Enhanced e-Learning Experience by Pushing the Limits of Semantic Web Technologies

We investigate a novel approach to e-Learning using Semantic Web technologies and aiming to optimise the learners' experience incorporating pedagogical strategies into the learning process. The increasing availability of Semantic Web based educational resources and the establishment of open metadata standards like IEEE LOM pave the way for enhanced e-Learning systems that support personalised learning based on a reasoning framework and formal ontologies. We use ontologies to describe learning objects and the learner state, and define pedagogical recommendation axioms that specify which learning objects are best suited for a particular learner in a specific situation. Recent pedagogical findings suggest that the individual learning can be optimised by means of guidance through learning pathways, i. e., a particular order in which learning objects have to be studied. To this end, we offer an OWL model for learning pathways as structured sequences. We show the strengths and limits of OWL and propose a solution to overcome problems such as handling of soft constraints and ranking of result sets. The calculation for ranking is based on individual weights for specific contextual as well as learner profile features and considers the degree of match between learning objects and learner's needs. The validity of our approach is shown by means of real-life course material, i.e. a complete course on the Philosophy of Didactics, implemented as a prototype system and interfaced to variouss standard Learning Management Systems.