Hide metadata

dc.date.accessioned2020-12-22T19:31:09Z
dc.date.available2020-12-22T19:31:09Z
dc.date.created2020-12-19T16:27:24Z
dc.date.issued2020
dc.identifier.citationKaliisa, Rogers Kluge, Anders Mørch, Anders Irving . Combining Checkpoint and Process Learning Analytics to Support Learning Design Decisions in Blended Learning Environments. Journal of Learning Analytics. 2020, 7(3), 33-47
dc.identifier.urihttp://hdl.handle.net/10852/81820
dc.description.abstractLearning analytics (LA) constitutes a key opportunity to support learning design (LD) in blended learning environments. However, details as to how LA supports LD in practice and information on teacher experiences with LA are limited. This study explores the potential of LA to inform LD based on a one-semester undergraduate blended learning course at a Norwegian university. Our findings indicate that creating valuable connections between LA and LD requires a detailed analysis of student checkpoints (e.g., online logins) and process analytics (e.g., online content and interaction dynamics) to find meaningful learning behaviour patterns that can be forwarded to teachers in retrospect to support the redesign of courses. Moreover, the teachers in our study found the LA visualizations to be valuable for understanding student online learning processes, but they also requested the timely sharing of aggregated LA visualizations in a simple, easy-to-interpret format, yet detailed enough to be informative and actionable. We conclude the paper by arguing that the potential of LA to support LD is improved when multiple levels of LA are considered.
dc.languageEN
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.titleCombining Checkpoint and Process Learning Analytics to Support Learning Design Decisions in Blended Learning Environments
dc.typeJournal article
dc.creator.authorKaliisa, Rogers
dc.creator.authorKluge, Anders
dc.creator.authorMørch, Anders Irving
cristin.unitcode185,18,1,0
cristin.unitnameInstitutt for pedagogikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin1861946
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal of Learning Analytics&rft.volume=7&rft.spage=33&rft.date=2020
dc.identifier.jtitleJournal of Learning Analytics
dc.identifier.volume7
dc.identifier.issue3
dc.identifier.startpage33
dc.identifier.endpage47
dc.identifier.doihttps://doi.org/10.18608/jla.2020.73.4
dc.identifier.urnURN:NBN:no-84842
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn1929-7750
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/81820/2/Kaliisa%2Bet%2Bal_Checkpoint%2B%2526%2BProcess%2BLA.pdf
dc.type.versionPublishedVersion


Files in this item

Appears in the following Collection

Hide metadata

Attribution-NonCommercial-NoDerivs 3.0 Unported
This item's license is: Attribution-NonCommercial-NoDerivs 3.0 Unported