Code-quality evaluation scheme for assessment of student contributions to programming projects

Project-based learning is the most common approach to software engineering education, due to its emphasis on the teamwork skills essential to real-world collaborations. This study developed an automated programming assessment system (APAS) featuring a code-quality evaluation scheme to overcome diffi...

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Veröffentlicht in:The Journal of systems and software Jg. 188; S. 111273
Hauptverfasser: Chen, Hsi-Min, Nguyen, Bao-An, Dow, Chyi-Ren
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 01.06.2022
Schlagworte:
Automated programming assessment system
Cooperative/collaborative learning
Programming education
Project-based learning
Quality
Cooperative/collaborative learning
Programming education
Automated programming assessment system
Quality
Project-based learning
ISSN:0164-1212, 1873-1228
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Zusammenfassung:Project-based learning is the most common approach to software engineering education, due to its emphasis on the teamwork skills essential to real-world collaborations. This study developed an automated programming assessment system (APAS) featuring a code-quality evaluation scheme to overcome difficulties in assessing the contribution of individual team members. Team participation is visualized on a weekly basis to provide insights pertaining to team dynamics, and metrics based on code quality allow the segmentation of students by level of contribution. Insights provided by the proposed system were also shown to facilitate interventions aimed at improving code quality. Empirical analysis based on submission data from 146 students (41 teams) demonstrated the feasibility of the proposed system in monitoring group-based learning projects at the university level, particularly in detecting free-riders. •A code-quality aware automated programming assessment system to monitor team programming projects.•A code-quality based evaluation scheme for assessment of student contributions in team programming projects.•A learning analytics workflow to explore teams’ collaboration in programming projects.•Code-quality improvement metrics to evaluate individual contributions in programming projects.•Free-rider detection using code-quality improvement metrics.
ISSN:0164-1212
1873-1228
DOI:10.1016/j.jss.2022.111273