Decoding Peer Assessment: An Algorithm to Navigate Group Problems Detection
Publication date
2025-07-20
Editors
Cristea, Alexandra I.
Walker, Erin
Lu, Yu
Santos, Olga C.
Isotani, Seiji
Advisors
Supervisors
Document Type
Part of book
Metadata
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License
taverne
Abstract
Universities often use group work to develop teamwork skills, but it may cause stress due to group issues. Peer assessments can provide an overview of groups’ performances and well-being, but effective interpretation is challenging and the burden is left to the teachers. This study addresses these challenges through a focus groups and a field study. It proposes a rule-based algorithm to automatically interpret peer assessments, identifies key contextual variables, and evaluates the algorithm’s effectiveness and usability in a real classroom setting.
Keywords
collaborative learning, group issues, human-centred design, peer assessment, teaching support, Taverne, Theoretical Computer Science, General Computer Science
Citation
Olthof, A, Saccardi, I & Masthoff, J 2025, Decoding Peer Assessment : An Algorithm to Navigate Group Problems Detection. in A I Cristea, E Walker, Y Lu, O C Santos & S Isotani (eds), Artificial Intelligence in Education - 26th International Conference, AIED 2025, Proceedings. Lecture Notes in Computer Science, vol. 15880 LNAI, Springer, pp. 433-440, 26th International Conference on Artificial Intelligence in Education, AIED 2025, Palermo, Italy, 22/07/25. https://doi.org/10.1007/978-3-031-98459-4_31, conference