Optimizing collaborative learning path by ant's optimization technique in e-learning system

The approach that we propose in this paper is part of the optimization of the collaborative learning in the e-learning environment. It is particularly interested in the automatic creation of groups called homogeneous teams, based on a set of criteria to highlight the similarity between the learners. This similarity is calculated using a similarity index that is the Euclidean distance. Then an optimal path guiding each community is built, through a dynamic adaptation of the optimization technique by ant colony. In this article, we have implemented the methodological framework and the algorithmic modeling of our approach, given that our future work will focus on the implementation and the empirical validation of our design.