Optimisation du regroupement des apprenants au sein d'une plate-forme d'apprentissage collaborative

Abstract

The subject is mainly located in the context of computer-assisted collaborative learning (CSCL). In this area of research, learners are grouped into groups to carry out their various educational activities (learning, problem solving, etc.) according to grouping strategies. Several researches have been done on the management of groups and their optimizations. The main objective of this work is to seek methods and techniques for optimizing clustering in order to integrate them into a collaborative learning system (CSCL) that supports the clustering process intelligent learners. In other words, the problematic of this research can be expressed as follows : given a set of learners N and a set of tasks to be performed M (of different difficulties and magnitudes), we seek the optimal composition of learners (in terms of group size and method of most appropriate grouping) in order to guarantee a maximum success rate. To do this, several techniques optimizations of algorithms can be used to achieve the objective of this work.