Intelligent component for adaptive E-learning systems

Existing e-learning systems are based on the quantity of information. They fail to consider an important factor for the success of the system, namely the user. An intelligent adaptive system should adjust the content in order to ensure faster and better performances in the learning process. Moreover, it should help students to develop new, desirable learning abilities. This paper presents the intelligent component of an adaptive e-learning system based on Bayesian networks; such a module makes an initial user classification using a psychological test, and continuously adapts according to user's interaction with the system.