TOWARDS THE RECOMMENDATION OF HIGHLY RELEVANT LEARNING OBJECTS TO THE LEARNERS

Abstract

Learning objects are reusable units of learning that are used for educational purpose. E-learning has now become quite prevalent in learning community, more specifically in the higher education. Teachers and learners play crucial role in the establishment of e-learning community but the system is still not freed of the traditional barriers of the conventional mode of education for the provision of learning contents. The educators and instructional designers are still working on confined repositories for the purpose of authoring learning objects. The learner’s context and behavioral patterns are still not properly integrated in the e-learning system .The study aims to propose architecture for e-learners to get personalized contents in an adaptive fashion. The initial purpose of this study is to perform a quantitative analysis of learning content. The study also contributes to the proper placement of Learning Objects Repository (L.O.R) in the proposed framework and the integration of various tools at the front layer. However the most important contribution of the research is to propose an algorithm that can rank LOs for a learner with reference to his pedagogical needs and learning goals.