Combining Local Testing with Automatic Commits: Benefits for Progress Tracking and CS2 Students' Learning Experience

Aleksandar Karakać, Denis Helic

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Many instructors in introductory programming courses experience high dropout and failure rates. Identifying struggling students early is a prerequisite to target this problem. To this end, instructors and learning analytics researchers may leverage version control by analyzing the students' commit histories. This approach relies on frequent pushes to the version control platform, which many instructors incentivize by offering test results each time a student pushes a commit. However, instructors who provide test cases that can be run locally (i.e., without creating a commit) may face coarse-grained commit histories. In this study, we analyze a CS2 course which offers both local and remote testing. Students were provided with tools that automatically create and push a commit on each local test run. We investigate to what extent these automatically created snapshots contribute to obtaining fine-grained commit histories and early initial push events. Our analysis uncovers distinct commit patterns among high- and low-performing students. Furthermore, we find that despite the commit automation and encouraging students to start early, many students pushed their first commit late. We triangulate this observation with survey results which confirm the late start of many students. The survey also identified reasons for students to opt out of automatic commit creation. Moreover, many students expressed a positive attitude towards testing their programs locally. Thus, our survey results underline that instructors should strive for providing students with comprehensive feedback that students can conveniently obtain.

Original languageEnglish
Title of host publicationITiCSE 2024 - Proceedings of the 2024 Conference Innovation and Technology in Computer Science Education
PublisherAssociation of Computing Machinery
Pages108-114
Number of pages7
ISBN (Electronic)9798400706004
DOIs
Publication statusPublished - 3 Jul 2024
Event29th Conference Innovation and Technology in Computer Science Education: ITiCSE 2024 - Milan, Italy
Duration: 8 Jul 202410 Jul 2024

Publication series

NameAnnual Conference on Innovation and Technology in Computer Science Education, ITiCSE
Volume1
ISSN (Print)1942-647X

Conference

Conference29th Conference Innovation and Technology in Computer Science Education
Country/TerritoryItaly
CityMilan
Period8/07/2410/07/24

Keywords

  • computer science education
  • cs2
  • educational data mining
  • git
  • learning analytics
  • version control

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Education

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