SemCCM: course and competence management in learning management systems using semantic web technologies

Abstract

The knowledge embedded into the Learning Management Systems (LMSs) contains great potential, but currently is not utilized well enough because the learning content is mainly tailored for human understanding and not for computer processing. The courses in the LMSs cover certain set of topics that are usually exposed through a few general keywords and areas. In this paper the SemCCM system that utilizes the state of the art Semantic Web tools, methods and datasets for automatic semantic annotation of LMS courses is presented. The SemCCM system complements the LMSs through extraction and ranking of the relevant DBpedia resources for each of the courses, and uses their Wikipedia categories for more general area determination. The extracted DBpedia resources, together with their categories represent the specific topics covered by the courses and provide more accurate course retrieval. Together with the users' completed courses, the extracted DBpedia resources are used for determination of the users' competencies. The SemCCM system presents the analysis results to the end users in several different perspectives, enabling semantically enhanced course and user search, graph based course and competence overview, as well as user comparison.