Correlating Students' Class Performance Based on GitHub Metrics: A Statistical Study

Abstract

What skills does a student need to succeed in a programming class? Ostensibly, previous programming experience may affect a student's performance. Most past studies on this topic use self-reporting questionnaires to query students about their programming experience. This paper presents a novel, unified, and replicable way to measure previous programming experience using students' pre-class GitHub contributions. To our knowledge, we are the first to use GitHub contributions in this way. We conducted a comprehensive statistical study of students in an object-oriented design and development class from 2017 to 2022 (n = 751) to explore the relationships between GitHub contributions (commits, comments, pull requests, etc.) and students' performance on exams, projects, designs, etc. in the class. Several kinds of contributions were shown to have statistically significant correlations with performance in the class. A set of two-samplet -tests demonstrate statistical significance of the difference between the means of some contributions from the high-performing and low-performing groups.