In spite of the long-standing tradition of including measures of visual-motor integration in psychological evaluations, visual-motor abilities have not been included in the Cattell-Horn-Carroll (CHC) theory of cognitive abilities or its complementary cross-battery approach to assessment. The purpose of this research was to identify the shared constructs of a popular test of visual-motor integration and a test of intellectual functioning, and to investigate how a test of visual-motor integration would be classified within the CHC model. A large normative sample of 3,015 participants that ranged in age from 5 to 97 years completed the Bender Visual-Motor Gestalt Test, Second Edition (Bender-Gestalt II; Brannigan & Decker, 2003) and the Stanford-Binet Intelligence Scale, Fifth Edition (SB5; Roid, 2003). Correlational analyses indicated positive moderate correlations across all age ranges between the Bender-Gestalt II Copy measure and the SB5 Nonverbal Visual-Spatial Processing subscale and between the Bender-Gestalt II Recall measure and the SB5 Nonverbal Visual-Spatial Processing and Nonverbal Working Memory subscales. Exploratory factor analyses revealed a three-factor model for four age groupings and four-factor model for one age grouping, suggesting factors which represent crystallized ability, fluid reasoning, and visual-motor ability. The results of this study suggest that the Bender-Gestalt II measures abilities that are not included in the SB5. Therefore, the Bender-Gestalt II would complement an intelligence test such as the SB5 in order to form a CHC Visual Processing (Gv) broad ability factor. These findings also address the need for further research to validate the constructs measured by newer versions of widely-used tests of cognitive ability.

This study had three main purposes. First, the relationship between Processing Speed (Gs) and poor word recognition skills was examined. Second, various formats of processing speed tests that measure different types of processing speed (i.e. naming facility, perceptual speed, semantic speed, attention and concentration) were administered to determine what aspects of Gs were more strongly correlated with word reading performance. Pearson correlations and coefficients of determination were used to evaluate the strength of the relationships and the shared variance. Third, the study sample was evaluated to determine what percentage of the poor readers participating in the study had slow processing speed.Forty-four students in grades 1-3, ages six- to ten-years old were administered the Woodcock-Johnson III Achievement reading tests of Letter-Word Identification, Reading Fluency, and Word Attack. The subjects were additionally administered the Woodcock-Johnson III Cognitive Abilities tests of Verbal Comprehension, Visual-Auditory Learning, Sound Blending, Visual Matching, Numbers Reversed, Decision Speed, Rapid Picture Naming, Pair Cancellation, and Cross Out.The results of the study indicated processing speed, as measured by the Gs Cluster score, was strongly correlated with word reading, r = .749, r2=.56. The Gs tests of Visual Matching, (r = .663, r2 = .44) and Decision Speed (r = .811, r2 = .66) were most strongly correlated with poor word reading skill. The Basic Reading Skills Cluster and the Test of Letter-Word Identification were both moderately correlated at various strengths with different formats of Gs tests. Tests of Visual Matching, Rapid Picture Naming, Pair Cancellation and Cross Out all had a moderate, significant correlation.Lastly, 47% of the poor readers (SS<85 on any of the measures of>reading) also had low Gs scores (SS<85).The results from the study demonstrate the need for further exploration of the impact of poor Gs on the development of reading skills, as well as determination of the most effective interventions for poor readers with slow processing speed.

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abstract: This study investigated the link between the cognitive clusters from the Woodcock&ndash;Johnson III Tests of Cognitive Ability (WJ III COG) and Broad Math, Math Calculation Skills, and Math Reasoning clusters of the Woodcock&ndash;Johnson III Tests of Achievement (WJ III ACH) using data collected over seven years by a large elementary school district in the Southwest. The students in this study were all diagnosed with math learning disabilities. Multiple regression analyses were used to predict performance on the Broad Math, Math Calculation Skills, and Math Reasoning clusters from the WJ III ACH. Fluid Reasoning (Gf), Comprehension&ndash;Knowledge (Gc), Short&ndash;Term Memory (Gsm), and Long&ndash;term Retrieval (Glr) demonstrated strong relations with Broad Math and moderate relations with Math Calculation Skills. Auditory Processing (Ga) and Processing Speed (Gs) demonstrated moderate relations with Broad Math and Math Calculation Skills. Visual&ndash;Spatial Thinking (Gv) and Processing Speed (Gs) demonstrated moderate to strong relations with the mathematics clusters. The results indicate that the specific cognitive abilities of students with math learning disabilities may differ from their peers. / Dissertation/Thesis / M.A. Educational Psychology 2011

The Cattell-Horn-Carroll Theory of cognitive functioning is a well-validated framework for intelligence. Cross-battery assessment is a means utilizing CHC theory in practice. School psychologists write recommendations with the assumption that teachers understand the cognitive abilities underlying basic academic tasks in the same way. Theoretically, the more similar the understanding of these two groups, the greater the likelihood of appropriate referrals and intervention fidelity. Teacher perceptions of their students' cognitive abilities impact the referrals that they make and intervention strategies that they implement. In this study, teachers and school psychologists were asked to sort basic academic tasks into the CHC broad abilities. The central research questions being asked are as follows: Are school psychologists and teachers equally proficient at identifying the broad cognitive ability demands of a basic academic task? How do the responses of the participants compare to the theoretical model presented? Do teachers and school psychologists become better at identifying the cognitive demands of a task with experience or higher levels of training? In order to answer the first research question, MANOVAs were performed. There was a significant overall difference between groups on their responses. While teachers and school psychologists differed significantly on five of the eight CHC broad ability scales. School psychologists were only significantly better at consistently identifying the basic academic tasks that utilized Fluid Reasoning. To answer the second research question, principal components factor analysis was performed. The factors created displayed limited similarity to the theoretical factors. Pearson correlations between the theoretical factors and the factors created through factor analysis revealed multiple positive correlations that accounted for more than 10% of the variance. The theoretical scales that were more significantly correlated were Fluid Reasoning, Auditory Processing, and Processing Speed. To answer the third research question, Pearson correlations were calculated. This analysis revealed that neither group develops a better understanding of the cognitive abilities required to perform academic tasks with experience. Level of education is not related to accuracy for teachers on any of the items. Level of education is significantly correlated with accuracy in identifying tasks that require Visual Processing for school psychologists. / School Psychology

<p>A Test Battery (TB) is a measurement method that is designed to assess a variety of ability constructs. The extent to which TB predicts future pilot performance has important implications for both flying organizations and applicants. The primary emphasis in the existing literature has been on scores of individual ability tests, in contrast to the scores of multiple ability tests that are typically indexed by composites derived from TBs. The selection literature lacks a focus on composite scores, and seldom links to the broad cognitive abilities that predominate TBs. The objective of this study was to investigate how the different broad ability constructs of TBs influence their predictive validities for pilot performance. Six ability groups were identified as the most common ability saturations of pilot selection TBs. On the basis of 89 studies and 118 independent samples, a series of meta-analyses were conducted to determine the criterion-related validity of the six categories of TBs for several criterions of pilot performance.</p> <p>The investigation revealed there was an overall small and positive relationship between TBs and flight performance. The six categories of cognitive ability TBs appeared to be valid predictors of pilot performance, and at least five of them generalize validity across studies and settings. More specifically, three sets of predictor groups were identified according to the magnitude of validity estimates. The highest validity group included <i>Work Sample</i> TBs (<i>r</i>=.34), the second highest validity group included TBs of <i>Acquired Knowledge</i>, <i>General Ability</i>, and <i>Motor Abilities</i> (<i>r</i>=.19, .18, and .17, respectively), and the lowest validity group included TBs of <i>Perceptual Processing</i> and <i>Controlled Attention</i> (<i>r</i>=.14 and .10, respectively).</p> <p>The results also indicated that there was substantial variability in the effect of cognitive abilities on flight performance, with evidence of moderators operating in most cases. Five potential moderator variables were examined that may moderate the TBs-performance relationship in flying. The analysis for the moderator variable of <i>the number of tests in the battery </i>(small battery/large battery), <i>regularity of TB use in pilot selection</i> (commonly used/uncommonly used), and <i>criterion level of measurement</i> (continuous/ordinal/dichotomous/ contingency table) revealed significant moderating effects on the correlations between flight performance and several types of test batteries. Other moderators related to <i>year of publication</i> (1987-1999/2000-2009/2010-2017) and <i>flying organization</i> (USAF/US Navy/Another military/Civilian) did not significantly influence the correlations between TBs and flight performance. The implications of the findings for practice are discussed, and recommendations for future research directions are provided.</p>