Modelling adult learners’ online engagement behaviour: proxy measures and its application

Wong, Adam; Chong, Sylvia

doi:10.1007/s40692-018-0123-z

Cited by 23Online Learning and AnalyticsOnline and Blended LearningCustomer churn and segmentation

Modelling adult learners’ online engagement behaviour: proxy measures and its application

Wong, Adam, Chong, Sylvia·2018·Journal of Computers in Education

DOI 10.1007/s40692-018-0123-z

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A substantial number of studies demonstrated strong theoretical grounding by integrating established engagement frameworks into their analyses.
“A substantial number of studies demonstrated strong theoretical grounding by integrating established engagement frameworks into their analyses (e.g., Tempelaar et al., 2018;Wong & Chong, 2018).”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Wong & Chong, 2018

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“Moreover, Wong and Chong (2018) defined online engagement as a unique collection of comprised active and collaborative learning, participation in enriching learning activities, communication with teachers and among learners, involvement in educational experiences, and feeling supported.”
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“In addition, there is a growing interest in analyzing LMS log data to measure student engagement in online learning environments, especially from a behavioral perspective (Umer et al., 2018; Wong and Chong, 2018; Motz et al., 2019; Lu and Cutumisu, 2022).”
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Authors: Wong, A., & Chong, S.
Affiliations: Singapore University of Social Sciences (SG)
Corresponding author: Chong, Sylvia
ORCID: Wong, Adam
Venue: Journal of Computers in Education
Publisher: Springer Science and Business Media LLC
Published: 2018-09-28
Volume: 5
Issue: 4
Pages: 463-479
ISSN: 2197-9987 (ISSN-L)
2197-9995
DOI: 10.1007/s40692-018-0123-z
OpenAlex: W2893188185
Cited by: 23
References: 46
Citations by year: 2025: 2 · 2024: 3 · 2023: 5 · 2022: 6 · 2021: 3 · 2020: 2 · 2019: 2
FWCI: 2.21
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Journal of Computers in Education (publishedVersion)
Funders: Singapore University of Social Sciences (RF16IRA01)
Topics: Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Social Sciences › Education › Online and Blended Learning
Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
Keywords: adult learners, online engagement, learning analytics, RFM model, online learning behavior, online learning platforms, engagement patterns

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