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Autor/inn/enKarga, Soultana; Satratzemi, Maya
TitelA Hybrid Recommender System Integrated into LAMS for Learning Designers
QuelleIn: Education and Information Technologies, 23 (2018) 3, S.1297-1329 (33 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Karga, Soultana)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1360-2357
DOI10.1007/s10639-017-9668-0
SchlagwörterElectronic Learning; Educational Technology; Technology Uses in Education; Instructional Design; Preferences; Value Judgment; Information Management; Learning Activities
AbstractIn the constantly evolving field of e-learning, the Learning Design (LD) sector constitutes a critical success factor, as it has the potential to preserve and disseminate effective pedagogical approaches and enhance the quality of the educational process. Recognizing the LD process as demanding in terms of time and expertise this paper answers the research question of how to leverage Recommender Systems (RSs) and reuse pre-existing LD solutions in order to support teachers in the LD process. In particular, this paper presents the implementation and the first evaluation results of Mentor. Mentor is an RS that supports teachers in finding pre-existing LDs, which cater better for their needs and preferences, so as to re-design them. Mentor is integrated into LAMS, which is a well-known tool for designing, managing and delivering sequences of learning activities. The first user-centric evaluation experiment results are presented and confirm the underlying assumption that Mentor can facilitate teachers in the LD process. Further results concerning the user's general perception and the perceived usefulness of Mentor are discussed. (As Provided).
AnmerkungenSpringer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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