Selection of appropriates E-learning personalization strategies from ontological perspectives

Abstract

When there are several personalization strategies of E-learning, authors of courses need to be supported for deciding which strategy will be applied for personalizing each course. In fact, the time, the efforts and the learning objects needed for preparing personalized learning scenarios depend on the personalization strategy to be applied. This paper presents an approach for selecting personalization strategies according to the feasibility of generating personalized learning scenarios with minimal intervention of the author. Several metrics are proposed for putting in order and selecting useful personalization strategies. The calculus of these metrics is automated based on the analyses of the LOM (Learning Object Metadata) standard according to the semantic relations between data elements and learners’ characteristics represented in the Ontology for Selection of Personalization Strategies (OSPS).

Keywords

• ontology
• personalization strategies
• metadata