Reengineering ILE: towards a model for adapting the learning path

The main challenge faced by ILE is its ability to offer tools adapted to each learner allowing him to learn effectively by taking into account the different constraints. In this article, we describe an approach to adapting the learner's path adapted to his profile while respecting the time he has for learning and making sure to maximize his mark during the final exam. To achieve this objective, a double-layer adapted learning path graph is generated, the educational resources associated with the path identified, the selection of the most suitable resources for each step carried out and the overall time of the estimated path and the forecast score of the final test calculated. Thereafter, the graph of the generated path is re-evaluated at each learning step taken to best adapt it to the learner.