Intelligence Measures Implications for the Assessment of Learning Disabilities at the Postsecondary

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Intelligence MeasuresImplications for the
Assessment of Learning Disabilities at the
Postsecondary Level

• Noel Gregg, Ph.D.
• University of Georgia
• International Society for Intelligence Research
• Vanderbilt University
• December 7, 2002

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Climate

• Students with LD continue to be fastest growing
  group the percentage increased from 25 percent
  in 1991 to 41 percent in 1998 (of students with
  disabilities).
• Students enrolling in more four-year colleges and
  universities.
• Graduate/Professional student enrollment
  increasing

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Critical Issues Impacting Documentation for
Accommodating Learning Disabilities in Higher
Education

• Litigious climate
• Definition
• Eligibility Criteria
• Functional limitation
• Comparison group/high functioning adults
• Adequate assessment tools
• Research

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The Eligibility Question

• Cut off
• Discrepancy

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Definitions/Eligibility Criteria

• Significant discrepancy between definitions used
  and eligibility criteria applied.
• Intelligence often not part of definitions but
  central to eligibility criteria.
• Cognitive and linguistic processing often part of
  definitions but not central to eligibility
  criteria

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Accommodations

• Decisions determined upon support from cognitive
  and linguistic processing abilities

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Procedure(Davis, Coleman, Gregg, 2000)

• Reviewed evaluation records of Regents Center
  selecting clients with available reports of
  previous evaluations that contained IQ scores and
  test scores for at least one of the following
• Pseudoword Decoding
• Real word decoding
• Reading Comprehension
• Spelling
• Mathematical Calculation Skills
• Prior tests were compared to results of a
  comprehensive psychoeducational evaluation
  conducted at the Regents Center.

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Sample Characteristics

• 378 Students Evaluated at the UGA Regents Center
  for Learning Disorders.
• 248 (65.6) had previously diagnosed learning or
  attention disorders, or language disorders
  impacting academic success.
• 152 of those 248 (61.3) had prior reports
  available for review.
• 127 had reports with IQ scores and at least one
  score on an academic skills test (83.6 of the
  152 with available prior reports One in six
  reports failed to contain such information).

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Trends

• Composite IQ score drops
• Pseudoword reading scores increase
• Realword reading scores increase
• Reading comprehension score drops
• Spelling scores remain the same
• Math scores remain the same

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Purpose of Study

• Collect two types of construct validity
• - Correlations between intelligence measures
• Differentiation between groups of college
  students
• Investigate the relationship between the WAIS-III
  Index Scales and the WJ III Cognitive and
  Clinical Clusters

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Regents Center For Learning Disorders (RCLD)
Criteria For Learning Disabilities

• IQ within, or above, the average range
• Academic deficit in one or more, but not all
  achievement areas
• Cognitive/linguistic Processing deficit(s)
  associated with each academic deficit

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• IQ Measure
• Processing Deficits and Strengths on Multiple
  Measures of Processing
• Attention
• Memory/Learning
• Phonologic/Orthographic Processing
• Fluency
• Executive Functions
• Visual-Motor
• Visual-Spatial/Visual-Perceptual
• Oral Language Skills (verbal fluency, vocabulary,
  listening comprehension, syntax, discourse,
  pragmatics)
• Social-Emotional Status
• Academic Deficit(s)
• ? Reading Decoding, Reading Rate, Reading
  Comprehension
• ? Written Expression (spelling, grammar,
  punctuation)
• ? Math calculation and Math Reasoning

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Note Woodcock-Johnson III Tests of Achievement
(Woodcock, McGrew, Mather, 2001)
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Intelligence MeasuresCorrelations for Students
with LD

• WJ III GIA and the KAIT
• KAIT Composite .66
• KAIT Crystallized .43
• KAIT Fluid .68
• WJ III GIA and the WAIS-III
• WAIS-III Full .64
• WAIS-III Verbal .53
• WAIS-III Performance .53

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Intelligence MeasuresCorrelations for Students
without LD

• WJ III GIA and the KAIT
• KAIT Composite .67
• KAIT Crystallized .51
• KAIT Fluid .62
• WJ III GIA and the WAIS-III
• WAIS-III Full .65
• WAIS-III Verbal .66
• WAIS-III Performance .50

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Table 3
T-test of Mean Differences Among Measures
Within Each Group¹
1. Gregg, N., Jordan, M., Wisenbaker, J., Davis,
M., Coleman, C., Hoy, C., Knight, D. (in
review) .Intelligence measures and implications
for assessment of learning disabilities at the
postsecondary level.
17
Results

• Strong evidence for the construct validity of the
  WJ III GIA as a measure of intelligence for the
  college population with and without learning
  disabilities
• WJ III GIA was significantly correlated to the
  WAIS-III and the KAIT score for students with and
  without learning disabilities

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Results

• Equal weighting of subtests into composite scores
  versus component analysis
• Component analysis (Causo Cliff, 1999)
• More potential incremental and discriminate
  validity
• More reliable difference scores
• More precise confidence intervals

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Results

• Significant difference between WAIS-III Full
  Scale Score and WJ III GIA, particularly for the
  group with learning disabilities (10 points)
• Auditory Processing Cluster (Ga)
• Verbal Comprehension (Gc)
• Processing Speed (Gs)

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Results

• Significant difference between WAIS-III Full
  Scale Score and WJ III GIA
• Influence of schooling and other environmental
  shifts in society (Gustafsson, 2001)
• 3 intelligence points per additional year of
  schooling
• 3 intelligence points per decade (Neisser et. al,
  1999)
• Flynn effect (Flynn, 1984, 1987)

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ResultsWAIS-III Indices and WJ III Clusters

• Greatest mean difference between groups (12.80)
  was on the WJ III Cognitive Efficiency Cluster-
  Extended
• WJ III Cognitive Efficiency taps into. . . . .
• Gc
• Gf
• Gsm
• Gs
• Working Memory
• WJ III Cognitive Efficiency includes verbal and
  nonverbal stimuli

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Cognitive Efficiency

• Daneman and Carpenter (1980) noted, that
  individual differences in memory capacity reside
  less with storage capacity and more with the
  efficient use of processes to maximize limited
  capacity.
• Gregg, et. al,(2001) found the WJ III Cognitive
  Efficiency to contribute a significant variance
  to decoding and spelling nonsense words.

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Significant Results

• A 12.46 mean difference between groups (12. 46)
  occurred on the WAIS-III Processing Speed Index
  and a 11.11 mean difference between groups was
  found on the WJ III Processing Speed Index.
• A 11.80 mean difference was found on the WJ III
  Auditory Processing Cluster and a 10.15
  difference on the WJ III Phonemic Awareness
  Cluster

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Significant Results

• A 11.51 mean score difference was found on the
  WAIS-III Working Memory Index and a 11.15 mean
  score difference on the WJ III Working Memory
  Cluster.
• A 8.33 mean score difference as found on the
  WAIS-III Verbal Comprehension Index and the WJ
  III Verbal Comprehension Cluster.

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Results

• WJ III Glr Cluster (5.73 mean score difference),
  WJ III Visual-Spatial Thinking Cluster (6.5 mean
  score difference), and WJ III Fluid Reasoning
  Cluster (6.53 mean score difference) were all
  significant between groups.
• WAIS-III Perceptual Organization Index (.91 mean
  score difference) was not significant between
  groups.

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Results

• WJ III Cognitive Fluency Cluster (5.97 point mean
  difference)
• Combines verbal fluency measures (Retrieval
  Fluency and Rapid Picture Naming) with Decision
  Speed, a task that has a strong Gs component.

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WJ III Academic Fluency Cluster

• McGrew, Ford Woodcock( in press)

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What does research really tell us about adults
with learning disabilities?

• Students with learning disabilities/reading
  disabilities become more accurate readers as they
  get older. . . .BUT continue to be SLOW READERS .
  . . . . . . . . . (FLUENCY/EFFICIENCY).

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What does research really tell us about adults
with learning disabilities?

• Neurobiological evidence demonstrating functional
  disruption for children, university students, and
  adults with dyslexia
• (Shaywitz, S., et.al.,2002)
• Specific neural systems for fast, automatic
  reading disrupted
• Epidemiological evidence of persistent reading
  disabilities

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Measuring Fluency

• Processing speed (general vs linguistic)
• Reading Fluency (words)
• Reading Fluency (sentences)
• Reading Fluency (text)
• Cognitive Fluency vs. Cognitive Efficiency

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Functional Processing Between Groups

• Normally-achieving students appeared to rely much
  more on their verbal knowledge (Gc)
• Students with learning disabilities were more
  dependent on their working memory and processing
  speed abilities.
• Significantly weaker on working memory,
  processing speed, and cognitive efficiency.

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Correlations for WAIS-III Indices and
Woodcock-Johnson III (WJ III) Clusters For
Normally Achieving (Non-LD) and Learning Disabled
(LD) Groups.¹
Gregg, N., Jordan, M., Wisenbaker, J., Davis, M.,
Coleman, C., Hoy, C., Knight, D. (in review)
.Intelligence measures and implications for
assessment of learning disabilities at the
postsecondary level.
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Functional Processing Between Groups

• Question arises as to whether the dependence of
  the students with learning disabilities on
  abilities such as working memory and processing
  speed is the result of deficits in verbal ability
  or whether comprised working memory and
  processing speed capacity leads to limited
  crystallized knowledge and underdeveloped verbal
  abilities.

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Functional Processing Between Groups

• Is there a multiplicative effect of Gc and
  working memory, since integrating new information
  in pre-existing knowledge structures depends on
  the ability to maintain that information for a
  period of time in an activated state.
• Hambrick and Engle (2002) found participants with
  lower levels of working memory capacity derived
  less benefit from domain knowledge.

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Functional Processing Between Groups

• One of the most significant findings from this
  study was the difference between the groups in
  the correlation of their verbal abilities to a
  variety of tasks
• fluid reasoning
• working memory
• speed of processing
• cognitive efficiency

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Importance of Gc

• Hunt (2000) poetically observed, Gc has been the
  wall flower of the intellectual trio (Gc, Gf
  and Gv)
• Hunt urged researchers to ask Gc to put away the
  horn-rimmed glasses, put on a party dress, and
  take a turn on the dance floor. Understanding the
  nature of Gc is as important to the study of
  intelligence as finding Cinderella was to the
  Prince (p. 124).

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Cognitive Predictors of Oral Receptive and
Expressive Performance

• Gregg, et. al (2002) examined the written
  expression abilities of college students with and
  without learning disabilities using a SEM.
• They found that both groups were using the same
  communicative functions.
• They found the group with LD differed in their
  factor loadings and correlationssuggesting
  dependence on difference cognitive processes.

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Assessment Postsecondary Population with
Learning Disorders

• Critical components to measure
• Phonological processing
• Orthographic processing
• Cognitive efficiency
• Fluency (verbal and nonverbal)
• Working memory
• Verbal abilities (receptive and expressive)

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Future Research

• Differential item functioning
• Component analysis
• Confirmatory factor analysis
• Structural equation modeling