Formal Operations and Learning Style Predict Success in Statistics and Computer Science Courses

Abstract

Measures of formal operations and learning style predicted success in introductory statistics and computer science courses. Using a final course grade cutoff of 80% or better as a criterion of success in the course, a discriminant analysis correctly classified 81% of the statistics students and 72% of the computer science students. Success was related to the presence of the ability to act as a formal operator and to the absence of a reliance on the concrete experiences learning style. These findings highlight the need to examine both cognitive maturity and learning style in studies of academic success at the college level.

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