A Software Engineering Capstone Course Facilitated By GitHub Templates

• URL: http://arxiv.org/abs/2410.12114v1
• Date: Tue, 15 Oct 2024 23:27:54 GMT
• Title: A Software Engineering Capstone Course Facilitated By GitHub Templates
• Authors: Spencer Smith, Christopher William Schankula, Lucas Dutton, Christopher Kumar Anand,
• Abstract summary: We propose using a GitHub template that contains all the initial infrastructure a team needs, including the folder structure, text-based template documents and template issues. In 2022/23 we observed 24% of commits happening on the due dates. After partially introducing the above ideas in 2023/24, this number improved to 18%. We propose an experiment where commit data and interview data is compared between teams that use the proposed interventions and those that do not.
• Score: 0.9786690381850356
• License:
• Abstract: How can instructors facilitate spreading out the work in a software engineering or computer science capstone course across time and among team members? Currently teams often compromise the quality of their learning experience by frantically working before each deliverable. Some team members further compromise their own learning, and that of their colleagues, by not contributing their fair share to the team effort. To mitigate these problems, we propose using a GitHub template that contains all the initial infrastructure a team needs, including the folder structure, text-based template documents and template issues. In addition, we propose each team begins the year by identifying specific quantifiable individual productivity metrics for monitoring, such as the count of meetings attended, issues closed and number of commits. Initial data suggests that these steps may have an impact. In 2022/23 we observed 24% of commits happening on the due dates. After partially introducing the above ideas in 2023/24, this number improved to 18%. To measure the fairness we introduce a fairness measure based on the disparity between number of commits between all pairs of teammates. Going forward we propose an experiment where commit data and interview data is compared between teams that use the proposed interventions and those that do not.

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