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Article

Revealing Impact Factors on Student Engagement: Learning Analytics Adoption in Online and Blended Courses in Higher Education

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School of Education, University of Tasmania, Launceston, TAS 7248, Australia
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School of Information and Communication Technology, University of Tasmania, Hobart, TAS 7001, Australia
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Tasmanian Institute of Learning and Teaching, University of Tasmania, Hobart, TAS 7001, Australia
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Department of Computing, Hong Kong Polytechnic University, Hong Kong, China
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School of Humanities, University of Tasmania, Launceston, TAS 7248, Australia
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Author to whom correspondence should be addressed.
Academic Editors: Marija Kuzmanović and Dragana Makajić-Nikolić
Educ. Sci. 2021, 11(10), 608; https://doi.org/10.3390/educsci11100608
Received: 30 August 2021 / Revised: 22 September 2021 / Accepted: 24 September 2021 / Published: 2 October 2021
(This article belongs to the Special Issue Student Preferences and Satisfaction: Measurement and Optimization)
This study aimed to identify factors influencing student engagement in online and blended courses at one Australian regional university. It applied a data science approach to learning and teaching data gathered from the learning management system used at this university. Data were collected and analysed from 23 subjects, spanning over 5500 student enrolments and 406 lecturer and tutor roles, over a five-year period. Based on a theoretical framework adapted from Community of Inquiry (CoI) framework by Garrison et al. (2000), the data were segregated into three groups for analysis: Student Engagement, Course Content and Teacher Input. The data analysis revealed a positive correlation between Student Engagement and Teacher Input, and interestingly, a negative correlation between Student Engagement and Course Content when a certain threshold was exceeded. The findings of the study offer useful suggestions for future course design, and pedagogical approaches teachers can adopt to foster student engagement. View Full-Text
Keywords: learning analytics; higher education; student engagement; student retention; learning management system (LMS) learning analytics; higher education; student engagement; student retention; learning management system (LMS)
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MDPI and ACS Style

Fan, S.; Chen, L.; Nair, M.; Garg, S.; Yeom, S.; Kregor, G.; Yang, Y.; Wang, Y. Revealing Impact Factors on Student Engagement: Learning Analytics Adoption in Online and Blended Courses in Higher Education. Educ. Sci. 2021, 11, 608. https://doi.org/10.3390/educsci11100608

AMA Style

Fan S, Chen L, Nair M, Garg S, Yeom S, Kregor G, Yang Y, Wang Y. Revealing Impact Factors on Student Engagement: Learning Analytics Adoption in Online and Blended Courses in Higher Education. Education Sciences. 2021; 11(10):608. https://doi.org/10.3390/educsci11100608

Chicago/Turabian Style

Fan, Si, Lihua Chen, Manoj Nair, Saurabh Garg, Soonja Yeom, Gerry Kregor, Yu Yang, and Yanjun Wang. 2021. "Revealing Impact Factors on Student Engagement: Learning Analytics Adoption in Online and Blended Courses in Higher Education" Education Sciences 11, no. 10: 608. https://doi.org/10.3390/educsci11100608

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