ON APPLICATION OF SEMANTIC WEB TECHNOLOGIES TO PERSONALISE LEARNING

The paper is aimed to analyse Semantic Web technologies application in education and present a methodology of learning personalisation based on Resource Description Framework (RDF) technology. Research results are two-fold: first, the results of systematic literature review on Semantic Web technologies and their application in education are presented, and, second, RDF triples-based learning personalisation methodology is proposed. Web 2.0 was an interaction between users, and Web 3.0 became an interaction between machines. Due to the fact that computers can understand information stored on the web, it is possible to interpret information like humans and intelligently generate and distribute useful content tailored to the needs of users. Semantic Web tools such as ontology and knowledge representation, semantic annotation of resources, knowledge reasoning and services are widely spreading among educators to improve education quality. Nowadays one of the educational tasks is learning personalisation, and in this paper, RDF technology as learning personalisation approach is proposed. According to this methodology, RDF-based personalisation of learning should be based on applying students' learning styles and intelligent technologies. The main advantages of this approach are analyses of interlinks between students' learning styles and suitable learning components (learning objects and learning activities). The methodology is based on applying pedagogically sound vocabularies of learning components (i.e. learning objects and learning activities), experts' collective intelligence to identify learning objects and learning methods / activities that are most suitable for particular students, and intelligent technologies (i.e. ontologies and recommender system). This methodology based on applying personalised RDF triples is aimed at improving learning quality and effectiveness.