Predicting Aptitude in Introductory Computing: A Classification Model

Abstract

The prediction of success in education has a long tradition. However, such studies in introductory courses in computers have just recently begun. This paper develops a model that classifies students as having high and low aptitude for introductory computing. The model was developed by applying logistic classification analysis. This analysis technique leads to the development of a decision rule that can be used to classify students and the identification of variables relevant to the classification model.