Publication:
The divergence of learning analytics research

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dc.citedby1
dc.contributor.authorKhuzairi N.M.S.en_US
dc.contributor.authorCob Z.C.en_US
dc.contributor.authorid56955746800en_US
dc.contributor.authorid25824919900en_US
dc.date.accessioned2023-05-29T08:10:21Z
dc.date.available2023-05-29T08:10:21Z
dc.date.issued2020
dc.description.abstractThis study represents a review of Learning Analytics journals with the goal to examine reported research objectives, educational data collected and the intended end-user of the corresponding analysed data proposed by all current studies available in relevant databases. A total of 62 research articles were selected from an initial accumulation of 373 papers for this review. The findings present a clear divergence of Learning Analytics research into distinct subsets and it is revealed that the term �Learning Analytics� is labelled indiscriminately. We then show how a categorization of research subsets will prompt a reduction of term sprawl and also to avert confusion in the current education research environment. With this key points above we offer an approach to classify future Learning Analytics research into three specific subsets (student-centric, teacher-centric and institution-centric) based on identifiable criteria with the goal of fostering new avenues for future ground breaking research works in education. � 2020 SERSC.en_US
dc.description.natureFinalen_US
dc.identifier.epage1571
dc.identifier.issue6 Special Issue
dc.identifier.scopus2-s2.0-85083704936
dc.identifier.spage1558
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85083704936&partnerID=40&md5=428b18c24edb48287beecf1ab3ac989d
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25512
dc.identifier.volume29
dc.publisherScience and Engineering Research Support Societyen_US
dc.sourceScopus
dc.sourcetitleInternational Journal of Advanced Science and Technology
dc.titleThe divergence of learning analytics researchen_US
dc.typeArticleen_US
dspace.entity.typePublication
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