Abstract : This paper presents a recommender system for learning objects which uses a collaborative filtering mechanism based on competencies. The model enables students to receive recommendations of learning objects automatically, according to students' interests but also according to competencies that have to be developed. The prototype implemented was able to recommend relevant contents to students, aiming at helping them in the development of competencies. The paper also presents a couple of experiments showing that the recommender system has a good level of accuracy for the suggestions made.
Nicholas Reynolds; Márta Turcsányi-Szabó. IFIP TC 3 International Conference on Key Competencies in the Knowledge Society (KCKS) / Held as Part of World Computer Congress (WCC), Sep 2010, Brisbane, Australia. Springer, IFIP Advances in Information and Communication Technology, AICT-324, pp.35-43, 2010, Key Competencies in the Knowledge Society. 〈10.1007/978-3-642-15378-5_4〉
https://hal.inria.fr/hal-01054676
Contributeur : Hal Ifip
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Dernière modification le : mercredi 9 août 2017 - 13:53:48
Document(s) archivé(s) le : mercredi 26 novembre 2014 - 15:45:36
Sílvio César Cazella, Eliseo Berni Reategui, Patrícia Behar. Recommendation of Learning Objects Applying Collaborative Filtering and Competencies. Nicholas Reynolds; Márta Turcsányi-Szabó. IFIP TC 3 International Conference on Key Competencies in the Knowledge Society (KCKS) / Held as Part of World Computer Congress (WCC), Sep 2010, Brisbane, Australia. Springer, IFIP Advances in Information and Communication Technology, AICT-324, pp.35-43, 2010, Key Competencies in the Knowledge Society. 〈10.1007/978-3-642-15378-5_4〉. 〈hal-01054676〉
