A fuzzy rule based intelligent advisor for self-paced learner in e-Learning environment

This paper presents a scheme for intelligent advice generation with the help of a fuzzy rule base, meant for a self-paced learner in an e-Learning environment. It employs a fuzzy machine that is fed with performance parameters e.g. score and time pertaining to a computer aided assessment of learner´s learning achievement. The fuzzy machine processes these performance parameters with the help of a fuzzy rule base to produce the crisp measures of the learner´s cognitive states in terms of knowledge, understanding and skill. On the basis of these defuzzified crisp diagnostic parameters advice is generated for the learner to suggest his future course of action targeted towards achievement of his learning objectives.