Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> User <s> The Adaptive Courseware Environment (ACE) [1] is a WWW-based tutoring framework which combines methods of knowledge representation, instructional planning, and adaptive media generation to deliver individualized courseware over the WWW. In this paper we like to introduce new cooperative components integrated in the ACE framework that support cooperative knowledge/data collection, expert finding and learner group organization. All these new cooperative components are realized with modified components of the BSCW environment [2]. A pedagogical agent in ACE is able to make recommendations for switching between individual and cooperative learning activities and find advanced or expert students in relation to one's own profile. <s> BIB001 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> User <s> The aim of this paper is to discuss how distributed learner modelling can benefit from semantic web technologies and which challenges have to be solved in this new environment. Heterogeneity of personalization techniques and their needs raise the question whether we can agree on one common data model for user profiles, which supports these techniques. In this paper we discuss an approach where a learner model can be distributed and can reflect features taken from several standards for a learner modelling. These features can be combined according to the requirements of specific personalization techniques, which can be provided as personalization services in a P2P learning network. RDF and RDFS as key tools of the semantic web allow us to handle such situations. We also sketch an architecture for such a network, where this approach can be realized. <s> BIB002 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> User <s> One distinctive feature of any adaptive system is the user model that represents essential information about each user. This chapter complements other chapters of this book in reviewing user models and user modeling approaches applied in adaptive Web systems. The presentation is structured along three dimensions: what is being modeled, how it is modeled, and how the models are maintained. After a broad overview of the nature of the information presented in these various user models, the chapter focuses on two groups of approaches to user model representation and maintenance: the overlay approach to user model representation and the uncertainty-based approach to user modeling. <s> BIB003
Learner models have been researched extensively in the educational adaptive hypermedia and the educational user modeling research areas. In this section, we summarize briefly the main learner characteristics that have been proposed by Brusilovsky and Millán BIB003 , Specht BIB001 , and Nguyen and Do  . Relevant standards and specifications for partial representations of learner data are IMS LIP, IMS ePortfolio, IMS Enterprise, IEEE RCD, FOAF, and HR-XML. A detailed discussion of data elements available in these standards is beyond the scope of this paper. Interesting work in this area has been presented by Dolog and Nejdl BIB002 .