Learning analytics in support of inclusiveness and disabled students: a systematic review

被引:0
|
作者
Mohammad Khalil
Sharon Slade
Paul Prinsloo
机构
[1] University of Bergen,Centre for the Science of Learning & Technology (SLATE)
[2] EarthTrust,undefined
[3] University of South Africa,undefined
关键词
Learning analytics; Inclusiveness; Disability; Disadvantaged groups; Disadvantaged students;
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中图分类号
学科分类号
摘要
This article maps considerations of inclusiveness and support for students with disabilities by reviewing articles within the field of learning analytics. The study involved a PRISMA-informed systematic review of two popular digital libraries, namely Clarivate’s Web of Science, and Elsevier’s Scopus for peer-reviewed journal articles and conference proceedings. A final corpus of 26 articles was analysed. Findings show that although the field of learning analytics emerged in 2011, none of the studies identified here covered topics of inclusiveness in education before the year of 2016. Screening also shows that learning analytics provides great potential to promote inclusiveness in terms of reducing discrimination, increasing retention among disadvantaged students, and validating particular learning designs for marginalised groups. Gaps in this potential are also identified. The article aims to provide valuable insight into what is known about learning analytics and inclusiveness and contribute knowledge to this particular nascent area for researchers and institutional stakeholders.
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页码:202 / 219
页数:17
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