Abstract
Forming effective groups for a high performance achievement is a crucial key in each learning environment. It involves more than just randomly assembling groups without taking in account the learning styles of each learner.
This paper presents an algorithm to build an adequate collaborative learning group based on heterogeneity or homogeneity of learners’ profiles. In order to verify the performance of the algorithm, several experiments were conducted in real dataset in virtual environment. The results of our study provide preliminary evidence that the algorithm’s performance may be affected by the group size using different similarity metrics.
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Bourkoukou, O., Bachari, E.E., Boustani, A.E. (2020). Building Effective Collaborative Groups in E-Learning Environment. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2019). AI2SD 2019. Advances in Intelligent Systems and Computing, vol 1102. Springer, Cham. https://doi.org/10.1007/978-3-030-36653-7_11
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