Towards recommender systems supporting knowledge sharing and transfer in vocational education and training

A number of recommender systems (RS) have been developed or are being developed in the context of technology enhanced learning (TEL). However, there is a lack of research focusing on the dual system of vocational education and training (VET). Knowledge sharing and transfer in VET have their own particularities. We suggest that RS can pro-actively support knowledge sharing and transfer and help users find information they need and are most likely interested in. We analyzed and identified tasks and goals of RS focusing on end-users in VET, and formulate them as multiple RS tasks in VET, which are compliant with our objective to support knowledge sharing and transfer. We suggest that a multidimensional RS adapted to the VET context, to fulfill and achieve multiple user tasks, is needed and introduce a hybrid multidimensional RS to support knowledge sharing and transfer in VET. A four dimensional RS approach, i.e. Similarity Degree, Quality Degree, Diversity Degree and Interest Degree, is presented. We developed a recommender system for the teaching and learning online community expertAzubi.