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dc.contributor.authorMangaroska, Katerina
dc.contributor.authorSharma, Kshitij
dc.contributor.authorGiannakos, Michail
dc.contributor.authorTrætteberg, Hallvard
dc.contributor.authorDillenbourg, Pierre
dc.date.accessioned2019-04-02T08:03:56Z
dc.date.available2019-04-02T08:03:56Z
dc.date.created2019-01-13T20:01:27Z
dc.date.issued2018
dc.identifier.citationJournal of Learning Analytics. 2018, 8 (3), 98-119.nb_NO
dc.identifier.issn1929-7750
dc.identifier.urihttp://hdl.handle.net/11250/2592842
dc.description.abstractThis study investigates how multimodal user-generated data can be used to reinforce learner reflection, improve teaching practices, and close the learning analytics loop. In particular, the aim of the study is to utilize user gaze and action-based data to examine the role of a mirroring tool (i.e., Exercise View in Eclipse) in orchestrating basic behavioural regulation during debugging. The results demonstrated that students who processed the information presented in the Exercise View and acted upon it, improved their performance and achieved a higher level of success than those who failed to do so. The findings shed light on what constitutes relevant data within a particular learning context in programming using gaze patterns. Moreover, these findings could guide the collection of essential learner-centred analytics for designing usable, modular learning environments based on data-driven approaches.nb_NO
dc.language.isoengnb_NO
dc.publisherUTS ePressnb_NO
dc.relation.urihttps://learning-analytics.info/journals/index.php/JLA/article/view/6119
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleGaze-Driven Design Insights to Amplify Debugging Skills: A Learner-Centered Analysis Approachnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber98-119nb_NO
dc.source.volume8nb_NO
dc.source.journalJournal of Learning Analyticsnb_NO
dc.source.issue3nb_NO
dc.identifier.doihttps://doi.org/10.18608/jla.2018.53.7
dc.identifier.cristin1655729
dc.relation.projectNorges forskningsråd: 290994nb_NO
dc.relation.projectNorges forskningsråd: 255129nb_NO
dc.description.localcodeThe Journal of Learning Analytics works under a Creative Commons License, Attribution - NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0).nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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