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dc.contributor.authorNafea, Shaimaaen
dc.contributor.authorSiewe, Francoisen
dc.contributor.authorHe, Yingen
dc.date.accessioned2018-12-13T14:42:46Z
dc.date.available2018-12-13T14:42:46Z
dc.date.issued2018-12
dc.identifier.citationNafea, S., Siewe, F., He, Y. (2018) ULEARN: Personalized Course Learning Objects Based on Hybrid Recommendation Approach. International Journal of Information and Education Technology, 8(12), pp.842-847.en
dc.identifier.issn2010-3689
dc.identifier.urihttp://hdl.handle.net/2086/17343
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractThe success of e-learning systems depends on their capability to automatically retrieve and recommend relevant learning content according to the preferences of specific learner profiles. Generally, e-learning systems do not cater for individual learners’ needs based on their profile. They also make it very difficult for learners to choose suitable resources for their learning. Matching the teaching strategy with the most appropriate learning object based on learning styles is presented in this paper, with the aim of improving learners’ academic levels. This work focuses on the design of a personalized e-learning environment based on a hybrid recommender system, collaborative filtering and item content filtering. It also describes the architecture of the ULEARN system. The ULEARN uses a recommender adaptive teaching strategy by choosing and sequencing learning objects that fit with the learners’ learning styles. The proposed system can be used to rearrange learning object priority to match the student’s adaptive profile and to adapt teaching strategy, in order to improve the quality of learning.en
dc.language.isoenen
dc.publisherInternational Journal of Information and Education Technologyen
dc.subjectCourse contenten
dc.subjectrecommender systemen
dc.subjectlearning objecten
dc.subjectlearner profileen
dc.subjectteaching strategyen
dc.titleULEARN: Personalized Course Learning Objects Based on Hybrid Recommendation Approachen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.18178/ijiet.2018.8.12.1151
dc.researchgroupSoftware Technology Research Laboratory (STRL)en
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NCen
dc.date.acceptance2018-10-08en
dc.exception.reasonThe output was published as gold open accessen
dc.researchinstituteCyber Technology Institute (CTI)en


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