One of the most important problems faced by teachers is grouping students into proper teams. The task is complex, as many technical and interpersonal factors could affect team dynamics, with no clear indication of which factors may be more relevant. Not only the problem is conceptually complex, but its computational complexity is also exponential, which precludes teachers from optimally applying strategies by hand. The tool presented in this paper aims to cover both gaps: first, it provides a range of grouping strategies for testing, and second, it provides artificial intelligence mechanisms that in practice tone down the computational cost of the problem.
|Title of host publication||Methodologies and Intelligent Systems for Technology Enhanced Learning, 6th International Conference|
|Editors||Mauro Caporuscio, Fernando De la Prieta, Tania Di Mascio, Rosella Gennari, Javier Gutiérrez Rodríguez, Pierpaolo Vittorini|
|Place of Publication||Switzerland|
|ISBN (Print)||978-3-319-40165-2, 978-3-319-40164-5|
|Publication status||Published - 26 May 2016|
Bibliographical noteThe full text is not available on the repository.
- Team formation
Alberola, J. M., del Val, E., Sanchez-Anguix, V., & Julián, V. (2016). A General Framework for Testing Different Student Team Formation Strategies. In M. Caporuscio, F. De la Prieta, T. Di Mascio, R. Gennari, J. Gutiérrez Rodríguez, & P. Vittorini (Eds.), Methodologies and Intelligent Systems for Technology Enhanced Learning, 6th International Conference (Vol. II, pp. 23-31). Switzerland: Springer Verlag. https://doi.org/10.1007/978-3-319-40165-2_3