A framework for interactive pattern based adaptive recommender agent using concept map for personalized e-learning: IPBARA

This paper addresses the issue of providing personalized user interface to e-learner under web based e-learning environment. A frame work, based on concept map trees, is proposed that intelligently tracks the learning pattern of an e-learner and helps the learner to attain his learning objective through the recommender agent. The system is expected to take certain period of adaptive training session to identify the various learning patterns prevailing in a web-based e-Learning environment.

I. Introduction

Along with the revolutionary development in the arena of Information and Communication Technology (ICT) elearning is undergoing a rapid change. This development requires massive amount of e-Learning resources generation. However most of the traditional systems do not have provision to appreciate personal learning. They provide the same content to students to learn or to let students opt content from the huge resources in the e-environment without giving any advice or assistance. This often leads learning process a difficult activity and makes c-lcarner uncomfortable. Therefore personalization of a learners educational activity enhances his total learning experience. The personalization of an educational activity is a process of combining learning resources in such a way that the learner is presented with only the appropriate material [1]. The appropriateness is considered on the basis of various aspects of the learners requirements: material should be limited to the knowledge which is actually to be acquired, and it should be well suited for personal way of learning.