Content Assistance and Recommendations in Learning Material

With the variety of Learning Materials (LM) available in Learning Management Systems and the Internet, the time a student requires to select the most appropriate content increases. Especially the use of the Internet to find new LM is time consuming and not necessarily successful. A study accomplished at our university shows, that students mainly look for alternative explanations, content related exercises and examples, which can be used in addition to the existing LM. In this paper we describe the System Learning Assistance Osnabrueck (LAOs), which is based on a collaborative tagging approach with the main goals to give content related assistance for available LM, but also recommend content in further LM e.g. from the Internet.