Title: A review on the ways to determine at-risk students in online learning

Authors: Si Na Kew; Zaidatun Tasir

Addresses: Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, 81310, Skudai, Johor Bahru, Malaysia ' Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, 81310, Skudai, Johor Bahru, Malaysia

Abstract: The systematic review on the ways to identify at-risk students is still limited. Hence, the purpose of this paper is to review the related papers so as to show a clear picture on the way to identify at-risk students by analysing their learning behaviours in online learning, including: 1) a brief introduction of each related research; 2) the purpose and the setting of the research; 3) the determinant of at-risk students; 4) the types of data being analysed to find out at-risk students; 5) the kind of tools or analytics methods used to determine at-risk students; 6) the strategies or intervention being suggested or applied to assist at-risk students. The results show that most of the data analytics techniques such as regression analysis have successfully identified at-risk students. Moreover, the determinant of at-risk students such as course grades, etc., and different strategies and intervention are summarised in this paper.

Keywords: online learning; at-risk students; log data; data analytics technique; learning analytics; learning behaviour.

DOI: 10.1504/IJDET.2022.124992

International Journal of Digital Enterprise Technology, 2022 Vol.2 No.1, pp.54 - 71

Accepted: 11 Oct 2020
Published online: 22 Aug 2022 *

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