Constructing Adaptive Individual Learning Environment Based on Multi-agent System

A multi-agent system (MAS) based integrated framework in support of adaptive and active learning in individual learning spaces is proposed in this paper. In the adaptive individual learning space, the key issue is how to dynamically generate personalized learning path consisting of domain concepts and present associated learning objects catering for a learner´s knowledge state and learning preference. As to this, a novel domain model with ontology layer, metadata layer and learning objects layer is proposed, and an efficient searching algorithm for the presentation generation base on the proposed domain ontology model is put forward.