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Attributional style as a predictor of success in a first computer science course
Authors:John W HenryMark J MartinkoMargaret Anne Pierce
Affiliation:1. COVID-19 Emergency Response, Centers for Disease Control and Prevention, United States;2. Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States;3. United States Public Health Service, United States;4. Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States;5. Abt Associates, Division of Health and Environment, Atlanta, GA, United States;6. General Dynamics Information Technology, Atlanta, GA, United States;7. IHRC, Incorporated, Atlanta, GA, United States;8. Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States;1. School of Educational and Social Sciences, Department of Educational Sciences, Carl von Ossietzky Universität Oldenburg, Germany;2. Department of Psychology, Christian-Albrechts-Universität Kiel, Olshausenstraße 75, 24118 Kiel, Germany
Abstract:The purpose of this study was to examine the relationships between attributions and performance in a computer science course. It was found that students with an optimistic attributional style performed better in a computer programming course than those students with a pessimistic attributional style. A second purpose was to examine the specific causal attributions stated by the students and to determine their relationship to course performance. It was found that course performance was related to specific causal attributions regarding ability.
Keywords:
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