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dc.contributor.authorEr, Erkan 
dc.contributor.authorGómez Sánchez, Eduardo 
dc.contributor.authorBote Lorenzo, Miguel Luis 
dc.contributor.authorAsensio Pérez, Juan Ignacio 
dc.contributor.authorDimitriadis Damoulis, Ioannis 
dc.date.accessioned2019-07-16T10:00:54Z
dc.date.available2019-07-16T10:00:54Z
dc.date.issued2019
dc.identifier.urihttp://uvadoc.uva.es/handle/10324/37044
dc.description.abstractWith the aim of supporting instructional designers in setting up collaborative learning activities in MOOCs, this paper derives prediction models for student participation in group discussions. The salient feature of these models is that they are built using only data prior to the learning activity, and can thus provide actionable predictions, as opposed to post-hoc approaches common in the MOOC literature. Some learning design scenarios that make use of this actionable information are illustrated.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherACMes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.titleInforming the design of collaborative activities in MOOCs using actionable predictionses
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.relation.publisherversionhttps://learningatscale.acm.org/las2019/
dc.title.eventSixth ACM Conference on Learning @ Scale, L@S2019es
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones


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