Personalized Blended E-learning System Using Knowledge Base Approach Based on Information Processing Speed Cognitive

Abstract

In recent years we have been observed that the demand of e-learning system increased due to vast growth in the field of electronic media. The e-learning system facilitates the learning from any parts of the world. The system of e-learning can also be made personalized blended e-learning system based on certain cognitive traits of the learner. Using blended e-learning system the performance of learners will be improved as well as the interest in that particular subject will also be developed. This paper discusses a blended e-learning system based upon the ability of information processing speed cognitive of a learner. The blended is based on combination of traditional video lecture and practical visualize videos. The students are grouped into three clusters on the basis of their cognitive ability. The machine will recognize each cluster and accordingly it will provide the learning contents. The inference rules and knowledge based approach have been used to make the machine under stable. The features are extracted for each student learning behavior. The system decides about the learning contents for each cluster based upon the observed behavior of that particular cluster and also monitors the growth of all the students.