Mining LMS data to develop an “early warning system” for educators: A proof of concept

Macfadyen, Leah P.; Dawson, Shane

doi:10.1016/j.compedu.2009.09.008

Cited by 1,045Online Learning and AnalyticsOnline and Blended LearningIntelligent Tutoring Systems and Adaptive Learning

Mining LMS data to develop an “early warning system” for educators: A proof of concept

Macfadyen, Leah P., Dawson, Shane·2010·Computers & Education

DOI 10.1016/j.compedu.2009.09.008

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Time spent on educational resources, as indicated by LA data, did not correlate to academic performance, despite the correlation between engagement and academic performance.
“Macfadyen and Dawson (2010), for example, found that time spent on educational resources, as indicated by LA data, did not correlate to academic performance despite the correlation between engagement and academic performance.”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Macfadyen and Dawson (2010)

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Authors: Macfadyen, L. P., & Dawson, S.
Affiliations: University of British Columbia (CA)
University of Wollongong (AU)
Corresponding author: Macfadyen, Leah P.
ORCID: Macfadyen, Leah P.
Dawson, Shane
Venue: Computers & Education
Publisher: Elsevier BV
Published: 2010-02
Volume: 54
Issue: 2
Pages: 588-599
ISSN: 0360-1315 (ISSN-L)
DOI: 10.1016/j.compedu.2009.09.008
OpenAlex: W2153378020
Cited by: 1,045
References: 51
Citations by year: 2026: 64 · 2025: 47 · 2024: 59 · 2023: 55 · 2022: 75 · 2021: 79 · 2020: 86 · 2019: 98 · 2018: 105 · 2017: 75 · 2016: 83 · 2015: 61 · 2014: 64 · 2013: 26 · 2012: 41
FWCI: 59.51
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Computers & Education (publishedVersion)
Research Online (University of Wollongong) (submittedVersion)
Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
Funders: Australian Government
Topics: Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Social Sciences › Education › Online and Blended Learning
Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords: learning management system data, early warning systems, at-risk students, student performance prediction, student engagement, forum, network analysis, student learning communities, educational dashboards, higher education

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Mining LMS data to develop an “early warning system” for educators: A proof of concept

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