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Minority Students in Special and Gifted Education 7 Assessment Practices, Definitions, and Classification Criteria In this chapter we discuss the influence of conceptual definitions, classification criteria, and assessment practices on the four educational classifications of concern here: mental retardation, emotional disturbance, specific learning disability, and giftedness. We begin with the disability classifications. Conceptual definitions and classification criteria have enormous influence on the assessment procedures applied during the determination of eligibility and special education needs. Although general assessment requirements are applicable to all disabilities (see Appendix 6-A), there are also specific requirements for each of the disability classifications considered in this chapter. SPECIFIC LEARNING DISABILITY Learning disabilities (LD) are a group of disorders that involve more than half the children in special education programs. LD prevalence has risen rapidly over the past 25 years. Disproportionate minority representation in LD occurs for Asian/Pacific Islanders, who are underrepresented by 2.7 times the rate of white students and for American Indian/Alaskan Natives, who are overrepresented by a factor of 1.2 times the white rate. All other groups are represented at or very close to the rate for white students.
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Minority Students in Special and Gifted Education Concept of Learning Disabilities The notion of learning disabilities and the attendant terminology arose in the mid-1960s when a psychologist, Samuel Kirk, first used the term “learning disability.” Kirk used the term as a catchall phrase to describe a number of different problems affecting the ability of certain children to learn. He noted that these problems manifested themselves in children who were otherwise capable, but were underachieving. There was a variance between the child’s level of achievement and the child’s presumed capabilities. Kirk defined learning disabilities as “a retardation, disorder, or delayed development in one or more of the processes of speech, language, reading, spelling, writing, or arithmetic resulting from a possible cerebral dysfunction and not from mental retardation, sensory deprivation, or cultural or instructional factors” (Kirk, 1962:263). This was a new concept, even though unexpected underachievement in otherwise capable children had been reported much earlier in association with dyslexia, word blindness, dysgraphia, and dyscalculia (Doris, 1993; Hallgren, 1950; Hinshelwood, 1917; Orton, 1925; Strauss and Werner, 1942). Parents, educators, and policy makers embraced the new term “learning disabilities” because it fulfilled a need to provide special education services to children whose failure to learn could not be explained by mental retardation, visual impairments, hearing impairments, or emotional disturbance. The new term represented a new category for describing children with learning impairments that were not attributable to obvious physical, emotional, or psychological shortcomings. There was no stigma attached because “Their difficulties in learning to read, write, and/or calculate occurred despite adequate intelligence, sensory integrity, healthy emotional development, and cultural and environmental advantage” (Lyon et al., 2001). Prior to Kirk’s revelation, children with learning disabilities were simply not being served. The new concept catalyzed parents and educators to act. In 1969 these children were eligible for services with passage of the Learning Disabilities Act. Eligibility continued in the Education of the Handicapped Act (EHA) (1975, 1977) and in the Individuals with Disabilities Education Act (IDEA) (1997, 1999). Legal Context Additional rules were formulated in 1977 specifically for the LD category (34 CFR 300.541). These rules were a compromise that no one particularly liked or supported at the time, but they have survived as an apparently objective method used to solve a difficult problem: determining which students among those with achievement problems should be eligible
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Minority Students in Special and Gifted Education for special education services in the category of LD. The objectivity and appropriateness of the method suggested in the 1977 regulations have been questioned over the past 15 years. The 1977 federal regulations established classification criteria that were not entirely consistent with the LD conceptual definition (see Appendix 6-B), which implied an underlying cognitive processing disorder as the core feature of the disability. The classification criteria had three broad components (see Regulation 540 in Appendix 6-A). The first was low achievement in one of seven areas. The second was “a severe discrepancy between achievement and intellectual ability” in one or more of the seven achievement areas. The third involved what are known as the exclusion criteria: LD could not be the result of inappropriate educational programming; visual, hearing, or motor impairment; mental retardation; emotional disturbance; or environmental, cultural, or economic disadvantage. These criteria could be summarized as defining LD as unexpected low achievement that cannot be explained by low ability, absence of an opportunity to learn, or other factors. State requirements for determining eligibility generally apply the discrepancy and exclusion factors, although there are substantial variations. The most recent national survey of state criteria (Mercer et al., 1996) indicated that 94 percent of states mentioned a processing disorder in the conceptual definition, but processing factors were included in only 33 percent of the states’ classification criteria. Virtually all states applied the exclusion factors (98 percent), and all included the achievement areas of reading, writing, and math. Dissatisfaction with the achievement-ability severe discrepancy criterion has led to consideration of achievement-domain-specific criteria for eligibility (see Chapter 8 for a discussion of problems with the severe discrepancy method). Domain-Specific Definitions Federal law defines LD not as a single disability, but as a group of disabilities that are expressed in one or more skill domains. The disabilities are manifested in the areas of: (1) listening; (2) speaking; (3) basic reading (decoding and word recognition); (4) reading comprehension; (5) arithmetic calculation; (6) mathematics reasoning; and (7) written expression. The broadness of this definition encompasses a wide range of learning difficulties eligible for treatment. However, the complexity of each skill domain and the overlap between the domains compromise diagnostic precision. Diagnosis is further complicated by the fact that disabilities in these areas may be accompanied by other disorders, which are not the cause of the LD.
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Minority Students in Special and Gifted Education Because definitional clarity is so elusive, developing a set of specific operational criteria for identifying individual children has been problematic. Some advocate modification of generic definitions to reflect separate evidence-based definitions of domain-specific disabilities. The development of operational definitions and criteria relevant to each domain would guide procedures to determine which students are eligible for reading disabilities or mathematics disabilities, etc. A great deal is now known about the most common of the learning disabilities—dyslexia or reading disability—and using this domain-specific definitional strategy, investigators have now begun to examine other common learning disabilities, for example, mathematics disability. In the following section we review the significant advances in understanding reading and reading disabilities. Reading Disability Dyslexia is characterized by an unexpected difficulty in reading in children and adults who otherwise possess the intelligence, motivation, and schooling considered necessary for accurate and fluent reading (Shaywitz, 1998). Recent epidemiological data indicate that like hypertension and obesity, dyslexia fits a dimensional model. In other words, within the population, reading ability and reading disability occur along a continuum, with reading disability representing the lower tail of a normal distribution of reading ability (Gilger et al., 1996; Shaywitz et al., 1992; B. Shaywitz et al., 2001; S. Shaywitz et al., in press). Dyslexia is one of the most common of childhood disorders, with a public school prevalence rate of approximately 6 percent (see Chapter 2). Previously, it was believed that dyslexia affected boys primarily (Finucci and Childs, 1981); however, more recent data (Flynn and Rahbar, 1994; Shaywitz et al., 1990; Wadsworth et al., 1992) indicate similar numbers of affected boys and girls. Longitudinal studies, both prospective (Francis et al., 1996; Shaywitz et al., 1995) and retrospective (Bruck, 1992; Felton et al., 1990; Scarborough, 1984), indicate that dyslexia is a persistent, chronic condition; it does not represent a transient developmental lag. Over time, poor readers and good readers tend to maintain their relative positions along the spectrum of reading ability (Shaywitz et al., 1995). Dyslexia is both familial and heritable (Pennington and Gilger, 1996). Family history is one of the most important risk factors; between 23 and 65 percent of children who have a parent with dyslexia are reported to have the disorder (Scarborough, 1990). Rates among siblings of affected persons of approximately 40 percent and among parents of 27 to 49 percent (Pennington and Gilger, 1996) provide opportunities for early identification of affected siblings and often for delayed but helpful identification of affected adults. Linkage studies implicate loci on chromosomes 6 and 15
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Minority Students in Special and Gifted Education for reading disability (Cardon et al., 1994, 1995; Grigorenko et al., 1997) and most recently on chromosome 2 (Fagerheim et al., 1999). Theories of dyslexia have been proposed that are based on the visual system (Demb et al., 1998; Eden et al., 1996; Stein and Walsh, 1997) and other factors, such as temporal processing of stimuli within these systems (Talcott et al., 2000; Tallal, 2000). Although other systems and processes may also contribute to the difficulty, there is now a strong consensus among investigators in the field that the central difficulty in dyslexia reflects a deficit in the language system. Investigators have long known that speech enables its users to create an indefinitely large number of words by combining and permuting a small number of phonological segments, the consonants and vowels that serve as the natural constituents of the biological specialization for language. An alphabetic transcription (reading) brings this same ability to readers, but only as they connect its arbitrary characters (letters) to the phonological segments they represent. Making that connection requires awareness that all words, in fact, can be decomposed into phonological segments. It is this awareness that allows the reader to connect the letter strings (the orthography) to the corresponding units of speech (phonological constituents) they represent. The awareness that all words can be decomposed into these basic elements of language (phonemes) allows the reader to decipher the reading code. In order to read, a child has to develop the insight that spoken words can be pulled apart into phonemes and that the letters in a written word represent these sounds. As numerous studies have shown, however, such awareness is largely missing in dyslexic children and adults (Brady and Shankweiler, 1991; Bruck, 1992; Fletcher et al., 1994; Liberman and Shankweiler, 1991; Rieben and Perfetti, 1991; Shankweiler et al., 1995, 1979; Share, 1995; Shaywitz, 1998, 1996; Stanovich and Siegel, 1994; Torgesen, 1995; Wagner and Torgesen, 1987). Results from large and well-studied populations with reading disability confirm that in young school-age children (Fletcher et al., 1994; Stanovich and Siegel, 1994) as well as in adolescents (Shaywitz et al., 1999), a deficit in phonology represents the most robust and specific (Morris et al., 1998) correlate of reading disability. Such findings form the basis for the most successful and evidence-based interventions designed to improve reading (National Institute of Child Health and Human Development, 2000). Implications of the Phonological Model of Dyslexia Basically, reading comprises two main processes—decoding and comprehension (Gough and Tunmer, 1986). In dyslexia, a deficit at the level of the phonological module impairs the ability to segment the written word into its underlying phonological elements. As a result, the reader experi-
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Minority Students in Special and Gifted Education ences difficulty, first in decoding the word and then in identifying it. The phonologic deficit is domain-specific; that is, it is independent of other, nonphonological, abilities. In particular, the higher-order cognitive and linguistic functions involved in comprehension, such as general intelligence and reasoning, vocabulary (Share and Stanovich, 1995), and syntax (Shankweiler et al., 1995), are generally intact. This pattern—a deficit in phonological analysis contrasted with intact higher-order cognitive abilities—offers an explanation for the paradox of otherwise intelligent people who experience great difficulty in reading (Shaywitz, 1996). According to the model, a circumscribed deficit in a lower-order linguistic (phonological) function blocks access to higher-order processes and to the ability to draw meaning from text. The problem is that the affected reader cannot use his or her higher-order linguistic skills to access the meaning until the printed word has first been decoded and identified. Suppose, for example, that an individual knows the precise meaning of the spoken word “apparition”; however, until he can decode and identify the printed word on the page, he will not be able to use his knowledge of the meaning of the word, and it will appear that he does not know the word’s meaning. Phonological Deficit in Adolescence and Adult Life Deficits in phonological coding continue to characterize dyslexic readers even in adolescence; performance on phonological processing measures contributes most to discriminating dyslexic and average readers, as well as average and superior readers (Shaywitz et al., 1999). Children with dyslexia neither spontaneously remit nor do they demonstrate a lag mechanism for catching up in the development of reading skills. In adolescents, fluency, defined as rapid, accurate oral reading with good comprehension, as well as facility with spelling may be most useful clinically in differentiating average from poor readers. From a clinical perspective, these data indicate that as children approach adolescence, a manifestation of dyslexia may be a very slow reading rate; in fact, children may learn to read words accurately, but they will not be fluent or automatic, reflecting the lingering effects of a phonological deficit (Lefly and Pennington, 1991). Because they are able to read words accurately (albeit very slowly) dyslexic adolescents and young adults may mistakenly be assumed to have “outgrown” their dyslexia. Data from studies of children with dyslexia who have been followed prospectively support the notion that the ability to read aloud accurately and rapidly as well as facility with spelling may be most useful clinically in differentiating average from poor readers in students in secondary school, college, and graduate school. It is important to remember that these older dyslexic students may be similar to their unimpaired peers on untimed
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Minority Students in Special and Gifted Education measures of word recognition yet continue to suffer from the phonological deficit that makes reading less automatic, more effortful, and slow. For readers with dyslexia, the provision of extra time is an essential accommodation; it allows them the time to decode each word and to apply their unimpaired higher-order cognitive and linguistic skills to the surrounding context to get at the meaning of words that they cannot entirely or rapidly decode. Other accommodations useful to adolescents with reading difficulties include note-takers, taping classroom lectures, using recordings to access texts and other books they have difficulty reading, and the opportunity to take tests in alternate formats, such as short essays or even orally (Shaywitz, 1998). Neurobiological Studies To a large degree, advances in understanding dyslexia have informed and facilitated studies examining the neurobiological underpinnings of reading and dyslexia. Thus, a range of neurobiological investigations using postmortem brain specimens (Galaburda et al., 1985) and, more recently, brain morphometry (Filipek, 1996), and diffusion tensor MRI imaging (Klingberg et al., 2000) suggest that there are differences in the temporo-parieto-occipital brain regions between dyslexic and nonimpaired readers. Rather than being limited to examining the brain in an autopsy specimen or measuring the size of brain regions using static morphometric indices based on CT or MRI, functional imaging offers the possibility of examining brain function during performance of a cognitive task. In principle, functional brain imaging is quite simple. When an individual is asked to perform a discrete cognitive task, that task places processing demands on particular neural systems in the brain. To meet those demands requires activation of neural systems in specific brain regions, and those changes in neural activity are, in turn, reflected by changes in brain metabolic activity, which in turn are reflected, for example, by changes in cerebral blood flow and in the cerebral utilization of metabolic substrates such as glucose. The term functional imaging has also been applied to the technology of magnetic source imaging using magnetoencephalography, an electrophysiological method with strengths in resolving the temporal sequences of cognitive processes. Recent findings using fMRI may help reconcile the seemingly contradictory findings of previous imaging studies of dyslexic readers (Shaywitz, B. et al., in press; Brunswick et al., 1999; Helenius et al., 1999; Horwitz et al., 1998; Paulesu et al., 2001; Rumsey et al., 1992, 1997; Salmelin et al., 1996; Shaywitz et al., 1998, submitted; Simos et al., 2000). In addition, some functional brain imaging studies show a relative increase in brain activation in frontal regions and right hemisphere systems in dyslexics com-
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Minority Students in Special and Gifted Education pared with nonimpaired readers (Shaywitz, B. et al., in press; Brunswick et al., 1999; Rumsey et al., 1997; Shaywitz et al., 1998, submitted; Georgiewa et al., 1999).The involvement of the posterior region centered about the angular gyrus is of particular interest, since this portion of association cortex is considered pivotal in carrying out those cross-modal integrations necessary for reading—that is, mapping the visual percept of the print onto the phonological structures of the language (Benson, 1994; Black and Behrmann, 1994; Geschwind, 1965). Consistent with this study of developmental dyslexia, a large literature on acquired inability to read (alexia) describes neuroanatomic lesions most prominently centered about the angular gyrus (Damasio and Damasio, 1983; Dejerine, 1891; Friedman et al., 1993). It should not be surprising that both the acquired and the developmental disorders affecting reading have in common a disruption in the neural systems serving to link the visual representations of the letters to the phonological structures they represent. While reading difficulty is the primary symptom in both acquired alexia and developmental dyslexia, associated symptoms and findings in the two disorders would be expected to differ somewhat, reflecting the differences between an acquired and a developmental disorder. In acquired alexia, a structural lesion resulting from an injury, such as stroke or tumor, disrupts a component of an already functioning neural system, and the lesion may extend to involve other brain regions and systems. In developmental dyslexia, as a result of a constitutionally based functional disruption, the system never develops normally so that the symptoms reflect the emanative effects of an early disruption to the phonological system. In either case, the disruption is within the same neuroanatomic system. A number of studies of young adults with childhood histories of dyslexia indicate that although they may develop some accuracy in reading words, they remain slow, nonautomatic readers (Bruck, 1992; Felton et al., 1990). The model used to study reading and reading disability has now been extended to the study of mathematics and mathematics disability. Though these studies are still in their infancy, the indications are that within the next decade, understanding of the underlying cognitive and neurobiological underpinnings of mathematics disability will be elucidated. Current Identification Procedures The concept of unexpected underachievement remains the central diagnostic criterion for designating a child as LD. Because the definition of LD in EHA/IDEA provided insufficient criteria for identifying eligible children, in 1977 the Department of Education published guidelines for the identification of an unexpected underachievement, settling on an operational defi-
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Minority Students in Special and Gifted Education nition of a severe discrepancy between achievement and intellectual ability, that is, an IQ-achievement discrepancy. Over time, it has become apparent that the use of the IQ-achievement discrepancy has the effect of delaying identification until the child falls below a predicated level of performance. Waiting for a child to exhibit failure sufficient to signal a significant discrepancy between IQ and achievement level takes time. This type of discrepancy cannot be measured until a child reaches approximately age 9 and by that time the student has been experiencing the frustration of academic failure for two to three years. A significant number of epidemiological data show clearly that the majority of children who are poor readers at age 9 continue to have reading difficulties into adulthood (Shaywitz et al., 1999). Thus, a reliance on the IQ-achievement discrepancy, when employed as the principal criterion for the identification of reading disability, possibly harms more children than it helps. Furthermore, good evidence indicates that it is possible to screen children as young as 4-5 years of age and identify those at risk for reading disability, an identification based on poor reading relative to chronological age, that is, poor reading defined solely on the basis of low reading achievement. The results of several studies indicate that there are no significant differences in cognitive characteristics (other than verbal ability) between children who are poor readers relative only to chronological age (i.e., poor readers defined by low achievement) and children defined as reading disabled on the basis of unexpected underachievement (i.e., on the basis of an IQ-achievement discrepancy) (Fletcher et al., 1994; Stanovich and Siegel, 1994). In addition, neurobiological evidence using sophisticated brain imaging technology supports the cognitive data in indicating similar patterns of brain organization in children defined as having a reading disability on the basis of unexpected underachievement and on the basis of low achievement for chronological age (Shaywitz, B. et al., in press). Important for future policy development, the IQ test results and whether or not a child shows a discrepancy between IQ and reading achievement have little significance for understanding or treating a reading disability. MENTAL RETARDATION Disproportionate representation in the mental retardation (MR) category, especially the mild level (MMR), is a long-standing concern in discussions of the participation of minority students in special education (Dunn, 1968; National Research Council [NRC], 1982). Although the numbers of and the degree of disproportionality in minority and nonminority students classified as MR and participating in special education have declined substantially over the past 25 years, the greatest degrees of special education disproportionality continue to occur in this category. Currently,
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Minority Students in Special and Gifted Education 2.63 percent of all black students receive special education services due to the MR disability, a rate that is 2.35 times the rate for white students. White and American Indian/Alaskan Native students are in MR programs at very close to the same rates, while Hispanic students have slight underrepresentation and Asian/Pacific Islanders have substantial underrepresentation (see Chapter 2). Disproportionate MR representation has been the most controversial and intractable pattern over the past few decades. Many changes in MMR have occurred since the 1982 NRC report. While MR was the disability category of interest in that report, during the intervening period many of the mild cases have ceased to be identified as mentally retarded in many states (MacMillan et al., 1996d). It is instructive to note the “vacillating prevalence” of MR among schoolchildren in the past half century (Mackie, 1969). Mackie reports that between 1948 and 1966 there was a 400 percent increase in the number of children served in public school programs for students with MR. During the latter phase of that time period, the American Association on Mental Deficiency adopted the Heber (1959, 1961) definition that set the upper IQ cutoff score at -1 SD (roughly IQ 85), leading Clausen (1967) to note that this was the most liberal, inclusive definition ever of the concept of mental deficiency. In the mid-1960s there was no LD category recognized in federal law, and public schools encountering a youngster with severe and chronic low achievement had few options for helping that child—either they classified him or her as MMR, or services were restricted to the interventions available in general education. The existence of two groups of individuals with MR has long been recognized (Dingman and Tarjan, 1960; Zigler, 1967). One is a more patently disabled group of individuals whose MR more often has a biological basis (referred to as “organic” by some) and whose IQ is commonly very low (i.e., below 50). Zigler (1967) proposed that this group of individuals represents a separate IQ distribution with a mean of approximately 35 and ranges from an untestable level up to an IQ of about 70. Zigler said that the intellectual functioning of this group of mentally retarded children reflected “factors other than the normal polygenic expression”—that these people had an “identifiable physiological defect.” A second group of individuals, referred to as “familial cases of mental retardation” evidence no organic impairment and are believed by Zigler to represent the lowest portion of the normal curve of intelligence. Predictions derived from these hypotheses generated by Dingman et al. were tested by Mercer (1973b), examining the presence of physical disabilities (e.g., seizures, ambulation, vision, and hearing problems) in individuals clinically identified as MR with IQ scores in the range of about 55-75, i.e., the familial type. She concluded: “Clearly, persons whose IQs are more than 3 standard deviations below the mean of
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Minority Students in Special and Gifted Education the population suffer from significantly more physical disabilities than persons whose scores fall within the normal curve (Mercer, 1973b:15). The two groups of individuals with MR are important to the issue of assessment. Physicians typically diagnose the organic cases (i.e., those with IQs below about 55-60), very early in childhood using clinical and laboratory tests, medical histories, and other evidence employed in medical diagnoses. As described in the discussion of referral in Chapter 6, more severe cases of MR are commonly enrolled in preschool programs and arrive for public school enrollment already classified as mentally retarded. The MMR or familial cases, however, have traditionally arrived for enrollment in school undiagnosed with any disability. Diagnosis as MMR occurs only after chronic and severe achievement problems are found, marked by failure to respond to normative instructional materials and methods and leading ultimately to referral and psychoeducational assessment in an effort to determine: (a) if the child has a disability and (b) a prescription for educational treatment. It is this second group of children ultimately classified as MMR over whom the role of educational assessment is most relevant. Behavioral Dimensions Defining Mental Retardation The dimensions of intellectual functioning and social competence (i.e., adaptive behavior) have been fundamental to most definitions of MR. The relative importance of these two dimensions, however, has varied in the different classification schemes proposed (MacMillan and Reschly, 1996). Definitions of MR adopted by the American Association on Mental Retardation (AAMR) have historically been the most influential in terms of being adopted in federal legislation and state education codes (Frankenberger and Fronzaglio, 1991). Moreover, the various AAMR definitions adopted since that of Heber (1961) reflect modest, but not insignificant, variations of that original definition, which read: “MR refers to subaverage general intellectual functioning which originates during the developmental period and is associated with impairment in adaptive behavior” (Heber, 1961:3). In subsequent revisions of the AAMR definition (Grossman, 1973, 1977, 1983; Luckasson, 1992), the importance of adaptive behavior vis-à-vis intelligence was enhanced, and the cutoff score on tests of intelligence defining “subaverage general functioning” has also varied. Intellectual Dimension Under Heber (1961), the criterion for subaverage general intellectual functioning was -1 SD (approximately IQ 85); however it was dropped to -2 SDs by Grossman (1973) (approximately IQ 70). Later, guidelines for employing IQ cutoff scores were adjusted, permitting identification of chil-
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Minority Students in Special and Gifted Education whereas others contend that the curricular content too closely parallels general education curriculum, with little attention afforded to the students’ emotional needs (Webber and Scheuermann, 1997). One possible explanation for this lack of attention to students’ emotional needs is the decline in availability of mental health and school-based counseling (Knitzer et al., 1990). Another concern in the area of service delivery is the tendency to implement ED curriculum and programs that have not been empirically validated. Program and material selection does not seem to be guided by data-driven outcomes (Peacock Hill Working Group, 1991). Instead, it would appear that programs and procedures that produce short-term behavioral changes are sought to address immediate rather than long-term needs (Webber and Scheuermann, 1997). To compound the problem even further, there is a shortage of certified teachers to work with ED students (Wald, 1996). Thus, untrained teachers are left to educate very difficult-to-teach students (Rockwell, 1993). When ED students employ the coercive tactics learned at home (albeit unintentionally) in the school setting with teachers who are ill prepared to manage such behavior patterns (Reid and Patterson, 1989), the result is an aversive series of student-teacher interactions that lead to classroom environments with low rates of praise delivery, positive student recognition, and instruction (Shores et al., 1993; Webber and Scheuermann, 1997; Wehby et al., 1998). Consequently, ED programs often feature a curriculum that is neither empirically validated sufficiently nor comprehensive enough to address the students’ academic and socio-behavioral needs—and, to compound the difficulties further, it is implemented by educators without the proper training. Classroom management practices. Classroom management practices have been widely criticized for what is referred to as a “curriculum of control” (Knitzer et al., 1990; Zable, 1992). A study conducted by Zable (1992) suggests that this emphasis on control has stemmed from administrative pressure, a mandate to emulate general education curricula, and a lack of options. It would appear that little emphasis is placed on identifying the function of the maladaptive behavior and then teaching appropriate replacement behaviors that meet the same functional need (Mace, 1994). Proactive procedures such as precorrection plans (Walker and McConnell, 1995) and rich praise delivery schedules (Wehby et al., 1998) are not being employed to enhance classroom instruction or to prevent behavior problems from occurring during instruction.
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Minority Students in Special and Gifted Education Screening and Assessment Practices The field of behavior disorders has been influenced by the recent shootings that have occurred in schools across the nation (Walker et al., 1999). This tragic series of events has highlighted the need for proactive approaches to identify and assess troubled youth who may be at risk for committing such atrocities. At first glance, screening and early detection appear to be rather simplistic; however, most emotional and behavioral disorders of childhood are not so extreme that they are easily detected by the untrained observer (Kauffman, 1997; Webber and Scheuermann, 1997). However, the field of emotional and behavioral disorders has made substantial progress over the past 20 years, particularly in the area of early detection and intervention. Researchers have established the importance of utilizing school-wide screenings to detect students at risk for ED, employing a variety of assessment tools and procedures based on the principle of multioperationalism, and designing and implementing comprehensive interventions that are linked to assessment results (Gresham, 1985, Gresham et al., 2000; Lane, 1999; Walker and McConnell, 1995). Programs and instruments such as the Systematic Screening for Behavior Disorders (Walker and Severson, 1992) and the Student Risk Screening Scale (Drummond, 1994) are now available for use in schools to identify students who may be at risk for emotional and behavioral disturbances. Over the past 10 years there has been a tremendous increase in the availability of assessment instruments and practices to assess the various domains of emotional and behavior disorders. Some of the more recent advances in assessment include: (a) the use of conditional probabilities methodology (Milich et al., 1987; Pelham et al., 1992); (b) functional assessment methodologies (Horner, 1994; Umbreit, 1995); (c) the notion of resistance to intervention (Gresham, 1991, 2001); (d) direct observation systems, such as the Multiple Option Observation System for Experimental Studies (Tapp et al., 1995); (e) the School Archival Records Search (Walker et al., 1991); (f) curriculum-based assessment (Shinn, 1989); and (g) psychometrically sound rating scales, such as the Child Behavior Checklist (Achenbach and Edelbrock, 1991) and the Social Skills Rating System (Gresham and Elliott, 1990), which can be completed by multiple informants (e.g., parents, teachers, and, in some instances, students). Federal regulations mandate that assessments be conducted by a multidisciplinary team of qualified specialists, given that the assessment results will not only influence eligibility and placement decisions, but also will help guide instructional programming. However, theory and practice do not always converge. Too often the teams have not embraced the advances in screening and assessment and therefore they do not function as intended.
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Minority Students in Special and Gifted Education Diagnostic, placement, and curricular decisions are frequently made based on limited, rather subjective information (Kauffman, 1997). DISABILITY ASSESSMENT PRACTICES Current assessment practices related to the determination of eligibility for disabilities are heavily influenced by legal requirements, as noted in Chapter 6. These requirements determine the kind of assessment that must be provided to all students considered for special education, including LD, MR, and ED. Compliance with these legal requirements is prompted by professional ethics and federal and state compliance monitoring activities, which typically focus on sample cases of students placed in special education. During these monitoring activities, careful scrutiny of the assessment practices and the domains of behavior examined establishes strong incentives for school district personnel to follow general assessment requirements and specific disability classification criteria, although at least some studies suggest that the criteria are applied loosely, especially in the determination of LD. The typical assessment battery for nearly all students with disabilities includes the administration of a comprehensive, individually administered test of current intellectual functioning (IQ test), an individually administered general achievement test, classroom observation of student behavior, and one or more behavioral checklists or rating scales typically completed by the teacher or parent. In some regions, various tests of underlying processes are utilized (e.g., visual-motor, auditory processing). This battery is used with virtually all students with disabilities. The only exceptions occur with students with severe or marked sensory disabilities, which may render psychological and educational assessment impossible. Medical specialists typically diagnose students with severe disabilities of these kinds, and special education eligibility determination is not the primary focus of the evaluation. The relative emphasis placed on the domains above—that is, current intellectual function, achievement, and behavior ratings—depends on the disability that is being considered by the multidisciplinary team. For students considered for the diagnosis of LD, there typically is in-depth consideration of achievement in one or more of the domains identified as problematic in the referral. For example, for a student referred due to low reading achievement, administration of several reading tests and additional formal and informal assessments of reading skills are likely in order to establish more precisely the degree and nature of the reading difficulty. Depending on state classification criteria and local practices, students considered for LD may also receive one or more tests of underlying psychological processes. Currently, measures of phonological processes are nearly
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Minority Students in Special and Gifted Education always part of an LD evaluation if the referral involves reading concerns. The intellectual ability/achievement discrepancy, in current practice, is the most fundamental part of the LD eligibility determination in most states, virtually necessitating the administration of individual IQ and achievement tests. Determination of eligibility in the category of MR is similar to that for the LD category in that tests of current intellectual functioning and achievement are nearly always involved. The MR diagnostic construct, as noted earlier, involves the dimensions of current intellectual functioning and adaptive behavior. Intellectual functioning is almost always assessed through the administration of individual IQ tests. The adaptive behavior domain, when it can be assessed formally, typically involves the results of one or more inventories in which the teacher, parent, or both serve as reporters on the child’s adaptive functioning. A general achievement test is almost always used with MR, as are other measures such as teacher- or parent-completed rating scales or checklists. However, the fundamental feature of MR eligibility determination is the IQ score, with confirming or supportive evidence from formal and informal measures of adaptive behavior. The assessment procedures for ED have the same general characteristics as those for MR and LD. An individually administered IQ test and one or more standardized achievement tests almost always are included in the evaluation for ED eligibility. In addition, the ED evaluation should, and sometimes does, emphasize measures of behaviors across different social contexts, as well as assessment of social skills—including peer relations and interactions with significant adults. Formal rating scales that focus on key behavioral dimensions, such as aggression, attention, hyperactivity, and depression, are nearly always used along with direct observations in relevant settings and interviews with the student, the teacher, and the parents. Depending on the region, students considered for the category of ED may or may not receive projective instruments, such as Rorschach, human figure drawings, and incomplete sentence techniques. Use of highly subjective projective approaches with dubious technical characteristics is more common in the states on the East and West coasts of the United States (Hosp and Reschly, 2002a). Although IQ and achievement tests are typically used with an ED assessment, the fundamental eligibility determination rests typically on reviews of behavioral incidents, social skills measures, and behavior/personality ratings completed by various respondents, who may include teachers, parents, and the student. GIFTED AND TALENTED Because eligibility to receive services as a gifted or talented student is not regulated by federal statutes, the process is usually guided by state-level
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Minority Students in Special and Gifted Education policies that range from law, to rule, to guidelines, to administrative code. In some states, identification of gifted students is not mandated at all. And existing policies on identification stem from widely varying definitions of giftedness and include widely disparate requirements. In some states, local school districts are not required to use the state definition or state guidelines and recommended identification processes. This results in widely different proportions of identified students. In the report of the Council of State Directors of Gifted Education (1999), the percentage of total students identified in those states reporting this statistic ranged from 0.22 percent in Nevada to 22.9 percent in Maryland.1 In Massachusetts only 14 percent of local education agencies identify gifted students. The age at which identification of gifted students begins is also determined at the state level. At least two states report that identification begins as early as pre-K (Council of State Directors of Programs for the Gifted, 1999) while 16 states simply recommend prekindergarten screening (Coleman and Gallagher, 1992). In some states, policies do not mandate identification until grade 4, and in some states the onset of the process is left to local discretion (Council of State Directors of Programs for the Gifted, 1999). The later the identification and screening process occurs, the less likely a student from a minority or low-income population is to be identified using criteria that rely heavily on academic achievement on standardized assessments. As Chapters 2 and 3 suggest, the pattern of lower achievement on standardized assessments of black, Hispanic, and Native American students is at least partially established by the beginning of kindergarten. By 4th grade, the percentages of whites scoring in the advanced range on the National Assessment of Educational Progress on reading, math, science, and writing were from two to five times as large as those for the under-represented minorities, with 0 percent of black and Hispanic students scoring in the advanced range in math, science, and writing (Donahue et al., 2001). The discrepancies among definitions, policies, and implementation of policy at the local school district level result in considerable variation from school to school in the creation of a pool of identified gifted and talented students. Even when a particular definition has been adopted—for example, outstanding academic performance—the subjective judgment of what represents outstanding performance is influenced by the normative performance of students in a given school or school district. 1 Many state directors of gifted programs did not report the percentage of students identified as gifted in their states.
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Minority Students in Special and Gifted Education Identification of Giftedness Many of the suggested practices in the literature on identification of gifted and talented students mirror those suggested for the identification of students with disabilities. There is widespread agreement that assessment tools must validly and reliably measure the construct of giftedness, using separate and appropriate identification strategies to identify different aspects of giftedness, using multiple criteria for identification, and including criteria that are appropriate for underserved populations (Callahan et al., 1995). Current identification practice, however, does not widely adhere to these principles. Perhaps the greatest challenge in determining the validity and reliability of an instrument to measure the construct of giftedness is defining the construct itself. There are some who believe that academic giftedness can be captured in the measure of general intellectual function, often referred to as “g,” that underlies all adaptive behavior (Sternberg, 1999; Jensen, 1998). Jensen (1998) explains: “the g factor reflects individual differences in information processing as manifested in functions such as attending, selecting, searching, internalizing, deciding, discriminating, generalizing, learning, remembering, and using incoming and past-acquired information to solve problems and cope with the exigencies of the environment” (p. 117). The hypothesis of a unitary intelligence factor is generally supported with evidence that g underlies performance across a broad range of tests. However, this interpretation is challenged by those who argue that separate dimensions of intelligence are identifiable, and students who demonstrate exceptionality on one dimension often are unexceptional on others (e.g., Gagne, 1985; Gardner, 1983; Stanley, 1984). Sternberg (1997) considers that analytic, creative, and practical intelligence are three different, largely uncorrelated dimensions that are expressed as different abilities both inside and outside the classroom. Gardner (1999) argues for eight separate intelligences, although there are no predictive empirical data to support his argument. Benbow and Minor (1990) studied extremely precocious 13-year-old students and found that mathematical and verbal giftedness were entirely distinct. Moreover, within-individual discrepancies are typically much greater for high-ability than low-ability students (Detterman and Daniel, 1989). As with disability determination, aligning assessment with the construct being measured provides just two legs of a table. The third leg required for functionality is alignment of the program or intervention. It does little good to broaden the definition of giftedness to include creativity, leadership, or musical ability if the program a school has to offer gifted students is advanced mathematics. Yet Callahan et al. (1995) found schools using intelligence tests to assess creativity and musical aptitude.
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Minority Students in Special and Gifted Education In their survey of school districts regarding identification of gifted and talented students, Callahan et al. (1995) found that despite contemporary understandings, most school divisions subscribed to the original federal definition found in the Marland report (U.S. Department of Health, Education, and Welfare, 1972). The construct of general intellectual ability in the federal definition of giftedness was the most frequently used construct guiding identification. Referral and Identification Procedures The initiation of the identification process in many localities is a call to teachers to simply nominate all students they believe to be gifted. In other school divisions, the initial consideration for gifted services may be initiated through a process of asking teachers to complete a checklist or rating scale on all students in the class or only those from the class judged to be gifted. In most cases, these nomination forms or checklists are based on a set of characteristics rather than on specific assessments of educational need. Widespread use of teacher judgment has been identified as a potential explanation for the disproportionate representation of minority students (other than Asians) as gifted and talented (e.g., Ford, 1995, 1996). Some scholars argue that teacher nominations are compromised by the generally low expectations that they hold for culturally and linguistically diverse learners (Clasen, 1994; Dusek and Joseph, 1983; Jones, 1988; McCarty et al., 1991) and their inability to recognize characteristics of giftedness when exhibited in nontraditional behaviors of minority children (Bermudez and Rakow, 1990). As discussed in Chapter 6, empirical findings regarding teacher bias in natural settings are inconclusive. It is not uncommon for schools to also collect nominations of parents, but parents of Hispanic and black students tend to refer their children at lower rates than white parents (Colangelo, 1985; Scott et al., 1992; Woods and Achey, 1990). The potential significance of teacher and parent involvement was suggested by the results of a program designed to increase minority participation in gifted programs that was launched some time ago in Greensboro, North Carolina (Woods and Achey, 1990). Although the program study was done in 1986-1989, its findings are noteworthy. Identification for the gifted program in grades 2 through 5 relied on a combination of standardized test scores and parent, teacher, peer, or self-nomination. Once nominated, a student was eligible for up to three rounds of aptitude and achievement testing: the first two were group evaluations, and the third was an individual evaluation. After testing, parents were notified of the test results. A qualifying score would admit the child to the program. If the child scored below the cutoff point, the parent or a school committee could request retesting. Students were required to reach a cutoff score that com-
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Minority Students in Special and Gifted Education bined achievement test scores, aptitude test score, and (with a much lower weight) scholastic performance. The highest scores from the three rounds were used to determine eligibility. The standards for determining giftedness were not altered in the program that targeted minority students. Rather, when a minority student was identified as at or above the 85th percentile on the school-wide standardized tests, the three-step evaluation was begun; no nomination was required. Two professionals were assigned to the program to administer individual tests, monitor test scores, track data, and ensure follow-through for the targeted students. Parents were notified after each round, but testing proceeded through the full battery unless there was a specific parent request to discontinue. Without altering standards for entry, the number of minority students in the gifted program increased by 181 percent, from 99 to 278 students. Minority students’ share of the gifted program increased from 13.2 to 27.5 percent. Only 15 percent of the minority students ultimately identified were identified on the first round of testing. In some school systems, the referral pool comes from reviewing group-administered tests and selecting those who score above some predetermined score. Archambault et al. (1993) report that 79 percent of teachers in a national survey claimed that achievement tests are used to identify the gifted in their schools, 72 percent use IQ tests, and 70 percent use teacher nomination. Not surprisingly, intelligence tests were the most frequently cited tests for measuring the construct of general intellectual ability, with general reliance on group tests. Individual tests were most often used only for further data gathering in borderline cases. School divisions with specific provisions for identifying gifted students from minority populations most often relied on traditional measures to accomplish this goal. Often the school districts listed individual intelligence tests as the vehicle for most effective identification of minority students. Screening by reviewing test scores is sometimes carried out in combination with teacher nominations, parent nominations, and/or peer nominations and sometimes as the sole source used in creating a screening pool. The next step in the decision process resulting in classification as gifted is sometimes based on a single score derived from the tests or the teacher nominations used in the screening process. In other cases, identification may entail the collection of a specified range of data, including scores derived from group or individually administered ability or achievement tests, creativity tests, teacher ratings, portfolio reviews, or interview data. While in 34 policy statements states recommended the use of multiple criteria for identification (Coleman and Gallagher, 1992), a survey of schools in 50 states found only very limited applications of this principle in practice (Patton et al., 1990).
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Minority Students in Special and Gifted Education The data that are collected in the assessment process may be reviewed by a team of educators, or students may be identified by the entry of the scores on a matrix that assigns arbitrary weights to particular scores or ratings; it assigns a prescribed number of the highest-scoring students or students meeting a preassigned total score to the gifted program. The use of such matrices has been criticized for presenting the illusion of being more culturally unbiased while, in truth, using a procedure that still gives greatest weight to the scores with most variability—test scores (Callahan and McIntire, 1994). In other identification procedures used in schools, students whose scores or other characteristics meet a set of prescribed criteria on the indicators are selected. Finally, a case study approach may be used, in which the data are used to describe educational needs and to assign program and curricular modifications. Screening and Identification in Underserved Populations The underrepresentation of American Indian/Alaskan Native, black, and Hispanic students in gifted and talented programs was reviewed in Chapter 2, using data from the periodic surveys of school districts conducted by the Office for Civil Rights. Concern with disproportionality is reflected in the federal Jacob K. Javits Gifted and Talented Students Education Act of 1988, which gave highest priority to “the identification of gifted and talented students who may not be identified through traditional assessment methods (including economically disadvantaged individuals, individuals of limited English proficiency, and individuals with handicaps” (p. 238). It is also reflected in court cases (e.g., Coalition to Save Our Children v. State Board of Education, 1995): racial discrimination has been the focus of suits brought against local school districts, often as a component of more general charges of discrimination within a school division (Karnes and Marquardt, 2000). Coleman and Gallagher (1992) reported that 38 state policies make some reference to issues of identifying gifted students from “culturally diverse populations, economically disadvantaged students and disabled students” (p. 11). In some states, there are specific guidelines for selecting tests or carrying out the identification process to help schools identify greater numbers of minority students; in other states, specific instruments are recommended (e.g., the Raven’s Progressive Matrices Test, the Matrix Analogies Test, the Torrance Test of Creative Thinking). These tests emphasize reasoning ability or “fluid” intelligence and de-emphasize information acquisition or “crystallized knowledge,” which is likely to be more culturally specific. The Raven’s Progressive Matrices, for example, assess nonverbal, ab-
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Minority Students in Special and Gifted Education stract reasoning by having students select which pattern pieces fit best into an overall array or matrix. While the cultural neutrality of the abstract patterns is appealing, its usefulness for gifted and talented identification has not been fully tested. One study found that scores on the test were not related to school performance (Mills et al., 1993), and it does less well at predicting academic achievement than most intelligence tests or specific ability measures (Baska, 1986; Raven, 1990). This does not suggest that the Raven’s is less able to identify exceptional ability; it may be that the students who score well are exceptional in respects not well tapped by school programs. The validity of these alternative methods and their effects on disproportionality are largely unknown, although nonminority and high-income students tend to perform better than their minority, low-income counterparts (Mills et al., 1993). Noting that state policies have not resulted in uniform adoption of procedures effective in increasing identification of low-income or minority students, Coleman and Gallagher (1992) investigated the factors that inhibited the adoption and implementation at the local level of more flexible and permissive identification policies. They found two major constraints to implementation. The first was a fear that increased numbers of identified students would not be accompanied by an increase in financial resources, and the second was a fear of legal suits that would be filed by parents whose children might have higher test scores but were not selected for the programs (reverse discrimination suits). While the literature is replete with suggestions for increasing the numbers of black, Hispanic, American Indian/Alaskan Native students, it is much more limited in the documentation of success of alternative strategies in recruiting and retaining such students in gifted and talented programs. However, several innovative efforts have been documented. One model focused on interactive staff development using core attributes of intellectual giftedness, corresponding observable behaviors (as they might be manifest in low-income and minority populations), and group decision making using multiple assessment tools. It was successful in generating greatly increased numbers of teacher nominations and subsequent identification as gifted (Frasier et al., 1995). A complex system (described by the authors as labor-intensive and time-consuming) using classroom observation, multicultural curriculum-based enrichment activities, standardized assessments, portfolio assessments, teacher nominations for screening and a dynamic assessment tool, literature-based performance assessment, standardized tests, and child interviews demonstrated that academically gifted students could be found “even in the most beleaguered schools” (Borland and Wright, 1994:170). A comprehensive screening of kindergarten children in an urban environment increased the identified 1st grade
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Minority Students in Special and Gifted Education students in that school division from 0.2 percent to 2 percent (Feiring et al., 1997). All the approaches noted above focused on identification and traditional conceptions of giftedness. Other nontraditional strategies with promise for identification are based on alternative conceptions of intellectual ability and include studies of the effects of curricular adaptations on identified students. One strategy, based on adopting an alternative conception of giftedness derived from Howard Gardner’s model of intellectual functioning and employing a set of performance assessment tasks, provided evidence that minority or economically disadvantaged students selected using this model during kindergarten and provided with systematic curricular intervention were more likely to be selected for programs for the gifted in 3rd grade (Callahan et al., 1995). Students at the high school level identified using Sternberg’s triarchic conception of intelligence and students who were instructed using strategies that matched their patterns of identified areas of strength performed better than students who were mismatched across a broad range of assessments (Sternberg et al., 1996). CONCLUSION A theme that runs through this chapter and, indeed, through the entire report warrants repeating here: addressing disproportion is far more complex than changing the participation numbers by adopting assessment tools that will identify a different racial/ethnic mix of students. The goal must be to better serve the educational needs of all students. Success in that endeavor will depend first on the alignment of program interventions to the educational needs of students, and only then on crafting better assessment tools and procedures. While the tools must be valid, reliable, and culturally unbiased, they must also effectively identify those students who need and can profit from the interventions made available at the school. Certainly as the needs of atypical learners are better understood, the interventions we design may, and should, change. Assessment practices must then evolve to serve the purpose of linking student need to program intervention. The research base that highlights the challenge of designing and administering assessments for students from very different cultures and socioeconomic backgrounds suggests, however, that persistent attention to the ability of the assessment tool to reliably identify educational need is warranted. In the next chapter we look at the major challenges to current assessment practices in this regard, and at alternatives that in the committee’s view would better serve the end of linking educational need to special and gifted program interventions.
Representative terms from entire chapter: