Understanding student retention in computer science education: The role of environment, gains, barriers and usefulness

Abstract

Researchers have been working to understand the high dropout rates in computer science (CS) education. Despite the great demand for CS professionals, little is known about what influences individuals to complete their CS studies. We identify gains of studying CS, the (learning) environment, degree’s usefulness, and barriers as important predictors of students’ intention to complete their studies in CS (retention). The framework aims to identify reasons that may contribute to dropout, using responses from 344 CS students. The eight-predictor model accounts for 39 % of the explained variance in student retention. A high level for degree’s usefulness has a positive effect on retention. Further, cognitive gains and supportive environment positively impact degree’s usefulness, while non-cognitive gains hinder it. Lastly, negative feelings (personal values) are found to reduce student retention. The overall outcomes are expected to contribute to theoretical development, in order to allow educators and policy makers to take appropriate measures to enhance students’ experience in CS studies and increase retention.