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The current landscape of learning analytics in higher education
The Royal Institute of Technology (KTH), School of Electrical Engineering and Computer Science, Stockholm, Sweden.
Örebro universitet, Handelshögskolan vid Örebro Universitet. (Informatik)ORCID-id: 0000-0003-1076-3442
The Royal Institute of Technology (KTH), School of Electrical Engineering and Computer Science, Stockholm, Sweden.
The Royal Institute of Technology (KTH), School of Electrical Engineering and Computer Science, Stockholm, Sweden.
2018 (Engelska)Ingår i: Computers in human behavior, ISSN 0747-5632, E-ISSN 1873-7692, Vol. 89, s. 98-110Artikel, forskningsöversikt (Refereegranskat) Published
Abstract [en]

Learning analytics can improve learning practice by transforming the ways we support learning processes. This study is based on the analysis of 252 papers on learning analytics in higher education published between 2012 and 2018. The main research question is: What is the current scientific knowledge about the application of learning analytics in higher education? The focus is on research approaches, methods and the evidence for learning analytics. The evidence was examined in relation to four earlier validated propositions: whether learning analytics i) improve learning outcomes, ii) support learning and teaching, iii) are deployed widely, and iv) are used ethically. The results demonstrate that overall there is little evidence that shows improvements in students' learning outcomes (9%) as well as learning support and teaching (35%). Similarly, little evidence was found for the third (6%) and the forth (18%) proposition. Despite the fact that the identified potential for improving learner practice is high, we cannot currently see much transfer of the suggested potential into higher educational practice over the years. However, the analysis of the existing evidence for learning analytics indicates that there is a shift towards a deeper understanding of students’ learning experiences for the last years.

Ort, förlag, år, upplaga, sidor
Elsevier, 2018. Vol. 89, s. 98-110
Nyckelord [en]
Learning analytics, Literature review, Higher education, Research methods, Evidence
Nationell ämneskategori
Systemvetenskap, informationssystem och informatik med samhällsvetenskaplig inriktning
Forskningsämne
Informatik
Identifikatorer
URN: urn:nbn:se:oru:diva-68631DOI: 10.1016/j.chb.2018.07.027ISI: 000449136900011Scopus ID: 2-s2.0-85053083367OAI: oai:DiVA.org:oru-68631DiVA, id: diva2:1243090
Tillgänglig från: 2018-08-30 Skapad: 2018-08-30 Senast uppdaterad: 2018-11-20Bibliografiskt granskad

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Hatakka, Mathias

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