Predictors of Persistence and Success in an Engineering Program

Abstract

This study identifies student variables that predict persistence and success in an undergraduate engineering program. Three logistic models were developed that predicted the probability of persisting successfully. Significant predictors included both cognitive and noncognitive variables; students who did well in science and mathematics courses and who were genuinely interested in engineering were more likely to persist and succeed. Predictor variables were not constant over time but changed as students progressed through the first two years of study, with performance in prerequisite science and mathematics courses emerging as the best predictors. The authors briefly discuss academic advising implications.