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Title: A hybrid recommender system integrated into LAMS for learning designers
Authors: Karga, Soultana
Satratzemi, Maya
Type: Article
Subjects: FRASCATI::Social sciences
FRASCATI::Engineering and technology
Keywords: Learning design
recommender systems
social tagging
technology enhanced learning
Issue Date: 2018
Publisher: Springer US
Source: Education and Information Technologies
Volume: 23
Issue: 3
Last Page: 1297
Volume Title: 1329
Abstract: In 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.
ISSN: 1360-2357
Other Identifiers: 10.1007/s10639-017-9668-0
Appears in Collections:Department of Applied Informatics

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