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The transition process from school to work is often challenging for young people, especially those with disabilities. In order to gather a meaningful transition, a cross battery assessment and a functional vocational evaluation are needed. In this case review study, a young adult aged 20 years 8 months, JC, had his autistic condition reviewed. Assessment was done so as to know the current status of JC’s abilities and skills and his state of readiness for vocational employment. With the results, JC could then use them to look for vocational training centers so as to develop more skills in the area of his vocational interest.

OBJECTIVE No previous empirical study has investigated whether the LD identification decisions of proposed methods to operationalize processing strengths and weaknesses (PSW) approaches for LD identification are associated with differential treatment response. We investigated whether the identification decisions of the concordance/discordance model (C/DM; Hale & Fiorello, 2004) and Cross Battery Assessment approach (XBA method; Flanagan, Ortiz, & Alfonso, 2007) were consistent and whether they predicted intervention response beyond that accounted for by pretest performance on measures of reading. METHOD Psychoeducational assessments were administered at pretest to 203 4th graders with low reading comprehension and individual results were utilized to identify students who met LD criteria according to the C/DM and XBA methods and students who did not. Resulting group status permitted an investigation of agreement for identification methods and whether group status at pretest (LD or not LD) was associated with differential treatment response to an intensive reading intervention. RESULTS The LD identification decisions of the XBA and C/DM demonstrated poor agreement with one another (κ = -.10). Comparisons of posttest performance for students who met LD criteria and those who did not meet were largely null, with small effect sizes across all measures. CONCLUSIONS LD status, as identified through the C/DM and XBA approaches, was not associated with differential treatment response and did not contribute educationally meaningful information about how students would respond to intensive reading intervention. These results do not support the value of cognitive assessment utilized in this way as part of the LD identification process.

The Cross-Battery Assessment (XBA) approach to identifying a specific learning disorder (SLD) is based on the postulate that deficits in cognitive abilities in the presence of otherwise average general intelligence are causally related to academic achievement weaknesses. To examine this postulate, we conducted a classification agreement analysis using the Woodcock-Johnson III Tests of Cognitive Abilities and Achievement. We examined the broad cognitive abilities of the Cattell-Horn-Carroll theory held to be meaningfully related to basic reading, reading comprehension, mathematics calculation, and mathematics reasoning across age groups. Results of analyses of 300 participants in three age groups (6–8, 9–13, and 14–19 years) indicated that the XBA method is very reliable and accurate in detecting true negatives. Mean specificity and negative predictive value were 92% and 89% across all broad cognitive abilities and academic domains. Mean sensitivity and positive predictive values, however, were generally q...

Processing Strengths and Weaknesses (PSW) models have been proposed as a method for identifying specific learning disabilities. Three PSW models were examined for their ability to predict expert identified specific learning disabilities cases. The Dual Discrepancy/Consistency Model (DD/C; Flanagan, Ortiz, & Alfonso, 2013) as operationalized by the Cross Battery Assessment Software (X-BASS; Ortiz, Flanagan & Alfonso, 2015), the Concordance-Discordance Model (C-DM; Hale & Fiorello, 2004), and the Psychological Processing Analyzer software (PPA v3.1; Dehn, 2015b) were evaluated. The DD/C approach as represented with the X-BASS system had a 100% agreement with the expert panel in the identification of specific learning disabilities and non-specific learning disabilities cases. The C-DM model was more conservative, identifying only 45% of the specific learning disabilities cases. The PPA software was too limited to be used in the study and is not recommended for use in identifying specific learning disabilities via a PSW approach. Although more research is needed, the results of this study would suggest that the DD/C and X-BASS provide the greatest utility for a PSW approach to identifying specific learning disabilities.

The Individuals with Disabilities Education Act allows three methods of determining whether a student qualifies for special education as a student with a specific learning disability (SLD). The first and most controversial is the Discrepancy model, which requires a significant discrepancy between the student’s intellectual ability and academic achievement. The second is the Response to Intervention (RTI) model, which utilizes a process to assess a student’s response to scientific, researched-based interventions. The third method involves reviewing the student’s unique pattern of cognitive strengths and weaknesses (PSW) that result in academic deficits. The present article reviews the research regarding the strengths and weaknesses of each model. Furthermore, due to the recent emergence of PSW models, this article concludes with the authors’ recommendations for further research prior to implementation of the PSW approach.

The Cattell-Horn-Carroll (CHC) cross-battery approach to assessing cognitive abilities has been introduced to the field recently as an alternative to traditional assessment instruments and techniques (Flanagan, McGrew, & Ortiz, 2000; McGrew & Flanagan, 1998). This theory-based method of assessment was developed to provide a more valid and defensible way of deriving meaning from test scores than that provided by the traditional (and largely atheoretical) Wechsler Scale approach. The present study is the first to investigate the validity of the cross-battery approach using a sample of elementary school children (N= 166) who were administered the Wechsler Intelligence Scale for Children-Revised (WISC-R; Wechsler, 1974) and Woodcock-Johnson Psycho-Educational Battery-Revised (WJ-R; Woodcock & Johnson, 1989). Structural Equation Modeling was used to examine whether (a) Wechsler-based CHC cross-battery assessment explained more variance in reading achievement than a traditional Wechsler model, and (b) whether the Wechsler-based CHC cross-battery model provided a more accurate description of the general and specific abilities on general and specific reading achievement than the traditional Wechsler model, as predicted in the extant ^/specific abilities literature. Findings showed that the g factor underlying the Wechsler-based CHC cross-battery model accounted for substantially more variance in reading achievement (25%) than the g factor underlying the atheoretical Verbal Comprehension-Perceptual Organization-Freedom From Distractibility (VC-PO-FFD) Wechsler model. In addition, findings demonstrated that when assessments are organized around the strong CHC theoretical model, specific cognitive abilities, including auditory processing (Ga), crystallized intelligence (Gc), and processing speed (Gs) explained a significant portion of variance in reading achievement beyond that accounted for by g. These

The Cattell-Horn-Carroll (CHC) Cross-Battery approach, originally known as the Gf-Gc Cross-Battery model of assessment, has been defined as “a time efficient method of intellectual assessment that allows practitioners to measure validly a wider range (or a more in-depth but selective range) of cognitive abilities than that represented by any one intelligence battery in a way consistent with contemporary psychometric theory and research on the structure of intelligence” (McGrew & Flanagan, 1998, p. 357). The CHC Cross-Battery approach provides at least two unique advantages: (a) data gathered both within and across test batteries can be interpreted theoretically and empirically within meaningful patterns; and (b) cognitive test data lead to examination of empirically validated links between specific cognitive abilities and specific academic areas (Flanagan & Ortiz, 2001). The approach provides practitioners with a classification system of cognitive abilities; existing cognitive tests can be evaluated according to the model, that is, subcomponents/subtests can be described based on their ability to assess cognitive abilities within the CHC model.