Un environnement sémantique à base d'agents pour la formation à distance (E-Learning)

Abstract

Nowadays, educational institutions, such as universities, more and more offer E-Learning contents. Some of these courses are blended with traditional education, while others are conducted completely online. The creation of learning content is a main task in every E-learning environment. The constraints of minimizing the time required for developing a learning content, for increasing its scientific quality and to adapt it in many situations (adaptive content), have been a principal aim and so several approaches and methods were proposed. Moreover, the intellectual and social characteristics, as well as the learning styles of individuals, can be very different. These differences lead persons to adapt the learning content by taking into account the learners profiles and their objectives. This research opens ways for advanced learning systems, which are able to learn the needs and characteristics of learners, respond to them immediately, and provide learners with learning content where adaptation is frequently improved and updated to the learners’ needs. So that, it may not be convenient if we don’t have additional information about the learner and the learning content (learning objective, prerequisites, learner background, levels … etc.). Therefore, we develop a collaborative system, where several authors work in a collaborative manner, to create and annotate educational materials using multi-agents system. The contribution of our system is the hybridization of adaptation techniques with those of collaboration and Semantic Web (ontology, annotation). We represent the learners’ profiles and the learning content using ontologies and annotations to meet the diversity and individual needs of the learners. We use the paradigm Agent in our system to benefit from the strong points of this paradigm such as modularity, autonomy, flexibility ... etc.