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ERIC Number: ED176808
Record Type: RIE
Publication Date: 1979-Aug
Reference Count: 0
Predicting Student Performance in a Computer-Managed Course Using Measures of Cognitive Styles, Abilities and Aptitudes.
Federico, Pat-Anthony; Landis, David B.
Measures of cognitive styles, abilities, and aptitudes from a sample of 166 Basic Electricity and Electronics School graduates were analyzed to determine if they were predictive of student achievement and times to complete instructional modules. Objectives of the research were to (1) identify measures of cognitive characteristics that may be predictive of student achievement in the first of 11 modules of the BE/E School; (2) determine whether the predictor pattern changes across the rudimentary modules of BE/E school; and (3) propose procedures for adapting instruction to student cognitive characteristics so as to improve student achievement and reduce the time to complete the basic modules. Graduates were measured on 24 cognitive characteristics. Using these data as predictors and module test scores and times to complete the modules as criteria, 22 stepwise regression analyses and two canonical analyses were computed. Results indicated that in seven of the eleven modules, measures of cognitive styles and/or abilities contributed more to the prediction of student achievement than did measures of cognitive aptitudes. In all 11 modules, measures of cognitive styles and/or abilities accounted for more of the variance in times to complete the modules than did measures of cognitive aptitudes, and shifts in predictor patterns were related to whether students were required to remember or use facts, concepts, principles, and/or rules. (Author/RAO)
Publication Type: Reports - Research
Education Level: N/A
Authoring Institution: Navy Personnel Research and Development Center, San Diego, CA.
Note: For related documents, see ED 160 872, ED 165 792, IR 007 583, IR 007 590, and IR 007 622 ; Parts may not reproduce clearly