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dc.contributor.authorKhalil, Mohammad
dc.date.accessioned2022-03-31T11:53:49Z
dc.date.available2022-03-31T11:53:49Z
dc.date.created2022-01-29T21:58:24Z
dc.date.issued2021
dc.identifier.isbn978-3-86956-512-5
dc.identifier.urihttps://hdl.handle.net/11250/2988841
dc.description.abstractClustering in education is important in identifying groups of objects in order to find linked patterns of correlations in educational datasets. As such, MOOCs provide a rich source of educational datasets which enable a wide selection of options to carry out clustering and an opportunity for cohort analyses. In this experience paper, five research studies on clustering in MOOCs are reviewed, drawing out several reasonings, methods, and students’ clusters that reflect certain kinds of learning behaviours. The collection of the varied clusters shows that each study identifies and defines clusters according to distinctive engagement patterns. Implications and a summary are provided at the end of the paper.en_US
dc.language.isoengen_US
dc.publisherUniversitätsverlag Potsdamen_US
dc.relation.ispartofEMOOCs 2021
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleWho Are the Students of MOOCs? Experience from Learning Analytics Clustering Techniquesen_US
dc.typeChapteren_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2021 The Author(s)en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
dc.identifier.doihttps://doi.org/10.25932/publishup-51729
dc.identifier.cristin1993294
dc.source.pagenumber259-269en_US
dc.identifier.citationEMOOCs 2021en_US


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