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Autor*innen: Fazeli, Soude; Drachsler, Hendrik; Brouns, Francis; Sloep, Peter
Titel: A trust-based social recommender for teachers
Aus: Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Santos, Olga C. (Hrsg.): RecSysTEL-2012: Proceedings of the 2nd Workshop on Recommender Systems in Technology Enhanced Learning 2012 in conjunction with the 7th European Conference on Technology Enhanced Learning (EC-TEL 2012), Saarbrücken, Germany, September 18-19, 2012, Aachen: RWTH, 2012 (CEUR workshop proceedings, 896), S. 49-60
URL: http://ceur-ws.org/Vol-896/paper4.pdf
Dokumenttyp: 4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache: Englisch
Abstract: Online communities and networked learning provide teachers with social learning opportunities to interact and collaborate with others in order to develop their personal and professional skills. In this paper, Learning Networks are presented as an open infrastructure to provide teachers with such learning opportunities. However, with the large number of learning resources produced everyday, teachers need to find out what are the most suitable resources for them. In this paper, recommender systems are introduced as a potential solution to address this issue. Unfortunately, most of the educational recommender systems cannot make accurate recommendations due to the sparsity of the educational datasets. To overcome this problem, we propose a research approach that describes how one may take advantage of the social data which are obtained from monitoring the activities of teachers while they are using our social recommender. (Orig.)