MASCE: A Multi-Agent System for Collaborative E-Learning

E-learning has become one of the most popular teaching methods in recent years. One of its modes is the blended learning where learners can read teaching materials asynchronously from a teaching website and collaborate with their peers, while providing for necessary face-to-face explanation, discussion, and physical operation in the classroom. In the computational intelligence field, the intelligent agent paradigm gained a tremendous interest in many application domains over the last two decades . This research project paper focuses on the use of intelligent agents in the sphere of e-learning education with the help of collaborative learning. Intelligent agents - the so called e-assistants or helper programs - can sit inside a computer and make the learning in e- learning happen dynamically to suit the need of the user. They can trap the user´s likes and dislikes in various areas, the level of knowledge and the learning style and accordingly recommend the best matching helpers for collaboration. The paper introduces a multi-agent system for collaborative e-learning (MASCE). MASCE is to assist teaching and learning process and also to encourage collaborative learning among peers. This system shall be used in a blended learning environment as a supplement to the face-to-face lecture where students can use the system in the lab or from home after attending the traditional lecture in the faculty. The objective is to incorporate the intelligence of the multi- agent system (MAS) in a way that enables it to actively and intelligently support the educational processes, where multiple agents can interact to exchange information so that students may collaborate on how best to gain knowledge.