Finding behavioral indicators from contextualized commits in software engineering courses with process mining - Smart Modeling for software Research and Technology
Conference Papers Year : 2023

Finding behavioral indicators from contextualized commits in software engineering courses with process mining

Abstract

Git4School is a dashboard helping teachers to monitor and make decisions during Git-based lab sessions in higher education computer science programs. This tool makes it possible to visualize the commits made by students over time according to the context and, in particular, the type of pedagogical intervention by the teacher (discussions between students on the problem, dissemination of a solution, etc.). Despite its visualizations providing indicators for decision-making, the tool does not provide information about the student's behavior. There are existing studies dealing with Process Mining (PM) in education, specifically in computer science courses and using Git. Through an empirical exploratory study, we explore the possibility of taking advantage of these contextualized commits using PM. We analyzed data from 5 teaching units covering different higher education levels using the bupaR library. Firstly, we discovered promising indicators to predict students' behavior during a lab session. Secondly, we identified several possibilities for future research on PM and contextualized commits. Finally, we have established a set of recommendations to help analyze contextualized commits using PM.
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Dates and versions

hal-04332205 , version 1 (08-12-2023)

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Mika Pons, Jean-Michel Bruel, Jean-Baptiste Raclet, Franck Silvestre. Finding behavioral indicators from contextualized commits in software engineering courses with process mining. 2nd International Workshop on Frontiers in Software Engineering Education (FISEE 2023), Jan 2023, Villebrumier, France. pp.56-68, ⟨10.1007/978-3-031-48639-5_5⟩. ⟨hal-04332205⟩
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