Learning time planning in a distance learning system using intelligent agents

This article aims to present two intelligent agents, APL planner agent and ARL regulatory agent, enabling distance learners to plan and dynamically regulate their personalized learning time. The planning considers the speed of learner's understanding, the teaching units expected time of learning, the constraint learning path, the pace and the periodic learning time of the learner, while the regulation takes into account the timetable's perturbations during the learning process. To achieve our goal we have based our work on modeling diagrams, pedagogical graph and the learner's properties. In this paper we focus on the work modeling of APL and ARL, while remaining to validate in a more elaborate version.