GACE School Psychology (724) study materials
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Interpreting Cognitive Scatter, Adaptive Behavior, and Poor Intervention Response

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Interpreting Cognitive Scatter, Adaptive Behavior, and Poor Intervention Response

Devon is a 9-year-old fourth grader referred for special education evaluation due to reading and math difficulties. Your assessment yields a WISC-V FSIQ of 82 (95% CI 77–87), Verbal Comprehension 88, Visual Spatial 91, Fluid Reasoning 85, Working Memory 78, and Processing Speed 76; the GAI is 88. On the WJ-IV, Broad Reading is 84, Broad Math is 79, and Broad Written Language is 81. Adaptive behavior composite on the Vineland-3 is 79 by teacher report and 86 by parent report. The teacher reports off-task behavior, and the cumulative file shows two years of Tier 2 interventions with inconsistent fidelity; CBM data show a slope of 0.4 words per week compared with a goal of 1.2. The eligibility team wants your recommendation: specific learning disability, intellectual disability, or neither. The state allows both ability–achievement discrepancy and patterns of strengths and weaknesses, and the district has no mandated model.

1. How do you interpret the cognitive, achievement, and adaptive behavior data, including the FSIQ versus GAI difference and the adaptive behavior scores?

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The first point is that the FSIQ of 82 and GAI of 88 are not meaningfully different for eligibility purposes; both fall in the low-average to borderline range, and the 6-point difference is well within what measurement error and index scatter can produce. The GAI excludes Processing Speed and Working Memory, both of which are relative weaknesses at 76 and 78. That pattern suggests that Devon’s performance is depressed by slow processing and working-memory limits, not by a broad intellectual deficit. The achievement scores (79–84) are also low-average to borderline, close to the cognitive estimates, so a severe ability–achievement discrepancy is not evident. Intellectual disability requires significantly subaverage intellectual functioning and concurrent deficits in adaptive behavior. The adaptive scores of 79 and 86 are not clearly in the deficit range, and the discrepancy between teacher and parent ratings argues for caution and further information. A diagnosis of ID is not supported. A specific learning disability is plausible, but not automatic: the achievement scores are low, and the CBM slope of 0.4 words per week against a goal of 1.2 suggests inadequate response-yet fidelity was inconsistent. The team must determine whether the low achievement is primarily due to processing weaknesses, attention problems, inadequate instruction, or a combination.

2. What additional data and decision rules would you use before selecting a disability category?

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I would not select a category from the cognitive and achievement scores alone. I would first obtain a detailed intervention history: what programs were used, for how many minutes per week, in what group size, who delivered them, and what fidelity checks exist. The statement that fidelity was inconsistent is a major confound; without adequate intervention, an RTI model cannot support a disability determination. I would collect classroom observations during reading and math, work samples, and teacher rating scales for attention and executive functioning, because off-task behavior could reflect ADHD, anxiety, or task difficulty. I would ask the family about medical history, sleep, vision, hearing, and any outside diagnoses, and I would request a health provider’s input if attention problems are prominent. I would review attendance and mobility. For a PSW approach, I would examine whether the processing weaknesses (working memory, processing speed) are theoretically linked to the achievement weaknesses and whether the pattern is specific rather than global. I would also check whether the low achievement is better explained by the cognitive profile itself-if the child’s achievement is consistent with overall ability, an SLD may not be the best fit. Decision rules should be set before the meeting: at least one achievement area substantially below expectation, a linked processing deficit, inadequate response to intervention, and exclusion of other factors. I would document each rule and the evidence for or against it.

3. Draft a defensible eligibility recommendation and explain how you would present it to the team.

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My recommendation would be to find Devon eligible as a student with a specific learning disability in reading and mathematics, while explicitly ruling out intellectual disability, provided that the team confirms adequate intervention and exclusionary factors. I would present the reasoning in a sequence. First, Devon does not meet ID criteria: the FSIQ and GAI are in the low-average range, and adaptive behavior is not clearly deficient across settings. Second, the achievement scores in reading, math, and written language are low and consistent with the referral concerns. Third, the processing weaknesses in working memory and processing speed are theoretically relevant to reading and math learning. Fourth, the CBM slope indicates inadequate response, but the team must acknowledge the fidelity problem and agree that the intervention was not adequately delivered. I would not rely on a rigid ability–achievement discrepancy because the discrepancy is not severe. I would use the PSW pattern cautiously and explain its limits. I would also state that the category does not determine services; the IEP should address explicit reading and math instruction, attention and executive-function supports, and progress monitoring. If the team concludes that the intervention was too poorly delivered to judge response, I would recommend a period of high-fidelity intervention with progress monitoring before finalizing eligibility, not a hasty classification.