A semantic web-based framework for information retrieval in E-learning systems

Abstract

The advent of the internet, the evolution of the World Wide Web (WWW), coupled with the e-learning paradigm has resulted in the availability of a plethora of learning resources on the Web. However, these resources are not being fully utilized to their greatest potential. Learners, educators and researchers seeking educational content usually spend a great deal of time sorting through resources on the web without satisfactory results. Most times, this is not because the information is not available, but because the techniques being applied by major search engines do not handle the semantics and personalization required in this context. In a bid to proffer a solution to the problem of discovering relevant resources online by different categories of users, this work presents an integrated framework for personalized information retrieval of educational content. The framework exploits semantic web technologies. Further work will include the implementation and testing of the framework.