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dc.contributor.authorVan der Merwe, A.
dc.contributor.authorKruger, H.A.
dc.contributor.authorDu Toit, J.V.
dc.date.accessioned2016-07-19T06:47:04Z
dc.date.available2016-07-19T06:47:04Z
dc.date.issued2016
dc.identifier.citationVan der Merwe, A. et al. 2016. A mathematical ranking model in learning analytics. Proceedings of the 16th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE-2016. Cadiz, Spain, 4-8 July. p.1525-1535. [http://cmmse.usal.es/cmmse2016/sites/default/files/volumes/Proceedings_CMMSE_2016_final.pdf]en_US
dc.identifier.isbn978-84-608-6082-2
dc.identifier.urihttp://hdl.handle.net/10394/17990
dc.identifier.urihttp://cmmse.usal.es/cmmse2016/sites/default/files/volumes/Proceedings_CMMSE_2016_final.pdf
dc.description.abstractThe introduction of new educationa l trends triggers the development of innovative methods to collect, analyse and report the data subsequently generated. This paper discusses the implementation of a multi-stage mathematical class ranking model as a method in learning analytics, applied to a Computer Science module. The model applies the principle of Pareto optimality in an outputs-only data envelopment model to categorise st udents into classes of similar efficiency which are ranked according to dominance. The model is then adapted to calculate improvem ent targets for each studen
dc.language.isoenen_US
dc.publisherCMMSEen_US
dc.subjectClass rankingen_US
dc.subjectdata envelopment analysisen_US
dc.subjectlearning analyticsen_US
dc.subjectPareto optimalityen_US
dc.subjectstudent rankingen_US
dc.titleA mathematical ranking model in learning analyticsen_US
dc.typePresentationen_US
dc.contributor.researchID10100059 - Van der Merwe, Annette
dc.contributor.researchID12066621 - Kruger, Hendrik Abraham
dc.contributor.researchID10789901 - Du Toit, Jan Valentine


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