User/tutor optimal learning path in e-learning using comprehensive neuro-fuzzy approach

Internet evolution has affected all industrial, commercial, and especially learning activities in the new context of e-learning. Due to cost, time, or flexibility e-learning has been adopted by participators as an alternative training method. By development of computer-based devices and new methods of teaching, e-learning has emerged. The effectiveness of such programs is dependent on powerful learning management systems. In this paper, a neuro-fuzzy approach is proposed based on an evolutionary technique to obtain an optimal learning path for both instructor and learner. The neuro-fuzzy synergy allows the diagnostic model to imitate instructor in diagnosing learners’ characteristics, and equips the intelligent learning environment with reasoning capabilities. These reasoning capabilities can be used to drive pedagogical decisions based on the learning style of the learner. The neuro-fuzzy implementation helps to encode both structured and non-structured knowledge for the instructor. On the other hand, for learners, the neural network approach has been applied to make personalized curriculum profile based on individual learner requirements in a fuzzy environment.