An Analysis of WISC-R Factors for Gifted Students with Learning Disabilities Karen A. Waldron and Diane G. Saphire

Intellectual patterns of gifted students with learning disabilities were studied to determine cognitive factors characterizing these children. Twenty-four gifted children with learning disabilities (LD) and a control group of nondisabled gifted children were administered the Wechsler Intelligence Scale for Children-Revised (WISC-R) (Wechsler, 1974). While differences between the two groups on individual subtests were examined, a comparison of broader factors was emphasized in discovering cognitive patterns that might suggest effective intervention. Experimental and control performances were compared on 14 factor scores, using cognitive classification systems ofBannatyne (1971), Kaufman (1975), Rapaport, Gill, and Schafer (1946), and Wechsler (1974). Gifted students with LD were more reliant on verbal conceptualization and reasoning than the control students. They also demonstrated deficiencies in short-term auditory memory and sound discrimination. The gifted group with LD exhibited the Organic Brain Syndrome factor (Wechsler, 1974) to a significantly greater extent than did the control group.

R

ecent studies of gifted students with learning disabilities (LD) have considered how the unexpected occurrence of learning problems in highly intellectual individuals affects their academic performance and behavior. Research thus far has emphasized appropriate methods of identifying these students (Daniels, 1983; Maker, 1977; Senf, 1983) and explored their academic performance, with consideration of their self-concept and behavior at school and home (Maker, 1977; Waldron, Saphire, & Rosenblum, 1987; Winne, Woodlands, & Wong, 1982). We have come to realize, however, that if we are to understand gifted children with LD, we must better comprehend their perceptual patterns and cognitive behaviors. This understanding would allow us to teach students through their stronger processing modalities while providing remedial and compensatory training in weaker areas. Waldron and Saphire (1989) reported that, when compared to a control group of gifted students, gifted students with LD performed significantly more poorly in a number of perceptual areas, including visual and auditory discrimination, visual and auditory sequencing, visual-spatial skills, and short-term auditory memory. There were no significant differences between groups in visual memory skills or listening comprehension.

They also noted experimental students' comparative weaknesses in reading, arithmetic, and spelling and concluded that many academic difficulties may be related to the perceptual problems. Research has also begun to explore the cognitive processes of gifted children with learning disabilities, but the findings have been limited. Because of diversity within this population, there are problems in discovering similar ability levels and common approaches to complex cognitive tasks (Whitmore & Maker, 1985). However, this very diversity may make it even more imperative to conduct cognitive studies. As Bauer (1982) noted, as a result of specific alterations in basic cognitive processes, gifted students with LD may be experiencing problems in any of the four stages of information processing: encoding, manipulation, response selection, and response execution. He indicated that differences in neurological development in areas such as short- or long-term memory also may affect learning patterns for particular students. Significant alteration of many of these patterns has been substantiated by Waldron and Saphire (1989). Whitmore and Maker (1985) and Fox and Brody (1983) noted that research is needed to determine whether unique cognitive combinations characterize the gifted learner with LD. Most of the work in considering cog-

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nitive aspects thus far has been done using the Wechsler Intelligence Scale for Children-Revised (WISC-R) (Wechsler, 1974). While it is generally acknowledged that an optimal measure of intelligence does not exist, the WISC-R "is a reasonable measure of where a youngster is currently able to function. It is the most frequently used structure for observing intelligent behavior" (Rosner & Seymour, 1983, p. 83). While earlier studies tended to rely on a 15-point discrepancy between verbal and performance areas of intelligence to indicate a learning disability, many children have this large a discrepancy without having a learning problem, and many children with LD may not have this large a discrepancy (Anderson, Kaufman, & Kaufman, 1976; Bloom & Raskin, 1980; Tannenbaum & Baldwin, 1983; Vance, Gaynor, & Coleman, 1976). The primary problem with the use of an intelligence test to identify gifted students with LD is that the disability may lower the IQ score so dramatically that the students do not qualify for inclusion in the school district's criteria for gifted, even though they demonstrate strong abilities in some areas. Despite this problem, Fox and Brody (1983) noted that careful review of the subtests will provide the clinician with a profile of cognitive strengths and weaknesses. High scores on some subtests may indicate giftedness, while comparatively weaker scores on others may indicate a disability. This consideration of WISC-R subtests and their subsequent combination into factors has been far more accurate in suggesting the presence of a learning disability than has the Verbal-Performance difference. In comparing relative strengths on individual WISC-R subtests for gifted students with LD, Daniels (1983) indicated that their scores on the Similarities subtest are often the highest. The Arithmetic and Digit Span subtests, with their emphasis on concentration, tend to generate the lowest scores. However, additional research into relative strengths on subtests is needed to determine if the differences are great enough to be significant, rendering their ranking a useful tool in identification. While individual subtest scores may be important for indicating specific strengths and weaknesses, the consideration of subtest clusters into broader factors might 491

allow educators and psychologists to note patterns of cognition supportive of more effective follow-up intervention. Smith, Coleman, Dokecki, and Davis (1977) compared the performance of students with LD on Bannatyne's (1974) four factors. They found that students scored higher on the Verbal Conceptualization factor than on the Sequencing or Acquired Knowledge factors, but that their performance on the Spatial Ability factor was the strongest. Fox (1983) reviewed studies comparing children with reading problems with those without problems using RugePs (1974) recategorization of Bannatyne's (1971) clusters on the WISCR. Fox noted that children with reading problems tended to be highest in spatial categories and lowest on sequencing skills, with conceptual abilities in between. Schiff, Kaufman, and Kaufman (1981) found that gifted children with LD had more scatter on the WISC-R Verbal scale than did non-learning-disabled children of average intelligence. While some research has been initiated using Bannatyne's (1974) clusters, there has been little research thus far into alternative factors of cognitive categories on the WISC-R for gifted students with LD, such as those proposed by Kaufman (1975), Rapaport et al. (1946), and Wechsler (1974). It is difficult to select one model for potential applicability to this population, because each system concerns itself with unique cognitive and/or behavioral areas. As Kaufman (1979) noted, "Which system is correct? . . . It is inappropriate to assume that one particular method is necessarily better than any other technique. Each has its specific uniqueness and utility for different individuals" (pp. 130-131). Within these models it is possible to select factors that allow for specific concerns about the current sample of students, such as their performance when compared with previously studied nongifted students with LD or reading disabled samples, or with samples that also include students from lower socioeconomic populations. For example, Bannatyne's (1974) Verbal Conceptualization factor (Similarities, Vocabulary, Comprehension) allows for the interpretation of learning disabled and culturally disadvantaged students' potential variations within the Verbal scale. Additionally, Bannatyne's (1974) Spatial 492

Ability factor (Picture Completion, Block Design, Object Assembly) represents "one of the most useful and practical subgroupings of Wechsler's subtests" (Kaufman, 1979, p. 152), because of its flexibility in application to varied populations. This factor tends to be the least dependent on special cultural or educational opportunities, therefore more accurately assessing the intellectual ability of children from disadvantaged environments. Additional studies of students with LD also indicated that they demonstrate relative factor strength on Spatial Ability subtests (Anderson et al., 1976; Vance et al., 1976; Zingale & Smith, 1978). Similarly, Bannatyne's (1974) Acquired Knowledge factor (Information, Arithmetic, Vocabulary) is of interest because it includes subtests that are all school related, subject to the influence of home environment, and involving long-term memory (Anderson et al., 1976; Lutey, 1977). One of the most frequently considered models is Bannatyne's (1974) Sequencing factor (Arithmetic, Digit Span, Coding), also called the "Freedom From Distractibility" factor and the "Third Factor" (Kaufman, 1975). The importance of this factor lies in its measurement of the behavioral as well as the cognitive domain, and in the frequency of factor occurrence in children with learning or behavioral disorders (Lombard & Riedel, 1978; Stedman, Lawlis, Cortner, & Achterberg, 1978). However, it is not accurate to conclude that all students with learning problems will demonstrate the increased distractibility measured by this factor, as is too frequently assumed in assessment (Kaufman, 1979). During years of intensive research, Kaufman (1975, 1979) observed and refined a number of factors for the WISCR standardization sample, some of which are of interest with the gifted-with-LD population. His Verbal Comprehension factor (Information, Similarities, Vocabulary, Comprehension) and Perceptual Organization factor (Picture Completion, Picture Arrangement, Block Design, Object Assembly, Mazes) were crossvalidated across sex and ethnicity for mentally retarded children (Van Hagen & Kaufman, 1975), children referred for learning or behavioral disorders (Lombard & Riedel, 1978; Stedman et al.,

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1978), and Chicano students (Reschly, 1978). Across these studies, these two factors were considered good indicators of students' verbal comprehension and perceptual organization skills. Based on Thorndike's (1926) and Jensen's (1969) distinction between the higher abilities involved in insightful problem solving and the lower skills in recalling stored information, Kaufman (1979) discussed the two Verbal subtest factors of Reasoning and Recall. He noted their importance for learning, observing that some students with vast stores of knowledge cannot respond well to problemsolving situations, while others with a poorer memory may solve even difficult problems with insight. Similarly, Kaufman's (1979) RightBrain Processing (Picture Completion, Object Assembly), Left-Brain Processing (Information, Similarities, Arithmetic, Vocabulary, Comprehension), and Integrated Functioning (Picture Arrangement, Block Design, Coding, Mazes) factors have strong implications for teaching. Faglioni, Scotti, and Spinnler (1969) found the right cerebral hemisphere to be particularly important in the processing of verbal information and in letter recognition, functions previously attributed to the left brain. Gibson (1965) and Pirozzolo and Rayner (1977) underscored the importance of integrated functioning by noting that, while the right hemisphere allows children to recognize letters and words as gestalts, the transmission to the left hemisphere allows for the conversion of these symbols into phonological and meaningful units. This consideration of brain functioning requires the inclusion of Wechsler's (1974) Organic Brain Syndrome (Kaufman, 1979). Based on the standardization sample, Wechsler noted that a pattern of low scores on the Digit Span, Coding, and Block Design subtests may indicate brain dysfunction. While this diagnosis should not be made on the basis of WISC-R data alone, the Organic factor was included as an indicator that more in-depth neurological testing might be appropriate. Rapaport et al. (1946), with refinement by Lutey (1977), presented an important dichotomy for the nonverbal subtests. The Visual Organization group (Picture Completion, Picture Arrangement) reJournal of Learning Disabilities

quires visual-perceptual awareness but little more coordination. The VisualMotor Coordination subtests (Block Design, Object Assembly, Coding) are strongly dependent on integration of perceptual-motor skills. The purpose of the present research was to analyze the patterns of subtests for gifted students with LD, using the classification systems of Bannatyne (1974), Kaufman (1975), Rapaport et al. (1946), and Wechsler (1974), to compare the results with factors computed for matched gifted students without LD, and to report findings that might be directed into classroom teaching strategies.

METHOD Subjects Thirty-two boys and 16 girls, ages 8 to 12 (mean age = 10 yrs, 2 mos.), participated in this research. There were 14 Mexican-American students, 7 in the control and 7 in the experimental groups. Four students in each group were from lower socioeconomic background, as indicated by school registration forms. For accurate data analysis purposes, experimental and comparison students were carefully matched for age (within 6 months), sex, mental abilities (within 10 points on the WISC-R), ethnicity, and socioeconomic status. Experimental students had a mean WISC-R Full-Scale IQ of 132 (range = 112 to 147), and controls had a mean of 133 (range = 108 to 152). One control subject had a Full-Scale IQ of 108 and 2 experimental subjects had IQs of 112 and 116, scores lower than those normally included in gifted research. However, these students were included because they were from economically disadvantaged school districts where their IQs were considered to be in the gifted range. Before their involvement in this study, all subjects had been tested within their districts and had been determined to be gifted; criteria for eligibility included IQ, standardized test scores, school achievement, and teacher-completed formal and informal scales. Success on these measures was rated based on performance of other students of similar socioeconomic backgrounds in the same district. Addi-

tional criteria, beyond IQ and achievement measures, included teacher observations of student characteristics associated with giftedness, that is, situational memory, excellent expressive language, imagination, curiosity, keen insights and humor, creative problem solving, strong use of logic and evaluation, and a variety of interests (Whitmore, 1980). Because appropriate identification of gifted students with learning disabilities has frequently proved difficult, strict criteria were used in this research. Initially, 123 school record files of gifted students participating in an enrichment program at Trinity University, San Antonio, Texas, were reviewed to suggest potential experimental and control subjects. Gifted control subjects were required to have achieved above the 90th percentile on standardized tests in language arts and arithmetic, and gifted subjects with LD were required to have scored below the 70th percentile, and to have demonstrated the uneven profile of scores typical in learning disabilities. Fifty-four students were selected for further review. Additionally, Texas Education Agency guidelines were used to determine the existence of a learning disability. To identify a disparity between student potential and school achievement, standard scores on the Wide Range Achievement Test (Jastak & Wilkinson, 1978) subtests were subtracted from WISC-R Full-Scale IQ scores. Since many nondisabled gifted students experience disparity between IQ and school achievement (Senf, 1983), a 4-point-greater difference was sought than that required by the state for a diagnosis of learning disabilities. Subjective information was also included for identification purposes. Parents of all subjects were interviewed twice by telephone concerning their child's developmental history, including any school-related problems. The parents then completed a detailed developmental history form describing family and school background. Issues indicating family instability and the child's emotional history were considered in order to remove from the study those children who might be subject to influences other than that of a learning disability. Subsequently, six students were removed from participation in the research because they did not meet learning disability criteria. No

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students with any handicaps other than a learning disability were included. None of the control students had ever participated in any special education programs for students with handicaps. Three of the 24 experimental students had been identified by their districts as having learning disabilities, while the remaining 21 subjects were initially identified during this research.

Procedures All subjects were administered the How I Feel About Myself self-concept scale (Piers, 1969), providing a measure of general self-concept factors. The report of comparisons between experimentals and controls on the six factors in this measure are contained in Waldron et al. (1987). Students were then administered the Verbal and Performance subtests of the WISC-R. Average reliability coefficients on this IQ test are Verbal, .94; Performance, .90; and Full Scale, .96 (Wechsler, 1974). They were also administered the Neurological Dysfunctions of Children Test (Kuhns, 1979); the Wide Range Achievement Test; the Durrell Analysis of Reading Difficulty (Durrell, 1955); the Wepman Auditory Discrimination Test (Wepman, 1958); and the KeyMath Diagnostic Arithmetic Test (Connolly, Nachtman, & Pritchett, 1976). The specific results of these tests are discussed in detail in Waldron and Saphire (1989). Comparisons between gifted students with LD and nondisabled gifted controls indicated that controls performed significantly better in all areas except visual memory and listening comprehension. The most significant problems of the gifted students with LD when compared to controls were in the areas of arithmetic computation and visual perception, including visual discrimination, visual sequencing, and visual-spatial awareness, based on an analysis of academic and perceptual subtests (Waldron & Saphire, 1989).

RESULTS AND DATA ANALYSIS To evaluate the abilities of the children in various areas, 14 factor scores were computed from each child's WISC-R 493

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scores. The factors used were Verbal Comprehension, Perceptual Organization, Reasoning, Recall, Right-Brain Processing, Left-Brain Processing, and Integrated Functioning (Kaufman, 1975); Sequencing ("Distractibility"), Verbal Conceptualization, Spatial Ability, and Acquired Knowledge (Bannatyne, 1974); Visual Organization and Visual Motor Coordination (Rapaport et al., 1946); and Organic Brain Syndrome (Wechsler, 1974). The individual subtests constituting each of these factors are given in Table 1. A factor score was computed by averaging the scores on the corresponding subtests. It was not possible to compute every factor score for every student, because some students were missing subtest scores. None of these students is missing more than 2 of the 12 subtests. Among the gifted group with LD, 14 students have complete data and among the control group, 17 students have complete data, Because a rank ordering of factors might allow better identification of gifted students with LD by indicating stronger and weaker cognitive areas (Kaufman, 1979), the average score on each of the factors was computed and ranked. The ordering of the factors was very similar for the two groups. Reasoning, Verbal Conceptualization, Left-Brain Processing, Verbal Comprehension, and Acquired Knowledge are the highest factor scores in both groups, while Sequencing ("Distractibility") and Organic Brain Syndrome are the lowest in both groups. The range of the averages is larger for the gifted group with LD than for the gifted group, with the highest gifted-with-LD average being higher than the highest gifted group average and the lowest being lower. To determine whether any of the factor scores differed significantly from any others, 95% Bonferroni confidence intervals were used (Morrison, 1976). Within each group, 14 taken two at a time, or 91 pairwise, comparisons were made. As a result, a significance level of .05/91 = .00055 was required for each individual test in order to maintain an overall or experimentwise error rate of less than .05. Within the gifted group with LD, 14 students had complete data; thus the critical value of 4.55 was determined from the / distribution with 13 degrees of freedom. 494

TABLE 1 Factor Components Factor Kaufman, 1975 Verbal Comprehension Perceptual Organization

Reasoning Recall Right-Brain Processing Left-Brain Processing

Integrated Functioning Bannatyne, 1971 Sequencing 3 Verbal Conceptualization Spatial Ability Acquired Knowledge Rapaport et al., 1946 Visual Organization Visual-Motor Coordination Wechsler, 1974 Organic Brain Syndrome a

WISC-R subtests Information, Similarities, Vocabulary, Comprehension Picture Completion, Picture Arrangement, Block Design, Object Assembly, Mazes Similarities, Arithmetic, Comprehension Information, Vocabulary, Digit Span Picture Completion, Object Assembly Information, Similarities, Arithmetic, Vocabulary, Comprehension Picture Arrangement, Block Design, Coding, Mazes Arithmetic, Digit Span, Coding Similarities, Vocabulary, Comprehension Picture Completion, Block Design, Object Assembly Information, Arithmetic, Vocabulary Picture Completion, Picture Arrangement Block Design, Object Assembly, Coding Digit Span, Coding, Block Design

Also known as the "distractibility" or "third" factor.

Two differences were significant: Gifted students with LD scored significantly higher on the Reasoning factor than on the Sequencing ("Distractibility") factor (/ = 4.76) and significantly higher on the Reasoning factor than on the Organic Brain Syndrome factor (/ = 5.02). Within the gifted group, 17 students had complete data; thus the critical value of 4.30 was determined from the / distribution with 16 degrees of freedom. None of the differences were found to be significant. Thus, while the ranking of the factors is very similar for the two groups, some of the factor scores for the gifted students with LD differ significantly from others, while none of the factor scores for the gifted group differ significantly. Comparisons were made to determine whether the two groups differed from each other on any of the factor scores.

For each factor, the difference between the score of each gifted child with LD and the matched gifted partner was computed for each pair of students for which the pertinent subtest scores were available. Table 2 shows the average score on each factor for each group of students. For each factor, these differences were examined to determine whether or not they could reasonably be assumed to arise from a normal distribution. If the hypothesis of a normal distribution was rejected using the Shapiro-Wilks statistic, then the difference between the two groups on that factor score was assessed by means of a signed rank test, as opposed to the usual / test, which assumes normality. Generally, departures from normality consisted of one or more outlying values that created a skewed distribution and that would have had an unJournal of Learning Disabilities

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duly large influence in a / statistic. The only significant difference occurred on the Organic Brain Syndrome factor (p = .023 for a two-tailed signed rank test on 13 observations). The gifted students with LD scored, on the average, 1.6 points lower on this factor than their gifted partners. Based on formulas developed by Davis (1959) and supported by Sattler (1974), Kaufman (1979) suggested a method for examining discrepancies between an individual's own scaled scores on the WISC-R. This "relative strength" measure allows for an understanding of the peaks and valleys of an individual child's profile. "Each scaled score is systematically compared to the child's own midpoint, with statistically significant differences used to determine meaningful fluctuations . . ." (Kaufman, 1979, p. 56). Therefore, all strengths and weaknesses are relative to the child's own ability. This measurement improves upon the practice of using a group mean of 10 and a standard deviation of 3 for determining strengths and weaknesses, a practice that artificially elevates the performance of high-IQ children (Kaufman, 1979). A measure of relative factor strength was used in this research to assess the strength of a student on a particular factor relative to that individual child's overall abilities. First, the child's Verbal scaled score average (Information, Similarities, Vocabulary, Comprehension, Arithmetic, and Digit Span subtests) and Performance scaled score average (Picture Completion, Picture Arrangement, Block Design, Object Assembly, Mazes, and Coding subtests) were calculated. For each of the subtests included in the factor of interest, the corresponding mean was then subtracted from the child's subtest scores. The differences were then summed to form the child's relative factor strength. For instance, for the Sequencing factor, the relative factor strength is given by (Arithmetic - Verbal average) + (Digit Span - Verbal average) + (Coding - Performance average). A large, positive relative factor strength indicates that the child excels in this factor, relative to her or his overall abilities, whereas a large, negative value indicates a relative weakness in the factor. The relative factor strength was computed for each factor for each child and

TABLE 2 Comparison off WISC-R Factor Averages

Factor

Gifted group with LD Mean SD

Reasoning Verbal Comprehension Left-Brain Processing Acquired Knowledge Verbal Conceptualization Visual Organization Spatial Ability Perceptual Organization Right-Brain Processing Integrated Functioning Visual-Motor Coordination Recall Sequencing Organic Brain Syndrome

15.45 15.40 15.25 14.73 14.59 14.02 13.79 13.78 13.32 13.02 12.85 12.44 11.87 11.54*

1.65 1.98 1.57 1.70 2.27 2.07 2.20 1.37 2.39 1.65 2.02 1.94 1.62 1.44

Gifted group Mean SD 14.83 15.18 14.93 14.70 15.11 13.55 13.70 13.90 13.55 13.71 13.31 13.14 12.90 13.10*

2.59 2.69 2.56 2.59 2.88 1.98 1.90 1.83 2.30 1.74 1.77 2.51 2.05 1.76

*Significant difference between the two groups at the .05 level.

the two groups were compared using / tests and signed rank tests, as appropriate. Normality was assessed by means of a Shapiro-Wilks test, as discussed above. The gifted group with LD had higher relative factor strengths on the Verbal Conceptualization factor than did the matched gifted students (p = .041 for a two-tailed, signed rank test on 22 observations). Thus, when compared to their overall abilities, gifted students with LD had more of a relative strength in Verbal Conceptualization than did the gifted students. On the Sequencing factor, the gifted students showed greater relative strength than the gifted group with LD at the .10 level (p = .087 for a two-tailed / test with 17 degrees of freedom). On the Reasoning factor, the gifted students with LD exhibited greater relative strength than the gifted group at the .10 level (p= .096 for a two-tailed / test with 21 degrees of freedom). The difference between the WISC-R Verbal score and Performance score was computed for each of the students. The differences for the gifted students were compared to the differences for the matched gifted students with LD and the gap between the Verbal and Performance scores was not found to differ between the two groups (p = .926 for a two-tailed t test with 23 degrees of freedom). The potential relationship between prematurity and brain damage was examined. Seven of the gifted students with LD and only one of the gifted students

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were born prematurely, as reported by the parents on the developmental history questionnaire. This difference between the two groups is statistically significant (p = .048 for a two-tailed Fisher exact test). All eight of the premature babies were male. The Organic Brain Syndrome factor scores of the premature children were compared with those of the remaining children. No significant difference was found between the two groups (p = .225 for a two-tailed two-sample / test). Another organic indicator, sleep disorder, was also considered. Three of the gifted students with LD and none of the gifted students had experienced sleep disorders. All three of these children were male. The Organic Brain Syndrome factor scores of the children with sleep disorders (average of 12.2) were virtually identical to those of the other children (average of 12.4). The WISC-R subtest scores of the gifted children and gifted children with LD were compared to determine if there were any significant differences between the two groups. For each subtest, only the pairs of students in which both students had the appropriate subtest score were used. The averages are shown in Table 3. Using paired sample / tests, the only subtest for which the two groups had significantly different scores was Digit Span (p= .030 with 12 degrees of freedom), with the gifted group with LD scoring lower than the control group. The difference in the Similarities subtest 495

scores was significant at the .10 level (p=.085 with 21 degrees of freedom), with the gifted group with LD scoring higher than the controls. Because Daniels (1983) suggested the rank ordering of subtests as an important means of identifying gifted subjects with LD, the rank ordering of WISC-R subtests for the two groups was compared. The rankings for the two groups were very similar, with Similarities the highest score in each group and Coding and Digit Span the lowest scores in each group. While the order of the average subtest scores for the two groups was very similar, the range in the averages for the gifted group with LD (5.50) was substantially larger than the corresponding range for the control group (3.77). To determine whether students tended to score higher on one subtest than another, 95% Bonferroni confidence intervals were constructed, as above. Since there are 12 taken 2 at a time, or 66, comparisons, the significance level for each comparison is .05/66 = .00076. This results in a critical value of f = 4.37 for the gifted group with LD and t = 4.15 for the control group. Within the gifted group with LD, the Similarities and Arithmetic scores were significantly higher (/ = 5.63 and / = 6.07, respectively) than the Digit Span score. Within the control group, the Similarities score was significantly higher (/ = 4.29) than the Digit Span score. Because of the importance of auditory discrimination abilities in the use of phonics as a method of decoding in reading, a measure assessing students' abilities to differentiate between similar sounds was included in this study. The Wepman Auditory Discrimination Test scores for the two groups were compared. The gifted students with LD made significantly more errors on this test than their gifted partners (p = .034 for a two-tailed t test with 23 degrees of freedom). Since professionals often look for neurological "soft signs" in students with LD, a neurological screening test was included in this research to note if gifted students with LD demonstrate these behaviors. The scores of the gifted students with LD on the Neurological Dysfunctions of Children Test (Kuhns, 1979) were compared to those of the gifted controls. No significant difference be-

TABLE 3 Comparison of WISC-R Subtest Averages Gifted group with LD Mean SD

Subtest Similarities Comprehension Vocabulary Block Design Arithmetic Information Picture Arrangement Picture Completion Mazes Object Assembly Coding Digit Span

16.41* 15.36 15.00 14.72 14.59 14.52 14.45 13.59 13.44 13.04 10.83 9.54**

2.79 3.14 3.01 2.43 2.26 2.11 2.20 3.14 3.29 2.55 3.11 3.31

Gifted group Mean SD 15.45* 15.05 14.82 14.00 14.00 15.00 13.64 13.45 13.81 13.64 12.17 12.08**

2.77 4.24 3.40 2.76 2.88 2.97 2.40 2.26 2.46 3.22 3.79 3.25

*Significant difference between the two groups at the .10 level. **Significant difference between the two groups at the .05 level.

tween the two groups was found (p = .719 for a two-tailed two-sample t test with 23 degrees of freedom). Because of the importance of visual and auditory memory to decoding skills in reading, memory assessment was included in this research. The two groups showed no significant difference on the Durrell Visual Memory subtest. For each of the two groups, the relationship between the Durrell Visual Memory subtest and the Durrell Word Recognition and Word Analysis subtests was examined by means of Spearman correlation coefficients. In the gifted group with LD, these two correlations were significantly different from zero and were positive (p = .013 for Visual Memory with Word Recognition and/?= .001 for Visual Memory with Word Analysis, with 24 observations for each), while in the control group neither of these correlations was significantly different from zero (p = .147 and/?= .821, respectively, with 24 observations for each). Similarly, the WISC-R Digit Span subtest was compared to the Durrell Word Recognition and Word Analysis subtests in each of the two groups. None of these correlations were significantly different from zero. In order to consider student relationships between language measures in this research, a series of correlations was performed. Spearman correlations were used to assess the relationship between scores on the Durrell Listening Comprehension subtest with the Vocabulary,

Similarities, Digit Span, Reasoning, and Picture Arrangement subtests of the WISC-R. Among the gifted children with LD, positive correlations were found between the Durrell Listening Comprehension and Vocabulary subtests (p = .021), between the Durrell Listening Comprehension and the Similarities subtests (p = .037), and between the Durrell Listening Comprehension and the Picture Arrangement subtest (p=.006). Among the gifted students, these correlations were not significantly different from zero, whereas the correlation between the Durrell Listening Comprehension and Digit Span subtest was negative (p= .011).

CONCLUSIONS For experimental and control students in this study, there was no significant difference noted between WISC-R Verbal and Performance IQ scores. These findings support Kaufman's (1979) contention that the traditional use of a 15-point discrepancy between Verbal and Performance scores may not be the best indicator of the existence of a learning disability. When compared with their own relative strengths on each of the factors, gifted students with LD were stronger on the Verbal Conceptualization factor (Bannatyne, 1974) and the Reasoning factor (Kaufman, 1979) than the controls. While the controls were also relatively strong in these areas, they did not Journal of Learning Disabilities

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demonstrate the same degree of reliance on these two factors. We may conclude that gifted students generally possess strong abilities to verbally conceptualize and to reason, but that gifted students with LD tend to be more reliant on these strengths. The presence of these two factors may also be masking the academic and perceptual problems that these students are experiencing, allowing them to appear more in control of classroom material than they actually are. The average performance of the gifted students with LD in this study on the nonverbal Spatial Ability factor (Bannatyne, 1974) tended to be lower than their performance on the Verbal Conceptualization factor (Bannatyne, 1974), although this difference was not significant. This result might indicate that they do not demonstrate the same cognitive profile as do the nongifted reading-disordered children reported by Rugel (1974), wherein children with reading problems tended to demonstrate the opposite WISC-R pattern, with strengths on the Spatial Ability factor and a lower ranking of the Verbal Conceptualization factor. Caution may need to be expended, therefore, in using the profile of children with reading disabilities in the identification of gifted students with LD. An important outcome of this study was in the significantly more frequent occurrence of the Organic Brain Syndrome factor (Wechsler, 1974) among the gifted subjects with LD, when compared with controls. While the results certainly would not have us conclude that organicity is the sole cause of the learning problems experienced by these children, the factor was the strongest indicator of differences between experimentals and controls. When administering the WISC-R, many examiners tend to omit Coding, or, more frequently, Digit Span, two critical subtests in the Organic Brain Syndrome factor. The present research and that of Daniels (1983) underscore the importance of these subtests for improved diagnosis of learning disabilities in gifted students. It is strongly recommended that diagnosticians routinely administer these important subtests. It is important to note that a comparison of results between gifted children with LD and nondisabled gifted children on the Neurological Dysfunctions of Chil-

dren Test did not indicate the presence of significant neurological indicators in either group. Since this test provides a survey of the existence of some of the soft signs neurologists view as indicative of organic problems, we may conclude that these indicators may not always be present in gifted children with LD. Results in this study indicated that, compared to their own mean subtest scores, the experimental students scored lower on the Sequencing ("Distractibility") factor (Bannatyne, 1974) than did the match control group. However, Kaufman (1979) hypothesized that while distractibility is an important variable, this factor may actually be a stronger indicator of cognitive ability than of attention, because the required skills of the three component subtests (Arithmetic, Digit Span, Coding) cannot be attributed solely to the presence of attention, and that it is "difficult to visualize children scoring very well on the three subtests merely or primarily because of close attention to the tasks" (p. 71). A comparison between experimentals and controls of the rank ordering of performance on individual WISC-R subtests did not indicate strong differences. Each group showed a strength in Similarities and a deficit in Digit Span. Most of the subtest averages were so close to each other that it was not possible to conclude which scores would generally be higher than others. Thus, there is no evidence that rank ordering of WISC-R subtests is an effective method of identifying the existence of a learning disability. The scatter among subtests was greater for the gifted students with LD. They performed higher (p = .085) on the Similarities subtest and significantly lower (p = .030) on the Digit Span than the controls, supporting the findings of Daniels (1983). In the present research, gifted students with learning disabilities were strongest in their use of verbal conceptualization and reasoning in processing information, and they were especially strong in their categorical thinking skills. They were significantly weaker in their rote recall of verbally presented information. Their ability to verbally conceptualize may be masking their problems with rote shortterm memory. An area of concern appears to be the

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overreliance on visual memory by gifted students with LD. Waldron and Saphire (1989) indicated no significant difference in visual memory skills between these students and nondisabled gifted students. However, when considering decoding skills in reading, the current study indicated that gifted students with LD demonstrated significant relationships between visual memory and word recognition and word analysis skills. The relationship with word analysis was particularly strong, indicating that students may be relying on their visual skills for reading. This research supports the finding of Daniels (1983) that gifted students with LD tend to demonstrate significant problems in rote auditory memory. No relationship was found between auditory memory and word analysis for these students. They also exhibited problems in auditory discrimination between similarsounding letters and words. Therefore, it appears that they may not be relying on the sound-symbol association skills critical for developing phonics, but may be relying almost exclusively on a "sight word" approach. Significant relationships were found between experimental students' vocabulary scores and listening comprehension and between their verbal abstract thinking, measured by the Similarities subtest, and their listening comprehension. Students' strengths in vocabulary, aided by their use of sentence context, may have supported their understanding. Additionally, there was a highly significant relationship for experimentals between tasks requiring temporal sequencing and listening comprehension, suggesting a tendency to correctly sequence events by time relationships. These language strengths may suggest a basis for optimal teaching techniques for this population. Results of this research might be replicated to further explore the cognitive processes of the gifted population with LD. There are indicators in this study that some commonly used methods for identifying nongifted students with LD, such as a large WISC-R Verbal-Performance discrepancy or a rank order of subtests, may not be useful with this population. These gifted students with LD scored lower on the Organic Brain Syndrome factor; however, no relation497

ship was found between this factor and more traditional indicators of a learning disability, such as prematurity, sleep disorders, or neurological soft signs. Further research is needed to fully understand the nature of the lower Organic Brain Syndrome scores. Additionally, relative to their own averages, gifted students with LD were stronger in verbal conceptualization than the gifted students. They tended to rely on visual skills for word recognition and analysis, and performed more poorly in auditory areas, such as sound discrimination and short-term memory. Such findings may be useful in refining or restructuring teaching techniques for gifted students with learning disabilities.

(1976). The Keymath diagnostic arithmetic test. Circle Pines, MN: American Guidance Service. Daniels, P.R. (1983). Teaching the gifted/learningdisabled child. Austin, TX: PRO-ED. Davis, F.B. (1959). Interpretation of differences among averages and individual test scores. Journal of Educational Psychology, 50, 162-170. Durrell, D.D. (1955). The Durrell analysis of reading difficulty. New York: Harcourt Brace Jovanovich. Faglioni, P., Scotti, G., & Spinnler, H. (1969). Impaired recognition of written letters following unilateral hemispheric damage. Cortex, 5, 120-133. Fox, L.H. (1983). Gifted students with reading problems. In L.H. Fox, L. Brody, & D. Tobin (Eds.), Learning-disabled/gifted children: Identification and programming (pp. 117-139). Austin, TX: PRO-ED. Fox, L.H, & Brody, L. (1983). Models for identifying giftedness: Issues related to the learningdisabled child. In L.H. Fox, L. Brody, & D. Tobin (Eds.), Learning-disabled/gifted children: Identification and programming (pp. 101-116). Austin, TX: PRO-ED. Gibson, E. (1965). Learning to read. Science, 148, 1066-1072. ABOUT THE AUTHORS Jastak, S., & Wilkinson, S. (1978). The wide range achievement test. Wilmington, DE: Jastak AsKaren A. Waldron is an associate professor of sociates. education at Trinity University. She holds a PhD in special education administration from Syracuse Jensen, A.R. (1969). Test bias and construct validity. Phi Delta Kappan, 58, 340-346. University. She is a specialist in diagnosis and remediation of learning disabilities and is conduct- Kaufman, A.S. (1975). Factor analysis of the WISCR at eleven age levels between 6Vi and 16Vi ing ongoing research on gifted children with learnyears. Journal of Consulting and Clinical Psying disabilities, with emphasis on identification and chology, 43, 135-147. follow-up intervention techniques for teachers, parents, and school counselors. Diane G. Saphire Kaufman, A.S. (1979). Intelligent testing with the WISC-R. New York: John Wiley. is an associate professor of mathematics at Trinity University. She holds a PhD in mathematics from Kuhns, J. W. (1979). Neurological dysfunctions of children test. Monterey, CA: McGraw-Hill. Carnegie-Mellon University. Her major research interests are statistics in the social sciences and the Lombard, T.J., & Riedel, R.G. (1978). An analysis of the factor structure of the WISC-R and the efmodeling of data from longitudinal surveys. Adfect of color on the Coding subtest. Psychology dress: Karen Waldron, Department of Education, in the Schools, 15, 176-179. Trinity University, 715 Stadium Dr., San Antonio, Lutey, C.L. (1977). Individual intelligence testing: TX 78284. A manual and sourcebook (2nd ed.). Greeley, CO: Carol L. Lutey. Maker, C.J. (1977). Providing programs for the gifted handicapped. Reston, VA: Council for ExREFERENCES ceptional Children. Anderson, M., Kaufman, A., & Kaufman, N. Morrison, D.F. (1976). Multivariate statistical methods. New York: McGraw-Hill. (J976). Use of the WISC-R with a learning disabled population: Some diagnostic implications. Piers, E. (1969). The Piers-Harris children's self concept scale. Nashville: Counselor Recordings School Psychologist, 13, 381-386. and Tests. Bannatyne, A. (1971). Language, reading, and learning disabilities. Springfield, IL: Thomas. Pirozzolo, F.J., & Rayner, K. (1977). Hemispheric Bannatyne, A. (1974). Diagnosis: A note on respecialization in reading and word recognition. categorization of the WISC scaled scores. JourBrain and Language, 4, 248-261. nal of Learning Disabilities, 7, 272-274. Rapaport, D., Gill, MM., & Schafer, R. (1946). Diagnostic psychological testing. Chicago: Year Bauer, R. (1982). Information processing as a way Book. of understanding and diagnosing learning disabilities. Topics in Learning & Learning Disabil- Reschly, D.J. (1978). WISC-R factor structures ities, 2(2), 46-53. among Anglos, Blacks, Chicanos, and NativeAmerican Papagos. Journal of Consulting and Bloom, A., & Raskin, L. (1980). WISC-R verbal Clinical Psychology, 46, 417-422. and performance I.Q. discrepancies: A comparison of learning disabled children to the normative Rosner, S.L., & Seymour, J. (1983). The gifted child with a learning disability: Clinical evidence. In sample. Journal of Clinical Psychology, 36, L.H. Fox, L. Brody, & D. Tobin (Eds.), Learning322-323. disabled/gifted children: Identification and proConnolly, A. J., Nachtman, U., & Pritchett, E.M.

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