Neuro Fuzzy intelligent e-Learning systems

E-learning is one way of learning, training or educating by electronic means. There are various approaches used for e-learning like Claude based approach, ontology based approach, semantic net approach, electronic course content management, also neuro-fuzzy based approach etc. This paper focuses on the Neuro-Fuzzy based approaches for e-learning. For this purpose different neuro systems, fuzzy systems as well as various intelligent tutoring systems are reviewed in his paper. It includes adaptive instruction generation in an E-learning environment for computer programming based on fuzzy logic, personalized e-learning recommender system based on fuzzy tree matching, learning knowledge objects delivery using fuzzy clustering, enhancement of e-learning activities using fuzzy ontology based user profile, Felder-Silverman learning style model for handling uncertainty using fuzzy logic. It also presents interactive educational tool for AI planning for robotics which is named as REACT! based on artificial neural network, detecting human expression using psychological signals based on neural networks. As well as it includes various intelligent tutoring system like ISCARE is used for motivating the students using psychological signals, also the system that improves social communication skills of children with multimodal sensory information, simulation based tutoring system called ViPS for physics education and finally CASE system is reviewed. The features of most of the intelligent e-learning systems are compared in this paper.