Dynamic case-based reasoning based on the multi-agent systems: Individualized follow-up of learners in distance learning

Abstract

In a Computing Environment for Human Learning (CEHL), there is still the problem of knowing how to ensure an individualized and continuous learner's follow-up during learning process, indeed among the numerous methods proposed, very few systems concentrate on a real time learner's followup. Our work in this field develops the design and implementation of a Multi-Agent Systems Based on Dynamic Case Based Reasoning which can initiate learning and provide an individualized follow-up of learner. When interacting with the platform, every learner leaves his/her traces in the machine. These traces are stored in a basis under the form of scenarios which enrich collective past experience. The system monitors, compares and analyses these traces to keep a constant intelligent watch and therefore detect difficulties hindering progress and avoid possible dropping out. The system can support any learning subject. To help and guide the learner, the system is equipped with combined virtual and human tutors.