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A Longitudinal Study on Student Persistence in Programming Self-assessments

Self-assessment is an educational practice that helps students evaluate their own learning by distributed practices. This evaluation potentially has an effect on student’s selfefficacy and therefore can influence their choice of activities and the likelihood of their success. The variation in the selfassessing behavior of students over the course of learning is often less explored. For instance, a student’s short-term behavior may not necessarily infer how they will behave in the long-term. It is unclear how such development in their selfassessing behavior is related to academic performance and the corresponding self-assessment strategies. This longitudinal study aims to fill the gap by examining a self-assessment platform used in an introductory programming class from three different semesters. We analyzed the activity logs and modeled students’ short-term and long-term study persistence on the platform using a probabilistic mixture model. The results suggest that short-term persistence was not related to short-term performance. However, the performance in the final exam was associated with earlier persistence patterns. A further analysis showed that low-performing students who maintained the self-assessment pattern improved in exams. Nevertheless, this longitudinal study contributes empirical evidence to the understanding of the development of self-assessment behavior in relation to academic performance.