Authors: Noureddine Gouasmi, Mahnane Lamia, Yacine Lafifi
Keywords: Collaborative Learning, Genetic Algorithm, Group Formation, Social Learning Network, Modified Order Crossover, Modified One-Point Cut Crossover.
Abstract
Social media and social networking have spread widely in everyday life, so it is important to use them in collaborative learning. Forming appropriate learning groups is, therefore, an important objective. This paper presents a novel approach based on a Genetic Algorithm (GA) for dynamic learners grouping in a Social Network Learning system (SNL). It offers some improved attributes applied for grouping learners and new genetic operators applied in the GA. The efficiency of the proposed approach was evaluated by comparing the groups formed using the proposed GA with randomly formed groups, resulting in the conclusion that the proposed GA is more effective and that the groups formed are more efficient.
Noureddine Gouasmi
ORCID: https://orcid.org/0000-0002-7882-2835
Badji Mokhtar - Annaba University,
P.O. Box 12, Annaba, 23000, Algeria
E-mail:
Mahnane Lamia
ORCID: https://orcid.org/0000-0003-4050-7183
LRS Laboratory, Badji Mokhtar - Annaba University,
P.O. Box 12, Annaba, 23000, Algeria
E-mail:
Yacine Lafifi
ORCID: https://orcid.org/0000-0001-8232-4196
Labstic, 8 Mai 1945 University, Guelma
P.O. Box 401, Guelma 24000, Algeria
E-mail:
DOI
https://doi.org/10.56415/csjm.v34.02
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