Abstract categorization ability as a predictor of learning disability classification |
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| Authors: | Marcia S Scott Daryl B Greenfield Esther Sterental |
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| Institution: | 1. Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany;2. Department of Radiology, University of Miami School of Medicine, Miami, FL, USA;3. Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada;4. Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany;1. School of Automation, Northwestern Polytechnical University, Xi’an, Shanxi 710072, PR China;2. School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore;3. Department of Computer Science and Engineering, Arizona State University, Tempe, Arizona 85281, United States |
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| Abstract: | Based on a theoretical analysis of the type of cognitive processing that should be sensitive to population differences, this study evaluated the diagnostic validity of a task measuring abstract categorization ability in six-, seven-, and eight-year-old learning disabled (LD) and non-LD peers. This research is part of a project, the major goal of which is the development of a cognitive-based preschool screening test for the early detection of children who may subsequently fail in school. Diagnostic validity is being evaluated within the context of the research strategy we have adopted. Data are presented that demonstrate that the component of abstract category knowledge that best discriminates LD children from non-LD peers, is knowledge of how members of abstract categories differ from each other. This is consistent with a priori predictions from theory. |
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