How e-learning systems may benefit from ontologies and recommendation methods to efficiently personalise resources. (26th January 2010)

• Record Type: Journal Article
• Authors: Kerkiri, Tania; Manitsaris, Athanassios; Mavridis, Ioannis
• Is Part Of: International journal of knowledge and learning. Volume 5:Number 3/4(2009)
• Page Start: 347
• Page End: 370
• Publication Date: 2010-01-26
• Subjects: knowledge management -- KM -- e-learning -- electronic learning -- semantic web -- ontologies -- recommendation algorithms -- resource personalisation -- learning styles -- information systems -- world wide web -- internet -- web application interoperability -- reputation metadata -- education -- student preferences -- student satisfaction -- student progress; Knowledge and learning -- Periodicals; Knowledge management -- Periodicals; 306.4205
• Languages: English
• ISSNs: 1741-1009

Abstract

Knowledge management systems suffer from the efficient management of the information they maintain. Current e-learning systems, is an application of a progressively more complex information domain, as they increasingly enhance their courses with the variety of web based resources to meet the educational needs of their participants. Thus, they face the problem of managing and personalising this knowledge. To confront this problem they already benefited from the semantic web technologies. Ontologies, a cardinal asset towards augmenting the interoperability among web applications, anticipate the accuracy of the retrieved data by means of effective matching of the user requirements. In this paper ontologies are explored to personalising resources. The framework of an e-learning system is described and a methodology is proposed applying recommendation algorithms. Personalisation is achieved via handling related metadata of the attendants' personality and preferences, as well as, reputation metadata, thus anticipating their satisfaction and educational progress.