Relation Between Student Characteristics, Git Usage and Success in Programming Courses.

Students’ prior knowledge and self-regulated learning are important predictors of academic success. A growing body of literature studies these predictors with respect to introductory programming courses. Especially in the first semester, cohorts exhibit a wide range of backgrounds with many students having no previous programming experience at all. Furthermore, many first semester students lack self-regulated learning capabilities. In the light of high drop-out rates in introductory programming courses, it is crucial to consider student characteristics, such as previously acquired programming skills or self-regulated learning capabilities. In this work, we collected data on such student characteristics via surveys and investigated the relation between survey data and students’ use of a version control system during a first semester programming course at a European university. We also related the survey data to the number of test cases students pass in their assignments. Using random forests, we investigated, how version control data can be used to predict student performance in an assignment and to what extent additional survey data can improve such predictions. Our results show that especially in an early phase of an assignment, data on prior knowledge and self-regulated learning can help predict student success.