Nikos Manouselis – författare

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.

As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.

This volume collects the papers selected for presentation at the Third Inter- tional Conference on Metadata and Semantic Research (MTSR 2009), held in Milan at the University of Milano-Bicocca (October 1-2, 2009). Metadataandsemanticresearchistodayagrowingcomplexsetofconceptual, theoretical, methodological, and technological frameworks, o?ering innovative computational solutions in the design and development of computer-based s- tems.Fromthis perspective,researchersworkinginthisareamusttackleabroad range of issues on methods, results, and solutions coming from di?erent classic areas of this discipline. The conference has been designed as a forum allowing researchers to present and discuss specialized results as general contributions to the ?eld. In order to give a novelperspective in which both theoreticaland application aspects of metadata research contribute in the growth of the area, this book mirrors the structure of the conference, grouping the papers into three main categories: (1) Theoretical Research: Results and Proposals; (2) Applications: Case Studies and Proposals; (3) Special Track: Metadata and Semantics for Agriculture,FoodandEnvironment.Thebookcontains31fullpapers(10forthe ?rstcategory,10forthesecondand12forthethird),selectedfromapreliminary initial set of about 70 submissions. Many people contributed to the success of the conference and the creation of this volume, from the initial idea to its implementation. Our ?rst ackno- edgement is to the members of the Steering Commitee, GeorgeBokosand David Raitt. We would also like to thank all Program Committee members and - viewers for their collaboration. Special thanks to Carlo Batini, on behalf of the DepartmentofComputerScience,SystemsandCommunicationoftheUniversity of Milan-Bicocca, who kindly hosted our conference.