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dc.contributor.authorSergis, S.
dc.contributor.authorZervas, P.
dc.contributor.authorSampson, Demetrios
dc.date.accessioned2017-01-30T10:48:44Z
dc.date.available2017-01-30T10:48:44Z
dc.date.created2015-11-04T20:00:34Z
dc.date.issued2014
dc.identifier.citationSergis, S. and Zervas, P. and Sampson, D. 2014. Towards learning object recommendations based on teachers' ICT competence profiles, in Proceedings of 2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT 2014), Jul 7-10 2014, pp. 534-538. Athens: Institute of Electrical and Electronics Engineers.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/5828
dc.identifier.doi10.1109/ICALT.2014.156
dc.description.abstract

© 2014 IEEE. Recommender Systems (RS) have been investigated in the Technology enhanced Learning (TeL) field for facilitating, among others, Learning Objects (LOs) selection and retrieval. However, most of the existing approaches focus on the learners' perspective and do not take into consideration teachers' profile. Moreover, the systems that do target teachers, do not explicitly exploit their ICT competence profiles. This can lead to recommending LOs that are beyond the teachers' current ability to use in their teaching practice. In this paper, we aim to tackle this problem and propose, as a first step, a set of mapping rules for aligning teachers' ICT competences and LO metadata elements. Moreover, a preliminary simulated evaluation is described, the results of which indicate that the mapping schema can provide robust identification of appropriate LOs based on both the users' ICT competences and the overall ratings of the educational resources.

dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.titleTowards learning object recommendations based on teachers' ICT competence profiles
dc.typeConference Paper
dcterms.source.startPage534
dcterms.source.endPage538
dcterms.source.titleProceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014
dcterms.source.seriesProceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014
dcterms.source.isbn9781479940387
curtin.departmentSchool of Education
curtin.accessStatusFulltext not available


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