A Personalized Pedagogical Objectives Based on a Genetic Algorithm in an Adaptive Learning System

The need for e-learning platforms to provide advanced and adapted training requires the introduction of new approaches to the resolution of the problems encountered. In this respect, the adaptability of training systems becomes a desired characteristic. The use of genetic algorithms makes it possible to automate the search for courses adapted to the profile of the learner. Indeed, we assign different learning paths to learners belonging to the same class. In this work, we present the approach and the architecture adopted for the development of our adaptive e-learning platform which allows to generate learning paths adapted to the profiles of the learners and according to the pedagogical objectives fixed by the teacher. Thus, we study the problem of adapting the learner's profile to pedagogical objectives as an optimization problem, using genetic algorithms to look for an optimal path. Finally, we conclude with an experiment and evaluation of our approach based on genetic algorithms. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs.