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dc.contributor.authorKant Shankar, Shashi
dc.contributor.authorRuiz Calleja, Adolfo 
dc.contributor.authorSerrano Iglesias, Sergio 
dc.contributor.authorOrtega Arranz, Alejandro 
dc.contributor.authorTopali, Paraskevi 
dc.contributor.authorMartínez Monés, Alejandra 
dc.date.accessioned2019-10-22T09:49:17Z
dc.date.available2019-10-22T09:49:17Z
dc.date.issued2019
dc.identifier.citationCaeiro Rodríguez, M.; Hernández García, A.; Muñoz Merino, P.J. Proceedings of the Learning Analytics Summer Institute (LASI Spain 2019), Vigo, Spain: CEUR, p. 71-83es
dc.identifier.issn1613-0073
dc.identifier.urihttp://uvadoc.uva.es/handle/10324/38674
dc.descriptionProducción Científicaes
dc.description.abstractMultimodal Learning Analytics (MMLA) uncovers the possibility to get a more holistic picture of a learning situation than traditional Learning Analytics, by triangulating learning evidence collected from multiple modalities. However, current MMLA solutions are complex and typically tailored to specific learning situations. In order to overcome this problem we are working towards an infrastructure that supports MMLA and can be adapted to different learning situations. As a first step in this direction, this paper analyzes four MMLA scenarios, abstracts their data processing activities and extracts a Data Value Chain to model the processing of multimodal evidence of learning. This helps us to reflect on the requirements needed for an infrastructure to support MMLA.es
dc.format.extent13 p.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherCEUR Workshop Proceedingses
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationMultimodal Learning Analyticses
dc.subject.classificationAnálisis de Aprendizaje Multimodales
dc.subject.classificationData Value Chaines
dc.subject.classificationCadena de valor de datoses
dc.subject.classificationMultimodal learning scenarioses
dc.subject.classificationEscenarios de aprendizaje multimodales
dc.titleA Data Value Chain to Model the Processing of Multimodal Evidence in Authentic Learning Scenarioses
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.relation.publisherversionhttp://ceur-ws.org/Vol-2415/es
dc.title.eventLearning Analytics Summer Institute (LASI Spain 2019)es
dc.description.projectEuropean Union’s Horizon 2020 research and innovation programme (grant 669074)es
dc.description.projectMinisterio de Ciencia, Innovación y Universidades - Fondo Europeo de Desarrollo Regional (projects TIN2017-85179-C3-2-R / TIN2014-53199- C3-2-R)es
dc.description.projectJunta de Castilla y León - Fondo Europeo de Desarrollo Regional (project VA257P18)es
dc.description.projectComisión Europea (project 588438-EPP-1-2017-1-EL-EPPKA2- KA)es
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/669074
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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