Decoding Peer Assessment: An Algorithm to Navigate Group Problems Detection

Publication date

2025-07-20

Authors

Olthof, Alyssa
Saccardi, IsabellaORCID 0000-0001-5567-3120ISNI 0000000526348846
Masthoff, J.F.M.ISNI 000000012419854X

Editors

Cristea, Alexandra I.
Walker, Erin
Lu, Yu
Santos, Olga C.
Isotani, Seiji

Advisors

Supervisors

Document Type

Part of book
Open Access logo

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