OLearner – An Ontology Based Learning Content Management System to Support Semantic Search and Contribution of Learning Objects

Abstract

E-Learning is a fast, just-in-time, learning process, which is becoming popular in distributed and dynamic environments such as the World Wide Web. The core of E-Learning is Learning Content Management System (LCMS). Traditional LCMS supports search of learning objects based on keywords. The conventional approach provides relevant as well as non-relevant results as they do not consider user's context. Also, precise search of non-textual resources such as audio-visual or multimedia based resources is not possible as these are not simple document files where keywords could be searched. The learner has to spend large amount of time in screening the learning resource to determine the best suiting his/her current learning requirements. In this paper an ontology based LCMS has been discussed. Ontology is a formal description of concepts in a real-world domain and helps to store the semantic information of that domain. It is more expressive than any other standard database model and facilitates knowledge sharing and reuse, i.e. a common understanding of various contents that reaches across people and applications. Developed LCMS incorporates semantic capabilities with the help of ontologies to enable semantic based contribution and retrieval of learning objects. Two very useful ontologies are created to describe the learner profile and the learning content. These ontologies have been used to classify the learning material, organize topics of a course and store the information pertaining to learner's profile. The proposed OLearner LCMS facilitates a resource contributor to contribute the resource to the OLearner portal with the metadata corresponding to the learning content and learner profile ontologies. These ontologies are further useful for a learner in searching a more precise and appropriate learning object.