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This research paper reviews the area of learning disabilities. The following issues are considered: definition of subtypes, reading disability, arithmetic disability, assessment, and remediation and accommodation.
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Historically, W. M. Cruickshank (1981) has suggested that the term learning disabilities is “one of the most interesting accidents of our professional times” (p. 81). It was never used before 1963 and developed from “prepared but informal remarks” (W. M. Cruickshank, 1981, p. 81) made by Samuel A. Kirk at a dinner for concerned parents of children with learning problems in Chicago. Shortly after the dinner, the parents organized themselves on a national level under the banner Association for Children with Learning Disabilities. Therefore, the term learning disabilities (LD) was adopted as a “functional term without precedents to guide those who attempted to define it and without research or common usage which would assist in its appropriate formulation as a functional term” (W. M. Cruickshank, 1981, p. 81).
This problem is complicated by the confusion in terms used to describe some or all of the LD population. W. W. Cruickshank (1972) observed that more than 40 English terms have been used in the literature to refer to some or all of the children subsumed under the LD label. Hammill, Leigh, McNutt, and Larsen (1981) also noted that a variety of terms—such as minimal brain dysfunction or injury, psychoneurological learning disorders, dyslexia, or perceptual handicap, to name a few—all have been used to refer to LD populations.
In response to the confusion surrounding the definitional issues, in 1981 the National Joint Committee for Learning Disabilities (NJCLD) adopted the following definitions:
Learning disabilities is a generic term that refers to a heterogeneous group of disorders manifested by significant difficulties in the acquisition and use of listening, speaking, reading, writing, reasoning, or mathematical abilities. These disorders are intrinsic to the individual and are presumed to be due to central nervous system dysfunction. Even though a learning disability may occur concomitantly with other handicapping conditions (e.g., sensory impairment, mental retardation, social or emotional disturbanced) or environmental influences (e.g., cultural differences, insufficient/inappropriate instruction, psychogenic factors), it is not the direct result of these conditions or influences. (Hammill et al., 1981, p. 336)
However, as a number of investigators have suggested (e.g. Fletcher & Morris, 1986; Siegel & Heaven, 1986; Wong, 1996), this definition also is difficult to operationalize because it is vague and unspecific. Wong (1996) and Keogh (1986, 1987) note that in spite of this definition and The Rules and Regulations for Implementing Public Law 94-142 (Federal Register, 1977), special-education categories still differ from country to country, state to state, and even within states from district to district. To complicate matters further, Epps, Ysseldyke, and Algozzine (1985) found that states using different category names to classify learning disabled children may actually be using the same criteria to identify these children and some states using the same category names may be using different identification criteria.
Mann,Davis,Boyer,Metz,andWolford(1983),inasurvey of child service demonstration centers (CSDC), found that although most of the CSDCs used the federal criterion of academic underachievement, only two thirds of the centers used even two or three other criteria, and only 3 of the 61 centers used all of the diagnostic criteria. Furthermore, 36 CSDCs did not distinctly state discernible diagnostic criteria.
In 1985, the U.S. Congress passed an act (PL 99-158) forming the Interagency Committee on Learning Disabilities (ICLD) “to review and assess Federal research priorities, activities, and findings regarding learning disabilities” (Silver, 1988, p. 73). According to Silver (1988) three specific mandates were identified by Congress: (a) the determination of the number of people with learning disabilities and a demographic description of them; (b) a review of the current research findings on the cause, diagnosis, treatment, and prevention of learning disabilities; and (c) suggestions for legislation and administration actions that would increase the effectiveness of research on learning disabilities and improve the dissemination of the findings of such research, and prioritize research on the cause, diagnosis, treatment, and prevention of learning disabilities.
In 1987, the committee presented its report to Congress. In this report, the ICLD recommended a legislated definition of LD based on a revision of the 1981 NJCLD’s definition. The new definition was to include (changes are in italics) “significant difficulties in . . . social skills.” Also, the final sentence was changed to read as follows: “with socioenvironmental influences (e.g., cultural differences, insufficient, or inappropriate instruction, psychogenic factors), and especially with attention deficit disorder, all of which may cause learning problems, a learning disability is not the direct result of those conditions or influences” (Silver, 1988, p. 79).
In addition, the committee argued that prevalence studies on learning disabilities should not and could not accurately be undertaken until there was national consensus on a definition of learning disabilities. However, since the publication of the report only one member of the NJCLD has supported that revised definitions, whereas the others have voted for nonsupport. At issue appears to be the phrase significant difficulties in . . . social skills. In spite of all the work and research, Silver (1988) concludes that a lack of a uniform definition and set of diagnostic criteria is one of the most crucial factors inhibiting current and future research efforts. This problem must be addressed before further epidemiological, clinical, basic, and educational research can result in meaningful, generalizable findings.
Several aspects of these definitions are controversial and difficult to operationalize:
- Exclusionary criteria. One aspect of these definitions is that the learning difficulty is not a result of some other condition.
- IQ-achievement discrepancy. There must be a discrepancy between so-called potential and achievement such that achievement is significantly lower than would be predicted from achievement.
- The learning problem is specific, generally confined to one or two cognitive areas.
The presence of certain factors means that an individual will not qualify as learning disabled; these are called exclusionary factors. The definition of learning disabilities assumes that: (a) a learning disability is not the result of an inadequate education; (b) the individual does not have any sensory deficits, such as hearing or visual impairment; (c) the individual does not have any serious neurological disorders that may interfere with learning; and (d) the individual does not have major social or emotional difficulties that might interfere with learning. All of these exclusions seem reasonable, but they are rarely evaluated systematically; furthermore, it is not clear that there is any reason to do so. Consider, for example, a student with a seizure disorder. If the student is shown to be achieving poorly on some achievement test—similar to an individual pure learning disability without a neurological disorder—should the student be denied the remediations that are available to students with a learning disability? In the view of this author, the answer is no.
In regard to the issue of adequate education for students in a postsecondary institution, it is difficult to believe that a student would complete secondary school without an education in the basic skills of reading, spelling, writing, and arithmetic. The problems may not have been remediated, but there has been significant exposure to the teaching of these skills. Similarly, individuals with learning disabilities often report depression, social anxiety, low self-esteem, and other emotional difficulties. It is quite likely that these symptoms are a consequence—not a cause—of their problems. We do not know which came first, the emotional difficulty or the learning disability, and in most cases we will never know. However, these emotional difficulties appear to become more serious as the person gets older, indicating that the presence of the learning disability may be creating the emotional problem rather than the other way around; we can never be certain. There does not appear to be any longitudinal research that provides evidence on the causal direction of the relationship between learning disabilities and emotional problems. However, it seems unethical not to identify and treat the learning disability just because there are concurrent emotional difficulties.
IQ tests are typically used in the identification of a learning disability. A great deal of weight is still given to the IQ score in the definition. In virtually all school systems and many colleges and universities, the intelligence test is one of the primary tests used in the identification of learning disabilities. In many cases, an individual cannot be identified as learning disabled unless an IQ test has been administered. One of the criteria for the existence of a learning disability is the presence of a discrepancy between IQ test score and achievement. I maintain that the presence of this discrepancy is not a necessary part of the definition of a learning disability; furthermore, it is not even necessary to administer an IQ test to determine whether someone has a learning disability. Many investigators (e.g., Fletcher & Morris, 1986; Reynolds, 1984–1985, 1985; Siegel, 1985a, 1985b, 1988a, 1988b, 1989a, 1989b) argue that not only is this assumption controversial, but it also may be invalid.
The intelligence test—and scores based on it—are not useful in the identification of learning disorders. There are both logical reasons for and empirical data to support this statement. It is often argued that we need IQ tests to measure the so-called potential of an individual. This type of argument implies that there is some real entity that will tell us how much an individual can learn and what we can expect of that person—that is, the IQ sets a limit on what the person can learn.
Lezak (1988) argues that IQ is a construct and does not measure any real function or structure. However, that argument has not prevented psychometricians from measuring this entity. But what is being measured? Presumably, intelligence means such skills of logical reasoning, problem solving, critical thinking, and adaptation to the environment. This definition appears to be a reasonable until one examines the content of the IQ test. IQ tests consist of measures of factual knowledge, definitions of words, memory, fine-motor coordination, and fluency of expressive language; they do not measure reasoning or problem-solving skills. They measure—for the most part—what a person has learned, not what he or she is capable of doing in the future. Typical questions on the IQ test consist of questions about definitions of certain words, about geography and history, tasks involving fine-motor coordination such as doing puzzles, memory tasks in which the person is asked to remember a series of numbers, and mental arithmetic problems in which individuals must calculate answers in their heads without the benefit of paper and pencil.
It is obvious that these types of questions measure what an individual has learned—not problem solving or critical thinking skills. In some of the subtests of the intelligence tests, extra points are given for responding quickly; therefore, the intelligence test puts a premium on speed. A person with a slow, deliberate style would not achieve as high a score as an individual who responded more quickly. Therefore, IQ scores do not represent a single entity; rather, are a composite of many skills. (For an extended discussion of the content of IQ tests, see Siegel, 1989a, 1989b, 1995.)
There is an additional problem in the use of IQ tests with individuals with learning disabilities. It is a logical paradox to use IQ scores with learning disabled individuals because most of these people have deficiencies in one or more of the component skills that are part of these IQ tests; therefore, their scores on IQ tests will be an underestimate of their competence. It seems illogical to recognize that someone has deficient memory, language, fine-motor skills, or any combination of these and then say that this individual is less intelligent because he or she has these problems.
One assumption behind the use of an IQ test is that IQ scores predict and set limits on academic performance, so that if a person has a low IQ score, educators should not expect much from that person’s academic skills. In other words, by using the IQ test in the psychoeducational assessment of possible learning disabilities, we are assuming that the score on the IQ test indicates how much reading, arithmetic, and so on that we would expect from a person. However, some evidence does contradict this assumption. There are people who have low scores on IQ tests—that is, scores less than 90 or even 80; yet, they have average or even above average scores on reading tests. Even text comprehension may be more influenced by background knowledge (Schneider, Körkel, & Weinert, 1989) or phonological skills (Siegel, 1993b) than IQ scores (Siegel, 1988b); logically, this should not occur if level of reading were determined by IQ scores.
The most widely used IQ tests, the Wechsler Intelligence Scales for Children–III (WISC-III) and the Wechsler Adult Intelligence Scales–Revised (WAIS-R) are actually composed of two scales—a Verbal Scale in which the questions are largely based on language, from which one calculates a Verbal IQ, and a Performance Scale, from which one calculates a Performance IQ. It is also possible to calculate a total or full-scale IQ score. If a discrepancy between IQ and achievement is used, then which IQ score should be used—the Verbal, Performance, or full-scale score? It is quite possible to be categorized as dyslexic on the basis of one IQ score but not if another IQ score is used. For example, Valtin (1978–1979) found that it makes a difference which scale is used, the Verbal or Performance Scale. Children are often classified as dyslexic when the classification is based on one scale, but they are not considered dyslexic when the decision is based on the other. In addition, depending on the type of IQ scores, the difference between the good and poor readers could be significant or not significant, depending on which IQ score was used in the definition.
There is also empirical evidence that suggests it is not necessary to use the concept of intelligence in defining reading disabilities. When children with reading disabilities were divided into groups based on their IQ level and compared on a variety of reading, language, memory, spelling, and phonological tasks, there were no differences between the IQ groups on the reading-related tasks (Siegel, 1988b). Therefore, the reading-disabled group was quite homogeneous in relation to reading-related skills; administering an IQ would not provide useful information about performance differences on reading-related tasks.
One typical use of the IQ test is to use the IQ score to measure the discrepancy between IQ and academic achievement. If there is a discrepancy, then the individual is said to have a learning disability. If the individuals are poor readers but show no discrepancy between their IQ and reading scores, then they are not considered reading disabled. Fletcher et al. (1989) maintains that it has not been clearly demonstrated that children with discrepancies in IQ and achievement have more specific disabilities than do poor achievers whose IQ scores were not discrepant. In fact, they contend that there is relatively little empirical evidence to show that similarly defined children differ on measures other than IQ. In an epidemiological study on the influence of various definitions of learning disabilities on the selection of children, Shaywitz, Shaywitz, Barnes, and Fletcher (1986) found that although variations in the use of IQ indexes led to the identification of different children as learning disabled, there were few differences in cognitive abilities. Moreover, there were few differences among identified LD children with discrepant and nondiscrepant IQ scores.
A significant number of studies have found no difference in the reading, spelling, phonological skills, and even reading comprehension of learning disabled individuals with high and low IQ scores and no differences between individuals with dyslexia and poor readers on measures of the processes most directly related to reading (e.g., N. Ellis & Large, 1987; Felton &Wood, 1991; Fletcher, Francis, Rourke, Shaywitz, & Shaywitz, 1992; Fletcher et al., 1994; Friedman & Stevenson, 1988; Gottardo, Stanovich, & Siegel, 1996; Hall, Wilson, Humphreys, Tinzmann, & Bowyer, 1983; Jiménez-Glez & Rodrigo-López, 1994; Johnston, Rugg, & Scott, 1987a, 1987b; Jorm, Share, Matthews, & Maclean, 1986; Share, McGee, McKenzie, Williams, & Silva, 1987; Siegel, 1988b, 1992, 1998; Silva, McGee, & Williams, 1985; Stanovich & Siegel, 1994; Taylor, Satz, & Friel, 1979; Toth & Siegel, 1994). For example, Siegel (1992) compared two groups of children who had low reading scores. One group, which was composed of individuals with dyslexia, had reading scores that were significantly lower than were those that were predicted by their IQ scores; the other group, the poor readers, had low reading scores, but these reading scores were not significantly lower than would be predicted by their IQ scores. On a variety of reading, spelling, and phonological tasks, results showed no differences between these two groups in reading comprehension. In other words, there is no need to use IQ scores to predict the difference between the individuals traditionally called learning disabled and those who have equally poor achievement but also have lower IQ scores. These results have also been replicated in a study of adults with reading disabilities (Siegel, 1998). These findings suggest that there is no need to use IQ tests to determine who is learning disabled. We need to use only achievement tests. In addition, IQ scores do not predict who is able to benefit from remediation (Arnold, Smeltzer, & Barneby, 1981; Kershner, 1990; Lytton, 1967; Van der Wissel & Zegers, 1985; Vellutino & Scanlon, 1996; Vellutino, Scanlon, & Lyon, 2000). One study (Yule, 1973) found that reading disabled children with lower IQ scores made more gains than did reading disabled children with higher scores.
Other research shows that reading problems may actually interfere with the development of language, knowledge, and vocabulary skills, further complicating the issue of the relationship between IQ and reading; this is called the Matthew effect. The Matthew effect refers to the bidirectional relationship between reading and cognitive development. Stanovich (1986, 1988a, 1988b) has conceptualized the Matthew effect as “the tendency of reading itself to cause further development in other related cognitive abilities”—that is, IQ—such that the “rich get richer and [the] poor get poorer” (Stanovich, 1986, p. 360). Certain minimum cognitive capabilities must be present to begin reading; however, after reading commences, the act of reading itself further develops these same cognitive capabilities; this relationship of mutual reinforcement is called the Matthew effect. This Matthew effect of a reciprocal relationship between reading and other cognitive skills is reflected in performance on an IQ test; consequently, it undermines the validity of using an IQ-discrepancy-based criterion because children who read more gain the cognitive skills and information relevant to the IQ test and thus attain higher IQ scores. Children with reading problems read less; therefore, they fail to gain the skills and information necessary for higher scores on the IQ test.
If the Matthew effect as described by Stanovich were operating, it would be expected that IQ scores would decline with increasing age because vocabulary and knowledge increase as a result—at least in part—of experiences with print. If reading disabled children have less experience with print than do children without reading problems, then the chance to acquire new knowledge is reduced and the IQ scores are expected to decrease over time. In a cross-sectional study, Siegel and Himel (1998) found that the IQ scores—in particular, vocabulary scores—of older dyslexic children were significantly lower than were those of younger dyslexic children. Similar declines in IQ and vocabulary were not noted for the normally achieving readers—that is, children who showed age-appropriate reading skills. However, standard scores of the children with reading problems compared to chronologically age-matched children remained relatively constant with time, so that there was not an overall decline in skills. Scores on a subtest of the IQ test, Block Design, a test of visuospatial as opposed to verbal skills, also remained constant over time. This subtest measures visuospatial skills more than it does verbal skills, and it is not directly related to the knowledge required by reading. In addition, younger children were much more likely to be classified as dyslexic (as opposed to poor readers) than were older children because of the so-called decline in IQ scores that resulted from lack of print exposure. Finally, if intelligence is a measure of some stable construct of ability or potential and IQ tests measure it, then these test results should be stable over time. Elliot and Boeve (1987) found that the variable time has a statistically significant effect on both children’s WISC-R verbal and performance scores. Therefore, for these students, it is questionable if the WISC-R is measuring a stable construct.
Ultimately, services may be denied to individuals who have not been administered an IQ test or who do not achieve a certain score on the IQ test (e.g., see Padget, Knight, & Sawyer, 1996). IQ scores are significantly correlated with socioeconomic status—that is, children from lower socioeconomic backgrounds are likely to have lower IQ scores probably because of a relative lack of experience with the vocabulary and knowledge measured by the IQ test. Children from low socioeconomic backgrounds are more likely to be classified as poor readers than are dyslexics even though these children have the same degree of reading difficulty as dyslexics (Siegel & Himel, 1998); this means that the use of the discrepancy definition discriminates against children from low-SES backgrounds. Some argue that we should use IQ test scores because IQ is correlated with achievement (e.g., Wong, 1996). As Tunmer (1989) has noted, parental income is correlated with reading achievement (the correlations are almost identical in magnitude to those between reading and IQ); why not use a discrepancy between parental income and reading achievement as a measure of dyslexia? A significant discrepancy would be needed for the individual to get remedial help. The social consequences and unfairness of this suggestion are obvious, but the principle is the same as using a discrepancy between IQ and achievement.
The requirement for the use of the IQ score provides us with the dilemma of determining an IQ score that is necessary for an individual to achieve to be considered learning disabled. Some studies use 80, others 85, others 90, and some even use 100. For example, although they recognize that there are problems with the use of IQ in the identification of learning disabilities, Padget et al. (1996) argue that
Clinical judgment may be needed when considering cases in which the Verbal IQ is below 90. Two cases in which this may be particularly important are older students who previously achieved a Verbal IQ above 90 and students who have low subtest scores only on the subtests that require significant auditory, sequential memory skills to perform the task. In most other cases when students score below these guidelines it strongly suggests that reading problems may be related to factors other than, or in addition to, dyslexia. (p. 59).
However, they present no evidence for this assertion. An opposing conclusion has been reached by G. Reid Lyon (1995) of the U.S. National Institute of Child Health and Human Development as follows:
The assumption that a discrepancy between achievement and aptitude (typically assessed using intelligence tests) is a clear diagnostic marker for learning disabilities or can be considered a pathognomonic sign is at best premature, and at worst invalid. (p. 5121)
Often, it is recommended that instead of the IQ test, measures of listening comprehension be used presumably because this will assess an individual’s level of cognitive processing (Aaron, 1991; Padget et al., 1996). Listening comprehension measures typically consist of the examiner’s reading aloud a passage to the individual and then asking him or her questions about the text. This type of task places heavy demands on memory, and if an individual fails to answer a question correctly, the examiner does not know whether the individual did not understand the passage or has merely forgotten the answer. Ability to remember what has been heard also depends on one’s background knowledge of the material in the text. Unlike when one reads text in which the material is available, one cannot refer back to the material in a listening comprehension task. Therefore, the time has come to abandon listening comprehension as an alternative to the IQ test.
Another assumption of many LD definitions—including US Public Law 94-142, Ontario’s Bill 82, and the NJCLD’s definition—is that there must be a discrepancy between IQ and achievement. In other words, the child’s achievement is not commensurate with his or her ability or intelligence (IQ).
The second assumption of the discrepancy definition is that measures of intelligence and measures of achievement are independent. This assumption has been questioned by some investigators (see Lyon, 1987, for a complete discussion), but I maintain that it is necessary if a discrepancy definition is to be meaningful. If one accepts the argument that intelligence is not orthogonal to achievement, then there would be no reason to expect a discrepancy. Therefore, a discrepancy definition is logical if and only if the presence of a learning disability does not affect IQ test scores but does affect achievement test scores. Then children with LD would have a discrepancy between the scores on their IQ tests and the scores on their achievement tests, whereas normally achieving children and those with other disabilities will have scores on these tests that are similar (not discrepant).
A number of investigators (Green, 1974; Hopkins & Stanley, 1981; Siegel, 1988a, 1988b) have suggested that this assumption of independence is questionable. Green (1974) argues, for example, that comparisons of scores for ability and achievement are meaningful only to the extent to which unique elements are measured.
Hopkins and Stanley (1981) examined the overlapping variance in a well-constructed intelligence test (the LorgeThorndike) and in two subtests (the reading and the arithmetic) of a well-constructed achievement test (the Iowa Test of Basic Skills). On average, 47% of the variance was found to overlap.This finding suggests that when one ability test and one achievement test are used, about 50% of the time the same concept is being measured; this clearly violates the assumption of independence among concepts measured by the ability and achievement tests. It can only be hoped that the other 50% of the variance is tapping something different that can provide insight to the true differences revealed by the comparison.
Discrepancy definitions also have been questioned on statisticalgrounds.Reynolds(1984–1985,1985)notesthatmany discrepancy models are based on grade equivalents. He points out that these models have problems in two areas. First, neither age nor grade-equivalent scores provide adequate mathematical properties (cannot be added, subtracted,multiplied, or divided) for use in discrepancy analysis. Second, the amount of retardation reflected by 2 years below grade level changes with increasing grade level. A much greater level of retardation is reflected by a 2-year deficit at Grade 2 than at Grade 7, and even less retardation would be reflected at Grade 11. Therefore, a much greater deficit would be needed for a child in Grade 3 to be identified as LD than for one in Grade 10.
In summary, the weight of the evidence leads us to conclude that IQ scores are irrelevant to the definitions of learning disabilities.
There are two types of specificity: The first involves the degree to which the individual’s problem is specific to one or more cognitive areas, and the second involves the issue of whether all children with learning disabilities should be considered one homogeneous group. A number of authors (Hall & Humphreys, 1982; Stanovich, 1986, 1988a; Swanson, 1988b, 1989) have maintained that one of the essential concepts of a learning disability is its specificity—that is, a learning disability is presumed to be caused by a neurological inefficiency that affects a narrow group of subskills of cognitive processes; this affects a specific domain of academic skills but leaves intellectually ability intact. In other words, a learning disability reflects a cognitive deficit possibly due to a neurological dysfunction that is comparatively specific to a particular domain (e.g., reading or arithmetic). Swanson (1988a) has suggested that these specific deficits must not stray too far into other cognitive domains, or the concept of a specific learning disability will blend with other more generalized conditions (e.g., mental retardation).As well, Stanovich (1986) maintains that definitions of dyslexia must rest on an assumption of specificity. He contends that dyslexia results from a brain or cognitive deficit that is reasonably specific to reading.
Siegel (1988a) and Bryant and Brown (1985) argue that this type of specificity is unrealistic. Siegel (1988a) maintains that if children have problems in working memory, this condition could affect a variety of academic tasks—especially in areas such as reading, spelling, and arithmetic. Brown and Bryant (1985) suggest that if a child has a severe language problem, this condition could influence a large number of cognitive areas: reading, writing, speaking, listening, or any combination. Moreover, Siegel (1988a) contends that implicit in the specificity assumption is the assumption that domains such as reading and arithmetic are entirely independent cognitive processes. This assumption is invalid because working memory and recognizing and labeling abstract symbols are involved in both reading and arithmetic skills, and a child who has difficulty with these cognitive processes is likely to have problems with tasks involving such skills (Siegel, 1988a).
The second type of specificity involves questions about the degree to which all children with LD have the same problems or whether there are subtypes. On the basis of what is now known, the concept of a generalized homogeneous group labeled LD children should be abandoned; the child with LD should be considered as part of a smaller, more clearly defined subtype (Siegel, 1988a). As well, other theorists (e.g., Bateman, 1968–1969; Benton & Pearl, 1978; Boder, 1973; Kinsbourne & Warrington, 1963; Rourke, 1983, 1985) have contended that differences within the population of children with learning disabilities may reflect the existence of distinguishable subtypes. In other words, not all learning-disabled children have the same types of disabilities, and independent subtypes include distinctive characteristics and antecedent conditions that consistently predict specific patterns of learning difficulties. Therefore, failure to differentiate among types of learning disabilities can lead to inaccurate conclusions. For example, Siegel and Ryan (1984, 1988) found that children with reading disabilities have difficulty processing certain aspects of syntax, whereas specific children with specific arithmetic disabilities (and no reading disability) do not. Differences between the same two groups have been found in working memory (Fletcher, 1985; Siegel & Linder, 1984; Siegel & Ryan, 1989a). Swanson (1988b) found that children with a reading disability may be characterized by different patterns of memory dysfunction. These differences are reflected on measures of achievement in reading and arithmetic. If all these children had been considered together as a homogeneous group, these differences might have been obscured.
A Resolution of Definitional Issues
Clearly the field of special education continues to have problems defining and classifying children with learning disabilities. Current discrepancy definitions are problematic and should be reconsidered because they cannot be justified in light of their illogical nature. But where does that leave us and where can we go from there?
One way in which meaning is given to a concept is by defining it operationally. Specifically, an operational definition explains a concept solely in terms of the operations used to produce and measure it. Recognizing that there are problems inherent in operational definitions (e.g., the meaning of the concept is restricted to the narrowly described operations used for measuring it), I suggest that learning disabilities (a) need to have an IQ threshold because I recognize that the field is not ready to accept Siegel’s (1989a, 1989b) challenge to the use of IQ tests; (b) should refer to a significant difficulty in a school-related area; and (c) should exclude only severe emotional disorders, second-language background, sensory disabilities, and specific neurological deficits.
Evidence (Siegel, Levey, & Ferris, 1985; Siegel & Ryan, 1989b) suggests that the type of operational definition used for the concept may influence the outcome and conclusions of the study. Siegel and Ryan (1989b) have argued that the actual definition used for a reading disability can make a difference in the conclusions that are drawn about information-processing characteristics of the children and whether there are readingdisability subtypes. In one study, poor readers (all with IQ scores equal to or above 80) were divided into four groups as follows: (a) those with deficits in phonological processing— inadequate phonological skills based on the reading of pseudowords, (b) those with word-recognition deficits, (c) those with comprehension-only deficits—inadequate reading comprehension skills but adequate word-recognition skills, and (d) those with rate-only deficits—slow reading speed but adequate word-recognition skills. When each disabled group was compared to an age-matched normally achieving group, distinct cognitive differences appeared. For example, children with a phonological deficit or a word-recognition deficit had scores that were significantly lower than were those of normal readers on short-term memory tasks but not on language tasks. The readers with rate-only deficits had cognitive profiles similar to those of normally achieving children. Therefore, the children with word-recognition problems are probably the ones with language deficits and those with only a reading comprehension problem probably do not have language problems.
In addition, there was approximately a 25% overlap between poor comprehenders and poor readers; therefore, had a reading comprehension test been used to define the learningdisabled group and word recognition not been used as a control,thereading-disabledgroupwouldhaveconsistedofsome children with word-recognition problems and some without.
This leads to the question How should a reading disability be defined? Stanovich (1986, 1989) has suggested that the core deficits in a reading disability are problems in phonological processing. Although reading is more than simply decoding and recognizing words (one has to remember what was read, put it into context, etc.), unfortunately currently there are no accurate tests to measure these variables (see Siegel & Heaven, 1986, for a complete discussion of this issue). Further empirical evidence suggests that when a difficulty with phonological processing, word recognition, or both is used as the basis of the definition of a reading problem, then disabled readers appear to have reasonably homogeneous cognitiveprofilesand—inparticular—deficitsinthelanguage areas (e.g., Fletcher, 1985; Rourke & Finlayson, 1978; Rourke & Strang, 1978; Siegel & Ryan, 1984, 1988, 1989b; Strang & Rourke, 1983b). Therefore we and others (e.g., Siegel & Heaven, 1986; Siegel & Ryan, 1989a; Vellutino, 1978, 1979) argue that single-word or nonword reading constitute the purest measures of reading and that an operational definition of a reading disability should be based on nonword tests to measure phonological skills, single-word tests to measure word recognition skills, or both.
The classification of children with arithmetic problems is equally problematic. As Siegel and Ryan (1989a) note, it is almost impossible to find a group of reading-disabled children who also do not have severe deficits in arithmetic. At the same time, a number of investigators (Fletcher, 1985b; Rourke & Finlayson, 1978; Rourke & Strang, 1978; Siegel & Feldman, 1983; Siegel & Linder, 1984; Siegel & Ryan, 1984, 1988, 1989a) have found a group of learning-disabled children with difficulties in arithmetic but with average or above-average reading scores. Some evidence (e.g., Fletcher, 1985a; Rourke & Finlayson, 1978; Rourke & Strang, 1978; Siegel & Feldman, 1983; Siegel & Linder, 1984; Siegel & Ryan, 1984, 1988, 1989a) suggests that these children with arithmetic deficits but normal reading (word recognition) have cognitive profiles that are different from those of children with reading difficulties. Therefore, it is important that children designated as arithmetic LD not have problems that are confounded by difficulties in reading.
Given the heterogeneity of LD groups, Siegel (1988b) contends that if all LD children are grouped together, then inaccurate conclusions may be reached. Evidence in support of this position has been found by many investigators (e.g., Fletcher, 1985; McKinney, Short, & Feagans, 1985; Rourke & Finlayson, 1978; Siegel & Linder, 1984; Siegel & Ryan, 1984, 1988, 1989a, 1989b). For example, Siegel and Ryan (1984, 1988, 1989a, 1989b) and Fletcher (1985) found differences between specific arithmetic-disabled children without reading problems and reading-disabled children in both short-term and working memory. McKinney et al., using a cognitive battery designed to assess a wide range of linguistic and perceptual abilities, were able to classify 55 firstand second-grade, school-identified LD children into six subtypes.They then demonstrated that the three subtypes with atypical cognitive profiles had poorer academic outcomes than did the three groups with normal or near-normal profiles. These differences might not have been evident had these children been grouped together and not divided into subtypes.
Because of this heterogeneity of LD groups, considerable effort has been made to identify specific subgroups of LD children who share common attributes that distinguish them from other subtypes. Not only do subtypes exist, but they also seem to take several forms in terms of achievement patterns, associated cognitive information-processing abilities, or both. Furthermore, these subtypes may vary as a function of etiology and age (e.g., McKinney et al., 1985; Rourke & Finlayson, 1978; Satz & Morris, 1981; Short, Feagans, McKinney, & Appelbaum, 1986; Siegel & Heaven, 1986).
Early subtype approaches are based on clinical inferences that have attempted to reduce complex data sets of subjects into presumably homogeneous classes largely based upon a priori considerations and visual inspection techniques. These methods have been criticized for their inability to manage simultaneously large quantities of information in an objective fashion as well as for the subjectivity that results from the bias of clinical decisions made at various stages during the subtype development and subject classification (see Satz & Morris, 1981, and Hooper & Willis, 1989, for a complete review).
More recently, with the availability of advanced computer technology, empirical classification models using applied descriptive multivariate statistics have been developed. This approach has involved a search for hidden structure in complex multidimensional data sets generally involving cognitive linguistic skills or direct measures of achievement or behavior (e.g., Doehring & Hoshko, 1977; Feagans & Appelbaum, 1986).
These methods also have difficulties. Hooper and Willis (1989) contend that standards of reliability and validity have frequently been overlooked or marginally addressed by investigators using these classification techniques. In addition, they suggest that “the adequacy and strength of models derived by empirical classification methods are influenced by many a priori clinical decisions including those regarding theoretical orientation, sample selection, and variable selection” (p. 104). Thus, the appropriate subtyping model remains an open question and may depend on the type of research undertaken.
Academic Performance Models
In spite of the difficulties inherent in subtyping models, a number of investigators (e.g., Fletcher, 1985; Rourke & Finlayson, 1978; Rourke & Strang, 1978; Siegel & Feldman, 1983; Siegel & Linder, 1984; Siegel & Ryan, 1984, 1988, 1989a, 1989b) have suggested that LD students in general can be divided on the basis of their academic achievement as measured by Wide RangeAchievement Test (WRAT) scores in reading, spelling, and arithmetic. Although each investigator has created his or her own classification scheme, two broad categories of subtype groups have emerged. The first contains children with at least reading deficits, and the second contains children with at least arithmetic deficits and normal-to-abovenormal reading scores. Some authors (e.g., Fletcher, 1985; Rourke & Finlayson, 1978; Rourke & Strang, 1978) have subdivided these groups further, basing their divisions on the presence of other deficits. For example, Siegel and Linder (1984) and Siegel and Ryan (1984, 1988, 1989a, 1989b) have used only two academic subtypes: (a) an arithmetic-disabled group, defined by scores equal to or below the 25th percentile on the WRAT Arithmetic subtest and scores equal to or above the 30th percentile on the WRAT Reading subtest and (b) a reading-disabled group, defined by scores equal to or below the 25th percentile on the WRAT Reading subtest and no cutoffs for the other two WRAT subtests. Fletcher (1985b) has developed the following four subtypes: (a) a reading-spellingdisabled group, (b) a reading-spelling-arithmetic-disabled group, (c) an arithmetic-disabled group, and (d) a spellingarithmetic-disabled group. According to this categorization, the reading-spelling-disabled group is defined as consisting of children with (a) WRAT Reading and Spelling subtest scores below the 31st percentile, (b) WRAT Arithmetic subtest scores above the 30th percentile, and (c) the arithmetic score must be at least one-half standard deviation above the reading score on the appropriate WRAT subtest. The reading-spelling-arithmetic-disabled group is characterized by children with scores on all three WRAT subtests below the 31st percentile. The arithmetic-spelling-disabled group contains children who have (a) WRAT Spelling andArithmetic subtest scores below the 31st percentile, (b) WRAT Reading subtest scores above the 39th percentile, and (c) at least one standard deviation between their reading and arithmetic scores. The arithmeticdisabled group consists of children who have (a) WRAT Reading and Spelling subtest scores above the 39th percentile, (b) WRAT Arithmetic subtest scores below the 31st percentile, and (c) difference of at least one standard deviation between their reading and arithmetic scores. In contrast, a series of studies by Rourke and his associates (Rourke & Finlayson, 1978; Rourke & Strang, 1978; Strang & Rourke, 1983a, 1983b) have identified the following three subtypes: (a) a general disabled group (reading-spelling-arithmetic-disabled), (b) a reading-disabled group, and (c) an arithmetic-disabled group. These investigators defined their reading-spellingarithmetic groups as consisting of children with WRAT subtest scores below the 19th percentile on all three subtests. The reading-spelling-disabled group consisted of children with (a) WRAT Arithmetic subtest scores at least 1.8 years higher than their WRAT Reading and Spelling subtest scores and (b) WRAT Reading and Spelling subtest scores below the 15th percentile. The arithmetic-disabled group contained children whose WRAT Reading and Spelling subtest scores were at least 2 years above the WRAT Arithmetic subtest scores.
Rourke and colleagues have developed subtypes of LD children based on patterns of academic performance (Fisk & Rourke, 1979, 1983; Ozols & Rourke, 1985; Porter & Rourke, 1985; Petrauskas & Rourke, 1979; Rourke & Finlayson, 1978; Rourke & Strang, 1978; Rourke & Fisk, 1981; Strang & Rourke, 1983, 1985a, 1985b; Sweeney & Rourke, 1978). Depending on the particular investigation, percentile cutoff scores of 20, 25, or 30 on the WRAT have been used to define a particular LD group.
In one study, Rourke and Finlayson (1978) investigated the performance of three groups of LD children on a neuropsychological battery. The subtypes were formed on the basis of their WRAT scores in reading, spelling, and arithmetic. The first subtype exhibited uniformly deficient performance in all three academic areas. They were found to be superior to a specifically arithmetic-disabled group on measures of visual-perceptual and visuospatial abilities. In the second subtype, children were relatively good at arithmetic as compared to their reading and spelling, but all areas were below average. Superior visuospatial abilities and Performance IQ scores were characteristic of this subtype. The third subtype was composed of children whose reading and spelling scores were average or above, but whose arithmetic score was at least 2 years below that. This group exhibited Verbal IQ scores that were higher than their Performance scores. Their performance on measures of visual-perceptualorganizational skills was somewhat deficient. Their performance on measures of verbal and auditory-perceptual abilities was superior to that of the first two groups, who were reading disabled and low achievers in arithmetic. Rourke and Strang (1978) found further deficiencies in this third subtype on complex psychomotor measures and differences in hand superiority on the Tactual Performance Test. Difficulties in visuospatial orientation, including right-left problems, and impaired bilateral tactile-perceptual abilities, including finger agnosia, were also characteristic of this group.
Strang and Rourke (1983a, 1983b) found that the specific arithmetic-disabled children made significantly more errors than did the reading and arithmetic disabled children on the Halstead category test. The arithmetic-disabled children had lower scores on those subtests, which “require a substantial degree of ‘higher order’ visual-spatial analysis” (Strang & Rourke, 1985b, p. 173). An analysis of the arithmetic errors made by the third group (specifically arithmetic disabled) on the WRAT subtest indicated a large number and variety of errors. The quality of errors, as expected, changed somewhat with age. The most prevalent types of mechanical errors were identified as follows: (a) spatial organization, (b) visual detail, (c) procedural errors, (d) failure to shift psychological set, (e) graphomotor, (f) memory, and (g) judgment and reasoning, indicating deficits in visuospatial and perceptualmotor abilities.
Ozols and Rourke (1985) compared the performance of two groups of LD children to a group of average-achieving children of the same age on four tasks—two verbal and two nonverbal. The groups were identified as follows: (a) a language-disorder group, who exhibited relatively welldeveloped visuospatial abilities but poor auditory-perceptual and language-related abilities (WRAT subtest percentile scores in reading, spelling, and arithmetic were all below 25); (b) a spatial-disorder group, who exhibited relatively welldeveloped auditory-perceptual and language-related abilities but poor visuospatial abilities (WRAT arithmetic subtest score was the only percentile score below 25). The languagedisorder group performed significantly more poorly on the verbal tasks than did the controls, and the spatial-disorder group performed significantly more poorly than did the controls on the nonverbal tasks.
Siegel and Ryan (1984) used performance on achievement tests to subdivide LD children into more heterogeneous groups. Three LD groups were created and compared to a control group of normally achieving children. The LD groups were (a) reading-disabled children who had low scores on the WRAT Reading test, a test of word recognition skills; (b) children who were arithmetic written work disabled who had low scores on the WRAT Arithmetic test, a measure of computational arithmetic skills; and (c) children with attention deficit disorder (ADD; hyperactive) but with no other learning disabilities. Typically, the reading-disabled children had significantly below-average ability to understand the syntactic and morphological aspects of language and—at the youngest ages—memory for sentences. None of the other LD groups showed deficits in these areas. The reading-disabled children had a significant deficit in reading and spelling nonwords and in recognizing the visual form of a spoken sound. None of the other LD children had deficits in these areas, with the exception of the youngest, specifically arithmeticdisabled children, who had some difficulties with these phonological skills in spite of their normal word-recognition skills. This finding may be a result of the definition of arithmetic disability, which at the youngest ages involves memory skills in addition to computational skills. Thus, these younger arithmetic-disabled children may represent the more severely disabled children compared to older children who have a specific arithmetic disability. The children with ADD and no other difficulties with achievement did have significantly lower scores on a reading comprehension test (which is in reality a memory test and may require attentional skills), but these children showed no other deficits.
All of the reading-disabled children had a severe deficit involving phonological skills. They were quite homogeneous in this respect. In most cases there was no overlap in the scores of the reading-disabled and normally achieving children of the same chronological age. Furthermore, for the reading and spelling of nonwords, the reading-disabled children performed more poorly than did younger controls matched for reading level, indicating a very serious deficit. The children with an arithmetic writing disability and the children with a reading disability had significantly lower scores on a short-term memory task involving visually presented letters, but Siegel and Linder (1984) found that for auditorily presented letters, the arithmetic-disability group performed in the normal range, indicating that the deficit of this latter group was limited to short-term memory for visually presented information.
Fletcher (1985) used a verbal and nonverbal memory task to test the hypothesis that subgroups of disabled learners show different performance patterns. All tasks were based on selective reminding procedures (i.e., in subsequent presentations, items are repeated only if they were not recalled on the previous trial) to determine what inferences could be drawn concerning storage and retrieval skills in these subgroups. Control subjects had to obtain percentile scores above 39 on the Reading, Spelling, and Arithmetic subtests of the WRAT and show no history of achievement difficulties. Disabled learners were placed into one of four groups depending on their pattern of WRAT scores. The groups were (a) readingspelling-disabled (R-S), (b) reading-spelling-arithmeticdisabled (R-S-A), (c) spelling-arithmetic-disabled (S-A), and (d) arithmetic disabled (A).
The findings indicated that not all LD children showed similar patterns of memory deficiencies. Children with reading problems showed only retrieval difficulties on verbal tasks, whereas children with arithmetic problems demonstrated both storage and retrieval problems on nonverbal tasks. Children with the R-S pattern had poorer verbal skills, whereas children with the arithmetic pattern showed poorer nonverbal skills. The R-S-A pattern had not been previously studied, but children demonstrating this pattern had relatively poor performance on the tasks used in this study.
Some studies were carried out in an attempt to determine the relative diagnostic power of a number of tests in discriminating between dyslexic children and those with other learning disabilities. In one study by Rudel and Denckla (1976), the performance of developmental dyslexic individuals was tested using visual-verbal tasks, such as naming pictured objects, letters, and numbers. A 2-year or greater lag in reading performance on a test of oral reading skill led to a classification of dyslexic.All participants were tested on rapid automatized naming tasks. Stimuli included colors, numerals, useobjects(e.g.,comb),andhigh-frequencylowercaseletters. The naming speed on all four tasks for normally functioning individuals was faster than for nondyslexic LD participants, and nondyslexic participants were significantly faster than dyslexic subjects.
In this study, the experimental children were termed learning disabled, but no reference was made to how they were so designated. The authors stated that division of participants into dyslexic and nondyslexic groups was done post hoc by determining the difference between reading age and mental age. Reading grade level was based on a test of oral reading skill; no mention was made of what oral reading test was used. The problems associated with such tests have already been discussed. The lack of information on the measures used in this study raises questions about the heterogeneity and severity of the problems demonstrated by the group being studied.
In a second study (Denckla, Rudel, & Broman, 1981), a series of tasks was administered: a rapid automatized naming task, the Oldfield-Wingfield Pictured Object Naming Test, visual-Braille letter learning (a paired associate learning task), visual-temporal spatial matching (a same or different response was required of the participant after he or she watched a series of light flashes emitted from a single stationary point source in a black box), and finally the silent detection of repeated target symbols (a pencil-and-paper version of the visual matching task paradigm). The dyslexic group had a high percentage of dysphasic errors and prolonged times on repeated naming compared to the nondyslexic LD children.
In this study, the participants were defined as dyslexic on the basis of a discrepancy between the WISC-R score and the score on the Gray Oral Reading Test. The same problems as in the earlier study emerge. The latter test is an oral reading comprehension test that cannot be regarded as a pure test of reading skill. Failure to do well on this test could be the result of poor decoding skills, poor attention, poor memory, or poor comprehension. The result is a heterogeneous sample with findings that have limited external validity.
Another attempt at subtyping on the basis of achievement test scores is described by Satz and Morris (1981). Although their subtyping scheme resembles Rourke’s, it is flawed by the use of grade-level retardation on the WRAT subtests for classification. This scheme is particularly problematic with the many older children in the study.
Rather than finding significant heterogeneity on language and memory functioning, these studies found homogeneity within the population of disabled readers. It is important to note that the studies that have found homogeneity within the reading-disabled population have used retardation in wordrecognition skills to define the reading-disabled population. In one very early study on subtyping that was unsuccessful, it was found that all reading-disabled children had difficulty with sound blending and short-term memory (Naidoo, 1972). As discussed later in this research paper, studies that have used other definitions (reading comprehension) do not find the same degree of homogeneity. As further evidence of this point, Siegel and Ryan (1989b) found that when a definition of reading disability was used that involved poor word-recognition or phonics skills, reading-disabled children had significant problems with phonological processing and understanding of syntax. However, children with low reading comprehension scores but good phonics, word recognition skills, or both did not show these problems. In summary, with achievement test definitions such as those used by Rourke and associates, Fletcher, and Siegel and colleagues, fairly homogeneous groups of reading-disabled children have emerged.
Regardless of the exact criteria used, this method of subtyping had identified groups of LD children whose arithmetic difficulties are not confounded by deficits in reading (word recognition). The emergence of a specific arithmetic-disabled subgroup has permitted investigators to clarify some of the characteristics that distinguish this group from other LD children with reading deficits.
Subtypes Within the Reading Disability Group
A number of investigators have assumed that a reading disability is not a single disorder but rather represents a group of more specific subtypes. Some of these conceptualizations are outlined in the following discussion. However, what appears to be heterogeneity is really not; because of definitional inadequacies, heterogeneity emerges. Several schemes have been used as subtyping systems. These schemes involve (a) the use of achievement tests to classify all LD children with the implicit assumption that all the children with a reading disability will show a reasonable similarity in cognitive performance and be different from those without a reading disability (as was described earlier), (b) the use of patterns of responses on reading tests to classify subgroups of disabled readers, (c) the use of neuropsychological measures to differentiate subgroups of disabled readers, and (d) the use of a large number of tests and elaborate multivariate statistical procedures to search for more homogeneous subgroups of disabled readers.
We examine attempts at subtyping according to these classification systems. It should be noted that there is a fundamental difference between the first type of subtyping scheme and the other three types. In the first type, patterns of achievement in other areas besides reading (e.g., spelling and arithmetic) are examined. Typically these studies—unlike the other three types—do not attempt to divide disabled readers into reading subtypes; rather, they try to differentiate disabled readers from other groups of LD children.
Classification Based on Reading Patterns. Some classification schemes based on qualitative differences in reading performance have been attempted. For example, Lovett (1984) proposed that there are two subtypes of disabled readers: rate disabled readers who read slowly but have adequate decoding skills and accuracy disabled readers who have below-average decoding skills. Lovett found a number of differences between the accuracy and the rate disabled readers. However, the conclusions reached by Lovett may be a function of her definition. It seems to be quite possible that her rate disabled readers were not really reading disabled. For example, they had to be 1.5 years below grade level on four out of five of the rate measures. Grade level is an imprecise measure and represents an ordinal rather than an interval scale. Subtracting grade levels is not an appropriate way of defining individual differences. In addition, the same level of grade retardation may mean a different discrepancy at various levels in the developmental continuum. For example, a younger child with even a slight grade-level retardation would score at a low percentile or standard score level, whereas an older child might not necessarily have a low percentile score even at a 1.5- or 2-year grade-level retardation (see Siegel & Heaven, 1986, for detailed evidence on this issue). As many of the children in Lovett’s study were at an older age level, in which a 1.5 grade level retardation does not necessarily indicate a serious impairment, the use of this criterion may mean that many of these children were not seriously reading disabled. The rate disabled children were not obviously impaired in spelling, language, comprehension, regular and exception word reading, or phonics, whereas the accuracy disabled children were. Although these rate disabled children may have been slower than average in reading speed (even this is unknown because of the grade-level criterion), it is not clear that they were different from normal readers. More important is that it is not clear that such children should be called disabled or dyslexic. They clearly have many good reading skills—for example, reading nonwords, reading exception words, and understanding syntax. They are probably below average in reading speed but not really disabled. Superficially, although it appeared that Lovett found subtypes, closer examination reveals that not all these children are truly reading disabled.
Vernon (1977) proposed a system for defining subgroups of poor readers based on variations in the level of the component skills involved in reading, such as letter discrimination, letter-sound correspondence, or slow reading. Unfortunately, such a system is not very useful without precise operational definitions or a methodology for separating these subgroups. Vernon’s analysis of reading appears to represent sequential development of skills related to reading rather than skills that are absent or present simultaneously. Another attempt at defining groups of reading-disabled children was made by Boder (1968, 1971, 1973), who developed a screening procedure for diagnosing reading disabilities on the basis of three so-called reading (but actually spelling) patterns. Boder’s screening procedure consists of a two-part test, flashed and nontimed presentation of words, and an individual spelling test based upon the child’s reading performance. Spelling is assessed by asking the children to spell words from their sight vocabulary (at or below reading level) and then an equal number from their unknown vocabulary at grade level. The rationale for this method is that including words from the children’s sight vocabulary allows for assessment of a child’s ability to revisualize words and inclusion of unknown words taps the ability to spell phonetically (Boder, 1971). On the basis of this screening procedure, Boder outlined a categorization scheme to classify children with dyslexia based on three patterns. The first subgroup is called dysphonetic because these children are supposedly characterized by an inability to develop phonetic skills, have difficulty in soundsymbol integration, and read in whole-word gestalts—that is, they appear to see reading as a pattern recognition task. The second subgroup is called dyseidetic; children in this group are characterized by the opposite problem. They experience difficulty in forming so-called whole-word visual gestalts and must sound out every word as if they were encountering it for the first time. The third subgroup is called alexic and are characterized by the problems of both the other groups. It is important to note that the categorization of a child is based on spelling—not reading—patterns.
Camp and Dolcourt (1977) developed and tested two parallel standardized reading and spelling forms to increase the utility of Boder’s concept utilization of subtypes. The word lists were revised to contain half phonetic (e.g., cave) and half dysphonetic (e.g., calf) words. In this new procedure, the examiner selected the list of spelling words that corresponded to the grade level the child could read 50% correctly. Camp and Dolcourt determined that dyseidetic individuals were diagnosed primarily by spelling performance, and because of Boder’s definition (less than or equal to 50% of sight vocabulary correctly spelled and misspellings of known irregular words), several children would be classified as dyseidetic even though they were reading above grade level. Children who have good reading but poor spelling skills are common (e.g., Lennox & Sigel), but they are not really dyslexic.
A number of studies have been carried out using Boder’s classification system, but many of them suffer from methodological and definitional problems that make their comparison extremely difficult and interpretation of their findings rather tenuous. For example, electrophysiological evidence for subgroups of developmental dyslexia has been reported by Fried, Tanguay, Boder, Doubleday, and Greensite (1981). Using Boder’s diagnostic approach Fried et al. applied event related potential (ERP) techniques to the study of word and musical chord auditory information processing in the left and right hemispheres of their dyslexic participants and compared their performance with that of a normal control group. They found that latency differences between ERPs evoked by word and musical chord stimuli were greater for the left hemisphere of the normal children, as expected from studies conducted in adults (Brown, Marsh, & Smith, 1973). The dyseidetic children, all of who could phonemically decode and encode reading material well, also exhibited a normal pattern of greater waveform differences in the left as opposed to the right hemisphere, although the magnitude of these differences differed from that in the controls (a finding that the investigators attributed to differences in attentional factors between the groups). In contrast, the dysphonetic group did not show the greater word-musical chord ERP waveform differences in the left hemisphere. Fried et al. interpreted these data as suggesting that the left hemisphere may not have a fully developed capacity to process auditory information in the normal manner. An unexpected finding was that the alexic participants produced results similar to those of the normal readers, despite the fact that they were postulated to have problems with both the right and left hemispheres. It is possible that the waveform differences observed in this group were a matter of chance. In any case, the differential performance of the dysphonetic and dyseidetic readers may be a function of severity in that the dyseidetic individuals may not have been really reading disabled.
A study by Telzrow, Century, Whitaker, Redmond, and Zimmerman (1983) investigated the demographic and neuropsychological characteristics of children in the various reading categories defined by performance on the Boder Test and found some differences between them. Unfortunately, the authors of this study fluctuated between calling their participants learning disabled and reading disabled to the extent that one does not really know much about the population under discussion. One is not told how the original diagnosis of developmental dyslexia was made, what measures were used, and what criteria for inclusion were adopted. Hence, it is possible that many were not really reading disabled.
A study by Nockleby and Galbraith (1984) compared the performance of dysphonetic individuals, those with nonspecific reading disabilities, and normal readers on eight dependent-variable tasks—four of which were described as requiring analytic-sequential processing and four that required processing in a simultaneous gestalt fashion. The analytic sequential tasks included Auditory Sequential Memory (from the Illinois Test of Psycholinguistic Ability, or ITPA), Visual Sequential Memory (ITPA), the Lindamood Auditory Conceptualization Test, and Sound Blending (ITPA). Simultaneous gestalt tasks included a facial memory task using 40 photographs of men and women that had to be identified later, a tactile-visual recognition test in which children had to recognize shapes placed in their hand by viewing a response card of those shapes, the Benton Visual Retention Test, and the Raven Coloured Progressive Matrices. It was hypothesized that a subgroup of reading-disabled children categorized by the Boder test as dysphonetic would perform poorly on tasks requiring analytic-sequential processing and normally on tasks requiring simultaneous gestalt processing. A subgroup of disabled readers categorized as having nonspecific reading retardation were predicted to perform as well as a comparison group of normal readers on all perceptual and memory tasks. The dysphonetic and nonspecific groups did not perform significantly differently from the controls on any of the simultaneous gestalt processing measures. Dysphonetic individuals performed significantly below the control group on the visual and auditory memory test. Both dysphonetic and nonspecific groups performed significantly below the control group on the Lindamood test. Sound blending was the only analytic-sequential task that did not discriminate among the reader groups. The authors concluded that these results support the hypothesis that dysphonetic dyslexic children are deficient in one information-processing strategy (analytic-sequential) and normal in the other process (simultaneous gestalt) and that children identified by Boder as having nonspecific reading retardation may have essentially intact processing for both modes. However, the authors suggested that the absence of a difference between the nonspecific and the dysphonetic groups on the Lindamood test appears to be evidence against Boder’s classification system because the Lindamood has been found to be a valid indicator of problematic phonetic skills in poor readers. That both groups performed almost identically on this task suggests that both are phonetically disabled. Only one dependent variable—visual memory—actually distinguished these two groups. The present results suggest that many children classified as nonspecific in fact have difficulties processing the sounds of language.
This study suffers in the way that many of the subtype studies do: Their definition of a reading disability is questionable. As outlined by Siegel and Heaven (1986), grade scores or age levels are not as appropriate as percentiles for identifying a reading disability. In addition, the Gray Oral Reading Test (used to define the groups) consists of a series of graded oral reading passages. Although this study classified reading-disabled subjects into Boder’s three subtypes, the dyseidetic group was ignored after the classification. It would be extremely valuable to know how the dyseidetic group performed on the Lindamood test, for example. If their performance was equally as poor as that of the other readers, considerable doubt would be cast on the dyseidetic category as a useful subtype. It is also important to know whether the dyseidetic group would in fact exhibit performance inferior to that of the other groups on the simultaneous gestalt processing tasks.
Malatesha and Dougan (1982) found that when Boder’s scheme was used, dysphonetic and normal readers had different patterns of scores on a dichotic listening test. Again, this apparent heterogeneity appears to be a function of the definition used. First, 1-year grade-level retardation in reading was used as the criterion for reading disability. As noted earlier, grade-level retardation is not a valid measure because grade levels are ordinal rather than interval levels of measurement. Furthermore, it does not represent the true degree of difficulty at all developmental levels. Second, a reading comprehension test was used (Gates MacGinitic). Variables such as reading speed, vocabulary, prior knowledge, attention, and memory contribute to scores on this measure, and a child may achieve a low score for any or all of these reasons.
Evidence for the homogeneity of the reading-disabled population and a failure to validate the subtypes outlined by Boder comes from work by Van den Bos (1984). He predicted that the children Boder classified as dyseidetic should not have a deficit in processing auditorily presented letters because their problem is theoretically in processing visual information. In contrast, Van den Bos found that memory for auditorily presented or visually presented letters did not differentiate the dyseidetic from the dysphonetic dyslexic individuals by Boder’s criterion. Conversely, Van den Bos predicted that according to Boder’s criteria, dyseidetics should perform more poorly than do dysphonetic dyslexic individuals on a letter-matching task because they presumably have difficulty with visual information processing. In fact, there were no significant differences between dysphonetic and dyseidetic participants on this task—all the dyslexic individuals performed significantly more poorly than did normally functioning individuals on this task. All the dyslexic participants had a particular problem with a task that involved determining whether two letters had the same name—a task that presumably relies on phonological processing skills. It should be noted that Van den Bos did not validate Boder’s subtypes. Van den Bos used a criterion of poor word-recognition skills to define the dyslexic group. Therefore, he had poor readers in the sense that I believe the term should be used. A more appropriate definition of dyslexia resulted in homogeneity within the group.
In another reading performance-oriented system, Larsen and Parlenvi (1984) suggested that there may be significant individual differences and perhaps subtypes in groups of poor readers. In their study of reading in Sweden, they noted that some second-grade poor readers were not as disrupted as good readers in accuracy or rate of reading of inverted words, whereas others were more disrupted. However, these authors were not specific about the type of reading test used to define their groups; hence, they may have had a heterogeneous group of poor readers who represented a continuum of severity. Those readers whose performance was less disrupted or even possibly improved by the inverted stimuli may have been the very poor readers (dyslexic in the sense I support) who were reading through the visual route. The others may not have been really reading disabled in the traditional sense. As can be seen from the descriptions of the previously discussed studies, classification based on reading performance has not clearly differentiated valid subtypes of disabled readers.
Classification Based on Neuropsychological Models
A study by Kinsbourne and Warrington (1963b) represented one of the initial attempts to explore the possibility of distinct subgroups of dyslexic children. They divided children referred because of reading backwardness into two groups on the basis of WISC Verbal-Performance IQ discrepancies. Group 1 consisted of six children who had at least a 20-point Verbal-Performance (V-P) discrepancy in favor of performance. They were termed the language-retarded group. Group 2 consisted of seven children with a 20-point V-P discrepancy in favor of Verbal. These children were termed the Gerstmann group (Kinsbourne & Wanington, 1963a). Group 1 exhibited delays in speech acquisition, verbal comprehension, and verbal expression. Their mean reading and spelling ages were almost the same and were significantly lower than their arithmetic ages (WISC subtest). Group 2 exhibited finger agnosia as characterized by poor performance on tests of finger order and differentiation. They showed significant retardation in right-left orientation and in arithmetic difficulty. The mean spelling age was 1 year lower than the mean reading age. The mean arithmetic age was nearly the same as the reading age.
Although age levels rather than percentile scores were used in this study and therefore the exact severity of the academic skills deficit remains unknown, the findings are interesting because of the patterns they present. The language-disabled group with poorer reading and spelling performance; the Gerstmann group with poorer spelling, arithmetic, and handwriting performance; and a possible third group with both patterns of deficit have been identified by other investigators, such as the groups of Rourke et al., Siegel et al., and Fletcher et al. as elaborated earlier.
Johnson and Myklebust (1962, 1967) suggested that individuals can have auditory dyslexia and visual dyslexia. Their classification was based on clinical descriptions rather than empirical evidence. Persons with visual dyslexia appear to experience deficits in visual perception and in memory; consequently, they have visual discrimination problems that result in confusion of letters and words that look the same. They can make discriminations but only very slowly. Individuals with auditory dyslexia experience difficulty in remembering auditory stimuli and in stringing these stimuli into sequences. They experience problems in distinguishing similarities and differences in sounds, perceiving a sound within a word, synthesizing sounds into words, and dividing words into syllables. It is important to note that there is no reliable empirical evidence for these groups as distinct subtypes.
A similar attempt by Mattis, French, and Rapin (1975) and Mattis (1978) identified three subgroups of children with reading disorders: (a) language, (b) articulation and graphomotor, and (c) visual perception. The language-disordered group had difficulty discriminating similar sounds, repeating sentences, and following complex verbal commands (Token Test), but they had relatively intact visuospatial skills. The articulation and graphomotor group had adequate language skills, but people in this group had difficulties with articulation of speech sounds and copying shapes. A third group, the visuospatial-disordered group, had difficulty remembering visual stimuli, some problems with spatial concepts (Raven’s Coloured Progressive Matrices), and relatively intact verbal skills. It is quite possible that the latter two groups were older and did not have reading problems that were as serious as those of the first group. The definition of reading disability used by Mattis et al. Contributed to this apparent heterogeneity; this is not to say that their classification scheme is incorrect. Rather, the heterogeneity in their sample may be a function of the definition of the reading-disabled group. Mattis et al. used children who were classified as retarded by two or more grades according to the WRAT. The problem with a gradelevel retardation definition of reading disability has already been described. Although this scheme may not be a problem with younger children, it is with older children because a two-grade discrepancy between actual reading grade level and expected grade level may actually mean that the child has a relatively high score and therefore cannot be considered reading disabled. Information about the ages and reading percentile scores of the three subgroups was not presented, so we do not know if this is the case. The group called visualperceptual disorder by Mattis et al. (1975) may have been older and may not have had as serious a reading problem (or even a reading problem at all). In addition, many of the skills measured by Mattis et al. (1975) seem to be deficient in this population; furthermore, without a normal comparison group, we do not know whether these results represent relative strengths and weaknesses or absolute low levels of performance by the groups.
Classification Based on Statistical Techniques
An example of a statistical approach to the definition of subtypes is that of Doehring, Trites, Patel, and Friedorowicz (1981), who investigated the interaction of subtypes of reading disabilities with language and neuropsychological deficits.Avariety of tests of reading and reading-related skills were administered, and the results for the total sample and for a variety of subsamples were analyzed by factor analysis to ascertain the stability of the types of reading disabilities that were identified. Three factors emerged from the classification: Factor 1/Type 0, difficulty with oral reading; Factor 2/ Type A, auditory-visual association difficulty (difficulty in the types of silent reading skills that require the association of the spoken equivalents of printed letters, syllables, and words); and Factor 3/Type S, a sequencing deficit (difficulty with syllables and words as compared to letters and numbers).
After analyzing the reading test results, the authors attempted to explore the possibility that different types of language deficits might be involved in different types of reading disabilities. Twenty-two language measures were used to measure both lower level and higher level language skills. In general, it was found that individuals with reading problems were about as impaired in language skills as they were in reading skills. The pattern of language deficits suggested that the greatest difficulty was at relatively low levels of language skills (that is, phonemic segmentation and blending, serial naming, and morphophonemic knowledge). The language skills closest to normal involved the higher levels of semantic knowledge. The language test profiles of the three types were not as sharply differentiated as were their reading test profiles.
Abattery of 37 neuropsychological tests was administered to determine the extent to which neuropsychological deficits interacted with each type of reading disability and to estimate the types of brain dysfunctions potentially associated with the reading disabilities. Factor analysis of the results did not differentiate any characteristic profiles of neuropsychological deficit. In addition, there was very little indication of any difference in relative incidence, localization, or severity of cerebral dysfunction among the three types of reading disabilities.
This study suffers from many of the same definitional problems as most other subtype studies do. A lag of approximately 2 years on reading measures defines the reading disability, and the study did not account for the fact that 2 years below grade level means very different things for a child in Grade 3 as opposed to a child in Grade 8. In this study, the age of the subjects sampled was extremely diverse (8–27 years), which means that there were enormous variations in the severity of the reading disability. It is hardly surprising that qualitative and quantitative differences in the reading performances of such a would emerge, but whether it makes sense to speak of subtypes rather than a range of performance depending on severity of deficits is questionable. The fact that normal readers scored below average in many related measures and individuals with reading problems scored in the normal range for some skills further confuses the interpretation. There seems to be a problem with the sensitivity of some of the measures used or alternatively with their relevance to a reading deficit. The volume of results at which one arrives after all these tests are administered is formidable but at the same time very confusing. It would probably make far more sense to break down the reading process itself into crucial areas and see how the participants performed in each area— for example, oral reading in context, word recognition, word attack, and silent reading. The findings from a more focused and detailed analysis of fewer measures might be more meaningful. The fact that 30–60% of the participants fell within the normal range on the oral reading tests makes one really wonder about the definition of reading disability in this study.
Furthermore, because a number of participants were classified into more than one type and had profiles characteristic of combined types, separation into three distinct groups becomes even more questionable. It seems that if one tested enough individuals (including normally functioning individuals) on enough measures, one would find enormous ranges of performances in both quality and quantity; it is questionable, however, how worthwhile it is to define them as different subtypes of a reading disability. The authors suggest that there seems to be a form of continuity between types, and I think that that is exactly what this study is all about. Most probably the authors have taken an extremely heterogeneous group of children in terms of reading performance and have emerged with three groups who are at different stages of the reading performance continuum. These styles of performing cannot be considered subtypes; rather, they represent different degrees of severity of a problem.
As with the language tests, the neuropsychological tests only reflected the heterogeneity of the group or in fact perhaps any reading-disabled group. With a more narrowed selection of measures and a detailed error analysis of actual reading performance (rather than a list of scores on so many measures), more meaningful subtypes might emerge. This study illustrates how inherent heterogeneity of the population under discussion affects subtypes. Doehring et al. found a significant overlap between reading-disabled and normal individuals on a variety of measures that tested the child’s understanding of basic syntax using similar but not identical measures. There was also a great deal of variability within each of the subtypes that they identified. Siegel and Ryan (1984) have found virtually no overlap between reading-disabled and normally achieving children but found that the performance of the reading-disabled children was very significantly below that of normally achieving children of the same chronological age. Siegel and Ryan’s subjects were homogeneous and selected on the basis of low scores on a word-reading test.
Rutter, Yule, and associates proposed the existence of two subtypes of reading disorders. They used a regression equation in which the expected reading level was predicted from a child’s IQ score (e.g., Rutter, 1978; Rutter, Tizard, & Whitmore, 1970; Rutter & Yule, 1973; Yule, 1967; Yule, Rutter, Berger, & Thompson, 1974). According to these authors, if the child’s reading level is significantly lower than that predicted from his or her IQ, then the child is said to be a retarded reader. They differentiate between backward readers (children who are at the bottom end of the reading attainment continuum) and retarded readers (children who are underachieving in relation to their chronological age and general level of intelligence) in sex distribution, neurological correlates, and association with speech and language disorders.
It should be noted that there was considerable overlap between the groups. Retarded readers who had (by definition) higher IQs were worse in their accuracy but not in comprehension and were worse in spelling but had higher scores in mathematics. We do not believe that these constitute meaningful subgroups. It is important to note that language measures (WISC) constituted part of the definition of IQ. Children with learning disabilities have language problems (Siegel, 1985a, 1985b; Siegel & Ryan, 1984; Vellutino, 1977, 1978, 1979); therefore, children will have lower IQ scores when a language-based test is used as a measure of IQ. It is impossible to measure IQ independently of language and reading skills. A definition in which subtypes are developed on the basis of IQ-reading level discrepancies therefore seems to be invalid (see previous discussion). The distinction between reading retardation and reading backwardness may represent a difference of severity in that children who are backward in reading have more cognitive deficits than do those who are retarded in reading (and hence have lower IQ scores).
Although Doehring (1984) notes that most subtype classifications of reading problems involve a visual nonverbal subtype, I contend that the appearance of this subtype is an artifact of the tests of reading used. When a subtype such as this one with visual nonverbal problems is used, I contend that they also have language problems, that they are the children with good phonics skills but low comprehension scores, or that their word recognition skills are adequate but because of attention difficulties they have problems with memory, speed, attention, strategies in relation to reading, or any combination of these problems.
Therefore, conclusive and convincing evidence of subtypes of reading disability has not emerged. In addition, there is homogeneity within the reading-disabled population. Apparent heterogeneity is a function of the definition used. As Doehring suggests, “The one simplifying assumption that I will continue to make for the present in my own work however is that the most profound reading disabilities involve difficulty in acquiring lower level coding and word recognition skills rather than higher-level skills and strategies” (Doehring, 1984, p. 211). If investigators use a wordrecognition definition, phonics (nonword) definition, or both of reading disability, there will not be a significant amount of variability on relevant cognitive functions within the readingdisabled population.
Reading disability involves a problem with phonological processing, language, and memory for verbal information. Reading-disabled children can be differentiated from other LD children on these variables. Visuospatial and perceptualmotor problems may also occur in dyslexia, but they are not the basic problem, nor are they characteristic of all dyslexic individuals in the same way in which language problems are.
If a logically consistent definition of dyslexia is used, all dyslexic (reading disabled) children have problems with language.
A Simple Model of Subtypes
What emerges from this confusing array of studies is the fact that there are clearly two subtypes of learning disability— namely, a reading disability (dyslexia) and an arithmetic disability. These subtypes have been validated in child and adult populations (e.g. Rourke & Strang, 1978; Shafrir & Siegel, 1994b; Siegel & Ryan, 1988, 1989a, 1989b). Shafrir and Siegel (1994b) compared three groups—individuals with arithmetic disability (AD), reading disability (RD), and both reading and arithmetic disabilities (RAD), with a comparison group with normal achievement (NA)—on a variety of cognitive and achievement measures. The main findings were as follows: (a) Each of the groups differed significantly from the others on tests of reading, spelling, memory, and other cognitive measures; (b) both the RD and RAD groups showed a deficit in phonological processing, vocabulary, spelling, and short-term memory; (c) the AD group performed similarly to the NA group on pseudoword reading and phonological processing but performed more poorly than did the NA group on word reading and vocabulary; (d) on many tasks, the RAD group performed more poorly than did the other groups; and (e) the AD and RAD groups performed more poorly than did the NA and RD groups on a visuospatial task. Therefore, this classification scheme for the subtyping of learning disabilities in adults appears to have validity.
Spelling: A Digression
Problems with spelling do exist, but they can co-occur with either reading or arithmetic difficulties, and it is rare to find a child who has difficulties with spelling and no problems in any other areas of functioning. Some children may have specific difficulties with spelling when they are required to write the word from memory rather than when they are required to recognize the correct spelling of a word.
In addition, English words are characterized by both regular spelling (e.g., singing, print)—that is, words in which the letter-sound correspondences are predictable—and irregular spelling—that is, spelling that is not predicted from the rules of spelling-sound correspondence (e.g., island, knight). The possibility exists that children may be able to spell regular words but have more difficulty with the irregular words. In any case, spelling difficulties do occur but (as noted earlier) usually in combination with other problems. Furthermore, studies such as Jorm (1981), and Lennox and Siegel (1993, 1996) have found significant differences in the understanding of letter-sound correspondence rules and the orthographic awareness between children who were poor readers and spellers and children who were only poor spellers. On the basis of findings such as these and for the reasons discussed previously, reading and spelling need to be treated as separate variables.
Types of Learning Disabilities
Over the past 30 years, it has become clear that there are two major clusters of learning difficulties. The most commonly known is a reading disability, sometimes called dyslexia. There is no difference in meaning between the terms dyslexia and reading disability. Another equally prevalent but less commonly known disability is an arithmetic (mathematics) disability, sometimes called nonverbal learning disability, developmental output failure, writing-arithmetic disability, or visual-spatial disability. Although there is, admittedly, some heterogeneity within the two major clusters, they do share enough common characteristics to be considered as specific entities.
Depending on the theoretical bias of the particular investigator, the country, the circumstances, and so on, the word dyslexia may be used instead of reading disability. However, there is no difference between dyslexia and a reading disability; they are exactly the same.
Dyslexia involves difficulties with phonological processing, including such abilities as knowing the relationship between letters and sounds and phonological awareness—that is, the ability to segment the speech stream into separate elements. Over the years, a consensus has emerged that one core deficit in dyslexia is a severe difficulty with phonological processing (e.g., Rack, Snowling, & Olson, 1992; Siegel, 1993b; Snowling, 1980; Stanovich, 1988a, 1988b). Children with a reading disability have a core deficit in phonological processing. The evidence that is available clearly demonstrates that adults with dyslexia have deficits in phonological processing (e.g., Bruck, 1990, 1992; Elbro, Neilsen, & Petersen, 1994; Felton, Naylor, & Wood, 1990; Gottardo, Siegel, & Stanovich, 1997; Greenberg, Ehri, & Perin, 1997; Pennington,Van Orden, Smith, Green, & Haith, 1990; Pratt & Brady, 1988; Read & Ruyter, 1985; Russell, 1982; Scarborough, 1984; Shafrir & Siegel, 1994a, 1994b; Siegel, 1998). Most individuals with dyslexia show problems in the area of memory and language (Siegel & Ryan, 1984, 1988; Snowling, 1980; Stanovich, 1988a, 1988b; Vellutino, 1978). Usually individuals with dyslexia have spelling problems, but the presence of spelling difficulties without reading difficulties does not indicate dyslexia. A definition of dyslexia that captures the other problems that often co-occur with it is illustrated in Padget et al. (1996):
Dyslexia is a language-based learning disorder that is biological in origin and primarily interferes with the acquisition of print literacy (reading, writing, and spelling). Dyslexia is characterized by poor decoding and spelling abilities as well as deficit in phonological awareness and/or phonological manipulation. These primary characteristics may co-occur with spoken language difficulties and deficits in short-term memory. Secondary characteristics may include poor reading comprehension (due to the decoding and memory difficulties) and poor written expression, as well as difficulty organizing information for study and retrieval. (p. 55)
Current theories of the development of reading skills in English stress that phonological processing is the most significant underlying cognitive process (Stanovich, 1988a, 1988b, 1988c). Children and adults with a reading disability have difficulty with phonological processing. Phonological processinginvolvesavarietyoffunctions,butinthecontextof the development of reading skills, the most significant in the association of sounds with letters or combinations of letters. This function is referred to as the understanding of graphemephoneme conversion rules, and because of the irregular nature of the correspondences in English, the learning of these rules is a very complex process. The child who is learning to read must map oral language onto written language by decomposing the word into phonemes and associating each letter (or combination of letters) with these phonemes.
The task of the beginning reader is to extract these grapheme-phoneme conversion rules. The alternative is simply to memorize each word as a visual configuration and to associate a meaning with it. This kind of learning may occur, but it is inefficient and makes tremendous demands on visual memory. In English, no one-to-one correspondence exists between a letter (or letters) and a sound. The same letter represents different sounds, and the same sound may be represented by different letters.
In an alphabetic language such as English, the best measure of phonological processing skills is the reading of pseudowords—that is, pronounceable combinations of letters thatcanbereadbytheapplicationofgrapheme-phonemeconversion rules but that are, of course, not real words in English. Examples, include such pseudowords as shum, laip, and cigbet. Pseudowords can be read by anyone who is familiar with the grapheme-phoneme conversion rules of English even though they are not real words and have not been encountered in print or in spoken language before.
The development of the ability to read pseudowords has been studied extensively (e.g., Calfee, Lindamood, & Lindamood, 1973; Hogaboam & Perfetti, 1978; Siegel & Ryan, 1988; Venezky & Johnson, 1973). Ample evidence indicates that children with dyslexia have a great deal of difficulty reading pseudowords. Studies such as those of Bruck (1988), Ehri and Wilce (1983), Snowling (1980), Siegel and Ryan (1988), and Waters, Bruck, and Seidenberg (1985) have shown that disabled readers have more difficulty reading pseudowords than do normal readers matched on either chronological age or reading level. For example, Siegel and Ryan (1988) studied the development of the ability to read pseudowords in normal and disabled readers aged 7–14 years. By the age of 9, the normal readers were quite proficient and performed at almost a perfect level for even the most difficult pseudowords, with—in some cases—as many as three syllables. Similarly, Backman, Bruck, Hebert, and Seidenberg (1984) showed that 10-year-olds perform as well as do adults on tasks involving the reading of pseudowords; however, Siegel and Ryan (1988) found that the performance of the reading-disabled children was quite different. These children appear to acquire these reading skills very late in development, and even reading-disabled children at the age of 14 were performing no better than were normal readers at the age of 7.
To control (at least partially) for experience with print, Siegel and Ryan (1988) used a comparison of disabled and normal readers matched on reading grade level. Even when the disabled readers and the normal readers were matched on reading level (hence, the disabled readers were considerably older than the normal readers), the performance of the reading-disabled individuals on a task involving the reading of pseudowords was significantly poorer than that of the normal readers.
Thus, difficulties with phonological processing seem to be the fundamental problem of children with reading disability, and this problem continues to adulthood. Many adults with a reading disability become reasonably fluent readers but still have difficulty reading pseudowords or read them very slowly (e.g., Barwick & Siegel, 1996; Bruck, 1990).
For children learning to read English, the learning of grapheme-phoneme conversion rules is a result of systematic instruction, and the extraction of the rules is a result of repeated encounters with print. No evidence is available as to how much of the development of decoding skills is a result of specific instruction in the grapheme-phoneme conversion rules and how much is a result of experience with print. In any case, the understanding of the grapheme-phoneme conversion rules develops rapidly in the first years of experience with print under normal conditions.
Some individuals have difficulties only with writing, spelling, or both. Because these written language problems usually occur in the context of problems with reading problems, arithmetic and mathematics problems, or both, the existence of a separate written language disability is not clearly established, nor is there a clear definition of it, especially in the adult population. Spelling difficulties can occur in the absence of severe reading disabilities (e.g., Bruck & Waters, 1988; Lennox & Siegel, 1993). There also may be problems with understanding or producing language. These problems have not been documented as distinct learning disabilities and are often components of dyslexia. If learning disabilities are to be treated as measurable entities and if individuals are to receive educational services based on the presence of a single or multiple learning disabilities, it is then obviously important to determine what these learning disabilities are.
Individuals with developmental output failure or writingarithmetic disability have difficulty with computational arithmetic and written language, typically in the absence of reading difficulties, although this disability can co-occur with dyslexia. They often have difficulties with spelling and have problems with fine-motor coordination, visuospatial processing, and short-term and long-term memory (e.g., multiplication tables), but they usually have good oral language skills (Fletcher, 1985; Johnson & Mykelbust, 1967; Kinsbourne & Warrington, 1963; Kosc, 1974; Levine, Oberklaid, & Meltzer, 1981; Morrison & Siegel, 1991a, 1991b; Rourke, 1991; Rourke & Finlayson, 1978; Shafrir & Siegel, 1994b; Siegel & Feldman, 1983; Siegel & Linder, 1984; Spellacy & Peter, 1978). Rourke and his associates (e.g., Rourke, Del Dotto, Rourke, & Casey, 1990; Rourke & Tsatsanis, 1996) have described a syndrome called nonverbal learning disabilities that is similar to writing-arithmetic disability. However, the operational definition of this learning disability is problematic; it is not clear how a diagnosis can be made. Often, these individuals have verbal IQ scores significantly higher than performance IQ, but this discrepancy is neither necessary nor sufficient to make the diagnosis. Often, they have lower arithmetic scores than reading scores, but the differences between these scores are not always significant (e.g., Rourke et al., 1990). (For an extended discussion of the definitional issue and conceptualization of this disability, see Morrison & Siegel, 1991a.)
Investigators (e.g., Fletcher, 1985b; Rourke & Finlayson, 1978; Rourke & Strang, 1978; Siegel & Feldman, 1983; Siegel & Ryan, 1984, 1988, 1989a, 1989b) have found evidence that children with specific arithmetic deficits and average or above-average word recognition scores on the WRAT appear to have a variety of cognitive and neuropsychological deficits that differentiate them from children with at least reading deficits as defined by depressed scores on the Reading subtest on the WRAT. The cognitive and neuropsychological profiles of children identified as specific arithmeticdisabled are also different from those of normally achieving children.
Evidence (Fletcher, 1985b; Siegel & Linder, 1984; Siegel & Ryan, 1984, 1988, 1989a, 1989b) suggests that those children meeting the criteria of the specific arithmetic-disabled subtype have deficits in short-term and working memory that are dependent on the type of stimulus and the aspect of memory assessed. Specifically, Siegel and Linder (1984), in a study of the role of phonemic coding in short-term memory, compared three groups of children—one with reading disabilities (as defined by scores on the WRAT Reading subtest of equal to or below the 25th percentile and no cutoff on the other two WRAT subtests), a second with arithmetic disabilities (as defined by scores on the WRATArithmetic subtest of equal to or above the 30th percentile), and a normally achieving group (as defined by scores of greater than or equal to the 30th percentile on all three WRAT subtests). The children, aged 7–13, were administered a series of tasks that involved the visual or auditory presentation of rhyming and nonrhyming letters and either an oral or written response. Patterns and levels of performance were compared statistically across three age groups (i.e., 7–8, 9–11, 12–13) and between each subtype and normally achieving children. Due to statistical problems, noncomparable age distributions, and small sample sizes, it was not possible to compare across subtypes. Results indicated that both older disabled groups—like their normal counterparts—had significantly poorer recall of rhyming as opposed to nonrhyming letters (except for the oldest—12–13 years—arithmetic-disabled group, in which the authors suggest that the children may be functioning at the upper limit of their visual short-term memory). For stimuli presented visually, the overall performance levels of both LD groups were significantly lower than those of the normally achieving group. For the auditory stimuli, only the readingdisabled group differed significantly from the normally achieving peers.
Fletcher (1985b) found differences in memory tasks between LD groups as defined by WRAT scores. He compared four groups of LD children (a reading-spellingdisabled group, a reading-spelling-arithmetic-disabled group, a spelling-arithmetic-disabled group, and an arithmeticdisabled group) and a normally achieving group of children on storage and retrieval aspects of memory for verbal and nonverbal stimuli. He found that relative to the normally achieving controls, both the arithmetic and the arithmeticspelling-disabled subgroups had significantly lower storage and retrieval scores on the nonverbal task but did not differ from each other; the reading-spelling subgroup differed only on retrieval scores on the verbal task; and the readingspelling-arithmetic subgroup differed on the retrieval scores on the verbal task and storage and retrieval scores on the nonverbal task. As with Siegel and Linder (1984), the differences between subgroups depended on the type of stimulus (verbal vs. nonverbal) and the aspect of memory (storage or retrieval) being assessed.
Siegel and Ryan (1988) also compared reading-disabled (as defined by WRAT subtest scores), specific arithmeticdisabled (as defined by WRAT subtest scores), and normally achieving children on a variety of skills involving grammatical sensitivity, phonology, and short-term memory. In general, it was found that older specific arithmetic-disabled children performed in a manner similar to that of the normally achieving group in grammatical sensitivity and phonological tasks. Some exceptions were found in that the arithmetic-disabled children in the 7–10 age group performed more poorly on a sentence repetition task; this difficulty was attributed to the short-term memory component of the task. Additionally, this age group performed more poorly than did normally achieving children on the nonword spelling sections (a writing task) of the phonics task. However, in tasks that measure short-term memory (phonological coding), the specific arithmetic-disabled group performed in a manner similar to that of the reading-disabled group and significantly more poorly than did the normally achieving group. The authors conclude that although both of the two disabled groups (compared with normally achieving children) have deficits in short-term memory, only the reading-disabled group had deficits in tasks said to represent a language disorder.
Siegel and Ryan (1989a) examined the same groups, using two working memory tasks—one involving sentences and the other involving counting.Again, the disabled groups differed fromeachotheronthetypesofmemorydeficitsobserved.The reading-disabled group differed from the normally achieving children on both tasks, whereas the arithmetic-disabled children differed from their normally achieving peers only on the counting task. It appears from the research (Fletcher, 1985b; Siegel & Linder, 1984; Siegel & Ryan, 1988, 1989a, 1989b) that although both subtypes of LD children have deficits in short-term and working memory, problems in children with reading deficits are more generalized and involve both verbal and nonverbal aspects of memory, whereas those in children with arithmetic deficits and normal or above-normal reading are more limited to visual, nonverbal, and numerical material.
Evidence from a number of sources (Fletcher, 1985b; Rourke & Finlayson, 1978; Share, Moffitt, & Silva, 1988; Siegel & Feldman, 1983; Spellacy & Peter, 1978; Webster, 1979) indicates that specific arithmetic-disabled children (as defined by deficient scores on the WRAT Arithmetic subtest and the age-appropriate scores on the WRAT Reading and Spelling subtests—Group 3) have age-appropriate auditory-perceptual and verbal abilities but are deficient on measures of visual-perception and visuospatial abilities. However, reading-disabled children (as defined by being relatively proficient at arithmetic as compared with their WRAT Reading and Spelling subtest scores—Group 2) have age-appropriate visual-perception and visuospatial abilities but are deficient on measures of auditory-perceptual and verbal abilities (Rourke & Finlayson, 1978). Also, Group 3 (arithmetic-disabled) children exhibit difficulty in tasks such as the Halstead Category Test, which require higher order visuospatial analysis and visual-perceptual organization (Strang & Rourke, 1983b). They also appear to exhibit deficits in measures of psychomotor abilities and on tests such as the Tactile Performance Tests (Reitan & Davison, 1974), the Grooved Pegboard Test, and the Maze Test designed to identify tactile-perceptual impairment (Rourke & Strang, 1978; Siegel & Feldman, 1983; Spellacy & Peter, 1978). On the other hand, Rourke and Strang (1978) and Strang and Rourke (1983) found that Group 2 children (relatively proficient in arithmetic, compared with their reading and spelling) are proficient at these tasks.
In addition, Rourke and Strang (1978) claim that the arithmetic subgroup (Group 3) exhibited normal right-hand performance but impaired left-hand performance—the exact opposite of the Group 2 children, who had impaired righthand performance but normal left-hand performance. Strang and Rourke (1983a, 1983b) suggest that the arithmeticdisabled subgroup has deficiencies in nonverbal conceptformation compared with other disabled subgroups. Specifically, when the types of errors made of the Arithmetic subtest of theWRAT were analyzed, it was found that the specific arithmetic subtype tended to make a larger number of errors, make a greater variety of errors, and attempted to answer questions without an apparent understanding of the strategies needed to solve the problems (Strang & Rourke, 1985a, 1985b). This error pattern was not found in children with reading disabilities (Group 2).
As with the research with memory deficits cited earlier, Rourke and Finlayson (1978), Rourke and Strang (1978), and Strang and Rourke (1983a, 1983b) suggest that the characteristics described are different from those of other learningdisabled students (who showed deficits on all the WRAT subtests, Group 1, or just on the reading and spelling subtests compared with the arithmetic subtest, Group 2). This finding hasledRourkeetal.(Rourke,1982,1983,1985,1987;Rourke & Finlayson, 1978; Rourke & Fisk, 1988) to hypothesize that those children with arithmetic deficits belong to the larger nonverbal LD group with right-hemisphere processing problems, whereas those children with deficits in reading as well as arithmetic belong to the larger linguistic learning-disabled group with left-hemisphere processing problems. Clearly, however, children who only have severe deficits in arithmetic can be differentiated from children with reading difficulties and from normally achieving children on cognitive and neuropsychological profiles.
In light of the previously described controversy and research findings, the use of specificity assumptions in the definition of learning disabilities is questionable; this is true regardless of whether one refers to domain specificity (the limitation of the disability to one or two cognitive areas) or population specificity (failure to use subtypes).
Assessment of Learning Disabilities
Determining who is learning disabled requires careful and systematic assessment.The three following questions address the assessment of learning disabilities: (a) How should achievementbemeasured;(b)whichtestsshouldbeused;and(c)what cutoff scores should be used to identify a learning disability?
The Measurement of Achievement
The arguments about the definition of learning disability center on the determination of whether an individual meets specific criteria for the diagnosis of a disability. First of all, to measure whether there are significant difficulties, one must use a systematic assessment of these academic areas; standardized (norm-referenced) tests appear to be the best way to do this. Why use norm referenced tests? The answer is simple: Those making the assessment want to compare an individual with others of the same age and know whether that person has a significant problem. A standardized test is the best way to accomplish this task. Nonstandardized assessments can be used, but they do not provide normative information that can be used for the purposes of comparison. With a nonstandardized or informal assessment, it is impossible to know whether an individual has made the number and type of errors that are typical of his or her age group and therefore are normal and expected, or whether the errors are atypical and unexpected and indicative of a problem. Nonstandardized tests may play an important role (to be discussed later), but the core assessment should use standardized tests. However, nonstandardized assessments do have a role in the evaluation of writing; this role is discussed later in the paper.
To assess learning disabilities, there are several types of tests that should be used. Specifically, an assessment of an individual for the possibility of a reading disability should include a measure of word-recognition skills. Word recognition is one of the critical building blocks in gaining meaning from print, and it is important to know whether these basic skills in this area are significantly below average (Stanovich, 1982). An assessment should include a reading test that involves the reading of what are called pseudowords—pronounceable combinations of English letters that can be sounded out with the basic rules of grapheme-phoneme correspondences. This type of test assesses the awareness of the phonological aspects of a language that is the key to decoding words in an alphabetic language such as English. Difficulties with these phonological skills are the basis of a reading disability (e.g., Bruck, 1990; Felton et al., 1990; Shafrir & Siegel, 1994a; Siegel & Ryan, 1988). A test of text reading—specifically, a reading comprehension test—should be included. Obviously, the measurement of text reading skills is particularly important to measure what individuals remember and understand from what they have read.
There should be a test of spelling involving the dictation of words; this parallels the type of spelling required in writing in the academic setting.
There should be a test of computational arithmetic skills to determine what the individual understands about the fundamental arithmetic operations. An assessment of mathematical problem-solving skills should be included.
There should also be an assessment of writing skills; this type of assessment is quite difficult for a variety of reasons. The time involved to allow someone to write may be extensive because one must allow time for planning as well as for the actual writing. Also, many individuals have learned to use a computer and prefer to write using a computer. Therefore, a proper assessment of writing might use a computer, which may not be feasible in most assessment contexts. It may be acceptable to ask the individual to bring in a sample of his or her writing, but some type of brief assessment in the context of the assessment is useful.The scoring of these written products is subjective and there does not appear to be agreement on what constitutes a widely accepted scoring system. However, Berninger (1994) has proposed a system that appears to have potential to consistently evaluate writing. She suggests six dimensions to evaluate writing: (a) handwriting quality (legibility), (b) handwriting fluency (number of words copied within time limits), (c) spelling single words from dictation (on standardized lists of increasing difficulty), (d) spelling in composition(percentageofcorrectlyspelledwords),(e)composition fluency (number of words produced within time limits), and (f) composition quality (content and organization of paragraph construction).
Identification of whether there is a learning disability should use a simple system. Brief tests of word recognition, decoding (pseudoword reading), reading comprehension, spelling, writing, and computational arithmetic and mathematical problem solving will detect most (if not all) of the learning disabilities. A low score on any of these tests is a danger signal. More detailed testing can then be conducted, but any testing should be related to remediation and not used without consideration of what new and useful information is provided by the test and whether it is really necessary—a point that is discussed in detail later in this research paper.
Types of Tests
There is considerable confusion in the field about how to measure achievement. Attempts at defining and studying learning disabilities suffer from a common fallacy of assuming that all tests that have the same label (e.g., intelligence test, reading test) measure the same skill (Siegel & Heaven, 1986; Siegel et al., 1985). When one considers the area of achievement tests, the labeling fallacy becomes even clearer. There appears to be almost an infinite variety of ways to measure reading, spelling, and arithmetic. The choice of which tests to use can determine whether a disability will be found. Consider the case of measuring reading achievement.
There are four types of material that are typically found in reading tests: (a) pseudowords, (b) single words, (c) sentences, and (d) paragraphs. For the reading of pseudowords, the individual is asked to read a set of pronounceable combinations of letters that test the understanding of the relationship between letters or groups of letters and their sounds. This type of test is simple and direct and measures a fundamental skill.
Tests of the reading of single, real words typically require that the individual read a set of words aloud. These words may vary on several dimensions, but usually these dimensions are not systematically assessed. For example, words may be regular—that is, they follow the letter-sound correspondence rules of English (e.g., fat, block)—or they may be exceptions to these rules—that is, they involve irregularity or unpredictable letter-sound correspondence (e.g., have, said, island, sword). A person may have difficulty with the irregular but not the regular ones. The words may be more familiar and in the person’s vocabulary, such as cat, book, and red, or they may be less familiar, such as predatory, terpsichorean, and oligarchy. Obviously, what is familiar and what is unknown depends on the age, vocabulary, and experience of the individual. Some words may be read correctly because they have been encountered before, whereas others may be read incorrectly (but almost correctly; e.g., intrigue read in-tri-gue instead of in-treeg) because they are not part of the individual’s vocabulary and have not been encountered before. The confounding of familiarity with other dimensions of a word makes the construction of a word-reading list a difficult task. In the case of each particular word, one simply does not know when a person reads a word correctly whether he or she has merely memorized it. Note that pseudowords do not present this difficulty.
The reading of both words and pseudowords assesses the basic problem in a reading disability—that is, difficulty with phonological processing; both tasks are relatively straightforward. However, the measurement of text processing becomes more complex. Text processing is typically measurable by tests that involve the reading of sentences and paragraphs. In both cases, there are often clues about the word from the surrounding context. Typically, nouns follow articles, verbs follow subjects, adjectives precede nouns, and so on. When an individual reads a word in context correctly, we do not know whether he or she has read the word or made a good guess from the context. Note that this problem is not an issue with the reading of single words or pseudowords.
The reading of sentences or paragraphs may occur silently or aloud. If the reading is silent, there is no way of assessing what the person is actually reading, although this type of reading may be more similar to what occurs in many reading situations. Questions about what has been read are the principal means to assess comprehension. In most cases, memory is a very important aspect of the testing of sentence and paragraph comprehension. Often, the material is removed so that it is not available when the questions are asked. The person may have read quite well but may forget the answer to the question. Even when the material is available, the individual’s performance is timed, or a fixed time is allowed to complete the test. At least some of the variance between individuals may be caused by variations in reading rate or speed of task completion—not a differential understanding of the material. There is, however, a significant difference between a slow reader and one who may not even be able to decode the words in the first place. Some students are able to decode the words and answer the questions on a reading comprehension test but need more time. Some have a problem with decoding the words. An assessment should be able to differentiate these two difficulties.
Reading tests vary in the output or type of response that is required. Some require an oral output that may involve some degree of facility with expressive language, whereas others require a written output—for example, answering multiplechoice questions. Still others involve having the person select a synonym for a word; in reality, this test is a measure of vocabulary. An individual may select the incorrect word not because of poor reading skill, but because he or she is not sure of the correct synonym.
The actual comprehension questions themselves may vary in several dimensions. They may involve inferences, memory for details, or the general point of the passage. It is very likely that a large part of reading comprehension ability consists of memory skills (e.g., Tal & Siegel, 1996). The individual must decode words and obtain meaning from them, but also he or she must retain the information in working memory and be able to answer questions about the content of the reading passage. It seems apparent, however, that memory is still a significant factor in tasks in which recall of exact wording or details is not essential. In these cases, the meaning must be retained and then operated on in some manner to produce an expected answer.
The individual’s familiarity with the material in the text can determine how the person will score on a reading comprehension test (e.g., Drum, Calfee, & Cook, 1981; Marr & Gormley, 1982; Schneider et al., 1989). For example, Schneider et al. found that background knowledge about soccer influenced comprehension of and memory for a story dealing with soccer, but there were no significant differences between children with high and low verbal aptitude skills. Therefore, background knowledge was a critical factor in text comprehension, but verbal ability was not.
Time to read can also be an integral part of the reading score. Anumber of factors can contribute to differences in the time taken to read a passage. For example, a person who recalled information about the story may have a faster time than does someone who could not recall the target information but who could remember its spatial location and look back quickly, who may in turn have a faster time than does a person who could not remember anything about the target information and had to search throughout the passage. Daneman (1984) has reported that much of the variance in reading comprehension scores disappears if individuals are allowed to look back at the passage that has just been read.
Another difficulty with reading comprehension tests is that frequently the questions can be answered with a reasonable amount of accuracy without reading or comprehending the passage (e.g., Tal & Siegel, 1996). Such questions as Where was the cow kept? can be answered by good guessing; cows are not likely to be kept in cars, closets, or bathtubs.
Obviously, the problem with having so much variability in the measurement of reading comprehension is that many different skills are assessed. Theoretically, there are many types of possible reading difficulties if this kind of measure of reading is used because the person could have a problem in any one or more of these components. Clearly, some of these combinations are more likely than others are, but the point is that it is unclear which dimensions are creating the problem when the individual achieves a low score on one of these sentence or paragraph reading tests. An individual may perform poorly on the more complex reading tests for any one of a number of reasons. For example, an individual may read a paragraph aloud correctly but forget the answer to a question or may read correctly but slowly. In reading single words, the person may produce a good phonetic but inaccurate rendering of a low-frequency word. The only reading task that is not confounded with other dimensions is the reading of pseudowords.
The Use of Cutoff Scores to Identify a Learning Disability
The question arises as to how low a score should be in order to identify a learning disability. One of the aspects of the definitional issues is that we are not dealing with a clearly identifiable entity when we speak of a learning disability. Andrew Ellis (1985) has noted, in regard to dyslexia, the proper comparison is with obesity, not measles:
For people of any given age and height there will be an uninterrupted continuum for painfully thin to inordinately fat. It is entirely arbitrary where we draw the line between ‘normal’ and ‘obese,’but that does not prevent obesity being a real and worrying condition nor does it prevent research into the causes and cures of obesity being both valuable and necessary. . . . Therefore, to ask how prevalent dyslexia is in the general population will be as meaningful, and as meaningless, as asking how prevalent obesity is. The answer will depend entirely upon where the line is drawn. (p. 172)
Measles is easy to diagnose because of the spots. People with learning disabilities have no spots, only some test scores. In a manner similar to the diagnosis of obesity, it is not clear at what point or how low the score is for the person to be considered learning disabled or how overweight a person must be before he or she is called obese. In the most extreme cases, it is clear. However, we are really dealing with degrees of severity and not with a clear question of absence or presence, except in the more extreme cases when the diagnosis is easy.
Deciding on the appropriate cutoff score below which one identifies a learning disability is problematic. As a guideline, many have typically used scores below the 25th percentile (e.g., Fletcher, 1985; Rourke, 1991). This cutoff is arbitrary, but there is some evidence of the validity of this score. First of all, a number of studies have found that this score separates learning disabled from normally achieving individuals on a variety of tasks (e.g., Fletcher, 1985; Rourke & Finlayson, 1978; Shaywitz, Fletcher, & Escobar, 1990; Siegel & Ryan, 1988). Does that mean that 25% of the population will be called learning disabled on the basis of that test? In reality, this is not the case, and this cutoff identifies about 7–8% of the population as learning disabled (Fletcher et al., 1994; Rourke & Finlayson, 1978; Shaywitz et al., 1990). Second, in this author’s experience, this score is correlated with teachers’ and parents’ perceptions of children’s problems in school and with the self-report of adults who report academic difficulties. Thus, the use of the 25th percentile as a cutoff score is correlated with observations in the real world. However, there is no way of knowing what is a valid cutoff score; there is no magic number to separate learning-disabled from non-learning-disabled individuals. An argument could just as easily be made for the 20th percentile or the 15th percentile instead of the 25th percentile. No blood test, X ray, or magnetic imaging technique can be used to diagnose a learning disability. However, for the educational system to identify who will receive the accommodations and remediation, we must take a continuous variable—for example, reading performance—and make it a dichotomous one.
A Simple Model
In this field there are issues of what constitutes appropriate assessment for learning disabilities. It certainly is the tradition to do extensive additional testing besides achievement testing. However, the usefulness of additional testing for the identification of learning disabilities is not clear. It is likely that the primary reasons for doing assessments are to document the existence of a learning disability and to recommend appropriate remediation and accommodations. In order to accomplish these aims, the achievement testing described previously is clearly needed. Typically, tests of cognitive processes and intelligence tests are included in many assessments. Do we really need tests of auditory memory, visual memory, language, and visual closure? Is there such an entity as auditory memory? Suppose the stimuli for an auditory memory task are words and the individual is asked to repeat them, or suppose they are musical phrases or melodies and the person is asked to discriminate them. Would conclusions about auditory memory be the same if these diverse stimuli were used? The question should always be How does the task or test being used in the assessment relate to the determination of the learning disability and the provision of remediation or accommodations? Of course, the individual may be interested in learning more about his or her strengths and weaknesses. An extended assessment may also be valid for these reasons. However, it is not necessary to define the learning disability to propose accommodations or remedial strategies.
Surber (1985) has summarized the problems with lengthy and detailed reports that include measures of cognitive processes and intelligence tests:
At the opposite end of the continuum, some of the more lengthy reports include every detail of the evaluation process, whether relevant or not. Both novice and experienced readers are left to wade through the jargon, attempting to ferret out the key elements that have relevance for the student and the teacher in the classroom. Consequently, items of greatest relevance become diluted in the sea of information being washed ashore. (p. 162)
There were a number of problems with the assessments of learning disability. The evaluations that I have seen have resembled a patchwork quilt in which none of the squares were the same. Each evaluation uses different tests, different terminology, and different labels for the learning disability. Here are some examples of the types of learning disabilities that were reported to exist: language-based learning disability, subtle verbal processing, attentional and long-term memory limitations, difficulty in visual processing speed, statistically significant disparity between relative conceptual language strengths compared with mathematics and written output, slow processing speed, visuoperceptual processing inefficiencies, problems with the ability to process auditory and visual information, mild frontal lobe disorder, and poor auditory processing.
The process of assessing whether there is a learning disability has been made unnecessarily complex. Standardized tests of reading, spelling, arithmetic calculation, and mathematical problem solving as described earlier are essential. Obtaining a sample of writing is important. Other tests may be done for interest or research but they are not essential to the diagnosis of a learning disability.
In addition to the achievement tests discussed earlier, an important part of any assessment is the use of analyses of errors. Systematic analyses of errors may provide useful information about an individual’s level of functioning in reading, spelling, and arithmetic, and they may provide information about appropriate accommodations. Numerous studies such as those of Barwick and Siegel (1996); Bruck and Waters (1988); Fowler, Shankweiler, and Liberman (1979); Guthrie and Siefert (1977); Lennox and Siegel (1993, 1996); McBride and Siegel (1997); Pennington et al. (1986); Siedenberg (1985); Smiley, Pascquale, and Chandler, (1976); Sprenger-Charolles and Siegel (1997); Tal and Siegel (1996); Weber (1970); Venezky and Johnson (1973); and Werker, Bryson, and Wassenberg (1989) have used analyses of errors as a means to understanding the nature of the difficulties in individuals with learning disabilities. A good assessment should systematically analyze the errors made by individuals.
Error analysis also provides some information about the types of questions the individual was able to answer correctly. For example, are the spelling errors good phonological equivalents of the word to be spelled (e.g., nature spelled as nachure)? Or are they good visual errors—that is, a close match to the visual form of the word (e.g., nature written as natur; e.g., Lennox & Siegel, 1993, 1996)? Analyses such as these help us understand the strategies that the individual is using and can provide guidelines for remediation.
Finally, an assessment should include a direct interview with the student to analyze strengths as well as weaknesses not detected by achievement tests. Many individuals with learning disabilities have talents in the areas of art, dancing, mechanics, music, sports, or any combination of these. For example, both Agatha Christie and W. B. Yeats had learning disabilities (Miner & Siegel, 1992; Siegel, 1988a) that can be documented but obviously were individuals with considerable talent. The recognition of these strengths is important to the development of educational strategies and to the selfesteem of the individual with learning disabilities (e.g., Vail, 1990).
Remediation and Accommodation
The following list includes some remedial techniques that are useful for helping individuals with learning disabilities.
For children, the following remedial measures are recommended for learning difficulties:
- To enhance word recognition skills, a word-family approach to draw attention to common word patterns (e.g., cat, bat, sat, hat that, fat, rat, mat) can be used.
- Talking books, books, or both can be used.
- Textbooks on tape should be provided if possible.
- The use of high-interest, low-vocabulary books.
- The use of procedures such as cloze tasks to improve the understanding of syntax.
- The use of a language experience approach—allowing the dictation of stories and then using the words from these stories as the basis for reading vocabulary.
- The use of a calculator should be considered to help with arithmetic facts and multiplication tables.
- The use of a computer (word processor) is encouraged; this may help improve the quality of written work. Using a computer spell check often and early in the writing process will ensure that the student sees correct spellings of words to enhance knowledge of common word patterns.
- Consideration should be given to the use of a tape recorder for projects, book reports, and so on, allowing the teacher to hear the quality of the ideas without relying on the written products.
- Copying from the blackboard is difficult; alternatives should be considered. For example, class handouts, photocopying other students’ notes, or tape recording oral lessons may be an option.
- The following additional recommendations should be considered for adults:
- Teaching metacognitive strategies to help individuals with learning disabilities enhances their learning (for a detailed discussion, see, e.g., Butler, 1995, 1998; Montague, 1997).
- Encouragement of self-monitoring strategies to organize information and to avoid confusion when doing more than one activity. Strategies could include drawing plans or making lists to follow sequential steps from a manual or verbal instructions.
- A literacy program and basic skills training in reading and arithmetic is a possibility for some individuals functioning at a very low level.
- Teaching people with learning disorders to make it clear when they do not understand is important. Even asking the person what they mean or to repeat the instructions in a different way may be helpful.
- If they have difficulty understanding, training people to ask the person to repeat the instructions in a different way can be helpful.
- Textbooks on tape should be provided.
- Tape recording of lectures should be allowed and encouraged if the instructor is willing to give permission. Consideration should be given to the use of a tape recorder for projects, reports, and so on; this would allow the teacher to hear the quality of the ideas without relying on the written products.
- If acceptable to the instructor, answers to essay questions should be completed in point form. Consideration should be given to a similar format for class assignments.
- Because of spelling difficulties, consideration should be given to not reducing grades for spelling errors.
- If possible, use a computer (word processor) for written work. This may help improve the quality of written work. Using a computer spell check often and early in the writing process will ensure that you see correct spellings of words to enhance your knowledge of common word patterns.
- Copying from the blackboard is difficult; alternatives should be considered. For example, class handouts, photocopying other students’ notes, or tape recording oral lessons may be an option.
- Alternate modes of examination (e.g., oral exams) may be considered.
Until the field of learning disabilities resolves the definitional issues, significant progress will not be made. We must examine our basic concepts about the nature of learning disabilities and our current practices. Specific and clear operational definitions will help the field advance. However, this resolution will not happen automatically. It will take a concerted effort by the field.
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