IDEAL: AN INTELLIGENT DISTRIBUTED EXPERIENCE-BASED ADAPTIVE LEARNING MODEL

Intelligent Tutoring Systems increasingly show promise as a technology that will expand the horizons of web-based education to anyone with an Internet connection. However, there are many considerable challenges in making such systems more effective. This work brings different dimensions together to form a proper foundation for E-Learning systems. It combines techniques from web- based learning, intelligent tutoring systems, course management systems, adaptive hypermedia systems, collaborative learning systems and traditional learning systems to present a better web-based intelligent tutoring system that conforms to the E-Learning standards. Finally, based on the experiencebased approach, this work has investigated the technical feasibility of applying a multi-agent technique to implement a prototype system for the proposed model. A web-based e-learning system called Intelligent Distributed Experience Based Adaptive Learning (IDEAL) has been implemented to test the functionality of the model.