Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Social Relations <s> Mobile technology enhanced learning pertains to the delivery of multimedia learning resource onto mobile end devices such as cell phones and PDAs. It also aims at supporting personalized adaptive learning in a community context. This paper presents a novel approach to supporting both aspects. The community aware content adaptation employs the MPEG-7 and MPEG-21 multimedia metadata standards to present the best possible information to mobile end devices. Meanwhile, interest patterns are derived from a community aware context analysis. We designed and developed a technology enhanced learning platform supporting architecture professionals' study at city excursions and other mobile tasks. <s> BIB001 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Social Relations <s> The definition of context experienced an evolution in the research area of context-aware computing, but still suffers from either generality or incompleteness. Furthermore, many definitions are driven by the ease of implementation. This paper introduces two extensions to available context definitions that provide a natural understanding of this concept to users of context-aware applications and facilitates the engineering of this concept for software developers of such applications. <s> BIB002 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Social Relations <s> One of the main software engineers' competencies, solving software problems, is most effectively acquired through an active examination of learning resources and work on real-world examples in small development teams. This obviously indicates a need for an integration of several existing learning tools and systems in a common collaborative learning environment, as well as advanced educational services that provide students with right in time advice about learning resources and possible collaboration partners. In this paper, we present how we developed and applied a common ontological foundation for the integration of different existing learning tools and systems in a common learning environment called DEPTHS (Design Patterns Teaching Help System). In addition, we present a set of educational services that leverages semantic rich representation of learning resources and students' interaction data to recommend resource relevant for students' current learning context. <s> BIB003
Social relations describe social associations, connections, or affiliations between two or more persons BIB002 . For instance, social relations can contain information about friends, neutrals, enemies, neighbors, coworkers, and relatives. Other researchers identify community BIB001 as an important context dimension. In TEL applications, the distinction is sometimes made between experts, teachers and peer learners BIB003 . The FOAF specification  is often used to describe such user relations and roles. Fig. 2 summarizes the context categories and their elements that have been described in this section. The categorization is used in Section 4 to identify to which extent current context-aware TEL recommender systems are able to generate recommendations adapted to the current contextual needs of users.