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Operational Definitions and Learning Disabilities: An OverviewAuthor(s): H. Lee SwansonSource: Learning Disability Quarterly, Vol. 14, No. 4, Operational Definitions and LearningDisabilities (Autumn, 1991), pp. 242-254Published by: Sage Publications, Inc.Stable URL: http://www.jstor.org/stable/1510661 .

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OPERATIONAL DEFINITIONS AND LEARNING DISABILITIES: AN OVERVIEW

H. Lee Swanson

In 1981, the National Joint Committee for Learning Disabilities (NJCLD) adopted the following definition:

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., sen- sory impairment, mental retardation, social, or emotional disturbance) or environmental influences (e.g., cultural differences, insufficient/inappropriate instruction, psychogenic factors), it is not the direct result of these conditions or influences. (Hammill, Leigh, McNutt, & Lar- sen, 1981, p. 336) This definition has been evaluated positively

compared to others (e.g., Interagency Commit- tee on Learning Disabilities, 1987; U.S.O.E., 1977; e.g., see Hammill, 1990; Silver, 1988). However, it is not an operational definition, because it does not specify the operations or procedures by which the construct of learning disabilities can be recognized and measured. For example, it is unlikely that current studies on learning disabilities would be published in refer- eed research journals if their subject sample description relied solely on the NJCLD definition. Therefore, if we are to enhance our understanding of learning disabilities, serious consideration must be given to the selection of parameters that go into an operational definition. It is in this spirit that this special issue of the Learning Dis- ability Quarterly was developed.

In this opening discussion, I seek to distill some ideas that unify what otherwise might appear to be a collection of unintegrated articles. The reader should remember, however, that each article is written from the authors' own research perspective. I deliberately solicited articles of di-

verse research perspectives to allow a number of issues to be considered. For example, in the first article Kavale, Forness, and Lorsbach discuss the limitations of operational definitions, whereas the article by Stanovich focuses on the irrelevancy of IQ. Likewise, Hynd, Marshall, and Gonzalez emphasize the relevance of studies originating from neuropsychology, Reynolds' article targets psychometric models, while Bryan considers primarily social cognition. No doubt, to integrate these diverse perspectives will be no small feat. The purpose of this special issue, however, is not to show or seek unanimity among the contributors on how to operationalize learning disabilities. Rather, the focus is on the commonality of conceptual issues that emerges in our attempts to operationalize learning disabilities.

OPERATIONALIZING LEARNING DISABILITIES

Before reviewing each article in more detail, I will outline what I think are some fundamental points when one attempts to operationalize the term learning disabilities (LD). Three points are considered: selection of indicators, function of indicators, and parsimony. Selection of Indicators

The ultimate goal behind operationalizing the term learning disabilities is to enhance our ability to replicate and generalize research findings to other samples with similar characteristics. Therefore, an obvious step in this process is for the researcher to specify the parameters or indicators used to determine a learning disability. That is, for each person with learning disabilities studied, a number is assigned that represents whether an indicator is present or absent, or

H. LEE SWANSON, Ph.D., Editor of the Learning Disability Quarterly, is Professor, School of Education, University of California- Riverside.

242 Learning Disability Quarterly



"how much" of the indicator the person pos- sesses. Because learning disabilities cannot al- ways be defined directly (you might not know one when you see one), children with learning disabilities are usually separated from a general population on an array of indicators (see Hall & Humphreys, 1982; Wong, 1985; for a discussion on this issue). Traditional indicators for sample selection include descriptive statistics from standardized intelligence, achievement and process measures, as well as the sample's age, grade level, gender, ethnicity, length of time in special education, and socioeconomic status (however, see Keogh, 1986b). Additional indicators are sometimes given to the study's setting and methodological characteristics.

These indicators must be selected with care. For example, merely reporting means and standard deviations from standardized tests does not allow easy replication due to the difficulty of gathering another sample with the same average characteristics. Instead, to enhance replication, researchers must provide specific details on how the subjects were selected and what types of subjects were excluded. If control subjects are used, they also need to be detailed in the same specific manner.

For example, problems may emerge when cut- off scores on certain measures are used in the sample selection process (e.g., Fletcher, Espy, Francis, Davidson, Rourke, & Shaywitz, 1989). Although cut-off scores refine sample characteristics, they may introduce other constructs than the one intended by the researcher in framing the hypotheses. A cut-off score below the 25th percentile on a reading test, for example, may indicate an underlying construct of poor and/or nonsystematic instruction, rather than an inher- ent disability in mental processing (a fundamental assumption of the learning disability construct; e.g., see Stanovich, 1986a, 1986b; Swanson, 1988). Thus, it is important to remember that indicators of learning disabilities may not be as exact as desired. Their selection involves both in- telligent decision making and construct validation. However, this decision-making process is muddled by two factors: variations in sample selection and strategies for isolating processes.

Variations in parameter selection. A ca- sual review of the literature suggests the exis- tence of a wide array of parameters in operationalizing the term learning disabilities (see

Keogh, 1983, 1988, 1990, for a review). For example, some students classified as learning disabled do not monitor their learning well (Borkowski, Estrada, Milstead, & Hale, 1989; Wong, 1991), cannot generate phonological codes effectively when processing visual information (Siegel & Ryan, 1988, 1989a, 1989b; Shankweiler & Crain, 1986), demonstrate poor metacognitive skills (Palincsar & Brown, 1987; Paris & Oka, 1989), and cannot negotiate social situations well (see Bryan, for a review, 1991).

Thus, depending on one's research interest, one might operationalize a student with learning disabilities as being unable (a) to think logically or symbolically, (b) to access a language system adequately, (b) to exhibit adaptive social behaviors, and so on. This wide variation in the selection of indicators makes it difficult to integrate findings, as well as to establish a common core of variables in sample selection (Frankenberger & Harper, 1987; Keogh, 1983, 1987; Shep- ard, Smith, & Vojir, 1983).

At this point, there appears to be little consensus in the field of learning disabilities on the directions one should go in operationalizing learning disabilities. This lack of direction is best captured by reviewing Alice's dilemma in Won- derland: "'Would you tell, me please, which way I ought to go from here?' said the Cat. 'I don't much care where-'said Alice. 'Then it doesn't matter which way you go,' said the Cat. 'So long as I get somewhere,' Alice added as an ex- planation. 'Oh, you're sure to do that' said the Cat, 'If you walk long enough"' (Carroll, 1916, p. 60).

Isolating operations. Given the diversity in possible directions for operationalizing learning disabilities, a strategy is needed for identifying a common set of indicators. One obvious strategy would be to combine several relevant dimensions of learning disabled children's adaptive and nonadaptive behavior (for example, classroom functioning) into an overall index or set of marker variables. Such an index would draw upon replicated findings across an array of research designs and measures. Although such a checklist or set of marker variables would be un- wieldy due to the number of items selected, in principle, at least, it might provide a common device for researchers to use in separating children with and without learning disabilities.

Of course, this ideal tool is unattainable since

Volume 14, Fall 1991 243



many of the relevant dimensions of learning disabled children's functioning, such as poor strategy use (e.g., Palincsar, Brown, & Campione, 1991), metacognitive deficiencies (e.g., Wong, 1991), or phonological awareness (e.g., Shank- weiler & Crain, 1986), are not standardized or even identified. Further, the learning disabled child's poor adapting characteristics would have to include not only measures of vocabulary, social judgment, and general information, but also

flexibility of thinking, responsiveness to systematic instruction, generalization of skills to various tasks, compensatory skills used within and outside the classroom, and so on. These latter characteristics exhibit themselves only in unique situations and others cannot be evaluated except by observing this child over an extended period. Thus, again, the researcher is left seemingly with unlimited possibilities in terms of operational definition. The selection process is further exac- erbated because of the lack of an accepted theory within the field (e.g., Swanson, 1988, also see commentaries), as well as political policies that ignore scientific data in the assessment of such children (e.g., see Adelman & Taylor, 1991; Chalfant, 1989; Keogh, 1986a, for review).

A more realistic strategy involves placing some constraints on these parameters by focusing on isolated operations, thereby operationalizing a learning disability in terms of a narrowly re- stricted range of operations. One example of an operational definition is outlined in an excellent chapter by Morrison and Siegel (1991) in which learning disabled children are defined as those who

(1) have IQ scores equal to or above 80 and (2) have one or more of the following: (a) WRAT (Wide Range Achievement Test) reading subtest scores equal to or below the 25th percentile, (b) WRAT arithmetic subtest score equal to or below the 25th percentile and WRAT reading scores equal to or above the mean on the Parent and or Teacher Question- naire. (Conners Parent and Teacher Rating Scales; see Goyette, Conners, & Ulrich, 1978, p. 91) This definition captures three high-incidence

disorders within learning disabilities: reading (word recognition), arithmetic (computation, written work), and attention. Consistent with the notion that a learning disability is intrinsic to the

child, each of these disorders is shown to demonstrate neurological and cognitive processing profiles (e.g., Fletcher, 1985). No doubt, such a definition presents a number of positive (e.g., easy identification for a broad constituency of researchers) and negative (e.g., construct validity, conceptual integrity) aspects. Of course, the major advantage in selecting this range of behaviors is that researchers utilize a common set of measures that, in turn, enhance our chances of replication.

Less restrictive definitions would attempt to capture operations that match some basic pre- mises in the field, most likely the following three assumptions: (a) learning difficulties are not due to inadequate opportunity to learn, general intelligence, or significant physical or emotional disorders, but to basic disorders in psychological processes; (b) these processing deficits are a re- flection of neurological, constitutional, and/or biological factors; and (c) there is a deficit that depresses only a limited aspect of contextually appropriate behavior.

Thus, when one attempts operationally to define a phenomenon such as learning disabilities, an effort is made to measure adequate opportunity to learn (documentation that optimal systematic instruction has occurred, but deficits in isolated processes remain); independence of specific processing difficulties from general academic aptitude (independence of a processing problem from general IQ); the relationship between neuropsychological inefficiencies and cognitive processing difficulties; and so on. Criteria for selection of learning disabled children might include cut-off points on intellectual, neuropsychological, dynamic, and information-processing measures. However, problems arise when one attempts to expand the number of operations into a definition. Some of these problems relate to the limited number of valid and reliable instruments available (e.g., Kavale & Mundschenk, 1991) and the weak link between neurological and cognitive indices (Orbzut & Boliek, 1991). Function of Indicators

The value of an operational definition rests on the purpose of a given study. Therefore, when evaluating the meaningfulness of an operational definition, one must ask: what is the function and/or relationship between the operational definition and the research question? A research question such as "what are the characteristics of




school-identified learning disabled children in special classrooms" requires a different set of operational parameters than "what are the processing deficits of learning disabled children high or low in social skills?". Thus, the value of the operational definition is linked to how specific the research hypothesis is.

Consistent with this issue is the notion of hypothesis specificity. For example, a research hypothesis such as the following: "poor reading in learning disabled children reflects more isolated processing deficits than in those who are slow or

generally poor readers," creates ambivalence about what to include in the operational definition. It is more precise to assert that "poor reading in children with learning disabilities is caused by phonological coding among such children who only have a specific deficit in word recognition." The phrase "among children who have a specific deficit in word recognition" clearly de- pends on a particular characteristic of the learning disabled sample-specific to a reading problem. In other words, the presumed cause of learning disabled children's reading problems is phonological coding (or vice versa). The researcher predicts that if the sample matches the operational definition of a certain subgroup- those with specific reading problems, those with reading and other problems-a clear relationship can be observed between phonological coding and the group with specific reading problems. Reading problems are not universally caused by phonological coding, according to the more precise hypothesis, but only a segment of the particular learning disabled population. These functions must be represented in the operational definition, the research question, as well as in the design of the study.

In sum, listing subject characteristics alone does not give substance to the operational definition of learning disabilities. The researcher se- lects the observable indicators that best match the theoretical definition of learning disabilities. As a general rule, the more specific the sample, and the more specific the research question, the more detailed description is needed to define the subject sample. Parsimony

As a general principle, one may argue that the best operational definition of learning disabilities is one that has been consistently refined across several studies. According to the law of parsi-

mony, such a refinement process isolates relevant parameters while deleting irrelevant ones. As part of this process, one strategy is to determine how much the parameters in the operational definition influence the findings of the study. When this question is answered adequately, substantial progress can be made in identifying only relevant parameters for inclusion in operational definitions. For example, if IQ variations within a certain range of scores have little effect on the outcome of the study, such scores may be judged as irrelevant to the operational definition of learning disabilities.

Some comment should be made on methodological strategies that attempt to isolate relevant/irrelevant variables. At least three options are available: First, researchers can a priori define their sample so that only subjects with performance patterns on certain variables are included. According to the above discussion, however, there is some question whether all or some of the subjects' characteristics are relevant to the research question. For example, if subjects are selected because they are white, male, have high SES, and have obtained IQ scores above 90, reading recognition scores below 25%, and math scores above the 35%, and if the researcher has a hypothesis about reading, is the issue of gender, ethnicity, and so on, relevant to the operational definition? Future studies may require that the researcher provide a ratio- nale for including descriptors based on their relevance to the learning disabled definition.

Second, the researcher can operationally define and measure an isolated variable of interest (in this case, reading) from a more broadly defined list of parameters on a sample of learning disabled subjects. For example, the researcher can subgroup the sample into two or more groups on a particular task (e.g., task related to phonological awareness) and examine the effects of various processing tasks in each group.

A third method involves controlling relevant and/or irrelevant variables through research design (e.g., reading-level matched design) or statistics (e.g., analysis of covariance with the influence of IQ, reading comprehension, etc., par- tialled out).

Let us briefly consider research on the relevance of variables related to three assumptions: specific learning problems, performance discrepancy, and exclusion (for a comprehensive re-




view, see Morrison & Siegel, 1991; Fletcher & Morris, 1986).

Specificity. Specificity refers to a learning problem that is confined to a limited number of academic or cognitive domains. The notion of specificity is tied closely to the way one classifies or subgroups performance. That is, children are classified and defined in terms of isolated processing, neurological, and/or academic deficiencies. Example classifications have included the Wide Range Achievement Test (e.g., Fletcher, 1985; Rourke, 1982; Siegel & Linder, 1984), processing skills (Boder, 1973; Lyon, 1985a, 1985b), developmental processes (Morris, Blash- field, & Satz, 1988), speed/accuracy (Lovett, Barron, & Ransby, 1988), neuropsychological profiles (Rourke, 1982; Rourke & Fisk, 1988), and so on. Learning disabled children are operationalized in terms of problems in specific processes (e.g., phonological coding) and/or academic areas (such as reading) and further contrasted with children who have problems in other domains (e.g., mathematics), and/or children of equal achievement, ability, and/or chron- ological age. These approaches tend to stay away from rather generalized definitions of learning disabilities (e.g., NJCLD), focusing instead on smaller, more clearly defined subtypes. Although, conceptually, the notion of specificity is critical to operational definitions, endeavors along these lines have been criticized, primarily in three areas.

First, it has not been established that isolating children on a particular domain separates them from other children who also experience difficulties in those domains. For example, Siegel (1989) and Siegel, Levey, and Ferris (1985) found few differences in performance between dyslexic and poor readers on reading, language, spelling, and memory measures.

Second, the literature is unclear on whether operationally defined subgroups of learning disabled children respond differently to intervention (e.g., see Lyon, 1985a, for a review). Thus, the social validity of operational definitions can be questioned. For example, Stanovich (1986a) stated that there are no data to suggest that the discrepancy-defined dyslexic reader responds differently to various educational treatments than do ordinary poor readers. A possible exception to this finding is the work by Lovett et al. (1990), in which operationally defined sub-

groups who fail at reading at different developmental stages responded differently to intervention.

Finally, operational definitions are more driven by enhancing measurement procedures, via test- ing and classification procedures, than by an- choring definitions to a theoretical framework. Kavale and Mundschenk (1990) found that most measures commonly used in assessment batter- ies reflect a form of psychometric engineering that obscures the poor conceptual basis of the test. That is, the measures used for definitional purposes obscure whether the specific deficit identified is of adequate construct validity.

Discrepancy between IQ and achievement. A number of operational definitions have attempted to establish that a learning disabled child's achievement is at a level that would not be expected based upon general ability. Tradi- tionally, identification of learning disabilities has relied primarily on uncovering a discrepancy between expected achievement and intellectual ability.

One means of operationalizing discrepancies between potential and actual performance is to compare the scores of children with learning disabilities on different standardized tests. These discrepancies are quantified using (a) informal judgments; (b) grade-level expectancies and the degree to which a child deviates from grade-level expectancy; (c) mathematical formulas that emphasize current achievement, IQ, or mental age; (d) standard score discrepancies; and/or (e) regression formulas that account for the effects of scores regressing toward the mean. The reliance on standardized tests to determine performance discrepancies is based on the assumption that la- tent sources of individual differences are related to mathematically derived constructs (i.e., factors). Although interpretations of mathematically derived constructs are unequivocal (Carroll, 1983), the goal of such procedures is to isolate global constellations of the strengths and weak- nesses in the functioning of students with learning disabilities. In a practical sense, it is assumed that standardized tests assess individual differences along some continuum and that test items reflect an educationally relevant construct; otherwise, the tests would be of little interest or value as a means of determining discrepancies in the performance of students with learning disabilities. Critical to the assumption of a discrepancy




is the notion of independence. That is, a learning disabled child's global aptitude would not be adequately predicted from the deficit area (e.g., reading is weakly correlated with IQ), whereas the normally achieving counterpart would repre- sent a different correlational pattern (achievement scores coincide with IQ).

Although the notion of discrepancy makes conceptual sense, it is probably the most contentious issue related to attempting to operationally define a learning disability. The issues raised in several reviews (e.g., Kavale, 1987; Lyon, 1987; Reynolds, 1985; Shepard, 1983; Siegel, 1988b, 1989, 1990; Stanovich, 1986a, 1986b, 1989) may be summarized as follows:

1. IQ tests do not measure potential; therefore, they should be excluded from discrepancy formulas. That is, IQ tests vary in the skills measured (covarying abilities) and, therefore, do not constitute adequate representation of a unitary construct such as potential.

2. The intercorrelational patterns between IQ and achievement measures are not distinct between ability groups.

3. IQ measures, in many cases, are not based on a learning model or theoretical framework.

4. Few cognitive differences exist between children with and children without discrepancies.

5. Discrepancies exist across a number of handicapped and nonhandicapped groups.

6. Discrepancy notions have been questioned on statistical grounds (this concern will be reviewed in the article by Reynolds).

Concern has been voiced about analyzing performance discrepancies strictly based on psychometric measures. For example, although the psychometric instruments predict fairly well the stability of performance discrepancies (McKin- ney & Speece, 1986), it may be difficult to define the mental processes necessary for effective learning, to identify subprocesses underlying academic tasks, as well as global processes required for school learning, and to provide a link between learning theories and educational practice (e.g., Wagner & Sternberg, 1984).

One promising framework for separating specific processing deficits from general intelligence focuses on modularity, that is, psychological processes that act independently of one another (Fodor, 1983; Stanovich, 1990). Tentative support for the concept of modularity has been found when processes that are most directly re-

lated to general intelligence (e.g., metacognition) are weakly correlated with lower level processes in a particular academic domain. In fact, some interesting results suggest that isolated reading processes, such as phonological coding, are independent of intelligence (e.g., Siegel, 1990). Thus, to operationalize a construct such as modularity, one would have to show that compo- nents related to intelligence (e.g., executive processing, prediction, self-monitoring) do not affect certain low-order processes during an ongoing cognitive activity. For an example, one would have to demonstrate that a high-level reading strategy, such as word or content predictability, remains independent of phonological access. As an illustration in the domain of reading, it has been suggested that high-level comprehension of discourse, such as the predictability of events (e.g., words), does not influence lexical access (see Balotta, Polatsek, & Rayner, 1985, for a review). It seems unlikely, however, that one would be able to show that a person's knowledge base and/or reasoning ability remains completely independent of his or her ability to read.

Exclusion. Very seldom do research studies on learning disabilities report that concomitant disabilities exist. Instead, a clear effort is made to distinguish learning disabilities from other general handicapping conditions, such as mental retardation and visual and hearing impairments. Further, it is typically specified that bilingual, socioeconomic status, and conventional instructional opportunity does not adequately account for the depressed scores. Thus, operational definitions allow one to infer that the learning problems experienced are intrinsic to the child.

Some investigators have challenged these assumptions (e.g., Braden, 1987; Kavale, 1980). For example, Rutter and Yule (1975) suggested that exclusionary definitions fail to specify the meaning of conventional instruction, sociocul- tural opportunity, average intelligence, and so on. Likewise, Taylor, Satz, and Friel (1979), in their comparison between children with dyslexia and children who had reading problems but did not meet exclusionary criteria (because of low IQ, low SES, etc.), found no group differences on several dimensions (e.g., severity of reading problems, neurological exams, parental reading levels, other achievement tests, reversal, and let- ter confusions). Further, Kavale (1980) argued that comparisons between learning disabled and




culturally disadvantaged groups in terms of symptomatology suggest more similarities than differences. Hence, there is little evidence to indicate that operational definitions need to include exclusionary criteria (Fletcher & Morris, 1986).

MAJOR DEFINITIONAL ISSUES After this overview of the issues, let us now re-

view some of the main points made by the con- tributing authors to this special issue. Testable and Meaningful Constructs

In the first article, Kavale, Forness, and Lors- bach suggest that defining learning disabilities has been one of the most contentious issues in the field. At the heart of the issue is the fact that definitions of learning disabilities do not possess experimentally testable constructs. Thus, what we think is learning disabilities is based upon social consensus rather than meaning. Further, ef- forts towards narrowing the parameters of the definition may not capture the true essence of a disability. For example, restricting our focus to reading, speaking, writing, reasoning, or mathematical abilities does not capture the complexity of learning disabilities. To date, our definitions have focused on variability and not on a range of associated behaviors.

Kavale et al. also propose that we are limiting our understanding of learning disabilities when we focus on operational definitions. That is, processes used to define operations do not really define. For example, any number of aptitude measures (IQ) could be used to define expected achievement and an even greater number to define actual achievement. Thus, our operations of learning disabilities are not precise because we have different concepts about what we do to measure aptitude, achievement, and so on. There are no rules by which to determine what are relevant or irrelevant operations.

The authors further argue that the poor state of learning disabilities theory prevents us from developing meaningful operational definitions. Thus, existing definitions, even those that include notions about discrepancies, tell us little about what a learning disability is. As a result, Kavale et al. maintain that broadening the definition to include social skills (see Bryan, this issue) is of little consequence when the theoretical mer- its of the definition have not been debated. In- stead, they recommend that we focus on opera-

tional interpretations of the best available knowledge. Choosing Conceptually Correct Measures

Stanovich also raises concerns about the learning disabilities definition, but argues that one concept - discrepancy - must be recon- ceptualized. Pointing out that at the heart of most learning disabilities definitions, especially as they apply to reading, lies assessment of a severe discrepancy between IQ and achievement, he maintains that the field has not adequately grappled with the issue of why IQ is used in discrepancy formulas. Specifically, Stanovich's ar- gument is that (a) IQ measures are not measures of potential; (b) it is difficult to differentiate readers of differing IQ; (c) variations in IQ tests create instability in subtypes; and (d) nonverbal IQ has little educational relevance. Although consid- erable research has been conducted on validat- ing the appropriateness of the discrepancy criterion (see Reynolds, this issue), such research suffers from an inability to separate readers with learning disabilities from poor readers. Further- more, Stanovich observes that the field of learning disabilities is characterized by having plunged itself into areas of educational practice and diagnosis without setting itself on a firm empirical foundation. As an alternative to IQ measures, he suggests that measures of listening comprehension be considered. Linking Definitions to Neuropsychological Evidence

In the past, criticism has been leveled at neurologically based definitions of learning disabilities because of the yet-to-be-demonstrated neurological patterns claimed to match psychometric patterns of performance (Morris & Satz, in press; Satz & Fletcher, 1980; Satz & Morris, 1981). In addition, a discrepancy between two federal definitions has brought further ambiguity into the neuropsychological criteria. That is, the PL 94-142 definition of learning disabilities removed the etiological role of neurological factors while emphasizing academics, whereas the NJCLD definition proposed a broader view of learning disabilities, stressing neurologically based causative factors. Currently, the importance of neuropsychological research in operationalizing learning disabilities is being reconsidered. Thus, sophistication of computer- ized (CT) scanning, magnetic resonance imaging (MRI), and positron emission tomography (PET)




scanning, as well as genetic studies (e.g., Pen- nington & Smith, 1988) have generated a new interest in the biological basis of learning disabilities.

The article by Hynd, Marshall, and Gonzalez indirectly suggests that children who have difficulty organizing, coordinating and integrating, and/or synthesizing stimuli experience academic failure due to an underlying cerebral dysfunction. These authors' review of postmortem and neu- roimaging studies provides provocative evidence in support of a neurological conceptualization of learning disabilities. In general, these studies suggest that anomalies related to learning disabled children and adults appear as asymmetries favoring the left side of the brain, primarily the infe- rior frontal, temporal, and parietal regions - areas that relate to linguistic functions. While individuals with severe reading disability do not seem to demonstrate any obvious structural defect or lesion that would be a marker for learning disabilities (i.e., the brains of individuals with LD and normals may look the same), there is less asymmetry between the left and right sides or re- verse asymmetry of the brain for the disabled than for the nondisabled population. These deviations are more likely related to neuropsychological development than brain damage or lesions in the postnatal period. Hynd et al.'s analysis also suggests specific deviations in learning disabled children's brain asymmetry that separate them from ADD/H children, for example.

In sum, the results of Hynd et al.'s analysis point to support for the notion that learning disabled children suffer neurological inefficiencies. However, because of the heterogeneity of the population, one cannot conclude that learning disabilities is strictly due to central nervous system dysfunction. Hynd et al.'s analysis is consistent, however, with the notion that severe learning disabilities is related to neurological factors. Measuring a Discrepancy

From a psychometric perspective, the critical question for the field of learning disabilities has been a severe discrepancy between a student's current level of academic attainment and the mean level of all other children of the same age, ability, or IQ score. In this issue, Reynolds suggests that it is possible to improve the objective identification of learning disabilities by emphasizing the discrepancy between age, ability, and current academic psychological process.

The concept of a severe discrepancy remains key for two reasons: (a) it denotes a validated criterion compared to other criteria; and (b) it denotes specificity. Unfortunately, as the article by Reynolds indicates, the use of different measurement models has created ambiguities in the population served within and between several states (Frankenberger & Harper, 1987; Merrell & Shinn, 1990). Based on a review of formulas (favoring the regression formula) and issues related to significant discrepancies, Reynolds con- cludes that the determination of a severe discrepancy does not create a sufficient condition for establishing a learning disability. Instead, one must demonstrate problems in basic information processing, possibly related to neuropsychological inefficiencies, as well as establish that unique or differentiated instruction has occurred. Social Cognition

The importance of social cognition in defining learning disabilities has been noted by the Inter- agency Committee on Learning Disabilities (1987), which suggested that children with LD manifest difficulties in social skills (see Forness & Kavale, 1991, for discussion). A recent chapter by Bryan (1991) provides a timely analysis of the extant literature on social cognition, specifically in the areas of perspective taking, moral development, and social problem solving. In her present article, however, Bryan argues that crit- ics of learning disabilities research, such as those who question whether the sample selection is operationally defined, are placing undue restrictions on research - restrictions that, in turn, threaten progress in the field. Citing examples of research that has challenged current operational notions, and, in turn, has caused a refor- mulation in our thinking of learning disabilities, Bryan maintains that undue constraints on our definition of learning disabilities have a decided affect on the directions taken by researchers

Although criticism of the field has overly focused on definition, she suggests that a shift is occurring, away from definition to the issue of research. Thus, sample selection becomes a sec- ondary concern, while greater emphasis is placed on the commonality of findings. Accord- ing to Bryan, results across variously defined samples have been fairly consistent and provide a common thread that mitigates issues of definition and methodology. Further, she notes some research bias against selecting school-identified




learning disabled students, pointing out that this group of students keeps emerging, in spite of ef- forts to make sample selection more strict. Ac- cording to Bryan, loosely defined samples are worthy of investigation, if for no other reason than to establish social validity. She further argues that if constraints are to be placed on the information collected on children defined as learning disabled, then self-concept information should be collected. Her point is that careful subject selection should be based upon previous work, not on setting undue standards in sample selection.

CONCLUSIONS AND NEW DIRECTIONS In general, based on the authors reviewed

here, it can be stated that (a) our operational definitions must have conceptual meaning (Kavale, Stanovich); (b) we must question the measures selected to establish a discrepancy (Stanovich, Reynolds); (c) we must not be restrictive in our definitions, but look for patterns of continuity in research results (Kavale et al., Bryan); and (d) we need to bolster our notion about the intrinsic difficulties in processing information (Hynd et al.).

As professionals in the field, we have some serious thinking to do if we are to capture the complexity of a learning disability. Specifically, the learning disabilities field must consider and scrutinize a number of operational definitions. The field is too new to isolate and accept a common set of measures that reflect a narrow range of operations. For example, serious consideration must be given to alternative measures of potential (such as suggested by Stanovich) and achievement. On the other hand, operational definitions must be derived from an accumulating knowledge base. Thus, the field should not give serious consideration to operational definitions that deviate too far from some of the critical assumptions mentioned earlier.

Other points could be considered in attempts to operationalize learning disabilities. Thus, this special issue is far from a final commentary on the operationalization of learning disabilities. Suggestions should be made for future research direction. I will attempt to make two. My suggestions are not based on a systematic analysis of operational definitions, but originate in the perspective of an editor for a journal that publishes learning disabilities research. Therefore, my suggestions are biased.

First, I believe it is necessary for us to re- work/reformulate our conceptual definitions within the context of learning theory. The authors in this special issue agree that we need to reconceptualize what we want our operational definition to include, articulate the parameters of the definitions, and ensure that our definition emanates from a sound theoretical framework that captures the processes of learning as well as the context in which learning occurs. Thus, definitions in published research reports must articulate the framework within which they are oper- ating. I would suggest that this endeavor entails reformulating some common assumptions that have a historical reference (such as those represented in the NJCLD definition). After this conceptual reworking, operationalized definitions and measures could be established. Such measures, in turn, would require a validity and relia- bility analysis.

I will illustrate this first phase by taking some liberty in synthesizing the research literature on learning disabilities from an information-processing perspective. While other perspectives can be considered, this is the most familiar to me. It appears to me that most studies published in psychological/educational and neuropsychological journals define, at least in part, a person with learning disability as an individual with least average general academic aptitude (consistent with Siegel and Stanovich's work, IQ test is not obli- gatory) who unexpectedly has difficulty per- forming certain cognitive processes and/or operations. The person's performance patterns on general aptitude measures reflect a factor struc- ture comparable to that of nondisabled counterparts on tests that load high on "g".

Problems in effectively utilizing certain cognitive processes, however, are reflected on tasks that make heavy demands on specific low-order processes (e.g., nonword reading tasks that rely on phonological codes) and/or higher order processes (e.g., problem-solving tasks that rely on metacognition) and/or processes that are sensi- tive to academic domains such as reading, mathematics and writing. The discrepancy between the person's average global information-processing ability and his or her impairment on isolated processes is assumed to be due to a cognitive/ neurological constraint or inefficiency. As mentioned, this constraint or inefficiency manifests itself in specific lower order processing (e.g.,




awareness and monitoring of attentional resources) and/or processes that facilitate the interaction between or coordination of lower and higher order processes.

I admit that I am on shaky ground because the literature is unclear about how specific high- and low-order processes interact or remain function- ally independent while a learning disabled student performs on an academic task (e.g., see Stanovich, 1990; Swanson, 1989). But I have couched my conception of learning disabilities within an information-processing framework. Research in this vein would have to operationalize a possible model to understand the depen- dence or independence among processes. This may be done by considering how learning disabled children's knowledge about various situations or contexts (such as a reading context) influences their cognitive processing. In designing my study, I would also have to provide a ratio- nale for the instrumentation by which learning disabilities is defined.

Second, after my notions about learning disabilities have been matched to a conceptual framework, future variations in operationalization would need to follow a research agenda. A proposed agenda for the new decade may include the following: 1. Measures must be analyzed in terms of con-

struct validity. The researcher is encouraged to provide multiple measures of potential and specific disability to ensure generality of the construct across tasks. Further, it is important that the measures come from a well-developed theory of learning.

2. Rigorous experimental and quasi-experimental designs should be used to compare learning disabled children with their counterparts. Further, multiple experiments will need to be published in order to enhance replication.

3. The learning disabilities construct needs to be tested in various contexts (within and outside the classroom).

4. Qualitative research designs need to be used in tandem with quantitative approaches. In conducting such research, it is vital to incor- porate conventional credible procedures (e.g., a complete rejection of reductionistic work would be inappropriate).

5. Information should be provided in the operational definition to demonstrate stability and/ or durability of the construct. For example, if

learning disabilities is due to an inability to benefit from the best instructional approach, some documentation must be gathered to demonstrate that the child has been exposed to such instruction. For example, it would not make sense to classify a child as having a phonological coding deficit if systematic instruction could easily modify such a problem. Thus, systematic effects of previous classroom instruction on learning must be measured.

6. The possibility that children defined differently by various operational definitions respond differently to instruction must be fully explored.

7. Future research studies must tie cognitive and academic performance with neuropsychological data. If the field is to assume that LD problems are intrinsic to the child, further development and use of neuropsychological indices is necessary. In addition, some of these indices must be available for assessment in the public school context (in contrast to MRI and PET scanning).

In summary, the theme that underlies most of the articles in this issue is that operational definitions of learning disabilities must be directed by a strategy that makes a serious attempt to capture meaningful constructs. Thus, an adequate operational definition of learning disabilities not only focuses on measurement, replication of sample, and meeting critical assumptions, it also takes into consideration its meaningfulness. Meaning is here defined in the context of theory, research question and design, as well as the construct validity of measures that capture the child's environmental and behavioral interac- tions, developmental structures, biological constraints, and cognitive processes.

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