to be educated within the same environment. Klinger and Vaughn (1999) synthesized 20 studies that investigated the perceptions of learning of over 4,659 students in kindergarten through twelfth grade. Among this group of students, 760 students had high incidence disabilities. The studies revealed that students with disabilities want to learn the same material, use the same books, and enjoy homework and grading practices as their nondisabled peers. Additionally, students without disabilities agreed. Both groups of students understood that students learn differently and as a result need teachers who are willing to teach using various styles to reach every learner. These students also appreciated having teachers that slowed down instruction when needed.

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For this reason it is important to consider the suggestions of Obiakor (2001, 2007), on some important placement principles:  Race and culture can matter in the placement of students.  Placements must be based on needs and not on students’ racial or cultural identities.  Language differences should never be misconstrued as a lack of intelligence.  Empathy is an important ingredient of good placement.  Good placements are usually the LREs.  Differences are not deficits.  Students are best served when their due process rights are respected.  Appropriate inclusion reduces biased exclusion of students in classroom activities.  Prejudicial placements have devastating effects on students.  The unique differences students bring to the classroom must be valued. The placement of students with disabilities into the general education classroom ensures students’ participation within the general curriculum, a mandate of the IDEA (Mastropieri & Scruggs, 2001). The case of Raul illustrates this idea.

The Case of Raul At the age of eight, third grader, Raul was diagnosed as a student with a learning disability. He was bilingual and used Spanish whenever in dialogue with his father, a native of Mexico who did not speak English. However, Raul and his Caucasian mother spoke English to one another. The school considers Raul’s home to be a bilingual household in that both English and Spanish were frequently used in the home environment. Raul enjoyed math tasks and demonstrated strength within this area. One the other hand, he was not very enthusiastic about reading. Additionally, he had difficulty with maintaining focus while being instructed by his general education teacher. The teacher was concerned that because Raul was so ‘‘busy’’ during class time he was not retaining the information from class. His teacher reported several behaviors about him that were concerning to her. He was out of his seat more often than he was in his seat and he did not raise his hand to answer questions. The teacher concluded that these behaviors interfered with Raul’s learning and the learning of others and clearly was indicative of a learning disability. His reading skills appeared to be low and his teacher wanted him tested for special education services. Raul did meet the criteria for a student with a learning disability. Immediately, he was assigned to a special education resource teacher. The teacher pulled Raul out of his general education classroom for reading and writing. This was approximately one to two hours of time spent outside of his general education classroom without his friends in general education. Raul’s reading skills did

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not get to grade level and his behavior did not improve. However, he remained engaged in math in the general education classroom, even when the curriculum required a large amount of reading. On the contrary, as Raul approached middle school, whenever he had to leave his general education classroom to come to the special education classroom, the behaviors would manifest within the small group at a more intense rate than what the general education teacher reported. It became clear that he would have been better served in the inclusive classroom.

Raul’s story is very common in our schools. We force students to become a part of a system that is ultimately damaging to their academic and social achievements. Students with disabilities, such as Raul, want to be a part of the classroom community of learners with their peers. They do not want to be excluded or stigmatized based on their placements. For example, Raul needed a culturally responsive teacher who would value his English language learner (ELL) experiences.

TEACHERS’ RESPONSIBILITIES IN THE INCLUSIVE PROCESS Educators must diversify their instruction, goals, and assessment to accommodate various learners within the general education classroom (Gadberry, 2009) to meet the range of developmental and educational needs present in today’s classrooms (King, 2003). When students with disabilities are placed in the general education classrooms, teachers must be prepared to accommodate them based on their individual needs (Berry, 2006). For example, in the case of Raul, had the teacher diversified her instruction to meet his needs, he would have found success in the general education classroom, and the problem behaviors would have subsided. The inclusion for students with disabilities is most effective when teachers are collaborative and consultative. This collaboration can facilitate the successful inclusion of students with disabilities (Carter, Prater, Jackson, & Marchant, 2009). Again, Raul’s teacher should have looked for other ways to collaborate and consult with his parents concerning classroom problems. But, she was more interested in labeling and/or excluding him. General and special education teachers discuss students’ needs. They problem solve together, demonstrate instructional techniques, participate in professional development, share resources, and network with other professionals (Conderman & Johnston-Rodriguez, 2009). Collaboration within inclusive settings can be described as co-teaching. According to Tobin (2005), co-teaching effectively uses the skills and unique talents of

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professionals. Earlier, Vaughn, Schumm, and Arguelles (1997) described five models of co-teaching in which collaboration can occur, namely:  One Teach, One Assist. In this model, one teacher provides the instruction for all students and the other teacher provides assistance to the students who need additional support. This model is beneficial for all students because it not only allows for students with disabilities to access the general curriculum but also provides instructional support for students without disabilities who require additional support.  Station Teaching: This model requires for students to be broken into three separate small groups. Two groups work with a teacher while one group works independently over a block period. Once that period is over, the students then rotate to another station. This model is beneficial because it allows for all students to work with in small groups and receive small group instruction.  Parallel Teaching: This model requires teachers to plan the lessons together then split the students into two groups to provide the same lesson within the smaller group within the same classroom. This model is beneficial because it allows for students to receive the small group instruction, but it also provides teachers the opportunities to learn from each others’ expertise and grow in their own areas of development.  Alternative Teaching: This model allows for one teacher to teach and the other teacher will pre-teach and reteach, as necessary, to students who need additional support.  Team Teaching: This model involves both teachers providing the instruction together to the students within the same classroom. The benefit of team teaching is that all students have the same access to each teacher at the same time within the general education classroom. For inclusion to become a reality within the school, teachers must be willing to provide differentiated instruction in schools and have the wherewithal to implement it within their classrooms. Again, in the case of Raul, the teacher should have tried to practice differentiated instruction to see how he could have been reached and helped to maximize his fullest potential. Differentiated instruction acknowledges the fact that not all students are alike and therefore do not all learn the same. It is an approach to teaching that advocates active planning to respond to individual student differences in classrooms (Hall, 2002; Tomlinson, 2001, 2004). Differentiated instruction requires teachers to be flexible in their teaching approaches and flexible in adjusting the curriculum rather than expecting students to modify themselves for the curriculum (see the case of David later

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in text). Earlier, Tomlinson (2001) noted that in order for differentiated instruction within inclusive settings to be successful, teachers must adhere to the following guidelines:  Clarify all key concepts and generalizations.  Use assessment as a teaching tool to extend versus simply measure instruction.  Emphasize critical and creative thinking as a goal in lesson design.  Engage all students in learning.  Provide a balance between teacher-assigned and student-selected tasks.

The Case of David David was a 7th grade student, with a learning disability, attending an urban elementary school. He sat in the back of the general education classroom with the other nine students with disabilities. He did not participate in class discussions and was hardly ever called upon to participate by his general education teacher. He did not feel a part of the classroom community and furthermore did not feel valued as a learner. David received ‘‘resource’’ services from the special education teacher, Ms. Norris, a novice teacher, who visited the general education classroom frequently. She established a positive relationship with the general education teacher, Mr. Ellis, very quickly. Ms. Norris talked to Mr. Ellis about the progress the students were making in the resource room. She expressed how actively they are engaged in learning within the small group. She suggested to Mr. Ellis that perhaps students would be more inclined to participate if they were spread out throughout the classroom. Mr. Ellis agreed and decided to move the students’ desks. Now the students were no longer identified as the students in the back of the class. Ms. Norris and Mr. Ellis began to plan together what was being covered in the curriculum. Ms. Norris would preteach the content to students in the resource classroom and they began to gain confidence to participate in the general classroom. Soon Ms. Norris and Mr. Ellis began planning on how students could remain in the classroom for the entire day. The two teachers decided to team teach. They broke up the subjects and each was responsible for teaching certain subject areas. The students were no longer pulled out of the general education classroom. They received their special education services within the general education classroom from both teachers. This was beneficial for all students within the classroom. David became one of the leaders within the classroom and provided support to other students who needed it.

As it appears, this case shows that like other students, David just wanted the opportunity to show that he could be successful within the general education classroom. He just had not developed the skills to do so. This is often the case with many of our students. They want to participate within the discussions and assignments in class; however, they have not yet acquired the skills to do so. Many times when students are removed from

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the general education classrooms to receive their special education services within a special education classroom, they are only receiving a watered down curriculum that places them at an even further disadvantage. This means that students with disabilities are not expected to learn as much as other students (Ellis, 2002).

GUIDING PRINCIPLES OF SUCCESSFUL INCLUSION According to Sailor and Roger (2005), inclusion must be addressed using a school wide model that benefits the maximum number of students both with and without disabilities. Every child must be a permanent member of the general education classroom (Causton-Theoharis & Theoharis, 2008). Sailor and Roger (2005) provided six guiding principles for a successful inclusion setting within the school. They are:  General education guides all students to learn, and parents are encouraged to participate in supporting the model. All students attend their regularly assigned school and are considered general education students. The general education teachers are responsible for all students. The students are instructed from the general education curriculum.  All school resources are configured to benefit all students. This means that all students are included in all activities, all resources benefit all students, and the school effectively incorporates all students in the instructional process.  Schools address social development and citizenship forthrightly by incorporating positive behavior supports at the individual, group, and school wide levels. These positive behavior supports are beneficial for all students, not just students with behavior challenges.  Schools are democratically organized, data-driven, problem-solving systems where all personnel take part in the teaching/learning process. This includes administrators, teachers, and support staff such as school social workers, psychologist, and speech therapists. Additionally, paraprofessionals are expected to deliver supervised instruction and report the outcomes of that instruction to the teachers. Parents and community members also are a part of the inclusion community.  Schools have open boundaries in relation to their families and communities. They understand their role in fostering positive working relationships with students’ families, by seeking input from them on various ways

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to bring their cultures into the classroom community of learners. Parent liaisons within inclusive schools work with other parents and school teams to ensure that voices of parents are heard. It is also useful for schools to have successful inclusive programs to develop and implement a family resource center, where families can seek information on various topics that may be useful to themselves and their families. Furthermore, partnerships with local businesses, different service learning opportunities, and community based instruction all serve to benefit students, families and schools.  Schools enjoy district support for undertaking an extensive systemschange effort. For this to occur, however, there must be a departure from traditional bureaucratic management and communication processes must have district support to allow for results sharing from the building level to the district level.

INCLUSIVE SCHOOLS: EFFECTIVE LEADERS Principals and other school leaders are critical in the educational reform of moving students from segregated classrooms to inclusive schools that are responsive to the growing heterogeneity of students attending schools (Salisbury, 2006). It is going to take effective leaders to move educational reform of social justice forward. According to Fullan (2001), effective leaders (a) have an explicit ‘‘making-a-difference’’ sense of purpose, (b) use strategies that mobilize many people to tackle through problems, (c) hold themselves accountable by measured and debatable indicators of success, and (d) must be ultimately assessed by the extent to which they awaken people’s intrinsic commitment, which is none other than the mobilizing of everyone’s sense of moral purpose. To prepare teachers for inclusive practices within schools means that school leaders must share the vision of inclusive education (Carter et al., 2009; CaustonTheoharis & Theoharis, 2008) and secure commitment from teachers (Carter et al., 2009). Clearly, to be effective in addressing the educational needs of diverse students, especially those with special needs, school administrators must encourage and implement progressive teacher practices in their schools. Effective leaders create cultures of success and encourage teachers to be effective. Grant and Gomez (1995) reported that effective teachers and

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leaders (a) have high expectations for their students and believe all students are capable of academic success; (b) communicate clearly, pace lessons appropriately, involve students in decisions, monitor students’ progress, and provide frequent feedback; (c) use culturally relevant teaching approaches that integrate students’ native language and dialect, culture, and community into classroom activities to make input more relevant and comprehensible, and (d) use curricula in teaching strategies that promote coherence, relevance, progression, and continuity. As Causton-Theoharis and Theoharis (2008) suggested, school leaders must work with educators to ensure that membership within the general education classroom is not optional or awarded to the ‘‘well behaved’’ students. Membership within the general education classroom must be given and supported so that all students are equipped to participate within an inclusive society. Clearly, it is up to the school leaders to place more funding into building strong general education classrooms for all students while also eliminating the spending that creates separate rooms for students. Finally, CaustonTheoharis and Theoharis (2008) noted that school leaders must provide training and professional development to increase the capacity for teachers to deliver high-quality education for all students. These leaders must be available to provide support to teachers when it is needed. In the end, implementation of effective strategies and best practices will lead to more positive academic outcomes for diverse students, especially those with special needs in inclusive classroom environments.

CONCLUSION Educating students with disabilities within the general education classroom, from the general curricula, signifies that these students are not only members within the classroom and school community, but they also are valued as unique learners within that community. It is important for educators to understand their role in facilitating inclusive programs within the school and making it a part of the culture of the school in which students are learning. It is critical for school leaders to build consensus around the vision that all students can achieve at high levels within an inclusive community of learners. Additionally, practitioners must continue to develop positive and supportive relationships with families of students with disabilities in a collaborative, consultative fashion. Finally, all stakeholders must be included in the educational system.

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REFERENCES Artiles, A. J., Harris-Murri, N., & Rostenberg, D. (2006). Inclusion as social justice: Critical notes on discourses, assumptions, and the road ahead. Theory into Practice, 45(3), 260–268. Berry, K. (2006). Teacher talk during whole-class lessons: Engagement strategies to support the verbal participation of students with learning disabilities. Learning Disabilities Research & Practice, 21(4), 211–232. Cardona, C. M. (2009). Teacher education students’ belief of inclusion and perceived competence to teach students with disabilities in Spain. Journal of the International Association of Special Education, 10(1), 33–41. Carter, N., Prater, M., Jackson, A., & Marchant, M. (2009). Educators’ perceptions of planning processes for students with disabilities. Preventing School Failure, 54(1), 60–72. Causton-Theoharis, J., & Theoharis, G. (2008). Creating inclusive schools for all students. School Administrator, 65(8), 24–25. Conderman, G., & Johnston-Rodriguez, S. (2009). Beginning teachers’ views of their collaborative roles. Preventing School Failure, 53(4), 235–242. Ellis, E. S. (2002). Watering up the curriculum for adolescents with learning disabilities, part I: Goals of the knowledge dimension. Available at http://www.ldonline.org/ article/Watering_Up_the_Curriculum_for_Adolescents_with_Learning_Disabilities,_Part_ I:_Goals_of_the_Knowledge_Dimension. Ford, A., Davern, L., & Schnorr, R. (2001). Learners with significant exceptionalities. Remedial and Special Education, 22(4), 214–225. Foreman, P., & Arthur-Kelly, M. (2008). Social justice principles, the law and research as basis for inclusion. Australian Journal of Special Education, 32(1), 109–124. Frattura, E. M., & Capper, C. A. (2007). Leading for social justice: Transforming schools for all learners. Los Angeles, CA: Corwin Press. Fullan, M. (2001). Leading in a culture of change. Malden, MA: Jossey-Bass. Fullan, M. (2003). Leading in a culture of change: Personal action and guide workbook. Malden, MA: Wiley. Gadberry, D. (2009). Is inclusion working in the music classroom? Journal of Music Therapy, 34(6), 254–273. Grant, C. A., & Gomez, M. L. (1995). Making schooling multicultural: Campus and classroom. Englewood Cliffs, NJ: Prentice Hall. Hall, K., Collins, J., Benjamin, S., Nind, M., & Sheehy, K. (2004). Saturated models of pupildom: Assessment and inclusion/exclusion. British Educational Research Journal, 30(6), 801–817. Hall, T. (2002). Differentiated instruction. Wakefield, MA: National Center on Accessing the General Curriculum. Available at http://www.cast.org/publications/ncac/ncac_diffinstruc. html. Retrieved on August 4, 2009. Hockenbury, D. P. (1999). What is right about special education. Exceptionality, 8(1), 6–14. Hosp, J. L., & Reschly, D. J. (2003). Referral rates for intervention or assessment: A metaanalysis of racial differences. The Journal of Special Education, 37(2), 67–80. Katsiyannis, A., Yell, M. L., & Bradley, R. (2001). Reflections of the 25th anniversary of the individuals with exceptionalities education act. Remedial and Special Education, 22(6), 324–339. King, I. C. (2003). Examining middle school inclusion classrooms through the lens of learner centered principles. Theory into Practice, 42(2), 151–158.

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Klinger, J. K., & Vaughn, S. (1999). Students perceptions of instruction in inclusion classrooms: Implications for students with learning disabilities. Exceptional Children, 66(1), 23–37. Mastropieri, M. A., & Scruggs, T. E. (2001). Promoting inclusion in secondary classrooms. Learning Disabilities Quarterly, 24(4), 265–274. Obiakor, F. E. (2001). It even happens in ‘‘good’’ schools: Responding to cultural diversity in today’s classrooms. Thousand Oaks, CA: Corwin Press. Obiakor, F. E. (2007). Multicultural special education: Culturally responsive teaching. Upper Saddle River, NJ: Pearson Merrill/Prentice Hall. Pugach, M. C., & Warger, C. L. (2001). Curriculum matters: Raising expectations for students with disabilities. Remedial and Special Education, 22(4), 194–196, 213. Rizza, M. G., & Morrison, W. F. (2003). Uncovering stereotypes and identifying characteristics of gifted students and students with emotional behavioral disabilities. Roeper Review, 25(2), 73–77. Sailor, W., & Roger, B. (2005). Rethinking inclusion: School wide applications. Phi Delta Kappan, 86(7), 503–509. Salisbury, C. L. (2006). Principals’ perspectives on inclusive elementary schools. Research and Practice for Persons with Severe Disabilities, 31(1), 70–82. Shealey, M. W., Lue, M. S., Brooks, M., & McCray, E. (2005). Examining the legacy of Brown: The impact on special education and teacher practice. Remedial and Special Education, 26(2), 113–121. Theoharris, G. (2007). Social justice educational leaders and resistance: Toward a theory of social justice leadership. Educational Administration Quarterly, 43(2), 221–258. Tobin, R. (2005). Co-teaching in language arts: Supporting students with learning disabilities. Canadian Journal of Education, 28(4), 784–801. Tomlinson, C. (2004). Fulfilling the promise of the differentiated classroom: Tools and strategies for responsive teaching. Alexandria, VA: Association for Supervision and Curriculum Development. Tomlinson, C. A. (2001). How to differentiate instruction in mixed-ability classrooms (2nd ed.). Alexandria, VA: Association for Supervision and Curriculum Development. Turnbull, R. (2003). A quality of life framework for special education outcomes. Remedial and Special Education, 24(2), 67–74. Vaughn, S., Schumm, J. S., & Arguelles, M. E. (1997). The ABCDE’s of co-teaching. Teaching Exceptional Children, 30(2), 4–10.

PART VI INSTRUCTIONAL METHODS FOR STUDENTS WITH DISABILITIES

CHAPTER 11 BEHAVIORISM WORKS IN SPECIAL EDUCATION Darlene H. Anderson, Michelle Marchant and Nancy Y. Somarriba In 2004, the National Council on Disability (NCD) published a document entitled ‘‘Educational Outcomes for Students with Disabilities,’’ forecasting ‘‘vast changes in the educational landscape’’ (p. 4) for exceptional students. The significant changes that have occurred in special education in recent years are generally attributed to the No Child Left Behind Act of 2001 (NCLB, U.S. Department of Education, 2002) and the Individuals with Disabilities Improvement Act of 2004 (IDEIA, U.S. Department of Education, 2004). Together these two statutes have placed strong emphasis on high academic and behavioral standards for students with disabilities and on the use of research-based or scientifically proven practices (Cook, Tankersley, & Landrum, 2009; Odom et al., 2005). The purpose of this chapter is to explain how the application of behavioral principles can support educators in the achievement of these important aims. It cannot be assumed that using popular instructional and management techniques will improve outcomes for all students. Current research suggests that additional studies are needed to determine whether certain well-known teaching strategies meet the criteria necessary to qualify as evidence-based (e.g., Chard, Ketterlin-Geller, Baker, Doabler, & Apichatabutra, 2009; Montague & Dietz, 2009). In the past, analytical tools used to determine ‘‘what works’’ in both general and special education have included Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 157–173 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019014

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meta-analyses (Forness, Kavale, Blum, & Lloyd, 1997), randomized controlled trials (RCTs; Thomas & Pring, 2004), quasi-experimental studies (Chard et al., 2009), and qualitative research designs (Brantlinger, Jimenez, Klinger, Pugach, & Richardson, 2005). Similarly, criteria for determining evidence-based practices have involved the use of single subject research (SSR), a ‘‘rigorous scientific methodology used to define basic principles of behavior’’ (Horner et al., 2005, p. 165). The current emphasis on high standards of performance for all students, including those with disabilities, requires a methodology such as SSR to establish evidence-based practices. As Horner et al. (2005) pointed out, ‘‘An array of effective interventions is now in use that emerged through single subject research methods’’ (p. 172). Special education and SSR methodology are both strongly linked to applied behavior analysis (ABA) (Marchant, Renshaw, & Young, 2006; Tawney & Gast, 1984), the ‘‘behaviorism’’ we see implemented in general and special education classrooms today. In 1968, the founders of ABA declared, ‘‘If a behavior is socially important y behavior analysis will aim at its improvement’’ (Baer, Wolf, & Risley, 1968, p. 1). If the change in the behavior makes a positive difference for the learner, the behavior is said to be ‘‘socially important.’’ More recently, a prominent behavior analyst similarly stated, ‘‘When properly implemented, ABA is all about meaningful learning’’ (Heward, 2005, p. 319). ABA’s emphasis on teaching new behavior through the application of ‘‘effective and scientifically validated’’ intervention (Van Houten et al., 1988, p. 383) likewise supports the use of strategies aligning with a behavioral perspective. Some experts contend that the behavioral approach has been one of the most salient and productive influences on the interventions used in the field of education since the passage of the Education for All Handicapped Children Act (currently known as the Individuals with Disabilities Education Act (IDEA) of 1990) (e.g., Tawney & Gast, 1984). Principles and methods commonly associated with ABA include positive and negative reinforcement, punishment, extinction, modeling, fading, functional behavioral assessment, contingent praise, self-monitoring, peer mediation, and differential reinforcement (Alberto & Troutman, 2009; Cooper, Heron & Heward, 2007; Heward, 2005).

CURRENT EDUCATIONAL PRACTICE ABA has been described as a precise psychological approach to the study of behavior (Bailey & Burch, 2002), involving well-defined principles that can be

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used in the analysis and modification of individual behavior (Miltenberger, 1997). Special education, on the contrary, has been characterized as ‘‘a customized instructional program designed to meet the unique needs of the individual learner’’ (Gargiulo, 2009, p. 9). Certainly the two disciplines have much in common; indeed, ABA specifically addresses issues at the focal point of IDEA. For instance, ABA’s stance on the right to effective behavioral treatment (Van Houten et al., 1988) is similar to special education regulations regarding the right to an appropriate public education and the right to be educated in the least restrictive environment. Evidence supporting the claim that ‘‘behaviorism works in special education’’ is apparent in many teaching methods shown to be effective in improving learning outcomes for students with disabilities. Specific examples of successful research-tested strategies incorporating behavioral principles include direct instruction to improve the academic performance of struggling young readers (Rupley, Blair, & Nichols, 2009), peer tutoring to improve the spelling skills of secondary students with emotional and behavioral disorders (Bowman-Perrott, Greenwood, & Tapia, 2007), self-regulated strategy development (SRSD) to increase writing ability (Baker, Chard, Ketterlin-Geller, Apichatabutra, & Doabler, 2009; Harris, Graham, & Mason, 2003), and time delay to teach students with moderate to severe disabilities important functional skills (Browder, Ahlgrim-Delzell, Spooner, Mims, & Baker, 2009; Graves, Collins, Schuster, & Kleinert, 2005). The following example illustrates how the application of behavioral principles can result in a successful outcome – in this case, improving the learning of a young student with disabilities receiving academic instruction in an inclusive setting.

BEHAVIOR ANALYSIS APPLICATION Five-year-old Ryan had been diagnosed at the age of 3 years with a developmental delay in speech and language. His Individualized Education Program (IEP) called for related services in speech and language, and Ryan additionally received medication to lessen the effects of hyperactivity. When his noncompliance in the general education classroom noticeably increased, his kindergarten teacher requested that Ryan receive a behavioral assessment to determine whether he needed additional support from the school psychologist or special education teacher. Direct observations were conducted to identify Ryan’s specific problem behaviors and the conditions in which they were most likely to occur. The data indicated that when Ryan

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was asked to perform a particular academic task, he yelled, ‘‘I don’t want to,’’ or ran away, refusing to work. The benefit (positive consequence) for Ryan seemed to be successfully avoiding the unwanted academic task. Because Ryan’s noncompliant behavior was becoming more frequent, observers assumed that avoiding the unwanted task was a stronger reinforcement than the anticipated punishment, that is, sitting on a chair during a brief time-out. The intervention derived from the behavioral analysis consisted of three components: (a) the academic task was simplified by breaking it down into smaller, more manageable parts; (b) Ryan was immediately given high levels of positive reinforcement consisting of one-on-one adult attention each time he completed a segment of the assigned task; and (c) he was no longer allowed to avoid task completion. The positive effects of the intervention were documented by counting the number of times Ryan performed the academic task within a given time period and comparing the result with his previous behavior and academic performance. With the successful outcome of the intervention, Ryan was able to remain in the general education classroom, rather than being referred for more intensive special education services. Observers found that Ryan was able to transfer his newly learned skills to various contexts as additional teachers assumed responsibility for implementing the intervention. Key behavioral applications shown to be effective when working with students with and without disabilities are highlighted in Ryan’s experience: (a) delivering positive reinforcement immediately following the desired behavior, (b) eliminating reinforcement for inappropriate behavior, (c) changing conditions (e.g., task difficulty) to increase the likelihood of successful task completion, (d) monitoring directly and continuously to document intervention effects, and (e) planning for skill transfer and maintenance.

ROLE OF BEHAVIORISM IN THE CLASSROOM In recent years, there has been a prominent increase in the inclusion of special needs students like Ryan in public schools and general education classrooms (U.S. Department of Education, 2004). The finding that students with special needs tend to exhibit challenging behavior is well established (McConnell, Hilvitz, & Cox, 1998). Due to the influx of special needs children and youth into inclusive environments, teachers face the challenge of meeting the needs of students with varying profiles and

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characteristics. The question is ‘‘How equipped are all teachers, including general educators, to manage classrooms representing a broad array of academic, behavioral, and functional needs?’’ Many teachers are insufficiently trained and supported to effectively handle this situation (Killu, 2008). Managing difficult student behaviors, whether academic or social/emotional, is one of the greatest concerns of teachers (McKinney, Campbell-Whately, & Kea, 2005). Behaviors cited by educators as being particularly troublesome include ‘‘attention problems, off-task behavior, difficulty with task completion, disruptions, lack of organizational skills, verbal and physical outbursts, passive and aggressive behavior, and poor social and interpersonal skills’’ (McConnell et al., 1998, p. 10). To effectively implement behavioral techniques, teachers would do well to view problem behavior as an opportunity to ‘‘teach’’ rather than as an opportunity to punish or suppress student responding (Peterson & LacyRismiller, 2005). ABA must be recognized as a discipline that can support educators in teaching new skills and effectively coping with instructional challenges. As mentioned previously, ABA accomplishes this aim by targeting academic and nonacademic behaviors of social significance (Cooper et al., 2007). Initially, the educator(s) must identify a ‘‘problem’’ behavior and then implement strategies, preferably positive strategies, which support the replacement of a problem behavior with an appropriate behavior serving the same function (or purpose). Thus, educators who commit to improving challenging behavior and select a behavioral approach must be well informed in the application of ABA principles and strategies; when implemented correctly, these strategies are considered to be evidencebased (Steege, Mace, & Ferry, 2007). Important steps in the behavior analytic process include (a) analyzing the problem behavior and environment, (b) determining the function of the problem behavior, (c) selecting an appropriate replacement behavior with a solid objective, (d) teaching and supporting the replacement behavior, (e) generalizing and maintaining the behavior, and (f ) monitoring the progress and outcomes of the target behavior. Although this list is not comprehensive, we believe that these six steps offer effective, manageable tools to support classroom teachers who are seeking to prevent and intervene with the challenges encountered in an inclusive classroom. These strategies offer educators sound tools needed to provide quality services to students who have varying needs, particularly those classified with a disability. In the next section, we seek to accomplish the following objectives: (a) define the six steps of the behavior analytic

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process and their purposes, and (b) describe how to implement each strategy in an educational setting.

ANALYZE THE PROBLEM BEHAVIOR AND ENVIRONMENT What is it? Why do it? As teachers encounter difficult instructional and behavioral challenges in their classrooms, they must be vigilant in evaluating the problem(s) at hand, using both informal and formal assessment methods. These methods include analyzing archival records, interviewing, evaluating permanent products, and observing the behavior directly. Completing an accurate analysis of the situation up front, when the problem has only begun to emerge, helps the educator define the terminal objective of the intervention and select the criterion for acceptable performance, which ultimately holds the implementer of the intervention accountable (Alberto & Troutman, 2009). It also provides a clearer understanding of the factors in the environment that may be contributing to the problem. How to Implement Accessing a student’s cumulative folder, generally available in the school’s front office, allows a teacher to analyze written records and review background information associated with the student’s health, physical, as well as sensory and learning needs. Interviewing may consist of talking with the student’s teachers or related service personnel (e.g., school psychologist, speech language pathologist, and occupational therapist), the student’s parents, and the student, if appropriate. Administering behavior assessments such as the Behavioral and Emotional Screening System (BASC-2; Reynolds & Kamphaus, 2004) and Conner’s Rating Scales (CRS-R; Conners, 2000) to parents, teachers, and students is a way to gather additional information relating to a student’s social and emotional needs. Direct observation of the student’s interactions with other students, teachers, and the environment can be recorded through anecdotal notes, with a scatter plot analysis, or as part of an Antecedent-Behavior-Consequence (A-B-C) analysis. This informationgathering process taps rich data sources, useful in determining the interaction between the student and the environment. The goal in such efforts is to arrive

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at a clear understanding of the interplay between contextual factors and the student’s behavior. An individual student’s learning style skill level and characteristics must additionally be considered when designing academic and behavioral intervention. For example, many children with learning disabilities (LD) experience frustration when they are asked to complete a task involving reading and writing. A short attention span and high levels of distractibility can create additional challenges for students with LD, particularly in academic settings in which personal connections with the classroom teacher are infrequent and levels of adult supervision limited. Such was the case with 9-year-old Shelby, identified as having a specific learning disability (SLD) at the age of 8 years. Shelby spent a large amount of her time looking around the room, playing with items at her desk, and talking to peers when she was supposed to be working. Results of an archival records review, behavioral assessment, and direct observation suggested that Shelby’s off-task behavior seemed to occur most frequently when she was asked to perform a difficult task and teacher assistance was unavailable. As instances of the off-task behavior were becoming more frequent, the teacher’s verbal reprimands, delivered as a punitive consequence when the behavior occurred, appeared to be ineffectual. Evaluating the antecedents and consequences preceding and following the problem behavior can help educators identify contextual factors in need of change and determine behavioral function.

DETERMINE THE FUNCTION OF THE BEHAVIOR PROBLEM What is it? Why do it? Once the interview and A-B-C data are collected, the next step is to evaluate the data and determine the effects that antecedent and consequent events have on the target behavior. Following this analysis, the function of the behavior can be identified. As teachers analyze the data, they look for trends across settings, times, and people, specifically focusing on the antecedents that precede or set the occasion for the target behavior and the consequences that follow or maintain the behavior (Alberto & Troutman, 2009; Umbreit, Ferro, Liaupsin, & Lane, 2007). The final outcome of this endeavor is to create a statement that clearly communicates the function of the problem behavior (Umbreit et al., 2007).

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How to Implement Reviewing multiple data sources is essential to identifying the function of a student’s behavior. Archival records provide background details about attendance, educational information, medical/health factors, and behavior concerns. Reviewing these records permits the teacher to explore patterns of behavior and performance across time and contexts. For example, the information collected may include various course subjects, grade levels, and people involved (e.g., teachers, related service personnel, administrators, parents, and health care providers). Archival record data are supported or negated as people associated with the student are interviewed about the student’s performance. The interviewer may ask questions such as (a) What happens before the problem behavior?, (b) Where does the behavior occur?, and (c) When does the behavior occur? A-B-C observations, in which antecedents and consequences affecting the target behavior are directly observed, likewise provide important input for developing a hypothesis concerning the function of behavior. As the teacher observes the student and the target behavior, she/he specifically records what happens before the behavior, what the behavior looks like during a given time period, and what happens following the behavior (Liaupsin, Scott, & Nelson, 2001). Incorporating information from all sources, the teacher aggregates and analyzes the data to determine the specific variable(s) that may be triggering or maintaining the behavior. For example, children with emotional difficulties sometimes exhibit aggressive behavior requiring immediate attention. Fifteen-year-old Enrique, a child with an emotional disturbance, was frequently out of his seat, kicking classmates’ chairs, putting gum in their hair, or hitting whoever was closest to him. A perusal of school records indicated that Enrique had a history of referrals to the counseling office for disruptive behavior. Results of the A-B-C observations suggested that Enrique’s problem behavior tended to escalate just before the ‘‘round robin math game’’ in which students were expected to take turns calling out homework answers. Based on a descriptive analysis incorporating all of the information collected, the math teacher proposed a function statement related to the problem behavior: During math instruction, Enrique disrupts his peers to avoid remaining in class and having to participate in the ‘‘round robin call out’’ math game. Other possible behavioral functions that may be identified in similar situations include attention and sensory stimulation (Alberto & Troutman, 2009; Umbreit et al., 2007).

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SELECTING A REPLACEMENT BEHAVIOR What is it? Why do it? Once the data have been thoroughly analyzed and the function of the behavior identified, the teacher selects an appropriate replacement behavior. The replacement behavior must serve the same function as the problem behavior and be well defined. To be well understood, the behavioral definition must include a clear description, allowing all parties involved to effectively discuss, observe, count, teach, and support the target behavior (Alberto & Troutman, 2009). A concrete definition encourages effective monitoring of the student’s progress and facilitates recognition of desired change.

How to Implement The teacher needs to create what is known as an operational definition of the target replacement behavior. This consists of describing the behavior in a way that makes it observable, measurable, and repeatable (Alberto & Troutman, 2009). It is critical to select descriptors that are specific (Liaupsin et al., 2001). One way to accomplish this is by selecting action verbs that are directly observed, such as write, walk, and say, rather than vague verbs, such as think, finish, and use (Alberto & Troutman, 2009). These verbs are incorporated into the written definition provided to all those involved in carrying out the student’s educational program. It is likewise recommended that educators provide both examples and nonexamples of the replacement behavior. For example, if a student is chronically out of seat and the target replacement behavior is ‘‘will stay in seat,’’ the teacher may construct a statement that contains an operational definition of the behavior: for example, ‘‘The student will sit with his buttocks on the chair, with all four legs of the chair on the floor.’’ A nonexample of the same definition may be phrased ‘‘The student sits partially on the chair and rocks backward in the chair.’’ An additional recommended approach to writing and sharing an operational definition of the replacement behavior is to create a behavioral objective (Alberto & Troutman, 2009; Umbreit et al., 2007). When children lack the necessary verbal skills to effectively communicate their needs, it may be appropriate to identify a replacement behavior that

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serves a communicative function. For example, Naoko, who was 4 years old when she was identified with aphasia, a communication disorder involving speech impairment and problems with speech comprehension, refused to pick up her toys when asked. Rather than comply with the teacher’s request, Naoko ran around the room, threw her toys at the teacher, and began to tantrum – kicking and screaming until she was put in the time-out room. Results of the A-B-C observations suggested that the function of Naoko’s behavior was to escape an overstimulating ‘‘music hour’’ following cleanup time. Naoko’s target replacement behavior, ‘‘asking politely for quiet time,’’ was operationalized as ‘‘Naoko will pick up a cue card displaying a picture of a child in quiet time and present it to the teacher when she wants to be excused from activities that are too stimulating.’’

TEACHING/SUPPORTING THE REPLACEMENT BEHAVIOR What is it? Why do it? Once an appropriate replacement behavior has been defined, the teacher must ensure that strategies are selected and implemented to help the student acquire and use the replacement behavior. These strategies will generally consist of one or more of the following four intervention methods: (a) modification of the setting (classroom or other context[s]), (b) instructional methods for teaching the desired behavior, (c) procedures for reinforcement, and (d) procedures for correction (Alberto & Troutman, 2009; Umbreit et al., 2007; Utah State Office of Education, 2008). How to Implement The hypothesized function of the target behavior will impact the teacher’s decision as to which intervention strategy or strategies will be used. It is beyond the scope of this chapter to provide a comprehensive list from which a teacher might select an intervention. However, to illustrate recommended evidence-based methods, a few strategies will be described for each of the four methods outlined above. To modify the setting (classroom or other context[s]), the teacher could reteach expectations/routines, modify assignments and curriculum, increase supervision, use specialized technology (such as a communication board), or

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adjust who is present when the behavior is likely to occur. Possible instructional techniques might include teaching a specific social skill, communication skills, study skill(s), or academic skills. This could be accomplished by individual instruction, demonstration, guided practice, group instruction, role play, cooperative learning, peer tutoring, prompts, physical guidance, fading, or chaining (Alberto & Troutman, 2009). For example, Keisha, a 10-year-old child with an intellectual disability, frequently engaged in verbal and physical outbursts during class activities. A-B-C data suggested that Keisha’s acting out behavior might be related to the need for teacher and peer attention. Results of a behavioral observation likewise indicated that Keisha lacked the skills necessary to participate and interact positively with her classmates. As the identified replacement behavior was a social skill that needed to be explicitly taught, that is, ‘‘How to Join in,’’ instructional techniques were implemented with the entire class to teach the children how to join in with their peers; opportunities to practice the skill were additionally provided through role play. Behaviorism (i.e., behavior change) is equivalent to using positive reinforcement to strengthen desired behaviors that are incompatible with the problem behavior (Kazdin, 2001). This statement implies that positive reinforcement strategies should be embedded within the intervention to increase the frequency of the desired behavior. The teacher must take three preliminary steps before establishing a positive reinforcement system: (a) identify potential reinforcers, (b) establish specific behavioral criteria, and (c) determine the schedule of reinforcement. Once these preliminary steps have been completed, the teacher will determine how to monitor and deliver the reinforcement. This can be accomplished in various ways: for example, specific reinforcement approaches include self-monitoring, behavioral contracting, group contingencies, home notes, lottery/raffle tickets, token economies, a visual chart, or a mystery motivator (Alberto & Troutman, 2009; Rhode, Jenson, & Reavis, 1992). Referring to the example above, Keisha’s newly learned skills were strengthened by rewarding her and the other children in the class with a lottery ticket that could be traded in later for a prize, each time they were ‘‘caught’’ using the skill in class or on the playground. When incorporating ABA principles, an emphasis on the use of positive strategies to increase the desired behavior is preferred. However, when the frequency of the target problem behavior must be reduced, correction procedures can be implemented. Evidence-based strategies within this category include differential reinforcement, extinction, punishment, response cost, time-out, and overcorrection (Alberto & Troutman, 2009; Utah State Office of Education, 2008).

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In Keisha’s case, correction procedures included reteaching the social skill, delivering corrective feedback, and taking away lottery tickets when the problem behavior resurfaced. It is essential that the teacher and others involved in using the correction procedures be well trained and familiar with the legal implications associated with these strategies (e.g., Utah State Office of Education, 2008).

GENERALIZING/MAINTAINING THE TARGET BEHAVIOR What is it? Why do it? As the student acquires the target behavior and begins to use it more fluently, the teacher must ensure that the behavior change transfers to other contexts and maintains over time. This is the ultimate and most meaningful form of behavior change because it ensures that the student will be inclined to use the behavior as part of her repertoire, thus influencing herself and society for the better (Alberto & Troutman, 2009). How to Implement Generalization requires careful planning. A teacher needs to work with others, including teachers, students, administrators, related service personnel, lunchroom personnel, playground personnel, and especially parents, to promote the transfer and maintenance of the behavior. One way this can be accomplished is to apply the same reinforcement or instructional strategy across various settings. For example, to encourage Jared, a 12-year-old child with autism, to apply a newly learned skill (asking for help) in multiple settings, Jared’s teacher organized a meeting that included the school psychologist, paraprofessionals, Jared’s parents, his evening babysitter, and the school custodian. All of these individuals received instruction in the intervention and were involved in its implementation. This ‘‘team approach’’ proved to be successful in decreasing Jared’s target behavior. Another technique is to design the intervention strategy so that it matches the ‘‘natural’’ environment (e.g., the general education classroom, a grocery store). A third technique is for the teacher to teach the behavior in such a way that it can be used with various examples or stimuli (e.g., reading various books, answering different types of telephones). Finally,

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manipulating the frequency and amount of reinforcement can facilitate generalization (e.g., reduce the frequency of reinforcers). In the above example, Jared received positive attention and fuzzy stickers to play with any time he asked for help appropriately. Eventually, the fuzzy sticker rewards were replaced with verbal praise, lessening Jared’s dependence on tangible rewards.

MONITORING THE TARGET BEHAVIOR What is it? Why do it? To determine whether the target behavior is changing in the intended direction, the teacher must evaluate it regularly. Continual monitoring (versus pre-post assessment) throughout all five steps allows the teacher to observe progress (or the lack of it) associated with the targeted behavior. It also allows implementers to determine when adjustments to the intervention need to be made. Lastly, it offers a summative evaluation of the impact of the intervention on the student’s behavior (Alberto & Troutman, 2009).

How to Implement Selecting the most effective monitoring system is essential for observing change (Alberto & Troutman, 2009). Umbreit et al. (2007) divided data collection systems into two categories: event-based and time-based. The topography of the behavior impacts which system is selected. If occurrences of the behavior are uniform, meaning that each occurrence is similar to the others, it is best monitored through an event-based approach (Alberto & Troutman, 2009; Umbreit et al., 2007). Event-based methods consist of (a) permanent products (e.g., collecting daily math seatwork), (b) frequency counts (e.g., marking a tally every time the student raises his hand), (c) rate (e.g., recording the number of words read in a 1-minute passage timing), and (d) intensity/magnitude (e.g., indicating the level of hitting or yelling) (Alberto & Troutman, 2009; Umbreit et al., 2007). Although Lucas attended a school for the blind during kindergarten, he began first grade in a public school. Shortly after his enrollment in the new school, his problem behavior, defined as yelling out answers when the teacher asked a question, escalated. The A-B-C observational data indicated that Lucas’ problem behavior allowed him to receive sensory stimulation

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because other students touched his arm when he yelled out. The intervention involved altering the classroom environment, specifically moving Lucas away from the other children so that they could not touch him. In addition, Lucas was taught to use the replacement behavior (to raise his hand) instead of yelling. The teacher reinforced the replacement behavior by touching Lucas’ hand each time he remembered to raise his hand to get her attention. The goal of the intervention was to increase the number of times Lucas raised his hand and decrease the number of times he yelled out. The IEP team determined that because it was uniform in occurrence, Lucas’ handraising behavior was event-based. Because the teacher was concerned with the frequency of Lucas’ behavior, frequency count was selected as the measurement system to be used in monitoring his progress. Specifically, the teacher counted the number of times Lucas raised his hand and compared this total to the number of times he yelled out. These data were collected every day. If a behavior is not uniform in length, then a time-based approach is more effective (Umbreit et al., 2007). Time-based methods include (a) duration (e.g., recording the length of time a student sits in his chair), (b) latency (e.g., recording the length of time it takes a student to start to comply with a teacher’s instruction), and (c) interval recording (e.g., indicating the occurrence or nonoccurrence of the behavior in a table that is divided into intervals of time – such as 10-second intervals). Other considerations associated with monitoring progress include determining the ideal time, length, frequency, and location of the observation. Emphasis must be placed on the notion of continual ongoing data collection, procedures deemed essential to capturing the progress and outcomes of the targeted behavior. The steps outlined above encompass a positive, function-based approach to intervention. Although future investigations are needed to fully address the quality indicators set by Horner et al. (2005) and to clearly establish function-based methodology as evidence-based, current levels of empirical support are promising (Lane, Kalberg, & Shepcaro, 2009).

CONCLUSION To the extent behavioral strategies are tailored to meet the needs of individual students, teachers, and other consumers, they inspire consumer satisfaction or social validity. This concept, increasing in importance in the field of ABA, emphasizes matching educational programming to the individuals involved and to the environment in which program

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implementation will occur (Albin, Lucyshyn, Horner, & Flannery, 1996). The view that educators need to focus on ‘‘fixing problem contexts, not problem behavior’’ (Carr et al., 2002, p. 8) is consistent with the application of positive behavior support (PBS) at individual, classwide, and schoolwide levels, a promising framework ‘‘firmly rooted in a behavior analytic tradition and a solid body of research’’ aimed at improving learning environments and outcomes for all students (Sugai & Horner, 2006, p. 246). The current widespread adoption of PBS strategies suggests the underlying behavioral principles are working, further validating their use. In brief, behaviorism works in special education because it is an effective and efficient approach, grounded in evidence-based practices shown to benefit students with various learning needs. As suggested earlier, analyzing and reflecting on a difficult classroom situation involves asking the following questions: (a) What happened? (What was the problem behavior?); (b) Why did it happen? (What were the antecedents and consequences that preceded and followed the behavior?); (c) What might this mean? (How might the situation have been handled differently?); and (d) What are the implications for intervention? (Hole & McEntee, 1999). The efficacy of gathering functional assessment information to design effective intervention strategies for students with disabilities has been demonstrated (Horner, 2000) and is consistent with the notion of functionbased support, the research validated process described in this chapter.

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CHAPTER 12 OTHER INNOVATIVE TECHNIQUES: POSITIVE BEHAVIOR SUPPORTS AND RESPONSE TO INTERVENTION John J. Wheeler and Michael R. Mayton Positive behavior supports (PBS) and response to intervention (RTI) are two innovative practices that have emerged within the field of special education and continue to gain momentum among practitioners (Kazdin, 2008; Wheeler & Richey, 2010). The purpose of this chapter is to provide a background as to the evolution of these practices, their fundamental components, and their efficacy in terms of their ability to address behavioral and learning challenges experienced by students with disabilities and those students deemed to be at-risk. It is our intent to address these practices from a developmental and historical perspective and within the context of evidence-based practices. The aim of this chapter is to extend the reader’s awareness of these approaches and increase the functional utility of these models within public schools.

ORIGINS OF POSITIVE BEHAVIOR SUPPORTS The 1997 Reauthorization of the Individuals with Disabilities Education Act (IDEA) ushered in a new paradigm for addressing challenging behavior in Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 175–195 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019015

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students with disabilities with the advent of PBS. However, the groundwork for the PBS movement initiated with a paper published by Horner and colleagues (1990) that described the need for nonaversive behavioral interventions in working with persons with severe disabilities. Although some have seen PBS as an outgrowth of applied behavior analysis (ABA) (Anderson & Freeman, 2000), others within the field of behavior analysis have been critical of PBS as being spawned more out of an ideological bent rather than as a research-based model (Johnston, Foxx, Jacobson, Green, & Mulick, 2006). So how does PBS align with ABA? PBS has been defined by Carr et al. (2002, p. 4) as an ‘‘applied science that uses educational methods to expand an individual’s behavior repertoire and systems change methods to redesign an individual’s living environment to first enhance the individual’s quality of life, and second, to minimize his or her problem behavior.’’ Clearly, the applications of behavioral principles are evident in PBS and perhaps the most striking difference is that PBS has placed a great deal of emphasis on quality-of-life and person-centeredness at its core. Carr et al. (2002) in their seminal article alluded to the emergence of PBS and point to ABA, the normalization and inclusion movement and person-centered values as being the foundations of PBS. Additional support for PBS has been fostered through the passage of key legislation aimed at the implementation of PBS practices within school settings to address challenging behavior at the primary (school-wide), secondary (classroom), and tertiary (individual) levels. Mandates such as the 1997 Reauthorization of IDEA and the most recent legislative mandate, the 2004 Individuals with Disabilities Education Improvement Act reaffirmed the use of PBS and that methods such as functional behavior assessments (FBAs) be conducted for students with disabilities who demonstrate challenging behaviors deemed serious enough by Individual Education Plan (IEP) teams to consider a change in the student’s placement (i.e., suspension or expulsion) or that represent chronic forms of challenging behavior that interfere with their learning and that of others (Wheeler & Richey, 2010). So in attempting to draw a comparative understanding between ABA and PBS, it is safe to say that the foundations of PBS lie largely in the contributions of research-based demonstrations from the field of ABA. Perhaps, one of the most distinguishing features of PBS that sets it apart from behavior analysis is that it attempts to extend a comprehensive model of ‘‘supports’’ aimed at enhancing the quality-of-life for an individual, rather than examining the efficacy of a ‘‘treatment’’ directed at a specific target behavior in isolation of the broader context surrounding it.

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PHILOSOPHICAL FOUNDATIONS OF PBS PBS is learner-centered, positive and nonpunitive, directed toward understanding the function(s) of challenging behavior and the setting event/ antecedent relationships that precipitate these responses in learners (Wheeler & Richey, 2010). It utilizes FBA to assist in identifying contextual variables that precipitate and maintain challenging behavior and in-turn result in the development of comprehensive multifaceted interventions that focus on (a) manipulating antecedent contextual variables or ‘‘triggers,’’ (b) teaching new skills to promote success within the learning environment, and (c) altering the contingencies for both positive and challenging behavior. To fully comprehend how to respond to problem behavior, we must understand the following assumptions offered by Crone and Horner (2003): 1. Behavior is functional and serves a purpose – The functions of challenging behavior include gaining access to social or tangible reinforcement, to avoid or escape unpleasant or aversive situations and to obtain or modify sensory input. 2. Challenging behavior is inefficient – For learners with disabilities who may have limited skill repertoires and based on their previous learning history, challenging behavior often serves, as their primary method for obtaining their desired needs in the absence of appropriate skill sets. These challenging forms of behavior unfortunately are not efficient in general terms for expanding the options for these individuals. 3. Behavior is predictable and contextually relevant – Challenging behavior is most often predictable and related to environmental ‘‘triggers’’ that precipitate these responses within certain contexts. Therefore, it is essential to understand the environments in which problem behavior occurs and the specific antecedents or ‘‘triggers’’ that elicit them. 4. Replacement behaviors can be taught – Once we have determined the function(s) associated with the behavior of concern and the antecedents and consequence events related to the occurrence of these behaviors, we can design an intervention plan. The intervention plan should have three major foci, namely to (a) manage antecedents so that the problem behavior is decreased or eliminated, (b) teach replacement skills that are functionally equivalent thus making the problem behavior less efficient for the learner in obtaining their needs, and (c) the use of differential reinforcement and the provision of meaningful consequences for desired behavior.

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ACCEPTANCE OF PBS WITHIN SCHOOLS Historically many schools have attempted to address problem behavior through the use of school-based discipline programs involving consequencebased approaches such as time-out, loss of privileges, corporal punishment, suspension, and ultimately expulsion. The use of such reactive procedures have been deemed to be ineffective in the long term at reducing problem behavior and offer little in terms of teaching meaningful replacement skills. Sadly, evidence of these reactive approaches still exists as evidenced by a report from the U.S. Office for Civil Rights at the U.S. Department of Education that indicated that 223,190 students nationwide received corporal punishment during the 2006–2007 school year (Human Rights Watch, 2008). Despite these data, there has been a favorable response among schools in terms of PBS. For example, in terms of school-wide PBS, more than 4,000 schools nationwide reported using PBS as the method of choice (U.S. Department of Education, 2005). Furthermore the number of schools that will adopt schoolwide PBS will significantly increase, perhaps even doubling in the next several years (U.S. Department of Education, 2005). The benefits of using PBS within schools is perhaps enhanced by the user friendly nature of this methodology and the direct benefits that the method offers, among which are the improved academic and enhanced social competencies of students and a safe environment for teaching and learning to occur (Bohanon et al., 2006).

COMPONENTS OF PBS As previously mentioned, PBS is a comprehensive model aimed at providing behavioral supports across three levels. These include school-wide PBS. School-wide PBS is directed toward targeting the majority of students within a school, approximately 80–85% with the focus being aimed at improving school climate for all students, a safe environment in which teaching and learning can occur and prevention of problematic behavior. This is perhaps best illustrated by a reduction in discipline referrals and improved student performance outcomes. School-based teams composed of teachers, administrators, related service personnel, and paraprofessionals are necessary when implementing school-wide PBS. An operational plan for PBS implementation typically involves having an understanding of what the behavioral expectations are in terms of student conduct, posting these expectations throughout the school and communicating them to students, parents, teachers, administrators, and staff. When implementing

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school-wide PBS, planning becomes an integral part of the process. Fidelity of PBS implementation is vital to the success. This requires that all personnel be consistent with how they implement these practices, respond to appropriate behavior on the part of students, and identify behaviors in need of support. Last, successful school-wide PBS depends on the application of PBS across classroom and individual learners who have more significant and chronic behavioral challenges in need of sustained and targeted interventions. Secondary or classroom behavioral supports generally affect approximately 5–15% (Crone & Horner, 2003) of the school population. Classroom-based interventions designed to foster group contingencies for success are favored and are primarily targeted as a means by which to address the behavioral support needs of learners deemed to be at-risk for challenging behavior. Typically, token economy programs and team-based models of reinforcement can serve as effective group contingency in such programs (Kazdin, 2008). With team-based models, students earn points based on the performance of their respective team or group. This is an excellent example of how classroom-based PBS can be effective for promoting a climate for learning and student success. Finally, at the tertiary or individual student level, behavior supports are utilized to meet the chronic or more challenging behaviors that are in need of sustained supports. This typically involves anywhere between 3 and 7% (Crone & Horner, 2003) of the student population within a respective school. The objective of providing individualized behavior supports is largely based on the collection of data during the functional assessment phase. FBA is a process by which data are collected specific to a student and a target behavior(s) that have impeded the student’s learning and that of others (Kazdin, 2008). The FBA usually begins with a structured interview of teachers, parents, and staff members who are familiar with the student. The structured interview asks probing questions relative to the description of the behavior of concern, its frequency and topography and any predictable events that occur before or after the behavior that serve to precipitate and or reinforce it. Following the structured interview, a review of student records and performance data is often helpful to gain a better understanding of the student, and then observational data are gathered. Observational data are obtained through various means, including the use of scatterplot data, that is, a frequency of the occurrence of the target behavior across 15-minute time intervals throughout the day across a full-week. Classroom observations involving the use of A-B-C

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(antecedent-behavior-consequence) recording is conducted to determine the antecedents or triggers that elicit the target behavior and the consequences that reinforce and maintain the behavior. The data from these multiple sources are compiled, and the school-based behavior support team discusses the results from the FBA. Then the team draws conclusions from the data and arrives at plausible hypotheses as to the cause/effect relationships between plausible antecedents and consequences and their proximity to the behavior. Once these hypothesis statements have been established, the team then begins to assemble the behavior support plan (BSP). Mostly, PBS has focused on multifaceted interventions aimed at minimizing the effects of distant setting events and antecedents through things such as task redesign and environmental engineering. The intent of these actions is to prevent any triggering effects on the behavior, while actively teaching replacement behaviors that serve the same function for the student, but in an appropriate form. Approaches such as differential reinforcement are used to provide meaningful consequences to the student for approximating desired behavioral responses. Consideration is also given to environmental and quality-of-life enhancements that can serve to enhance the acquisition of new skills within the student’s behavioral repertoire. Last, replacement behaviors are selected that serve the same function for the learner as to maximize their efficiency. A failure to recognize this latter point will often result in a failure to promote and sustain the new behavior. In essence, PBS seeks to change the ‘‘form’’ of a behavior, that is, what it looks like so to speak rather than the ‘‘function’’ or purpose it serves.

SUMMARY AND CONCLUSIONS In summary, the immersion of PBS practices within the schools has substantially increased since the initial mandate in 1997 of the Reauthorization of the IDEA. Despite this increasing trend, gaps in the quality of these services continue to exist, some perhaps due to philosophical conflicts and also perhaps due to a lack of training and fidelity in the implementation of these intervention methods. More work needs to be done to examine the ‘‘evidence-base’’ concerning these practices given that we are yet to have the volume of controlled studies needed to meet the operational standard that Horner et al. (1990) have recommended. This is particularly the case where school-wide implementation of PBS is concerned as this often involves a

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myriad of interventions tied to a treatment package making systematic and controlled study difficult given the volume of extraneous variables.

RESPONSE TO INTERVENTION RTI is a multilevel framework for systematic progress monitoring and intervention delivery that is currently being utilized as a means of attempting to prevent worsening academic and behavioral difficulties within individual students, identify the presence of disabling conditions, and, ultimately, integrate research-based interventions into teaching practice to enhance educational efficacy for all learners. RTI’s dissemination and use within public schools has been driven by a unique convergence of legislative and societal forces, and its implementation has seemingly added to the influence of the inclusion movement to further blur the historically dichotomous philosophical and ideological relationship that has existed between the overarching missions of general and special education. It is arguable that RTI has been at least partially responsible for increasing the relative sensitivity of general education toward better meeting the needs of struggling and at-risk learners before they experience the extensive and prolonged levels of academic and behavioral difficulties that can otherwise lead them closer and closer to more restrictive educational placements. Like PBS, RTI has its foundations in ABA and provides a model of service delivery based on early intervention and the prevention of more severe forms of academic and behavioral difficulties. Unlike PBS, RTI is a framework within which evidence-based interventions are selected and delivered and ongoing, data-based educational decisions are made, rather than a type of ‘‘applied science’’ (Carr et al., 2002, p. 4) or specific intervention in and of itself.

Evolution of a School-Based Methodology RTI is not a new approach. In fact, its ‘‘active ingredients’’ are decades old, utilizing time-tested methodologies such as setting measurable and observable goals and objectives, data-based decision making, and the scientific technology of single-subject research. These conceptual workings have their roots buried deep in the origins of behavior analysis and its application to humans and the problems of society at large. However, it has taken decades of societal change and legislation for the behavior analytic model to be applied to education on the nearly universal scale that we now

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see with RTI. The broad stages of this evolutionary process can be categorized as: (a) the movement to apply the behavior analytic model to the problems of society at large, (b) application of single-subject research methodology and behavioral principles to problems in education, and (c) the increasing responsibility and accountability of public schools toward students from all facets of society. Table 1 outlines some selected, important events that shaped this evolution.

Definition, Tiers, and Components There is no single definition of RTI to be found in the literature. In fact, there are almost as many definitions of RTI as there are authors who write about it (see Table 2 for examples). However, from the mix of definitions we can glean a set of common themes, that is, that RTI is a process that involves (a) a multitier system that incrementally builds in intensity, (b) identification and utilization of a range of research-based interventions that are systematically chosen and applied in response to a student’s change in performance (or lack thereof), and (c) systems and procedures for identifying students at-risk and conducting formative and summative evaluations of behavioral and academic progress. Making assimilation of the model even more potentially complicated is the fact that multiple types of RTI implementation approaches have been identified within the literature base, including problem-solving and standard protocol approaches (Fuchs & Fuchs, 2007; Johnson & Smith, 2008; Wright, 2007), as well as hybrid and other approaches. It should be noted that RTI systems can contain any number of tiers of prevention placed between general and special education settings, but the use of three tiers (including general and special education as the first and final tiers, respectively) is generally recommended and described within the literature (e.g., Fuchs & Fuchs, 2007). Within tier I of the model, instruction is provided in general education settings and involves all students. The focus at this level of the process is on prevention, and heavily emphasized are empirically validated, evidence-based instructional practices and student progress monitoring that is conducted at the school or district level. If a student is not performing successfully within this tier, one of the main points of investigation should be: Can we be reasonably certain that the student’s lack of successful performance is not due to a lack of sufficiently applied, efficacious instructional practice? In addition to functional systems for school-wide/district-wide monitoring of student performance, procedures

Application of single-subject research methodology and behavioral principles to problems in education

Movement to apply the behavior analytic model to the problems of society at large

Stage

Single-subject research designs are used to study academic behaviors (e.g., Glover & Gary, 1976), behavior management (e.g., Hall et al., 1968), social behavior (e.g., Hauserman et al., 1973), early intervention (e.g., Hart & Risley, 1975), teacher behavior (e.g., Jones et al., 1977) Publication of The Technology of Teaching (Skinner, 1968) Publication of What Psychology Has to Offer Education – Now (Bijou, 1970)

Mid-1960s to 1970s

1970

1968

1968

Publication of The Development of Performance in Autistic Children in an Automatically Controlled Environment (Ferster & DeMyer, 1961) The seminal article, Some Current Dimensions of Applied Behavior Analysis (Baer, Wolf, & Risley, 1968) is published

1961

Milestone/Event Science and Human Behavior (Skinner, 1953) is published

Year

Teaching and learning processes are comprehensively analyzed and deconstructed in behavioral terms ‘‘The concepts and principles of behavioral analysis are applied directly to the classroom teaching situation: to the observable behavior of the pupil in relation to the teacher’s techniques of instruction, the instructional materials, the contingencies of reinforcement, and the setting conditions’’ (Bijou, 1970, p. 67)

Developing single-case methodologies add to the usability and applicability of applied behavior analysis to real-world educational situations and problems

‘‘The methods of science have been enormously successful wherever they have been tried. Let us then apply them to human affairs’’ (Skinner, 1953, p. 5) Charles B. Ferster pioneers with children with autism the application of techniques from laboratory research in behavior analysis (Kennedy, 2005, p. 21) ‘‘A society willing to consider a technology of its own behavior apparently is likely to support that application when it deals with socially important behaviors, such as retardation, crime, mental illness, or education’’ (Baer, Wolf, & Risley, 1968, p. 91)

Significance

A Sampling of Important Milestones in the Evolution of RTI.

1953

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The increasing responsibility and accountability of public schools toward students from all facets of society

Stage Passage of Public Law 94-142: The Education of All Handicapped Children Act U.S. Department of Education regulations are passed (34 C.F.R. 300.541, 1977) regarding the learning disabilities category outlined within P.L. 94-142

P.L. 94-142 reauthorized: The Individuals with Disabilities Education Act (IDEA)

Conceptualizing Behavior Disorders in Terms of Resistance to Intervention is published (Gresham, 1991)

P.L. 94-142 reauthorized: The Individuals with Disabilities Education Act (IDEA)

1977

1990

1991

1997

Milestone/Event

1975

Year

Table 1. (Continued )

Public schools are mandated to (a) identify children with disabilities based on general definitions/categories and (b) serve all children, regardless of the type or severity of disability Classification criteria were established that used the IQ-achievement discrepancy model for identifying students with learning disabilities (LD), a model that has, ‘‘nearly from the moment of its adoptionyfaced persistent criticism’’ (Wright, 2007, p. 8) Services and disabling conditions are expanded: Transition planning is added, and autism and traumatic brain injury are added as separate conditions ‘‘That is, children can and should be classified as BD if their behavioral excesses, deficits, or situationally inappropriate behaviors continue at unacceptable levels subsequent to schoolbased interventions’’ (Gresham, 1991, p. 23) Requirements are introduced regarding functional behavioral assessment, behavioral support plans, and the ‘‘manifestation determination.’’ Schools are encouraged to use PBS as a proactive behavior management tool

Significance

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Publication of Responsiveness to Intervention: An Alternative Approach to the Identification of Learning Disabilities (Gresham, 2002) P.L. 94-142 reauthorized: The Individuals with Disabilities Education Improvement Act (IDEIA) Development of U.S. Department of Education regulations based on IDEIA 2004 (34 C.F.R. 300 & 301, 2006)

2002

2006

2004

Passage of P.L. 107-110: The No Child Left Behind Act (NCLB)

2001

Legislation supports NCLB with statements regarding the inclusion of students with disabilities in all state and district assessment programs States are prohibited from requiring the use of the discrepancy model, and schools are directed to (a) provide evidence that adequate instruction was delivered by qualified general education teachers and (b) use data-based methods for the ongoing evaluation of student progress (Wright, 2007)

Based on state-wide standardized test results, schools that receive Title I funding must make Adequate Yearly Progress or be placed on a list of failing schools, provide special tutoring, and, eventually, be restructured or closed altogether RTI is presented as a preferable alternative to the discrepancy model for identifying students with LD

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Table 2.

Example Definitions of RTI.

Author(s)

Year

Definition

Gresham

2002

Semrud-Clikeman

2005

Daly, Martens, Barnett, Witt, & Olson

2007

Johnson & Smith

2008

Stecker, Fuchs, & Fuchs

2008

Vargas

2009

‘‘Responsiveness to intervention can be defined as the change in behavior or performance as a function of an intervention’’ (p. 479) ‘‘The multitier process suggested by response to intervention (RTI) ties assessment to intervention for those children requiring more specialized and intensive treatment than is available in the first tier or in the general education classroom. A feature of RTI is academic and behavioral screening with a valid assessment measure and continued monitoring if substantial progress has not been demonstrated’’ (p. 565) ‘‘This process, referred to as response to intervention (RTI), involves ongoing evaluation of children’s responsiveness to evidence-based interventions of differing intensity and individualization as a basis for making instructional intervention and eligibility decisions’’ (p. 563) ‘‘RTI is a school-wide process that integrates instruction, intervention, and assessment’’ (p. 46) ‘‘Response to intervention (RTI) encompasses a process for evaluating whether students react to evidence-based instruction as expected. Typically considered a multitiered, prevention-intervention system, successive levels of instructional support are provided when a student’s response to the academic program is sufficiently poor, particularly as compared to his or her peers’ responses’’ (p. 10) ‘‘Response to intervention (RTI) requires specifying particular skill or performance deficits in ‘struggling’ students and assessing their progress once changes are implemented (the intervention)’’ (p. 68)

used to answer this question should involve the ongoing monitoring and evaluation of (a) adequate means of resource procurement and management (including both educational materials and professional development), (b) empirical justification/evidence for the core instructional components currently in use, (c) measures of treatment integrity, and (d) application of practices sensitive to and effective with diverse groups of learners (Stecker, Fuchs, & Fuchs, 2008). Within tier II of the model, instruction is typically provided in pull-out settings and involves small groups of students who have not responded favorably to tier I approaches. The focus at this level of the process is on the provision of instruction that is more specialized for meeting the needs of

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individual students. Intervention type, frequency, and setting (e.g., group size and the specialization level of involved professionals) are monitored and adjusted within a data-based decision-making model similar to the ‘‘clinical teaching cycle,’’ that is, assess, plan, teach, evaluate, and adjust. If a student is not performing successfully within this tier (usually after a maximum of one grading period), one of the main points of investigation should be: Is this student a candidate for even more intensive and specialized educational services? Tier III educational services are the most intensive and targeted toward the specific deficits of individuals (e.g., within an IEP), although instruction within this tier can occur one-to-one or in small groups of students with similar needs. Since tier III is not necessarily synonymous with special education, the focus at this level is on comprehensive evaluation and highly specialized, systematically delivered instruction rather than special education, per se. Students may be identified as eligible for special education services under the provisions of IDEA 2004 through the use of assessment data gathered in tiers I and II, but it is important to point out that use of an ongoing RTI process does not supersede parental rights under the law to, at any point, request a formal evaluation to determine a student’s eligibility for special education services. If a student is not performing successfully within the initial stages of this tier, one of the main points of investigation should be: Is this student presenting indicators of the presence of disability that need to be taken into account in a carefully designed and targeted educational program? As with the definitions of RTI, the number and type of ‘‘essential’’ components vary according to the literature that one reads. However, in addition to multitier implementation, the list of necessary components usually includes (a) universal screening and evaluation (Glover & DiPerna, 2007), (b) a collaborative/team-based approach (National Joint Committee on Learning Disabilities, 2005), and (c) data-based decision making (Barnes & Harlacher, 2008). Universal screening and evaluation include the creation and monitoring of aggregated data sets that display system-wide or school-wide trends across amassed ratings of individual students, allowing decision makers to readily identify students who are beginning to dip below minimal levels of acceptable performance. Sources of universal data can include curriculum-based measurement, standardized or other test scores, number and type of office referrals, rating scales, and direct observations. Within monitoring systems of this type, there is usually a predetermined cut-off point, percentile rank, norm-referenced score, performance criterion, etc. at which students are identified for possible inclusion in the RTI process (screening) or subsequent tiers within the process (evaluation).

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Collaborative, team-based approaches have also been identified as essential to the RTI model. However, specific roles and levels of responsibilities within RTI implementation vary across types of professionals, especially as students move from tier to tier. Overall involvement of general education teachers with RTI implementation tends to decrease as students move to higher-level tiers. For example, a general education teacher may be the sole interventionist for a student within tier I, while he or she may only be responsible for normal classroom instruction delivered to the entire student group as well as gathering one aspect of behavioral or academic data for the student within tier II. Conversely, involvement of professionals such as school psychologists, speech-language pathologists, and content area specialists tends to increase as students move to higher-level tiers. In this way, the mix of roles, responsibilities, and even the number and type of professionals involved can change the dynamics of school-based teams and how they operate. Data-based decision making has also been a hallmark of RTI and in its most common form can resemble a changing criterion design. In fact, it has been recommended that single-case designs be used as a means of adding an empirical base to decision making within RTI implementation (e.g., Barnett, Daly, Jones, & Lentz, 2004). Within the RTI framework and elsewhere, data-based decision making usually consists of a cyclic algorithm that is some variation of the following process: 1. Assess current performance/gather baseline data. 2. Set measurable performance goals, as well as the time frame for intervention. 3. Create decision rules (i.e., for raising the goal, altering or replacing the intervention, fading the intervention, and determining that no further intervention is required). 4. Gather intervention data. 5. Analyze data (e.g., by comparing current performance to a normreferenced criterion, a standard-based criterion, or to past performance using level and trend of both baseline and intervention time-series data sets) 6. Apply decision rules.

Application RTI is mainly applied as a method for (a) identifying students who are struggling or at-risk before difficulties intensify and (b) intervening in a research-based, systematic manner for the amelioration of academic and/or

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behavioral skill deficits and risk factors. However, the Individuals with Disabilities Education Improvement Act of 2004 (IDEIA 2004) also adds provision for use of the RTI model in identifying students with learning disabilities. What follows is a brief sampling of some of the ways that the model has been applied in the areas of academics, behavior, and identification of disabling conditions. Academics One of the historic difficulties with the general education/special education system has been that students must often experience difficulty of sufficient intensity, frequency, and duration and be labeled within an existing disability category before they can receive the programmed help that they need. RTI has been a direct part of other efforts to be more proactive and counter this undesirable trend, and the RTI model for prevention/ intervention has been successfully applied to the educational tasks of improving reading/literacy skills (e.g., Compton, Fuchs, Fuchs, & Bryant, 2006; Justice, 2006; Mesmer & Mesmer, 2008) and mathematics skills (e.g., Fuchs et al., 2005; Fuchs et al., 2008). In addition, there is growing evidence that students who are culturally and linguistically diverse can benefit from the application of RTI to improve literacy development and oral reading skills (e.g., Al Otaiba et al., 2009; McIntosh, Graves, & Gersten, 2007; McMaster, Kung, Han, & Cao, 2008). Behavior Because RTI is a framework within which interventions are identified and delivered, student behavior can be addressed in addition to academics. Although empirically investigated to a somewhat lesser degree than academic areas such as reading/literacy (but seemingly no less discussed in the professional literature, e.g., Barnett et al., 2006; Gresham, 2004), the application of RTI to the prevention and intervention of challenging behavior in schools is also showing promise. Fairbanks, Sugai, Guardino, and Lathrop (2007) investigated the effects of RTI (within a two-tier system) on the behavior of students in second grade who were not responding favorably to classroom behavior management procedures already in use. Findings demonstrated that all participants benefited measurably from the interventions delivered within an RTI framework, although some (6 of 10) had to progress to tier II before experiencing adequate change in rates of target behaviors. Other recent RTI research, for example, has focused on areas such as improving the behavior of students at-risk for developing emotional or behavioral disorders (Cheney, Flower, & Templeton, 2008)

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and the potential efficacy of function-based tier II interventions to reduce the rates of challenging behavior of elementary school students who were not responding positively to a system of school-wide PBS (McIntosh, Campbell, Carter, & Dickey, 2009). Identification Within the RTI model, a student is identified as having a specific learning disability (SLD) when he or she (a) is shown to experience significant levels of low achievement in a particular academic discipline and (b) fails to respond to ‘‘quality instruction,’’ which can be defined as evidence-based instructional practices delivered to an adequate extent and with acceptable levels of treatment integrity. There have been a number of research-based demonstrations of the RTI process as a valid means of identifying the presence of SLDs (e.g., Fuchs et al., 2005; Speece & Case, 2001); however, there are those who argue against the validity of using such a model for this purpose, especially apart from the use of other diagnostic tools (e.g., Kavale, Kauffman, Bachmeier, & LeFever, 2008). Recent research has made the case that the RTI framework is also a valid means for identifying disabilities other than SLDs, such as emotional disturbance (Gresham, 2005), and the identification model continues to be validated in subsequent demonstrations of its efficacy for this purpose (e.g., the description of largescale implementation in Torgesen, 2009).

Congruence with PBS RTI and PBS have fundamental features and philosophies in common that make the two systems quite complementary to one another in regard to the tiers/levels at which they work and the components integral to their operation (see Table 3 for a brief comparison). Marchant et al. (2009) discuss the importance of screening, identification, and treatment within systems of PBS and outline the roles of school teams in gathering and evaluating various forms of behavioral data to effectively accomplish these three tasks. The authors state that within a system of PBS ‘‘collection and examination of data are linked to teaching practice and improved student outcomes; thus, data-based decisions are considered essential to intervention planning at all levels of the behavioral continuum’’ (p. 138). The parallels within their research to the RTI model as discussed within this chapter are striking, particularly the themes dealing with screening and identification, team-based approaches, data-based decision making, linking the ongoing

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Table 3.

Congruence of PBS with RTI.

Response to Intervention Tiers

Focus

I

District/school/ classrooms

II

Small groups

III

Individuals

Positive Behavior Supports Integral component

Integral component

Focus

Levels

School-wide Primary School-wide data Universal screening collection, focus and evaluation, on prevention of focus on prevention challenging of academic and behavior behavioral difficulty Classroom Secondary Relevant Intervention type, environmental frequency, and variables are setting are monitored assessed and altered and adjusted or augmented Individual Tertiary Comprehensive Intensive instructional behavioral supports intervention is are provided provided through through a comprehensive functional assessment and, in behavioral most cases, the assessment and the resulting resulting behavior individualized support plan education plan

collection of data directly to teaching practice, and references to services delivered across a continuum. Sailor, Stowe, Turnbull, and Kleinhammer-Tramill (2007) outline five elements they define as essential to a merger of standard-based education and school-wide PBS. Included within these elements are an exhortation for the adoption of preventive approaches to behavior that are applied universally and involve the use of research-based methodologies informed by the collection of relevant data. Similarly, Carr et al. (2002) discuss relevant features of PBS that include (a) an emphasis on prevention, (b) teaching new skills and restructuring curricula to better meet student needs, and (c) the acceptance of a broad range of data to be used in informing intervention practices. Within these prominent examples of PBS and its essential components, it is clear that the thread of similarity with RTI runs long and deep. As schools move forward into the 21st century and experience everincreasing student populations and diversity, policy makers and school personnel must continue to make choices that integrate a broader range of evidence-based practices into the day-to-day procedures, instruction, and

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behavior management of the students in their care. Emerging empirical databases have shown PBS and RTI to have prescriptive value in the prevention, reduction, and amelioration of the academic and behavioral difficulties increasingly experienced by modern students. It remains to be seen how and to what extent the integration of these two approaches will be implemented and studied within our schools, but based on the knowledge and understanding currently available to us, it seems expedient that we apply these models in tandem and with adequate, measurable treatment fidelity.

REFERENCES Al Otaiba, S., Petscher, Y., Pappamihiel, N. E., Williams, R. S., Dyrlund, A. K., & Connor, C. (2009). Modeling oral reading fluency development in Latino students: A longitudinal study across second and third grade. Journal of Educational Psychology, 101, 315–329. Anderson, C. M., & Freeman, K. A. (2000). Positive behavior support: Expanding the application of applied behavior analysis. The Behavior Analyst, 23, 85–94. Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1, 91–97. Barnes, A. C., & Harlacher, J. E. (2008). Clearing the confusion: Response-to-intervention as a set of principles. Education and Treatment of Children, 31, 417–431. Barnett, D. W., Daly, E. J., Jones, K. M., & Lentz, F. E. (2004). Response to intervention: Empirically based special service decisions from single-case designs of increasing and decreasing intensity. Journal of Special Education, 38, 66–79. Barnett, D. W., Elliot, N., Wolsing, L., Bunger, C. E., Haski, H., McKissick, C., & Vander Meer, C. D. (2006). Response to intervention for young children with extremely challenging behaviors: What it might look like. School Psychology Review, 35, 568–582. Bijou, S. W. (1970). What psychology has to offer education – now. Journal of Applied Behavior Analysis, 3, 65–71. Bohanon, H., Fenning, P., Carney, K. L., Kim, M., Harris, S., Moroz, K. B., Hicks, K. J., Kasper, B. B., Culos, C., Sailor, W., & Pigott, T. D. (2006). School-wide application of positive behavior support in an urban high school: A case study. Journal of Positive Behavior Interventions, 8, 131–145. Carr, E. G., Dunlao, G., Horner, R. H., Koegal, R. L., Turnbull, A. P., & Sailor, W. (2002). Positive behavior support: Evolution of an applied science. Journal of Positive Behavior Interventions, 4, 4–16. Cheney, D., Flower, A., & Templeton, T. (2008). Applying response to intervention metrics in the social domain for students at risk of developing emotional or behavioral disorders. The Journal of Special Education, 42, 108–126. Compton, D. L., Fuchs, D., Fuchs, L. S., & Bryant, J. D. (2006). Selecting at-risk readers in first grade for early intervention: A two-year longitudinal study of decision rules and procedures. Journal of Educational Psychology, 98, 394–409.

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Crone, D. A., & Horner, R. H. (2003). Building positive behavior support systems in schools. New York: Guilford. Daly, E. J., Martens, B. K., Barnett, D., Witt, J. C., & Olson, S. C. (2007). Varying intervention delivery in response to intervention: Confronting and resolving challenges with measurement, instruction, and intensity. School Psychology Review, 36, 562–581. Fairbanks, S., Sugai, G., Guardino, D., & Lathrop, M. (2007). Response to intervention: Examining classroom behavior support in second grade. Exceptional Children, 73, 288–310. Ferster, C. B., & DeMyer, M. K. (1961). The development of performances in autistic children in an automatically controlled environment. Journal of Chronic Diseases, 13, 312–345. Fuchs, L. S., Compton, D. L., Fuchs, D., Paulsen, K., Bryant, J., & Hamlett, C. L. (2005). Responsiveness to intervention: Preventing and identifying mathematics disability. Teaching Exceptional Children, 37(4), 60–63. Fuchs, L. S., & Fuchs, D. (2007). A model for implementing responsiveness to intervention. Teaching Exceptional Children, 39(5), 14–20. Fuchs, L. S., Fuchs, D., Craddock, C., Hollenbeck, K. N., Hamlett, C. L., & Schatschneider, C. (2008). Effects of small-group tutoring with and without validated classroom instruction on at-risk students’ math problem solving: Are two tiers of prevention better than one? Journal of Educational Psychology, 100, 491–509. Glover, J., & Gary, A. L. (1976). Procedures to increase some aspects of creativity. Journal of Applied Behavior Analysis, 9, 79–84. Glover, T. A., & DiPerna, J. C. (2007). Service delivery for response to intervention: Core components and directions for future research. School Psychology Review, 36, 526–540. Gresham, F. M. (1991). Conceptualizing behavior disorders in terms of resistance to intervention. School Psychology Review, 20(1), 23–36. Gresham, F. M. (2002). Responsiveness to intervention: An alternative approach to the identification of learning disabilities. In: R. Bradley, L. Danielson & D. P. Hallahan (Eds), Identification of learning disabilities: Research to practice (pp. 467–519). Mahwah, NJ: Erlbaum. Gresham, F. M. (2004). Current status and future directions of school-based behavioral interventions. School Psychology Review, 33, 326–343. Gresham, F. M. (2005). Response to intervention: An alternative means of identifying students as emotionally disturbed. Education and Treatment of Children, 28, 328–344. Hall, R. V., Lund, D., & Jackson, D. (1968). Effects of teacher attention on study behavior. Journal of Applied Behavior Analysis, 1, 1–12. Hart, B., & Risley, T. R. (1975). Incidental teaching of language in the preschool. Journal of Applied Behavior Analysis, 8, 411–420. Hauserman, N., Walen, S. R., & Behling, M. (1973). Reinforced racial integration in the first grade: A study in generalization. Journal of Applied Behavior Analysis, 6, 193–200. Horner, R. H., Dunlap, G., Koegal, R. L., Carr, E. G., Sailor, W., Anderson, J., Albin, R. W., & O’Neill, R. E. (1990). Toward a technology of ‘‘nonaversive’’ behavioral support. Journal of the Association for Persons with Severe Handicaps, 15, 125–132. Human Rights Watch. (2008). A violent education: Corporal punishment of children in US public schools. New York: Author. Johnson, E. S., & Smith, L. (2008). Implementation of response to intervention at middle school. Teaching Exceptional Children, 40(3), 46–52.

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Johnston, J. M., Foxx, R. M., Jacobson, J. W., Green, G., & Mulick, J. A. (2006). Positive behavior support and behavior analysis. The Behavior Analyst, 29, 51–74. Jones, F. H., Fremouw, W., & Carples, S. (1977). Pyramid training of elementary school teachers to use a classroom management ‘‘skill package’’. Journal of Applied Behavior Analysis, 10, 239–253. Justice, L. M. (2006). Evidence-based practice, response to intervention, and the prevention of reading difficulties. Language, Speech, and Hearing Services in Schools, 37, 284–297. Kavale, K. A., Kauffman, J. M., Bachmeier, R. J., & LeFever, G. B. (2008). Response-tointervention: Separating the rhetoric of self-congratulation from the reality of specific learning disability identification. Learning Disability Quarterly, 31, 135–150. Kazdin, A. E. (2008). Behavior modification in applied settings (6th ed.). Long Grove, IL: Waveland Press. Kennedy, C. H. (2005). Single-case designs for educational research. Boston: Pearson. Marchant, M., Anderson, D. H., Caldarella, P., Fisher, A., Young, B. J., & Young, K. R. (2009). School-wide screening and programs of positive behavior support: Informing universal interventions. Preventing School Failure, 53(3), 131–143. McIntosh, A. S., Graves, A., & Gersten, R. (2007). The effects of response to intervention on literacy development in multiple-language settings. Learning Disability Quarterly, 30, 197–212. McIntosh, K., Campbell, A. L., Carter, D. R., & Dickey, C. R. (2009). Differential effects of a tier two behavior intervention based on function of problem behavior. Journal of Positive Behavior Interventions, 11, 82–93. McMaster, K. L., Kung, S., Han, I., & Cao, M. (2008). Peer-assisted learning strategies: A ‘‘tier 1’’ approach to promoting English learners’ response to intervention. Exceptional Children, 74, 194–214. Mesmer, E. M., & Mesmer, H. A. (2008). Response to intervention (RTI): What teachers of reading need to know. The Reading Teacher, 62(4), 280–290. National Joint Committee on Learning Disabilities (NJCLD). (June, 2005). Responsiveness to intervention and learning disabilities. Report prepared by the NJCLD representing eleven national and international organizations. Available at www.ldonline.org/njcld. Retrieved on May, 2009. Sailor, W., Stowe, M. J., Turnbull, H. R., & Kleinhammer-Tramill, P. J. (2007). A case for adding a social-behavioral standard to standards-based education with schoolwide positive behavior support as its basis. Remedial and Special Education, 28, 366–376. Semrud-Clikeman, M. (2005). Neuropsychological aspects for evaluating learning disabilities. Journal of Learning Disabilities, 38, 563–568. Skinner, B. F. (1953). Science and human behavior. New York: Macmillan. Skinner, B. F. (1968). The technology of teaching. New York: Appleton-Century- Crofts. Speece, D. L., & Case, L. P. (2001). Classification in context: An alternative approach to identifying early reading disability. Journal of Educational Psychology, 93, 735–749. Stecker, P. M., Fuchs, D., & Fuchs, L. S. (2008). Progress monitoring as essential practice within response to intervention. Rural Special Education Quarterly, 27(4), 10–17. Torgesen, J. K. (2009). The response to intervention instructional model: Some outcomes from a large-scale implementation in reading first schools. Child Development Perspectives, 3(1), 38–40.

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U.S. Department of Education, Office of Special Education Programs. (2005). Technical assistance center on positive behavioral interventions and supports: Final report. Washington, DC: Author. Vargas, J. S. (2009). Behavior analysis for effective teaching. New York: Routledge. Wheeler, J. J., & Richey, D. D. (2010). Behavior management: Principles and practices of positive behavior supports (2nd ed.). Upper Saddle River, NJ: Pearson. Wright, J. (2007). Response to intervention toolkit: A practical guide for schools. New York: Dude.

PART VII INTERVENTION METHODS

CHAPTER 13 SCIENTIFICALLY SUPPORTED INTERVENTIONS Martha L. Thurlow, Courtney Foster and Christopher M. Rogers Evidence-based, research-based, field-validated, peer-reviewed, scientifically supported – a slew of terms is being tossed around to modify the term interventions. These terms have appeared in the hope that by defining ‘‘good’’ interventions, educational practice will stop the ‘‘band-wagon’’ approach that has been said for years to characterize what goes on in classrooms. What do these terms mean? Is there a way to define scientifically supported interventions that makes sense in an environment where solid experimental research usually produces nonsignificant findings (Viadero, 2009), and where there is disagreement on what should be considered ‘‘scientific support’’? And, if some agreement can be reached, then what do we now know about scientifically supported interventions? In 2001, the reauthorization of the Elementary and Secondary Education Act (ESEA) first used and defined the term ‘‘scientifically based research.’’ That law stated that scientifically based research ‘‘means research that involves the application of rigorous, systematic, and objective procedures to

Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 199–212 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019016

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obtain reliable and valid knowledge relevant to education activities and programs,’’ and then provided a list of what this research included:  Systematic, empirical methods that draw on observation or experiment.  Rigorous data analyses that are adequate to test the stated hypotheses and justify the general conclusion drawn.  Measurements or observational methods that provide reliable and valid data across evaluators and observers, across multiple measurements and observations, and across studies by the same or different investigators.  Experimental or quasi-experimental designs in which individuals, entities, programs, or activities are assigned to different conditions and with appropriate controls to evaluate the effects of the condition of interest, with a preference for random assignment experiments, or other designs to the extent that those designs contain within-condition or across-condition controls.  Presented in sufficient detail and clarity to allow for replication or, minimally, the opportunity to build systematically on findings.  Accepted by a peer-reviewed journal or approved by a panel of independent experts through a comparably rigorous, objective, and scientific review (No Child Left Behind [NCLB] Act, 2001, Section 7801(37)). This definition, as Zirkel and Rose (2009) pointed out, emerged from consideration of previous definitions used in the Reading Excellence Act of 1999 and the Education Sciences Reform Act of 2002, as well as professional efforts such as those by the National Research Council (1998) and the National Reading Panel (2000). It carried into the Individuals with Disabilities Education Act of 2004, which used other terms besides scientifically based research, including ‘‘scientific, research-based intervention,’’ ‘‘alternative research-based procedures,’’ ‘‘scientifically based [academic, literacy] instruction, and ‘‘peer-reviewed research.’’ The emphasis given to scientifically supported interventions grew out of concern, in part, about the poor performance of students on state assessments, and the nature of instruction that was producing such poor performance. Along with the flurry of articles and commentaries on what the term means and implies, researchers began to change their approaches or to justify how their research was scientifically based. In a recent article, Burns and Ysseldyke (2009) suggested that one evidence-based practice (direct instruction) was used by educators most frequently and another intervention that lacked an evidence base (perceptual-motor training) was used least frequently. They also reported, however, that ‘‘some practices

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with little empirical support (e.g., modality instruction) are reportedly used with some frequency, and special education teachers reported using ineffective approaches (social skills training) as frequently as they did those approaches with a strong research base (applied behavior analysis)’’ (p. 3). The Institute for Education Sciences (IES) has invested considerable effort in developing Practice Guides (e.g., Herman et al., 2008; Pashler et al., 2007) and Intervention Reports (e.g., What Works Clearinghouse, 2009) to assist the field in identifying scientifically based interventions. Yet, the field wonders whether there are no other effective practices that either have not been subjected to rigorous research or have been inadequately researched. Educators wonder what to do when something that they know works for an individual child does not have evidence backing, or when a scientifically supported intervention is inconsistent with the goals and objectives of a student’s instructional plan. This chapter explores the evolution of best practice and the concept of scientifically supported interventions in education. We begin by reviewing approaches used for establishing scientific support for interventions. We then provide a short historical perspective on scientifically supported interventions in general and special education. This is followed by a guided scenario of moving from research to practice to show the process of considering scientific support to select interventions in a school setting.

APPROACHES TO ESTABLISHING SCIENTIFIC SUPPORT FOR INTERVENTIONS Federal education laws increasingly seem to expect educational research to follow the same processes, approaches, and designs as all scientific research. Scientific inquiries typically are based on empiricism, seen as methodical and producing results that are reliable and generalizable, all of which are appealing when examining educational approaches (National Research Council, 2002). The implementation of scientific inquiry uses experimental conditions, comparison of control groups to groups who received the educational intervention, and clearly measurable outcomes. Experimental conditions require random assignment, which means that participants are just as likely to be selected for the control condition as they are for the experimental/intervention condition. In most educational settings, research rarely achieves random assignment of participants to control and experimental conditions because students are grouped into classrooms with

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teachers who have different teaching styles, communication styles, and relationships with individual students (Odom et al., 2005). Another characteristic of true experiments is the careful measurement of the degree of the effect of an intervention on students in the experimental group in comparison to the control group. One way to compare the impact of instructional strategies on groups of students to the measured ability of a control group of students in a standardized manner is to compute ‘‘effect sizes.’’ Determining and reporting effect size as part of presenting educational research findings is a necessary component of empirical research (Thompson, Diamond, McWilliam, Snyder, & Snyder, 2005). As Gersten et al. (2005) pointed out, Cohen (1988) indicated the relative strengths of effect sizes, with 0.2 being small, 0.5 being moderate, and 0.8 and greater being large. The higher the effect size number, the smaller the likelihood that the amount of difference could be accounted for by chance, as opposed to being considered due to some aspect of the different conditions – control versus experimental (Cohen, 1988). In a mega-analysis of meta-analyses of special education practices, Forness, Kavale, Blum, and Lloyd (1997) suggested that effect sizes ‘‘approaching the range of .40 or greater conventionally tend to be considered significant’’ (p. 6).

Experimental Approach Since the passage of NCLB Act (2001), the use of the term ‘‘scientifically based research’’ has become widespread among educators seeking information on instructional practices for which effectiveness is well established. Educational research inquiries using experimental procedures have always been preferred and the findings considered more reliable, despite the fact that these types of inquiries are less frequently pursued (National Research Council, 2002). It is suspected that consumers of educational research may be becoming more savvy in examining the literature for those studies that are rigorous, systematic, and objective. These features are reflected most clearly in the experimental approach, often called the ‘‘randomized clinical trial (RCT)’’ (Odom et al., 2005). Experimental research in education endeavors to demonstrate, through the objectively randomized selection of students to participate in either the intervention group or the control group, and the careful presentation of the targeted instructional approach to the intervention group and the typical teaching approach to the control group. At the same time, all factors that might inadvertently influence students’ performance outcomes are systematically held constant. There is rigorous

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measurement and comparison of student outcomes in the intervention and the control conditions.

Group Experimental Approach Traditionally, experimental research in education has used a ‘‘group experimental’’ approach, with relatively large populations of general education students being taught in either typical or new (i.e., intervention) ways. Most often, the classroom is the level of examination – that is, the instructional practice of interest is used for a whole classroom of students while another classroom receives a typical (i.e., comparison) instructional approach. The focus in group experimental studies is the degree of impact of the new instructional practice of interest on the group receiving the practice in comparison with the group not receiving the instructional practice (Gersten et al., 2005). Impact usually is measured by a test of knowledge and skills. The emphasis is on whether the new or different practice helped more students learn more content more of the time than the typical instructional practice. In other words, attention is paid to the impact on the majority of students. This is in contrast to the single-subject experimental design, which focuses on the impact on individual students (Cook, Cook, Landrum, & Tankersley, 2008b).

Single-Subject Design Approach The single-subject research design is a methodology used extensively in special education, in part due to its alignment with special education’s focus on individualized instruction. In fact, this approach to data gathering is consistent with typical practices of special educators (Tankersley, Harjusola-Webb, & Landrum, 2008). In this methodology, a researcher (or educator) gathers several observations or assessment data points of student performance to establish a pre-intervention baseline. Then, an intervention is introduced into the instructional situation and multiple observations or data points of student’s performance are again collected. These data points serve as repeated measurement of what the student is to learn. When data are analyzed, it is determined whether the intervention was responsible for the change in the student’s performance. This establishes a functional relationship between the student’s performance data and the instructional practice (Tankersley et al., 2008). Researchers may

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manipulate the conditions such that the student’s performance data are examined with the intervention in place as well as with the intervention removed. When there is a difference in student performance from the baseline to the intervention, we can say that the intervention was likely responsible for the student’s performance and is a scientifically supported intervention.

Quasi-Experimental Approach This methodology differs from true experimental research in that participants are not randomly assigned to specific intervention or control conditions. Because there is no random assignment, groups may differ in meaningful ways that could interfere with determining the effect of the intervention. We often see this type of research in education because the research is conducted in schools and in intact classrooms to avoid disturbing the typical day-to-day activities. The use of intact groups poses a problem for researchers when they want to make claims about the effectiveness of the intervention. Greater confidence in findings from quasi-experimental research is gained when researchers can provide evidence that the treatment and the control groups were functionally equivalent (Cook, Tankersley, Cook, & Landrum, 2008a) before the intervention started.

Correlational Approach Correlational inquiries seek to discern the extent to which there is a relationship between two factors or phenomena. Correlation does not meet the standards of true experiments because it does not allow for assertions about a cause-effect relationship. This is the case primarily because the design does not establish that an intervention directly resulted in a positive change in the target outcome. That is, it may be that one phenomenon came before the other, or the other came before the one, or some other phenomenon influenced both (Cook & Cook, 2008). Correlational studies often use statistical procedures such as regression analysis or hierarchical linear modeling (HLM) on extant data to explore the extent to which a factor, such as a demographic characteristic, is related to performance on an academic task or test (Thompson et al., 2005). While correlation does not meet the same level of rigor as experimental conditions, inquiry of this type can be useful as a first step to establish that there is a relationship between

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two phenomena, such as increased performance on a test after the institution of a new instructional approach. It can also be used before designing experiments that can hold other potentially confounding factors constant, such as an explanation that increased performance is due to a practice effect of answering nearly identical questions from one grade to the next in a specific subject area (Cook & Cook, 2008).

Qualitative Approach Research inquiries with a focus on qualitative data procedures have the purpose of deriving deeper meaning from research efforts. Rather than developing a description of a phenomenon, which is the purpose of a nonexperimental effort with quantitative data, examining qualitative data can permit an explanation of any patterns the data are suggesting. Although RCTs provide causal information, answering ‘‘what is happening here, and is it a systematic cause,’’ qualitatively oriented inquiries can provide an answer to the question ‘‘why’’ and can assist in the formulation of plausible hypotheses about the processes that yield specific outcomes for specific research participants (Brantlinger, Jimenez, Klingner, Pugach, & Richardson, 2005; National Research Council, 2002). Brantlinger et al. (2005) also noted that, unlike quantitative research, which seeks to meet standards of reliability and validity, qualitative research seeks to meet standards of credibility and trustworthiness. They go on to offer guidelines for quality in qualitative research. In the range of approaches in special education research, qualitative research can assist in exploring what can occur in the implementation of best practices, especially around fidelity issues and ways teachers incorporate new teaching strategies into their practice (Cook et al., 2008a).

Meta-Analysis Approach When reviewing a body of experimental research about specific instructional strategies, researchers often complete meta-analyses using statistical procedures for computing ‘‘effect sizes,’’ usually calculating Cohen’s d (Cohen, 1988). The calculation of effect sizes permits consumers of research to understand the relative value of the impact of an intervention on student outcomes. Yet, many authors of research reports provide only the p values to indicate significance, idiosyncratically focusing readers on their

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findings without a standardized way to compare inquiry findings across the body of research (Rosnow & Rosenthal, 1996). Use of p values as the sole coefficient to determine impact of individual studies does not offer an easy way to attend to study-specific factors such as differing participant group sizes. Thus, empirical meta-analyses offer readers, through use of statistical procedures, which can be applied also by the readers themselves (Rosnow & Rosenthal, 1996), to determine effect sizes to allow for comparisons of the findings of one research study to another. Teachers looking for evidencebased practices may find meta-analyses particularly useful in their largescale summative examinations of effects of practices being studied (Banda & Therrien, 2008). The use of meta-analysis as a research approach has increased in frequency and in the number of researchers using it across the past 30 years. A search through Google Scholar, a common search engine, for articles with the term ‘‘meta-analysis’’ in the title in education-related journals yielded over 7,000 individual results. Of those results, over 5,000 have a date of 2000 or later, and over 3,000 have a date of 2005 or later. A similar search using the Education Resources Information Center (ERIC) database yielded over 850 individual results, dating back to the mid-1970s. Of those items, nearly 380 were published since 2000, and over one-quarter (about 220) had a publication year of 2005 to the present. When focusing on the incidence of the meta-analysis approach in special education research, the review of the same ERIC database yielded nearly 100 individual results, with about 60 studies since 2000, and over half of those since 2005.

HISTORICAL PERSPECTIVES ON SCIENTIFICALLY SUPPORTED INTERVENTIONS The accountability movement in education has been with us for a relatively long time. Accountability for educational outcomes fits with the charge of educating students with disabilities, in that an important element has always been to ensure that the instruction they are provided has an impact and that these students are achieving desired outcomes (Horner et al., 2005; Odom et al., 2005). At the same time, special education has, since its inception, focused on the individual student and individualized education programs. The intent is to do what works for each student. This focus on the individual presents what some see as a tension with the education of the general student population through a common educational approach or

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instructional strategy. This apparent tension seems to come to a head when scientifically supported interventions are provided to all students, including students with disabilities, within a general education environment. Some educational scholars point out that effective and empirically based techniques have been developed for students with disabilities; yet, the implementation of these instructional practices is neither systematic nor completed with fidelity (Cook & Schirmer, 2003). One reason for this, consistent with the tension between individualized and whole-group approaches, may be the extreme variability in student characteristics in the special education population (Cook et al., 2008a). Furthermore, as Browder and Cooper-Duffy (2003) noted in their examination of special education teachers’ work with students with significant cognitive disabilities, the students’ unique and uncommon needs and challenges often result in instructional practices formed from a ‘‘values-based, rather than an evidence-based, policy’’ (p. 161). Special education has enjoyed its own rich history of research methodologies. Single-subject experimental designs appear to be a preferred method of dealing with some of the instructional contexts and student characteristics present in special education (Odom et al., 2005). These unique characteristics originate from the fact that there are various student characteristics (reflected in, but not synonymous with, the federal disability categories) and a wide array of special education contexts. Single-subject research allows for those specific nuances to be studied (e.g., a student with learning disabilities in a self-contained setting using a reading program) while maintaining the rigor of experimental research in determining scientifically supported interventions (Odom et al., 2005). When practitioners look to research to find scientifically supported interventions, they face a daunting task. As consumers, educators need to be able to quickly focus on the utility and feasibility of effective interventions. As Cook et al. (2008b) noted, two things are important in the search for scientifically supported interventions: (a) search and locate the research, and (b) determine that the research has high quality. In the past, educators at the local level were left to sort through research typically presented in journals and not written for the practitioner. In recent years, accessible and helpful resources have emerged to assist educators in narrowing down their search for scientifically supported practice. Listed here alphabetically are some of these resources:  Best Evidence Encyclopedia, www.bestevidence.org: A free web site created by the Johns Hopkins University School of Education’s Center

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for Data-Driven Reform in Education (CDDRE) with funding from the Institute of Education Sciences, U.S. Department of Education. This resource is intended to give educators and researchers fair and useful information about the strength of the evidence supporting various programs available for students in grades K-12.  RTI Action Network, http://www.rtinetwork.org: Guides educators and families in the large-scale implementation of Response to Intervention (RTI) so that each child has access to quality instruction. The RTI Action Network is a program of the National Center for Learning Disabilities, in partnership with the nation’s leading education associations and top RTI experts.  What Works Clearinghouse (WWC), http://ies.ed.gov/ncee/wwc: Established in 2002 by the U.S. Department of Education’s Institute of Education Sciences, the WWC is a central and trusted source of scientific evidence for what works in education. Even though these resources provide a better way to narrow down information on the numerous interventions, there are still some specific questions that should guide a practitioner’s reflection and judgment about the value of certain educational interventions. Because a demonstrated set of quality indicators does not exist, particularly for special education, we see a mixture of practices that include effective interventions, interventions with limited fidelity of implementation, and interventions based on professional judgment of effectiveness. Along with scientific evidence of effectiveness and the various research methodologies employed, educators may want to look for similarities between the research sample and their own student populations. For example, educators may want to look at the length of time the intervention was studied. They also may want to note any specific requirements of the intervention that may involve additional professional development for staff or that may present a conflict with the implementation of other interventions.

CASE STUDY OF REFLECTIONS ABOUT SCIENTIFICALLY SUPPORTED INTERVENTIONS To show the nature of the reflection process in which educators should engage as they consider evidence of scientifically supported interventions, we provide a brief case study. This case study demonstrates a process that practitioners might use to identify the need for scientifically supported

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interventions as well as the process for identifying those interventions that have scientific support. Anywhere Middle School is a medium-sized school located in the southeastern region of the United States. This middle school is a rural school for students in grades 6–8. It has a student population of about 300. Ms. Goode, principal, has been an educator for 25 years and has been the school’s principal for the past 6 years. Over the past 3 years, Ms. Goode has noticed a problem with the reading achievement at her school. Anywhere Middle School, once a consistently high performing school, is now showing a steady decline in reading achievement. In looking at past data, 80% of students were meeting the reading achievement standards. Over the past 3 years, the school has seen achievement go from 80% proficient to 72%, then 65%, and is now at 63% proficient. In meeting with her leadership team, Ms. Goode reviews the performance data and the data that were collected throughout the past year from teacher observations and school formative and benchmark assessments. As the team members review the data, they remain mindful of the fact that their student population has undergone changes. The community where the school is located has become a more mobile community and the student population is more diverse. In addition, the staff has noted that more struggling readers and students with specific reading disabilities have become part of the school family. The team determines that the current reading program may not be meeting the needs of all of the student population and that a new reading program would be a better alternative. But which one is the best? Ms. Goode knows of many good reading programs that her colleagues are using but she wants to be sure that the reading program she chooses is the best fit for her school. The school leadership team decides to search the research literature from available web sites to find information about effective reading programs. After the initial search, the team meets again to discuss the four reading programs that were chosen preliminarily as potential evidence-based practices. The team begins to dissect the information on the four reading programs. All of the reading programs that the team chose were based on research, but as this team knows, not all research is of equal quality. Program A, Program B, and Program C all have at least three independent empirical studies where the intervention was provided to a group of students and their performance was compared to a similar group of students that did not receive the intervention. Program D had only one empirical study, and that study produced a small effect size. Other research found for Program D included several correlational studies; although showing promise, the

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correlational studies did not meet the criteria identified by Ms. Goode and her staff. Thus, they eliminate Program D from consideration. With three reading programs still under review, Ms. Goode and her team search deeper into the research to answer specific questions about the interventions. Their questions include: What students were included in the sample? How long was the study conducted? and What were the specific effect sizes produced by the interventions? Program A and Program B each included a diverse student sample in its research. The diverse samples did include students with specific reading disabilities and struggling readers as well as a diverse representation of ethnicities. Program C offered a somewhat diverse sample group, but Ms. Goode and her staff noted that there were no students who struggled with reading in the sample. Although research showed Program C to be an effective reading intervention, Ms. Goode and her staff are concerned that the program may not produce the same results at their school. They continue to probe more deeply into Program A and Program B and eliminate Program C from consideration. The research of Program A and Program B was conducted over the period of an entire school year. Periodic measures of student performance were taken throughout the study to show gains or losses in student achievement. In addition, both programs had effect sizes ranging from .43 to .62. There was very little difference in the technical quality of the research for Program A and Program B. However, one unique difference between the two programs stood out to the team. Program A research was accompanied by a few qualitative studies that gave Ms. Goode and her team information about the teachers’ perceptions of the intervention. Teachers found Program A to be easily understood and its components to be easily embedded into routine classroom instruction. Teachers also noted that Program A was very engaging for students because of its diverse reading materials and instructional activities. Because Program A had the strong empirical research critical to establishing effectiveness as well the professional judgment of teachers who actually used the program in their classrooms, it seemed to Ms. Goode and her staff that this would be the best choice for their school.

CONCLUSION The term ‘‘scientifically supported interventions’’ means different things to different people simply because there is no agreement on what constitutes

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‘‘scientific support.’’ Federal law has moved the discussion along by promoting interventions that have empirical support and by providing examples of the characteristics of that research. In this chapter, we reviewed several approaches to scientific research, including experimental, singlesubject, quasi-experimental, correlational, qualitative, and meta-analysis approaches. We also addressed the apparent conflict between effective and empirically based interventions tested on groups of students and the individualized approach for students with individualized education programs. Historically, educators have continued to move in directions that refine the definition of scientifically supported interventions. At the same time, there has been attention to the nature of support for interventions and to identifying what type of support makes most sense and when. Our case study of Anywhere Middle School demonstrated that identifying scientific support is a process that relies on different types of scientific support so that good reflections and decisions can occur. It is likely that the focus on ‘‘scientific support’’ will continue for some time. Part of that focus undoubtedly will also be on what are considered to be nonscientifically supported interventions.

REFERENCES Banda, D. R., & Therrien, W. J. (2008). A teacher’s guide to meta-analysis. Teaching Exceptional Children, 41(2), 66–71. Brantlinger, E., Jimenez, R., Klingner, J., Pugach, M., & Richardson, V. (2005). Qualitative studies in special education. Exceptional Children, 71(2), 195–207. Browder, D. M., & Cooper-Duffy, K. (2003). Evidence-based practices for students with severe disabilities and the requirements for accountability in ‘‘No Child Left Behind.’’ The Journal of Special Education, 37(3), 157–163. Burns, M. K., & Ysseldyke, J. E. (2009). Reported prevalence of evidence-based instructional practices in special education. The Journal of Special Education, 43(1), 3–11. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Cook, B. G., & Cook, L. (2008). Nonexperimental quantitative research and its role in guiding instruction. Intervention in School and Clinic, 44(2), 98–104. Cook, B. G., & Schirmer, B. R. (2003). What is special about special education? Overview and analysis. The Journal of Special Education, 37(3), 200–205. Cook, B. G., Tankersley, M., Cook, L., & Landrum, T. J. (2008a). Evidence-based practices in special education: Some practical considerations. Intervention in School and Clinic, 44(2), 69–75.

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Cook, L., Cook, B. G., Landrum, T. J., & Tankersley, M. (2008b). Examining the role of group experimental research in establishing evidence-based practices. Intervention in School and Clinic, 44(2), 76–82. Forness, S. R., Kavale, K. A., Blum, I. M., & Lloyd, J. W. (1997). Mega-analysis of metaanalyses: What works in special education and related services. Teaching Exceptional Children, 29(6), 4–9. Gersten, R., Fuchs, L. S., Compton, D., Coyne, M., Greenwood, C., & Innocenti, M. S. (2005). Quality indicators for group experimental and quasi-experimental research in special education. Exceptional Children, 71(2), 149–164. Herman, R., Dawson, P., Dee, T., Greene, J., Maynard, R., Redding, S., & Darwin, M. (2008). Turning around chronically low-performing schools: A practice guide. NCEE 2008-4020. Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance. Horner, R. H., Carr, E. G., Halle, J., McGee, G., Odom, S., & Wolery, M. (2005). The use of single-subject research to identify evidence-based practice in special education. Exceptional Children, 71(2), 165–179. National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction. Washington, DC: National Institute of Child Health and Human Development. National Research Council. (1998). Preventing reading difficulties in young children. Washington, DC: National Academy Press. National Research Council. (2002). Scientific research in education. Washington, DC: National Academy Press. No Child Left Behind Act. (2001). 20 U.S.C. 630 et seq. (Pl 107-110). Odom, S. L., Brantlinger, E., Gersten, R., Horner, R. H., Thompson, B., & Harris, K. R. (2005). Research in special education: Scientific methods and evidence-based practices. Exceptional Children, 71(2), 137–148. Pashler, H., Bain, P., Bottge, B., Graesser, A., Koedinger, K., McDaniel, M., & Metcalfe, J. (2007). Organizing instruction and study to improve student learning (NCER 2007-2004). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Research. Rosnow, R. L., & Rosenthal, R. (1996). Computing contrasts, effect sizes, and counternulls on other people’s published data: General procedures for research consumers. Psychological Methods, 1(4), 331–340. Tankersley, M., Harjusola-Webb, S., & Landrum, T. J. (2008). Using single-subject research to establish the evidence base of special education. Intervention in School and Clinic, 44(2), 83–90. Thompson, B., Diamond, K. E., McWilliam, R., Snyder, P., & Snyder, S. W. (2005). Evaluating the quality of evidence from correlational research for evidence-based practice. Exceptional Children, 71(2), 181–194. Viadero, D. (2009). ‘No effects’ studies raising eyebrows. Education Week, 28(27), 114–15. What Works Clearinghouse (2009). WWC intervention report: Adolescent literacy – SuccessMaker. Washington, DC: Author. Zirkel, P. A., & Rose, R. (2009). Scientifically based research and peer-reviewed research under the IDEA. Journal of Special Education Leadership, 22(1), 36–50.

CHAPTER 14 SCIENTIFICALLY UNSUPPORTED TREATMENTS FOR STUDENTS WITH SPECIAL NEEDS Julie A. Deisinger BACKGROUND Students with special needs include children with impaired attention, disruptive behavior, learning disabilities, and developmental disorders, among many other conditions. When a child has been diagnosed with such a disorder, his or her parents may seek treatment that could assist the child to be more academically and socially successful. Numerous interventions exist for the treatment of childhood disorders; however, these treatment methods differ in the types and amounts of evidence supporting their usefulness and effectiveness (Lilienfeld, 2005). Professionals in psychology, education, physical therapy, and occupational therapy have begun to emphasize the need for clinicians and educators to engage in evidence-based practice (EBP; American Psychological Association, 2005) through the use of scientifically supported techniques that target clients’ problems (Detrich, 2008; Saleh et al., 2008; Stephenson, 2004). The American Psychological Association (2005, p. 1) defines EBP as ‘‘the integration of the best available research with clinical expertise in the context of patient characteristics, culture, and preferences.’’ Therapists who engage in EBP must familiarize themselves with research findings about Current Issues and Trends in Special Education: Identification, Assessment and Instruction Advances in Special Education, Volume 19, 213–236 Copyright r 2010 by Emerald Group Publishing Limited All rights of reproduction in any form reserved ISSN: 0270-4013/doi:10.1108/S0270-4013(2010)0000019017

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various treatment approaches and use such information when selecting interventions for their clients (Detrich, 2008; Saleh et al., 2008). The impetus for EBP derives from the premise that empirically based treatments will yield better outcomes for clients than methods that lack scientific support (Detrich, 2008). Unfortunately, some clinicians still may utilize nonscientifically supported treatments (Nathan & Gorman, 2002). Kazdin and Whitley (2006) reported that more than 550 different psychotherapeutic methods are used with children, and most of these methods have not been investigated using randomized controlled trials or even uncontrolled pre- versus post-treatment evaluations. Thus, it is possible that therapists may not have encountered upto-date research findings about the relative merits of various treatment strategies. Alternatively, they may have been trained to apply certain types of intervention for specific clinical conditions (Tavris, 2003). As a result, therapists may persist in the use of such methods, either due to a belief in their supposed effectiveness or simply out of habit (Garb & Boyle, 2003). Furthermore, well-intentioned parents sometimes implement ineffective treatments for their children with special needs, due to a lack of understanding about the distinction between evidence-based versus non-evidence-based treatment. In some instances these nonscientifically supported treatments might be benign, but in other cases they could be harmful (Lilienfeld, 2005). The purpose of this chapter is to identify biomedical and psychoeducational treatments that lack sufficient scientific evidence to recommend their use among children with special needs. Information about empirically unsupported treatments will be presented in relation to several representative childhood disorders. Possible explanations will be given concerning the reasons that therapists and parents might mistakenly opt for non-evidencebased treatments. Finally, information will be provided regarding ways to recognize treatments that at best are ineffective, and at worst pose a threat to children’s well-being.

ATTENTION-DEFICIT/HYPERACTIVITY DISORDER Attention-deficit/hyperactivity disorder (ADHD) is a disruptive behavior disorder involving problems with attention, impulsivity, and hyperactivity (American Psychiatric Association, 2000). Biomedical interventions that are not scientifically supported for the treatment of ADHD include elimination diets, nutritional supplements, homeopathic remedies, and biofeedback (Rojas & Chan, 2005).

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Unsupported Dietary Interventions One of the best-known nonscientific approaches for ADHD treatment is the Feingold diet (Lilienfeld, 2005; Rojas & Chan, 2005; Waschbusch & Hill, 2003). This diet is based on the assumption that ADHD symptoms are an adverse reaction to chemicals called salicylates, which are found in artificial flavoring and coloring agents that have been added to foods. The Feingold regimen claims that eliminating these food additives from a child’s diet will lead to a reduction in ADHD symptoms and improved functioning, both cognitively and behaviorally (Cormier & Elder, 2007; Rojas & Chan, 2005; Waschbusch & Hill, 2003). Early studies appeared to support the effectiveness of the Feingold diet, but those investigations contained significant flaws. For example, they typically failed to employ a double-blind design (Rojas & Chan, 2005; Waschbusch & Hill, 2003), which requires that neither the experimenters nor the participants are aware of who is receiving an actual treatment versus a sham treatment (McDermott & Miller, 2007). Instead, early research on the Feingold diet relied too heavily on behavioral ratings from parents who were aware of the treatment being given to their children. Subsequent reviews of these studies reported that use of the Feingold diet did not lead to meaningful improvements in children’s functioning, and further noted that any observable improvements were most likely due to parents’ expectations rather than the diet itself (Waschbusch & Hill, 2003). Tightly controlled experimental investigations of the Feingold diet suggest that less than 10% of children with ADHD obtain any benefit from this approach. Unfortunately, there is no way of identifying which children with ADHD might be among the few whose symptoms might improve as a result of this treatment. In addition, there is no evidence indicating that the Feingold diet yields better outcomes than stimulant medication or behavior modification, both of which are commonly employed, evidence-based treatments for ADHD. For these reasons, the Feingold diet is not a scientifically supported treatment (Lilienfeld, 2005; Rojas & Chan, 2005; Waschbusch & Hill, 2003). Other elimination diets for the treatment of ADHD exclude sweeteners such as sugar or aspartame. It is widely believed that ADHD is caused by excessive consumption of sugar, but carefully designed research does not support this idea (Cormier & Elder, 2007; Lilienfeld, 2005; Rojas & Chan, 2005; Waschbusch & Hill, 2003). Similarly, studies on the effects of aspartame have found little evidence that excessive ingestion of aspartame aggravates ADHD symptoms (Waschbusch & Hill, 2003).

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Another dietary intervention for ADHD is the oligoantigenic diet, which is founded on the hypothesis that ADHD symptoms represent allergic reactions to various foods. These supposedly include not only sugars and food dyes but also wheat, corn, eggs, dairy products, chocolate, and nuts, in addition to other foods (Rojas & Chan, 2005). Therefore, this diet allows the consumption of only foods that do not fall within the categories listed (Rojas & Chan, 2005). Rojas and Chan (2005) stated that studies examining the usefulness of the oligoantigenic diet contained multiple design flaws. These investigations tended to use parental ratings of their children’s behavior as the only measure of improvement, without any other corroborating evidence for such ratings. In addition, they employed small samples that limited the generalizability of their findings, and they usually failed to compare the effects of the diet against a proven medication such as methylphenidate. Thus, there is insufficient evidence that this type of diet is an effective treatment for ADHD (Rojas & Chan, 2005). In contrast to elimination diets, the supposed rationale for using nutritional supplements is that the symptoms of ADHD are due to insufficient amounts of key nutrients (Waschbusch & Hill, 2003). On the basis of this belief, dietary supplementation with amino acids, fatty acids, or megavitamins has been recommended; however, carefully controlled studies do not reveal any significant benefits as a result of their use (Lilienfeld, 2005; Rojas & Chan, 2005; Waschbusch & Hill, 2003). In fact, Waschbusch and Hill (2003) cautioned that using amino acid supplements to treat ADHD poses a risk of toxicity.

Other Biomedical Interventions Homeopathic medicine seeks to cure health problems by administering small, dilute doses of a drug that elicits symptoms which are similar to the symptoms in need of treatment (‘‘Swiss Study’’, 2005). Although some European studies of the drug pycnogenol claim that using this substance offers relief from ADHD symptoms, these studies lack sufficient scientific control (Lilienfeld, 2005; Waschbusch & Hill, 2003). Neurofeedback, or electroencephalographic (EEG) biofeedback, is becoming an increasingly popular alternative to stimulant medication for the treatment of ADHD (Lilienfeld, 2005; Rojas & Chan, 2005; Waschbusch & Hill, 2003). Through the use of machines that provide visual and auditory cues, children reportedly experience a reduction in ADHD symptoms by

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learning to increase the activity of brainwaves that are associated with sustained attention, while decreasing brainwaves that are correlated with inattention (Waschbusch & Hill, 2003). However, studies that have sought to demonstrate the effectiveness of neurofeedback for the treatment of ADHD suffer from various methodological shortcomings. These include inadequate sample sizes, lack of homogeneous participant groups, failure to include control groups, failure to include a credible sham treatment for purposes of comparison, inconsistent use of outcome measures, a lack of clinically meaningful measures of improvement, and failure to conduct long-term follow-up investigations (Lilienfeld, 2005; Rojas & Chan, 2005; Waschbusch & Hill, 2003). Beyond the lack of solid confirmatory evidence about the effectiveness of neurofeedback, a further drawback of this approach is that it imposes financial and time burdens on families (Rojas & Chan, 2005).

Unsupported Psychoeducational Interventions Several psychoeducational interventions for ADHD have very little scientific support. For example, play therapy often can be used for allowing children to explore psychological conflicts that are difficult for them to discuss; however, no controlled research studies demonstrate the utility of play therapy as a treatment for ADHD (Lilienfeld, 2005). Cognitive training programs have also been suggested as a way to help children overcome their ADHD symptoms. These programs teach children self-instructional techniques to improve their impulse control and cognitive focus, but studies of their effectiveness indicate that they produce little or no improvement in either behavior or academic performance (Lilienfeld, 2005; Waschbusch & Hill, 2003). Additionally, eye movement desensitization and reprocessing (EMDR) has been suggested as a treatment for children with ADHD (Waschbusch & Hill, 2003). This method, typically used for the treatment of posttraumatic stress disorder (PTSD), supposedly alleviates traumatic memories through the use of repetitive, side-to-side eye movements (Devilly, 2002). However, there is neither a theoretical rationale nor an empirical basis for the use of EMDR as a treatment for children with ADHD (Waschbusch & Hill, 2003). Finally, an environmental strategy that has been explored is the use of settings in nature to promote increased attentional ability in children with ADHD (Rojas & Chan, 2005). Since some evidence suggests that nonADHD individuals experience enhanced attention in outdoor spaces, it seems plausible that children diagnosed with ADHD similarly might be

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better able to pay attention in such environments. However, the only research study that has examined this topic contained numerous design problems such as failure to verify participants’ ADHD diagnosis, heterogeneity in the type and severity of ADHD symptoms, the use of retrospective parental ratings, failure to examine other typical ADHD symptoms such as hyperactivity and impulsivity, and failure to include a comparison group. Therefore, it is not yet possible to say with any certainty that the use of outdoor settings is an effective method for promoting increased attention among children with ADHD (Rojas & Chan, 2005).

READING DISORDER (DYSLEXIA) Reading disorder, otherwise known as dyslexia (Wicks-Nelson & Israel, 2003), is the name given to reading ability that is significantly less than expected for a person’s age, intellectual ability, and level of educational attainment (American Psychiatric Association, 2000). A substantial body of research demonstrates that a reading disorder is due to impairment in associating visual symbols, such as letters or words, with the sounds for these written symbols. Thus, a reading disorder is a deficit in phonological processing, rather than a visual processing difficulty (Wicks-Nelson & Israel, 2003). Nevertheless, vision-based interventions may be attempted for children with a reading disorder, such as visual tracking exercises or the use of eyeglasses with prisms, bifocals, or colored lenses. None of these methods is scientifically supported, and they may impose unnecessary expenses on families (American Academy of Pediatrics, 1998; Stephenson, 2004). Another nonscientific intervention for dyslexia is the Doman-Delacato patterning treatment (Stephenson, 2004), also known simply as patterning (American Academy of Pediatrics, 1999). This technique uses a series of exercises, performed for several hours daily, during which volunteers manipulate a child’s head and limbs in ways that supposedly mimic the preand postnatal movements of neurologically unimpaired children. The theory underlying the use of patterning claims that learning problems are the result of failure to complete a given stage of neurologic development; thus, the way to remediate such problems supposedly requires intensive practice of behaviors that occurred at earlier stages of development, to correct any existing damage to the brain and nervous system (American Academy of Pediatrics, 1999). However, controlled studies of patterning have not supported this assumption. Furthermore, patterning regimens impose

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unnecessary stress on families because they are costly and time-consuming (American Academy of Pediatrics, 1999; Stephenson, 2004).

AUTISM SPECTRUM DISORDERS Autism spectrum disorders (ASDs), also known as pervasive developmental disorders, encompass a range of conditions that vary in severity. ASDs involve significant impairment in communication and social skills as well as the possible presence of unusual interests or repetitive behaviors (American Psychiatric Association, 2000). Children with ASDs often experience ongoing, severe impairment in academic and social functioning. Because the causes of ASDs are not fully known, and because their symptoms are so chronic and debilitating, ASDs are particularly susceptible to treatment using non-evidence-based methods (Herbert, Sharp, & Gaudiano, 2002; Simpson, 2008). In fact, Smith (2008, p. 4) called ASDs a ‘‘fad magnet’’; as many as one-third of all children with ASDs receive non-empirically supported interventions (Smith & Wick, 2008). Some of the non-evidence-based treatments for ASDs have already been discussed in this chapter. Biomedical interventions such as vision therapy (Smith, 2008; Smith & Wick, 2008) and psychoeducational treatments such as patterning (American Academy of Pediatrics, 1999; Smith, 2008) and play therapy (Bodfish, 2004; Smith, 2008) have been used among children with ASDs despite a lack of scientific evidence to support their utility. Unsupported Dietary Interventions A plethora of other non-empirically supported interventions for ASDs also exists. Similar to what has been previously reported, elimination diets and nutritional supplements are among the biomedical treatments that have been attempted with ASDs. A commonly employed elimination diet for ASDs is the gluten-free/casein-free (Gf/Cf) diet (Elder, 2008; Smith & Wick, 2008). This approach is based on a belief that children with ASD have difficulty digesting gluten (a protein found in wheat and other grains) and casein (a protein contained in dairy foods). It is further believed that gluten and casein peptide fragments become absorbed into the bloodstreams of children with ASD, entering their brains and interfering with typical neurotransmitter functioning, as well as contributing to the development of repetitive movements and rituals, language delays, and hyperactivity (Elder, 2008; Levy & Hyman, 2005; Wallace, 2009).

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Despite the immense popularity of the Gf/Cf diet, evidence regarding its usefulness is inconclusive (Romanczyk, Gillis, White, & Digennaro, 2008; Wallace, 2009). Herbert et al. (2002) reported that most research on the Gf/Cf diet consisted of only case studies or anecdotal reports. A recent double-blind study evaluated the effects of the Gf/Cf diet on autistic symptoms and found no significant differences when comparing the Gf/Cf regimen versus a placebo diet (Cormier & Elder, 2007; Elder, 2008; Meletis & Zabriskie, 2007; Myers, Johnson, & The Council on Children with Disabilities, 2007). Beyond its ineffectiveness, the Gf/Cf diet can be difficult to implement because some children with ASDs have extremely limited food preferences, thus making it hard for parents to eliminate foods that contain either gluten or casein (Bihari, 2006; Elder, 2008). Additional factors that contra-indicate the use of the Gf/Cf diet include its cost, the time required to learn new methods of food preparation, the possibility of resulting nutritional deficiencies for children with ASDs, and the stress experienced by other family members when trying to maintain such a highly restrictive diet for a family member with ASD (Bihari, 2006; Elder, 2008; Levy & Hyman, 2005; Smith, 2008; Smith & Wick, 2008; Wallace, 2009). Another elimination diet that has been tried for children with ASD is the specific carbohydrate diet (SCD), which prohibits the ingestion of grains, lactose, and sucrose (Wallace, 2009). This dietary approach derives from the idea that children with ASDs are unable to digest complex carbohydrates, thereby supposedly contributing to an overabundance of harmful bacteria in the digestive tract (Wallace, 2009). To prevent this occurrence, a diet is provided that contains smaller carbohydrate molecules (Levy & Hyman, 2005). When following the SCD, forbidden foods include sugar, fructose, corn syrup, potatoes, yams, and various grains and dairy products (Wallace, 2009). However, other than anecdotal information, there is no scientific evidence supporting the usefulness of the SCD (Levy & Hyman, 2005; Wallace, 2009). As with the Gf/Cf diet, another potential drawback of the SCD is the possibility of inadequate nutrition (Levy & Hyman, 2005). A further problem may involve the heightened expectations of families who implement this diet, as they may experience feelings of guilt when the expected improvement in symptoms fails to materialize (Levy & Hyman, 2005). Administering vitamin supplements is still another unscientific treatment for ASDs. Vitamins A, C, and E have been suggested as being able to improve immune functioning among children with ASDs, but there is no research evidence to back such claims (Smith & Wick, 2008; Wallace, 2009). Furthermore, high doses of vitamin C can result in diarrhea or the development of kidney stones (Levy & Hyman, 2005; Schechtman, 2007).

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The most common vitamin supplement used among children with ASDs is a combination of vitamin B6 and the mineral magnesium (Levy & Hyman, 2005; Schechtman, 2007). This combination supposedly leads to improvements in speech, eye contact, attention span, sleep, and general health, while reducing hyperactivity and self-stimulatory behavior (Wallace, 2009). However, many early studies of vitamin B6 plus magnesium were flawed due to reliance solely on parent reports rather than the reports of independent observers (Herbert et al., 2002). Carefully designed studies have not supported the usefulness of the vitamin B6/magnesium combination for treating ASD (Romanczyk, Arnstein, Soorya, & Gillis, 2003; Romanczyk et al., 2008; Smith, 2008; Smith & Wick, 2008). Safety concerns also accompany the use of this approach. Increased doses of vitamin B6 may lead to nerve damage (Herbert et al., 2002; Levy & Hyman, 2005) or peptic ulcer disease (Romanczyk et al., 2003) as well as changes in gait and loss of postural and fine-motor control (Wallace, 2009). In addition, high doses of magnesium are associated with weakened reflexes and slowed heart rate (Herbert et al., 2002) as well as seizures (Schechtman, 2007). According to Levy and Hyman (2005), the next most commonly used nutritional supplement for ASDs is dimethylglycine (DMG). This overthe-counter antioxidant is administered with the expectation that it will improve neurotransmitter functioning while also improving eye contact, speech, and frustration tolerance (Herbert et al., 2002; Levy & Hyman, 2005; Wallace, 2009). Yet double-blind studies have not yielded any differences between groups receiving DMG versus a placebo (Herbert et al., 2002; Levy & Hyman, 2005; Romanczyk et al., 2008; Schechtman, 2007; Smith & Wick, 2008).

Unsupported Medications The hormone secretin supposedly produces marked improvements in the expressive language and behavior of children with ASDs (Herbert et al., 2002; Richman, Reese, & Daniels, 1999; Smith, 2008). Based on a single case study published in 1998, thousands of parents sought secretin therapy for their children with ASDs (Herbert et al., 2002). Although no serious side effects may be associated with secretin (Richman et al., 1999), there have also been no credible scientific studies showing that it has any utility as a treatment for ASDs (Bodfish, 2004; Smith & Wick, 2008). Double-blind studies reported that secretin was indistinguishable from a placebo (Romanczyk et al., 2003; Schreibman, 2005) and had no beneficial effects

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on receptive and expressive language (Herbert et al., 2002; Myers et al., 2007; Smith, 2008), nor did its use result in any meaningful changes in social interactions or stereotyped movements (Richman et al., 1999). Various other medications have also been employed as treatments for ASDs. Among them are antibiotics, antiviral and antifungal agents, immunoglobulins, and over-the-counter antacids. The antibiotic vancomycin was tested on a small sample of children with ASDs, based on the premise that their behavioral symptoms might be due to toxins produced by the intestinal flora (Levy & Hyman, 2005; Schechtman, 2007). Although the children did show improved functioning following vancomycin use, this outcome could have been obtained simply as a result of healthier bowel functioning. In addition, the study was not fully blinded (Schechtman, 2007). Furthermore, the routine use of vancomycin is not recommended because it could lead to the development of resistant bacterial strains (Levy & Hyman, 2005). Antiviral medications such as valacyclovir have also been attempted as treatment for ASDs. The use of antiviral drugs derives from a belief that ASDs are caused by prenatal and neonatal exposure to as yet unidentified viruses (Levy & Hyman, 2005; Schechtman, 2007). However, there have been no published studies that have formally investigated the effectiveness or safety of this treatment method. Levy and Hyman (2005) cautioned that chronic use of antiviral dugs may result in bone marrow suppression and reported that other undesirable side effects might include headache, abdominal pain, dizziness, nausea, and depression. In addition, antifungal agents have been prescribed for the treatment of ASDs. This approach developed in response to anecdotal reports that children infected with the yeast Candida albicans later developed ASD (Herbert et al., 2002; Levy & Hyman, 2005; Schechtman, 2007). To correct this supposed problem, antifungal medications such as fluconazole, nystatin, or metronidazole are prescribed. In conjunction with this treatment, children with ASDs might also be placed on a low-sugar diet to further reduce the likelihood of yeast overgrowth by limiting potential food sources for the yeast (Levy & Hyman, 2005; Schechtman, 2007; Smith, 2008). Although this method is popular, no published studies have examined the effectiveness of antifungal treatment (Levy & Hyman, 2005; Smith, 2008). Also, just as with antiviral medications, antifungal drug use may lead to other health problems. For example, nystatin use may result in diarrhea, and chronic use of fluconazole may cause liver toxicity (Levy & Hyman, 2005). Because human immunoglobin has been used successfully to treat autoimmune disorders such as myasthenia gravis, some investigators have

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hypothesized that administering intravenous immunoglobulin to children with ASDs could correct immune system deficiencies that might contribute to the symptoms of ASDs (Levy & Hyman, 2005). Three small studies have used this treatment approach, with inconclusive results (Levy & Hyman, 2005; Schechtman, 2007). One study claimed to find improvement following immunoglobulin administration, but a second study reported no improvement in half of its participants, and the third study stated that none of its participants demonstrated any benefit from such treatment. Also, the use of immunoglobulin therapy poses risks for blood-borne infection and possible side effects such as rash and meningitis (Levy & Hyman, 2005). The over-the-counter antacid famotidine, sold under the brand name Pepcid, has also been tried as a treatment for ASDs (Lilienfeld, 2005; Schechtman, 2007; Stephenson, 2002). One study (Linday, Tsiouris, Cohen, Shindledecker, & DeCresce, 2001) employed a single-subject, randomized, double-blind design comparing the effects of famotidine versus placebo in a sample of eight boys with ASDs. Four of the children reportedly showed behavioral improvement, but the other four were nonresponders. There were several methodological flaws in this study, including the fact that the treatment was not truly double-blind. Although both the famotidine mixture and the placebo looked the same, they could be distinguished by their taste (Stephenson, 2002). In addition, behavioral ratings were given by primary caregivers, were not corroborated by other independent observers, and lacked norms against which to compare the participants’ scores (Stephenson, 2002). Also, children who exhibited stereotypic behaviors showed no improvement in response to famotidine, and one child experienced an increase in selfinjurious behavior while on famotidine that resolved when the placebo was administered. Linday and colleagues further wrote that because none of their participants had noteworthy gastrointestinal symptoms before this study, any observed improvements in behavior could have been simply the result of treating asymptomatic esophagitis. As reported in the Brown University Child and Adolescent Behavior Letter (‘‘Famotidine Studied’’, 2001), more studies must be performed before conclusions can be made about the safety and effectiveness of using famotidine among children with ASDs.

Other Biomedical Interventions The use of magnets as a biomedical intervention for autism has also been explored. According to Smith (2008, p. 19), the purpose of this approach is to ‘‘redirect energy flow in the body,’’ presumably to reduce symptom

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severity. Using this method, individuals with ASDs might have magnets placed on their bodies; alternatively, they might sleep on a bed or under a blanket containing magnets. Yet there have been no scientific studies that have researched this approach (Smith, 2008). Also, owing to the weakness of the magnetic fields generated by most ‘‘therapeutic’’ magnets, ‘‘there is no plausible mechanism by which stationary magnets could exert a beneficial influence on human health’’ (Ruscio, 2006, p. 83). A highly publicized biomedical approach to ASDs is nonvaccination (Fraleigh, 2009; Herbert et al., 2002; Offit, 2008; Smith, Ellenberg, Bell, & Rubin, 2008). This approach claims that vaccines such as the measlesmumps-rubella (MMR) vaccine have caused an increase in the number of children with ASDs. Thus, the way to avoid contracting ASDs is to refuse vaccination (Herbert et al., 2002; Offit, 2008). The original controversy over the MMR vaccine and its supposed link to ASDs began with case studies published in 1998 by British researcher Andrew Wakefield (Smith et al., 2008). Although the Wakefield study initially was not widely publicized in the United States, parents and physicians may have become aware of it through the Internet. Examination of vaccine usage rates in the United States revealed that refusal of the MMR vaccine increased from a rate of 0.77% of children in 1995 to 2.1% of children in 2000 (Smith et al., 2008). Wakefield’s 1998 findings have never been replicated (Fraleigh, 2009) and are now viewed by the scientific community as ‘‘significantly flawed’’ (Smith et al., 2008, p. e836). At least 10 epidemiological studies have been unable to confirm that the MMR vaccine is a causal factor for autism (‘‘There Is a Lack’’, 2005), and the World Health Organization, the American Medical Association, the American Academy of Pediatrics, and the United States Centers for Disease Control and Prevention all have rejected the notion that vaccinations cause ASDs (Schreibman, 2005; Simpson, 2008). Furthermore, the risks associated with vaccine refusal are real and potentially fatal (Herbert et al., 2002). In countries where MMR vaccine use has declined, there have been corresponding outbreaks of measles, including some measles-induced deaths that could have been prevented by vaccination (Fraleigh, 2009; Offit, 2008; Smith et al., 2008). Related to the idea that vaccines may cause ASDs is the notion that a particular component of vaccines may lead to the development of ASDs. Thimerosal, a mercury-containing preservative, is often cited as the ingredient in vaccines that causes ASDs (Bihari, 2006; Fraleigh, 2009; Levy & Hyman, 2005; Schechtman, 2007). Because mercury is a heavy metal that can cause nerve damage (Ng, Chan, Soo, & Lee, 2007), thimerosal has been removed from many vaccines (Levy & Hyman, 2005; Schechtman, 2007).

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The United States Food and Drug Administration reported that thimerosal in vaccines does not pose any risks other than occasional localized allergic reactions (Curtis & Patel, 2008). Another study examined children who had been prenatally exposed to thimerosal and found little evidence of adverse outcomes (Curtis & Patel, 2008). Other potential sources of mercury contamination include tooth fillings, excessive consumption of ocean fish such as tuna or swordfish, exposure to mercury contained in thermometers (Ng et al., 2007; Schechtman, 2007), and fish oil supplements (Wallace, 2009). In the belief that ASDs might be the result of heavy metal toxicity, some physicians have suggested chelation, a therapy that removes heavy metals from the body (Levy & Hyman, 2005; Schechtman, 2007; Smith, 2008). However, the idea that mercury poisoning is responsible for the symptoms of ASDs is suspect because children with ASDs seldom manifest the typical symptoms of mercury poisoning, which include ataxic gait, peripheral neuropathy, hypertension, skin eruptions, and constricted visual fields (Ng et al., 2007). Furthermore, there is no scientific evidence that chelation leads to improvement in ASD symptoms (Schechtman, 2007). Also, chelation therapy can be toxic to the liver and kidneys (Bihari, 2006; Levy & Hyman, 2005) and may even cause death (Schechtman, 2007; Smith, 2008). For these reasons, the American Academy of Pediatrics issued a strong statement against the routine use of chelation therapy for children with ASDs (Cohen, 2006; Myers et al., 2007).

Unsupported Psychoeducational Interventions Besides the numerous biomedical treatments for ASDs that lack scientific support, there are several non-evidence-based psychoeducational interventions for ASDs. One such approach, called options therapy or Son-Rise, was created by parents of a boy who supposedly had ASD (Herbert et al., 2002). Intended for use in residential settings, options therapy claims that children with ASDs will improve if their caregivers communicate an attitude of acceptance and encouragement. However, no published studies exist to support the claims of this approach (Herbert et al., 2002; Schreibman, 2005; Smith, 2008; Smith & Wick, 2008). Another psychoeducational approach is facilitated communication (FC). Many youngsters with ASDs not only have impaired communication but also may exhibit a motor deficit called apraxia, which is an inability to properly execute purposeful movements (Herbert et al., 2002). Both problems supposedly can be overcome through the use of a typewriter or

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keyboard with the assistance of a ‘‘facilitator’’ who guides the hand of the person with ASD while typing on the keyboard (Herbert et al., 2002). Families of children with ASDs were delighted that these children supposedly could communicate with them by typing messages, but these messages often came from children who did not even look at the keyboard and who typed using just one finger. A study of this typing technique found that even expert typists could not type meaningful sentences when typing with one finger while not looking at the keyboard (Herbert et al., 2002). Over 50 carefully controlled studies later revealed that the children were not actually the ones doing the communicating. Instead, the facilitators were responsible for the content of the typed messages (Herbert et al., 2002; Levy & Hyman, 2005; Myers et al., 2007; Riggott, 2005; Romanczyk et al., 2003; Schechtman, 2007; Schreibman, 2005; Simpson, 2008; Smith, 2008; Stephenson, 2004). Sensory integration therapy (SIT) is another technique for the treatment of ASDs that lacks an empirical basis. In the 1950s, this method was devised by an occupational therapist who believed that the brains of children with ASDs are deficient in processing visual, auditory, gustatory, and tactile stimuli as well as information pertaining to the body’s location in threedimensional space (Schechtman, 2007). To remediate these hypothesized difficulties, SIT engages children with ASDs in physical activities that are designed to improve sensory and motor functioning, such as swinging on a swing or in a hammock, jumping on a trampoline, or spinning in a chair (Herbert et al., 2002; Schechtman, 2007; Smith, 2008). Other sensory interventions might include wearing weighted articles of clothing (Kane, Luiselli, Dearborn, & Young, 2004), wearing clothes made only of fabrics with certain preferred textures, and removing tags and labels from clothing items (Schechtman, 2007; Smith, 2008; Stephenson, 2004). This approach is frequently used but lacks scientific support demonstrating its effectiveness (Botts, Hershfeldt, & Christensen-Sandfort, 2008; Herbert et al., 2002; Lilienfeld, 2005; Romanczyk et al., 2003; Schechtman, 2007; Schreibman, 2005; Stephenson, 2004; Smith, 2008). In a vein similar to SIT, another nonempirically supported treatment is auditory integration training (AIT). This method derives from the concept that children with ASDs may be overly sensitive to either high- or lowfrequency sounds. To address this problem, AIT requires children with ASDs to listen daily to music that has been filtered to eliminate these sound frequencies. Doing so reportedly allows these children’s auditory systems to function more normally (Herbert et al., 2002). However, studies that compared AIT against a placebo version of AIT have shown that it does not yield any improvement in ASD symptoms (Herbert et al., 2002;

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Levy & Hyman, 2005; Schreibman, 2005; Smith, 2008). Furthermore, some AIT devices may produce sound pressure levels that could be harmful (Schechtman, 2007). Other harmful effects that reportedly have resulted from the use of AIT include disturbances of sleep and appetite as well as headaches, earaches, stomach aches, and increased aggression and hyperactivity (Romanczyk et al., 2003). In fact, the New York State Education Department classified AIT as ‘‘an invasive procedure that could cause harm if not properly administered or monitored’’ (Romanczyk et al., 2003, p. 374). Another type of non-evidence-based therapy for ASDs is a multisensory environment (Stephenson, 2004), also known as a Snoezelen environment (Botts et al., 2008; Stephenson, 2004). Such an environment gently stimulates the five basic senses, which in turn supposedly leads to improvements in coordination, mood, motivation, concentration, behavior, and relationships (Botts et al., 2008). Multisensory environments are becoming more commonplace in public school settings, but the only published studies that have examined the claims of the Snoezelen franchise were conducted in residential settings. Although the findings of these investigations suggest that Snoezelen might be used as an alternative to a time-out room, they do not provide strong support for its other claims. For example, although a few of these studies indicate that aggressive and self-injurious behavior declines in the Snoezelen environment, these effects do not appear to generalize to other settings. At this time the use of a multisensory environment does not have a solid empirical basis (Botts et al., 2008; Stephenson, 2004). Botts et al. (2008) further cautioned that while the use of a Snoezelen environment does no harm, its cost would be better spent on research to identify clinically effective programs and on funding to support their use. Finally, animal therapy (e.g., therapeutic horseback riding) has been promoted as an intervention for children with ASDs, despite a lack of evidence in support of its usefulness (Schreibman, 2005; Smith, 2008). Dolphin-assisted therapy (DAT) has received considerable media attention. Proponents of this method assert that dolphins are particularly responsive to children with special needs and further claim that dolphins’ use of echolocation relaxes children and even changes cellular metabolism in humans (Romanczyk et al., 2003). One study of dolphin therapy concluded that this form of treatment led to lasting improvements in the attention, speech, and motor skills of children with ASDs. However, the design of this study was flawed due to failure to include a control group and failure to consider that maturation alone might account for perceived changes in participants’ symptoms (Romanczyk et al., 2003). Additional concerns about DAT stem from its cost, which is $2,600 per week on average,

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excluding airfare and lodging to reach the facilities that offer such treatments (Romanczyk et al., 2003).

REASONS CAREGIVERS CHOOSE SCIENTIFICALLY UNSUPPORTED TREATMENTS Wong and Smith (2006) reported that the use of complementary and alternative therapies is more common among children with chronic conditions than among children in the general populace. This is particularly true for children with ASDs (Bodfish, 2004), but children with other types of disorders also may be the recipients of unconventional treatments for which there is little or no scientific support. Parents and caregivers may choose non-evidence-based treatments for their children for a variety of reasons. One contributing factor may be the vast number of alternative treatments from which to choose, making it difficult for parents to know which avenue to pursue (Romanczyk et al., 2008). People also tend to pursue non-evidence-based therapies when available treatment methods are not fully effective, are somewhat unpleasant, are hard to implement (Alferink, 2007), or are viewed as socially acceptable (Callahan, Henson, & Cowan, 2008). Another reason for parents’ use of scientifically unsupported treatments may relate to their concerns about the safety of prescription medications or to an assumption that alternative treatment methods may have fewer or less harmful side effects than medicines (Hanson et al., 2007). Some parents may prefer a more natural or holistic approach due to a widespread perception that natural treatments are supposedly safer (Capriotti, 2005; Hanson et al., 2007). Seemingly natural methods such as vitamin supplementation may also be preferred due to their easy accessibility and lower cost in comparison to other forms of treatment (Hanson et al., 2007). Romanczyk and colleagues (2008) listed several other factors that may influence parents’ decisions concerning which treatments to select for their children with special needs. The first of these is a belief that children’s treatment providers are experts who know what is in the children’s best interest. Unfortunately, some physicians and early intervention specialists may lack sufficient knowledge about evidence-based treatments to make appropriate recommendations (Rhoades, Scarpa, & Salley, 2007; Stahmer, Collings, & Palinkas, 2005). Yet parents may continue to seek the services of a less-informed treatment provider for other reasons such as a therapist’s likeability, the amount of time or attention that he or she gives to clients, his

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or her tendency to downplay the severity of children’s symptoms, and the promise of a favorable outcome (Romanczyk et al., 2008). Also, some parents may be enticed by the pronouncements of a particular expert or ‘‘guru’’ who claims to have discovered a remarkable ‘‘breakthrough’’ in the treatment of a given disorder (Romanczyk et al., 2008, p. 372). This supposed expert may use impressive credentials, case studies, and testimonials to persuade parents to utilize treatment approaches that have no theoretical basis or empirical support. He or she also may benefit from the commonly held belief that a newer approach is automatically superior to an older treatment method (Romanczyk et al., 2008). Besides treatment providers, relatives and friends may influence parents’ choices regarding treatments for their children (Green, 2007; Romanczyk et al., 2008). Well-meaning but misguided family members or friends may communicate a distrust of recommendations offered by professionals and may suggest that children’s difficulties will eventually disappear over time without any intervention. Alternatively, they may recount success stories about children whose conditions supposedly have improved as a result of using scientifically unsupported techniques. Relatives and friends may assume that since a treatment appeared to work for one child, it will work for everyone. This rationale overlooks the fact that not all children with a given diagnosis are the same, nor will they all respond similarly to a given treatment (Romanczyk et al., 2008). Additionally, some nonscientifically based treatments may falsely appear to yield positive outcomes that are actually the result of maturation over time (Romanczyk et al., 2003) or are due to a placebo effect in which improvements are perceived merely because they are expected (Bootzin & Bailey, 2005; Ruscio, 2006; Stanovich, 2009). Still another factor that may contribute to parents selecting nonempirically supported treatment for their special-needs children is what Romanczyk and colleagues (2008) refer to as ‘‘Hedge your bets – Do a little bit of everything in the belief that it can’t hurt’’ (p. 362). When adopting this outlook, parents may naively assume that all treatment approaches may be combined in any way, without regard to the timing or amount of treatment provided. They may obtain both evidence-based and non-evidence-based treatment and may subsequently attribute any noticeable improvements to the nonempirically supported method rather than to the evidence-based approach (Ruscio, 2006). Parents of special needs children may select scientifically unsupported treatments because they may have trouble differentiating between credible versus non-credible sources of information about various treatment options (Smith & Wick, 2008; Stanovich, 2009). Searching for ways to help their

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children, they may pursue treatment approaches that they learned about from secondary sources such as the Internet, television, radio, newspapers, magazines, or books, without taking time to evaluate the scientific merits of such interventions (Bell, 2005; Green, 2007). In particular, parents may place unwarranted faith in non-evidence-based treatments as a result of having heard or read testimonials from individuals who claim that a novel treatment worked wonders (Ruscio, 2006; Stanovich, 2009). Although testimonials may seem quite compelling, they do not constitute scientific evidence about the effectiveness of a treatment. A testimonial is an account of isolated, uncontrolled events based on the experiences of a single individual. Since these events are unique to a particular person in a particular set of circumstances, there is no guarantee that the same results will be obtained for other people in other circumstances (Schreibman, 2005). Furthermore, the possibility exists that either placebo effects (already described) or vividness effects may explain the positive results being extolled in a testimonial. The term ‘‘vividness effect’’ refers to the fact that people tend to remember information which is presented in a dramatic way (Stanovich, 2009, p. 60). For example, parents may read or hear an emotionally charged report from another parent who claims that an unorthodox treatment led to significant improvement in a child’s symptoms. Such testimonials tend to be remembered better than more accurate but less emotionally engaging information which states that the same treatment does not work for most other children. Parents who are swayed by testimonials, or by supposed experts who claim to have made revolutionary discoveries, may believe in what Stanovich (2009, p. 123) terms the ‘‘great leap model’’ of science. Many individuals harbor the notion that science advances on the basis of extraordinary discoveries. In reality, however, scientific progress tends to occur at a slow pace, building little by little on the findings of carefully designed research that has been previously conducted. Because most people in the general public are unfamiliar with the so-called gradual synthesis model of science (Stanovich, 2009, p. 123), they may be easily persuaded by sources who claim to have found a radically new way to address hard-to-treat problems. Sadly, when non-evidence-based treatments are administered to students with special needs, these children and their parents incur ‘‘opportunity costs’’ (Ruscio, 2006, p. 192). By pursuing the supposed opportunities presented by empirically unsupported treatments, parents consequently waste time, effort, money, and hope which could have been better spent on implementing an empirically supported intervention. Also, although at best a child’s condition might remain the same, it is possible that his or her

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condition may be aggravated by the use of a non-evidence-based treatment (Ruscio, 2006). Worse yet, using an empirically unsupported treatment may harm a child, either physically or psychologically, and in some cases may even lead to death.

WARNING SIGNS OF PSEUDOSCIENCE Fraudulent science that is not based on the findings of well-designed research is termed pseudoscience (Lilienfeld, Lynn, & Lohr, 2003; Ruscio, 2006). Non-evidence-based therapies constitute examples of pseudoscience, which can be recognized by several warning signs. First, such interventions use vague jargon to convey the impression of scientific terminology while simultaneously attempting to create a mystique about the treatment (Ruscio, 2006; Smith & Wick, 2008). Second, they have not undergone the rigorous peer review process that true science demands. Empirically supported treatments have withstood the scrutiny of genuine experts who have carefully reviewed the research investigations on which these treatments were based. The peer review process ensures that these investigations were well-designed and well-executed and that their results and implications were reported accurately. In contrast, non-evidence-based treatments have not undergone such evaluations (Lilienfeld et al., 2003; Ruscio, 2006; Smith & Wick, 2008). Often, these treatments are first reported directly to the mass media, rather than to scientific journals for purposes of peer review (Stephenson, 2004). Third, pseudoscientific treatments rely almost exclusively on testimonials, anecdotes, and personal experiences or opinions, rather than on the findings of carefully conducted scientific research (Lilienfeld et al., 2003; Ruscio, 2006; Smith & Wick, 2008; Stephenson, 2004). Fourth, scientifically unsupported treatments have not been evaluated using methods that might expose their flaws (Ruscio, 2006). In fact, proponents of pseudoscientific treatments may even claim that traditional scientific methods cannot be used to properly evaluate these treatments and their effects (Stephenson, 2004). A fifth characteristic of pseudoscientific treatments is that their underlying theories have little or no connection with observable reality or with wellestablished scientific knowledge (Ruscio, 2006; Smith & Wick, 2008; Stephenson, 2004). The sixth red flag is a claim that such treatment approaches are holistic, natural, organic, or the like. These terms appeal to parents but fail to communicate any scientific explanations about how such treatments work (Lilienfeld et al., 2003; Ruscio, 2006; Smith & Wick, 2008).

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Seventh, pseudoscientific treatment providers tend to overlook or minimize inconsistencies, reporting only evidence that supports a treatment while ignoring contradictory or disconfirming information (Lilienfeld et al., 2003; Ruscio, 2006; Smith & Wick, 2008). An eighth indicator of nonempirically supported treatments is their reliance on the pronouncements of a supposed authority, rather than on scientific data, as evidence of their effectiveness (Ruscio, 2006). Yet another warning sign of unscientific treatments is their tendency to make exaggerated claims (Ruscio, 2006; Stephenson, 2004), using descriptors such as ‘‘miracle,’’ ‘‘revolution,’’ ‘‘breakthrough,’’ and so on (Smith & Wick, 2008, p. 250). In addition, pseudoscientific treatments tend to remain static and unchanging, even in the face of new scientific developments or contradictory research findings (Lilienfeld et al., 2003; Ruscio, 2006; Smith & Wick, 2008). Finally, claims that the scientific establishment has conspired against the use of a given treatment, as well as evidence that proponents have a vested financial interest in the use of a particular treatment, should alert parents and caregivers that the proposed treatment may not be scientifically supported (Stephenson, 2004).

CONCLUSION The non-evidence-based treatments that were described in this chapter exhibit the hallmark features of pseudoscience. They involve interventions that lack solid theoretical foundations and research evidence to support their use. These treatment strategies may make bold claims about their effectiveness but actually may yield no improvement, and in some cases may even cause harm. Understandably, parents who are considering the use of scientifically unsupported treatments for their children with special needs may be desperately hoping to find a way to eliminate or at least alleviate their children’s difficulties. However, they are more likely to be successful in their search for useful treatments by remembering the familiar axiom that if something seems too good to be true, then it probably is.

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