A Novel Scheme For Information Retrieval From E-Learning Repository

Abstract

The repository of any learning management system (LMS) keeps growing and becomes a rich source of learning materials with the passage of time. This learning resource may serve subject experts by allowing them to reuse the existing material while preparing online instructional materials. At the same time it may help the learners by allowing them to retrieve the relevant documents for efficiently achieving their learning goals. We have proposed a novel scheme for searching documents relevant to concept knowledge to be imparted to students, which assists subject experts in synthesizing the course material, by facilitating them to reuse existing learning objects available in e-learning repository. It also helps students in finding relevant learning resources efficiently for interactive e-learning. This paper presents an efficient way of retrieving information related to the teaching domain from a vast reservoir of documents. We have employed fuzzy clustering, fuzzy relation along with information retrieval techniques to discover the underlying structure of knowledge and identify knowledge based relationship between learning material and retrieving the relevant documents. The experiments conducted to judge the suitability of fuzzy clustering for discovering good document relationships and to evaluate the performance of the proposed information retrieval system, show encouraging results. A practical implementation of this technique has also been demonstrated in the implementation of eLGuide, a framework for an adaptive e-learning system.