Measuring Self-regulated Learning Processes in Computer Science Education

Abstract

Self-regulated learning (SRL) is important for computer science education. Yet, students often do not have SRL skills to benefit their learning. In this study, we examined 187 (n=187) students’ SRL behaviors while they built programs with an automated feedback tool. Anchored in Winne and Hadwin’s (1998) COPES model of SRL, our results showed that novices used more operators to debug compiler errors, while more experienced programmers used more operators to debug non-compiler errors. Finally, a random forest classifier showed that prior knowledge was the most important COPES feature predicting learning gain, followed closely by the student’s perceived programming ability, use of evaluations with the automated feedback tool, and operators used to debug non-compiler errors on failed programs.