Ontology-Based Generic Learning Path Recommendations
E-learning is one of the most challenging "E-domains". In general it refers to a wide range of applications and processes designed to deliver instruction through computational means. It is seen as a technology-based learning alternative and as an extension to the classic classroom model. In this paper an approach is presented to make individual recommendations about the next steps of a learning path through an e-learning course. The developed algorithm computes recommendations about what to learn next, based on individual and automatically detected learning style preferences as well as learning strategies of classified peer learners.