The Formation of Collaborative Learning Teams in Schools Through Mathematical Optimization for Improving the Classroom Climate
| dc.contributor.author | Candia-Véjar Alfredo | |
| dc.contributor.author | Faúndez, Álvaro | |
| dc.contributor.author | Rojas, Camila | |
| dc.contributor.author | Jeria, Isidora | |
| dc.contributor.author | Benítez, Natacha | |
| dc.contributor.author | Tupper, María Ignacia | |
| dc.contributor.author | Inostroza, Romina | |
| dc.contributor.author | Bellenger, Etienne | |
| dc.contributor.author | Pérez-Galarce, Francisco | |
| dc.coverage.spatial | Estados Unidos | |
| dc.date.accessioned | 2026-07-20T13:47:51Z | |
| dc.date.available | 2026-07-20T13:47:51Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | School climate plays a fundamental role in teaching and learning processes, directly influencing the achievement of educational objectives. Moreover, climate-related issues often manifest as bullying, which remains a persistent challenge for education systems worldwide. In this context, teamwork emerges as a key strategy to foster student interaction, strengthen friendship networks, and reduce bullying and aggression. However, traditional team assignment methods—such as student self-selection, teacher allocation, or random distribution—fail to account for the complexity of student interactions and individual characteristics. This study introduces a web-based decision support system designed to assist in team formation within educational settings by utilizing optimization models and algorithms, thereby promoting a more interconnected and inclusive student network. The models incorporate factors such as team diversity, victim protection, and student preferences. Its primary input is a social network along with derived metrics (e.g., betweenness centrality and triadic relationships), which feed into three non-linear integer optimization models that aim to consolidate, create, or enhance student interpersonal relationships. Additionally, the models were evaluated through a large quasi-experiment using both quantitative and qualitative analyses across four dimensions particularly relevant to educational activities: team dynamics, attitude toward the team, team cohesion, and team performance. Empirical results demonstrate that it is possible to improve the classroom climate without compromising the four team-related dimensions. This collaborative learning technology serves as a valuable resource for enhancing collaborative educational strategies and fostering a more inclusive and supportive classroom environment. | |
| dc.identifier.citation | IEEE Access, Vol. 14 (2026) pp. 8250-8268. | |
| dc.identifier.doi | https://doi.org/10.1109/ACCESS.2026.3653114 | |
| dc.identifier.issn | 2169-3536 | |
| dc.identifier.orcid | https://orcid.org/0000-0003-2953-6522 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12254/7672 | |
| dc.language.iso | en | |
| dc.publisher | IEEE | |
| dc.rights | Atribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL) | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/cl/ | |
| dc.subject | Collaborative learning | |
| dc.subject | team formation problem | |
| dc.subject | mathematical optimization | |
| dc.subject | classroom climate | |
| dc.title | The Formation of Collaborative Learning Teams in Schools Through Mathematical Optimization for Improving the Classroom Climate | |
| dc.type | Article |
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