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dc.contributor.authorPappas, Ilias
dc.contributor.authorGiannakos, Michail
dc.contributor.authorMikalef, Patrik
dc.date.accessioned2017-11-13T09:58:42Z
dc.date.available2017-11-13T09:58:42Z
dc.date.created2017-01-18T14:17:03Z
dc.date.issued2017
dc.identifier.issn1042-1726
dc.identifier.urihttp://hdl.handle.net/11250/2465732
dc.description.abstractThe use of video-based open educational resources is widespread, and includes multiple approaches to implementation. In this paper, the term “with-video assignments” is introduced to portray video learning resources enhanced with assignments. The goal of this study is to examine the factors that influence students’ intention to adopt with-video assignments. Extending the technology acceptance model by incorporating students’ emotions, we applied partial least squares structural equation modeling based on a sample of 73 students who systematically experienced with-video assignments in their studies. In addition, students’ activity was analyzed using aggregated time series visualizations based on video analytics. Learning analytics indicate that students make varying use of with-video assignments, depending on when they access them. Students are more likely to watch a greater proportion of the video when they use with-video assignments during the semester, as opposed to during the exams. Further, the findings highlight the important role of students’ emotions in adopting with-video assignments. In addition, perceived usefulness of with-video assignments increases their positive emotions and intention to adopt this medium, while perceived ease of use increases only their intentions. Together, these constructs explain 68% of the variance in students’ intention to adopt with-video assignments.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringer Verlagnb_NO
dc.titleInvestigating students’ use and adoption of with-video assignments: lessons learnt for video-based open educational resourcesnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.journalJournal of Computing in Higher Educationnb_NO
dc.identifier.doi10.1007/s12528-017-9132-6
dc.identifier.cristin1430987
dc.relation.projectNorges forskningsråd: 255129nb_NO
dc.description.localcode© Springer Verlag. This is the authors' accepted and refereed manuscript to the article. LOCKED until 17.1.2018 due to copyright restrictions. The final publication is available at https://link.springer.com/article/10.1007%2Fs12528-017-9132-6nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknikk og informasjonsvitenskap
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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