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P2 Can Pre-class GitHub Contributions Predict Success by Student Teams?

课前 GitHub 贡献能预测学生团队的成功吗?
ICSE 2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)2022匹配度 1/10 · 该论文研究学生课前 GitHub 贡献与团队项目表现之间的关联,属于软件工程教育/数据挖掘方向,与用户关注的静态分析、LLM/Agent 改进程序分析、浮点程序分析及贝叶斯程序分析均无直接关系。引用 0 inbox
Jialin Cui, Ruochi Li, Kaida Lou, Chengyuan Liu, Yunkai Xiao, Qinjin Jia, Edward Gehringer, Runqiu Zhang
crossref: 2026-09-12crossref: 2026-09-12

AI 速览

一句话:首个研究学生课前 GitHub 贡献与团队项目表现的关系,识别公共提交、仓库数及特定语言仓库规模等关联因素。

GitHub 被全球大量师生用于教学和团队协作,团队项目也是软件工程课程的重要环节。本文首次考察学生课前在 GitHub 上的贡献,试图刻画在团队项目中表现优异与表现欠佳的学生团队。研究分析学生的公开提交数、仓库数量以及特定语言仓库的规模等指标,识别这些课前活动与团队项目质量之间的关联。作者进一步从教育者和学生两个角度讨论这些发现的启示。该工作表明,课前 GitHub 贡献可为理解团队项目表现提供有用信号,但仍需谨慎解读其预测能力与因果性。

问题
研究学生课前 GitHub 贡献能否用于预测或区分在团队项目中表现好与不好的学生团队,并找出相关活动指标。
方法
分析学生课前 GitHub 数据中的公开提交数、仓库数量和特定语言仓库大小等指标,比较其与团队项目质量的关系。
评估
基于学生团队项目数据,识别与项目质量相关的课前贡献因素,并从教育者和学生视角讨论其实践启示。
原文摘要(Abstract)

Over one million teachers, students, and schools around the world use GitHub to reach their learning goals. GitHub promotes team-work, and group or team projects are a necessary element of the software-engineering curriculum. Past studies on GitHub have explored how to integrate GitHub into teaching and how to mine information from GitHub to help students. To our knowledge, we are the first to study the previous contributions of students to GitHub in order to characterize student teams that perform well on team projects, compared to student teams that did not perform so well. We identify factors such as the number of public commits, number of repositories, and size of repositories in certain languages that are associated with the quality of team projects. We discuss the implications of this from the point of view of an educator and a student.

链接与引用

DOI 原文 ·

BibTeX
@inproceedings{paperbot10972,
  title = {Can Pre-class GitHub Contributions Predict Success by Student Teams?},
  author = {Jialin Cui and Ruochi Li and Kaida Lou and Chengyuan Liu and Yunkai Xiao and Qinjin Jia and Edward Gehringer and Runqiu Zhang},
  booktitle = {ICSE},
  year = {2022},
  doi = {10.1109/icse-seet55299.2022.9794264}
}