Rule-Based Fuzzy Logic for Automatic Learning Process in an E-learning Environment

With an upgrading technology of web-based education E-Learning performs a best effect for the student based on the programming language. However, student modeling in many cases deals with uncertainty and it is a difficult process. It cannot be exactly said that a learner knows or does not know a domain concept. On the other hand, domain concepts which were previously known by the learner may be completely or partially forgotten. Thus, at present they may be partly known or completely unknown. The teaching process itself changes the status of knowledge of a user. The representation of the learner"s knowledge is a moving target and a learning control system is a nonlinear system. For this problem this paper presents the Rule-Based Fuzzy Logic for automatically learning Process for the Student to provide an Adaptive Instruction through E-learning. This introduces a FuzKPBE (a rule based fuzzy Knowledge definer with Personalized Brilliancy Evaluation), which predicts the relevant course and concepts based on individual skill set on every concept.