Learners' Cognitive Styles and Psychological Types as Intervening Variables Influencing Performance in Computer Science Courses

During the past twenty years, many educators have tried to incorporate technological progress and processes into the nation's schools. As the demand for computer science courses continues its phenomenal growth into the 1980s, the problems of identifying components of computer science aptitude and predicting academic success in computer science courses become increasingly important. This article is based on the critical analysis of the most recent research studies concerning the identification of components of computer science aptitude responsible for success in computer science courses. The analysis attempts to answer three questions: 1. Do certain cognitive styles have a bearing on performance in computer science courses?; 2. Do certain psychological types have bearing on performance in computer science courses?, and 3. Do certain background variables (sex, age, academic classification, prior computer experience, academic program, and high school and college grade point averages) have relevance for performance in computer science courses? Finally, implications for matching curriculum and instructional strategies with students' different cognitive styles, personality types, and background information are presented and suggestions for advisement and placement of prospective computer science students, and recommendations for further research in this area are made.