Title
Open-Source Software in the Classroom: Empowering Students to Self-Select Projects to Contribute
Abstract
Contribution: Instructors are leveraging open-source software (OSS) as a way to experience authentic examples of software problems with their students. Recommender engines might assist students in selecting the right project based on metrics mined from project repositories (e.g., GitHub). This vision is realized through GitMate, a GitHub-based recommender for supporting students in their OSS selection. Background: Contributing to OSS is a valuable way to immerse students into the realities of software development. When it comes to OSS selection, self-selection seems to be the most engaging alternative. Yet, students lack the time (and skills) to analyze project facets and draw comparisons among OSS projects. Research Questions: How can students be assisted to select a good OSS project to contribute to? Specifically, how would a recommender system might help? The envisioned intervention should be useful not only in finding the right project but also challenging students’ initial selections with other alternatives, spurring reflection. Methodology: The aim is to act upon a dependent variable (mind changing in project selection) through an independent variable (project comparison). This is achieved through GitMate, a recommender system on top of GitHub. Its search facilities are used for students to locate three projects at their wish. Next, GitMate recommends similar projects based on the project facets (e.g., number of committers, commits, and stars), mined from GitHub. Pondering the importance of distinct facets, students can now tradeoff different projects. The experiment checks whether students change their first choice. Findings: The results indicate that GitMate helps students compare GitHub projects to the extent of making them change their first choice. Nearly, 80% of the students changed at least one project as a result of using GitMate. This seems to suggest GitMate being effective on its goal: facet-based comparison thinking during OSS selection.
Year
DOI
Venue
2022
10.1109/TE.2022.3147318
IEEE Transactions on Education
Keywords
DocType
Volume
Browser extensions,open-source projects,recommenders,software engineering (SE)
Journal
65
Issue
ISSN
Citations 
4
0018-9359
0
PageRank 
References 
Authors
0.34
18
2
Name
Order
Citations
PageRank
Juanan Pereira100.34
Oscar Díaz241562.28