Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/617
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dc.contributor.authorKarga, Soultana-
dc.contributor.authorSatratzemi, Maya-
dc.date.accessioned2020-03-14T10:04:14Z-
dc.date.available2020-03-14T10:04:14Z-
dc.date.issued2018-
dc.identifier10.1007/s10639-017-9668-0en_US
dc.identifier.issn1360-2357en_US
dc.identifier.issn1573-7608en_US
dc.identifier.urihttps://doi.org/10.1007/s10639-017-9668-0en_US
dc.identifier.urihttps://ruomo.lib.uom.gr/handle/7000/617-
dc.description.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.en_US
dc.language.isoenen_US
dc.publisherSpringer USen_US
dc.sourceEducation and Information Technologiesen_US
dc.subjectFRASCATI::Social sciencesen_US
dc.subjectFRASCATI::Engineering and technologyen_US
dc.subject.otherLearning designen_US
dc.subject.otherrecommender systemsen_US
dc.subject.othersocial taggingen_US
dc.subject.othertechnology enhanced learningen_US
dc.titleA hybrid recommender system integrated into LAMS for learning designersen_US
dc.typeArticleen_US
dc.contributor.departmentΤμήμα Εφαρμοσμένης Πληροφορικήςen_US
local.identifier.volume23en_US
local.identifier.issue3en_US
local.identifier.lastpage1297en_US
local.identifier.volumetitle1329en_US
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