A context-aware adaptive learning system using agents

Evolution of Web technologies has made e-learning a popular common way of education and training. As an outcome, learning content adaptation has been the subject of many research projects lately. This paper suggests a framework for building an adaptive Learning Management System (LMS). The proposed architecture is based upon multi-agent systems and uses both Sharable Content Object Reference Model (SCORM) 2004 and semantic Web ontology for learning content storage, sequencing and adaptation. This system has been implemented upon a well known open-source LMS and its functionalities are demonstrated through the simulation of a scenario mimicing the real life conditions. The result reveals the system effectiveness for which it appears that the proposed approach may be very promising.

Research highlights
► Design an adaptive system based on service oriented architecture that can be integrated with current learning management systems.
► The use of multi-agent architecture in Java programming environment.
► The use of semantic Web ontology and learning content standards at two different abstract layers for storing learning contents.
► The use of ontology to empower the adaptive system where learning content standards show weakness in personalization. In response to LMS events about user interactions, the ontology related to the current learner may be updated accordingly and may be added as a new behavior to content selector and content organizer agents.