An Optimized Method for Adaptive Learning based on PSO Algorithm

Abstract

The field of education and in particular distance e-learning is experiencing sustained growth, because of the rapid evolution of information technology. This movement to open access to quality education to everyone, while eliminating geographic or economic barriers is part of open pedagogy. Among the innovations of open pedagogy we find MOOCs (Massive Open Online Courses) which constitutes a new online teaching system, a MOOC offers free courses to a public which is measured on a global scale, these educational devices allow young and old alike and whatever their geographic location, to develop knowledge on various fields. One of the main problems with MOOCs, however, is that learners are unable to complete the course, resulting in a very low completion rate. In this article, we propose a solution which consists in making the MOOC adapted to each learner, tailor-made courses based on the knowledge and preferences of each learner. This attempt to set up a suitable course for the benefit of the learner will be inspired by the behavior of swarms by using the PSO method "Particle Swarm Optimization" in order to strengthen the construction of the best choices in the system.