Indicators of engagement
Open accessAbstract
Student engagement has become synonymous with the measurement of teaching and learning quality at universities. The almost global adoption of learning management systems as a technical solution to e-learning within universities and their ability to record and track user behaviour provides the academy with an unprecedented opportunity to harness captured data relating to student engagement. This is an exploratory study that aims to show how data from learning management systems can be used as an indicator of student engagement and how patterns in the data have changed with CQUniversity?s recent adoption of Moodle as its single learning management system.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Student engagement has been investigated from a number of angles within a wide range of digital learning modalities, often using measures that claim to reflect engagement from learning management systems (LMS).
“student engagement has been investigated from a number of angles within a wide range of digital learning modalities, often using measures that claim to reflect engagement from learning management systems (LMS) (Beer et al., 2010).”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Beer et al., 2010
The Introduction and LMS indicators of engagement section describe using LMS activity data, including click counts from Blackboard and Moodle, as possible indicators of student engagement. The Engagement section also describes engagement as having several dimensions. The paper does not establish that engagement has been investigated across a wide range of digital learning modalities; its investigation focuses on LMS-based learning. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Does Active Learning Work? A Review of the Research
Prince, M. (2004) · Journal of Engineering Education · doi:10.1002/j.2168-9830.2004.tb00809.x · Cited by 7,334 · cited 2× · see citing works
“The core components of active learning are student activity and engagement in the learning process (Prince, 2004).”
Flagged first, then by citations
Research works printed but not linked: 18
- Blin, F., & Muro, M. (2007). Why hasn't tecnology disrupted academics' teaching practices? Understanding resistance to change through the lens of activity theory. Computers and Education, 50(2008), 15. https://doi.org/10.1016/j.compedu.2007.09.017 · DOI
- Bulger, M. E., Mayer, R. E., Almeroth, K. C., & Blau, S. D. (2008). Measuring Learner Engagement in Computer-Equipped College Classrooms. Journal of Educational Multimedia and Hypermedia, 17(2), 129-143. · DOI
- Campbell, J. P., Oblinger, D. G., & DeBlois, P. B. (2007). Academic Analytics. Educause Review(July/August 2007).
- Chen, P.-S. D., Gonyea, R., & Kuh, G. (2008). Learning at a distance. Journal of online education, 4(3). http://innovateonline.info/index.php?view=article&id=438&action=login
- Coates, H. (2007). A model of online and general campus-based student engagement. Assessment & Evaluation in Higher Education, 32(2), 121-141. https://doi.org/10.1080/02602930600801878 ___________________________________________________________________________________ Proceedings ascilite Sydney 2010: Full paper: Beer, Clark & Jones 85 · DOI
- Coates, H., James, R., & Baldwin, G. (2005). A critical examination of the effects of learning management systems on university teaching and learning. [Journal Article]. Tertiary education and management, 11(2005), 19-36. https://doi.org/10.1080/13583883.2005.9967137 · DOI
- Dawson, S., Macfadyen, L., & Lockyer, L. (2009). Learning or performance: Predicting drivers of student motivation. Paper presented at the Same places, different spaces. Proceedings ascilite Auckland 2009, Auckland. · DOI
- Douglas, I. (2008, 14 December 2008). Measuring Participation in Internet Supported Courses. Paper presented at the 2008 International Conference on Computer Science and Software Engineering, Wuhan, China. https://doi.org/10.1109/CSSE.2008.1632 · DOI
- Douglas, I., & Alemanne, N. D. (2007). Measuring Student Participation and Effort. Paper presented at the International Conference on Cognition and Exploratory Learning in Digital Age, Algarve, Portugal.
- Dutton, J., Durron, M., & Perry, J. (2002). How Do Online Students Differ From Lecture Students? [Journal]. Journal for Asynchronous Learning Networks, 6(1), 20.
- Eynon, R., Fry, J., & Schroeder, R. (2008). The ethics of internet research. In N. Fielding, R. M. Lee & G. Blank (Eds.), The handbook of online research methods (pp. 18). London: SAGE Publications.
- Heathcoate, L., & Dawson, S. (2005). Data Mining for Evaluation, Benchmarking and Reflective Practice in a LMS. E-Learn 2005: World conference on E-Learning in corporate, government, healthcare and higher education.
- Kirkup, M., & Carrigan, M. (2000). Video surveillance research in retailing: Ethical issues. Internation Journal of Retail and Distribution Management, 28(11), 10.
- Malikowski, S. R., Thompson, M. E., & Theis, J. G. (2007). A model for research into course management systems: bridging technology and learning theory. [Research paper]. Journal of educational computing research, 36(2)(2007), 24. https://doi.org/10.2190/1002-1T50-27G2-H3V7 · DOI
- McAlpine, L., & Weston, C. (2004). Reflection: issues related to improving professors' teaching and students' learning. Instructional Science, 28(5), 363-385. · DOI
- Purdue University. (2009). Signals tells students how they're doing even before the test. http://news.uns.purdue.edu/x/2009b/090827ArnoldSignals.html · DOI
- Vrasidas, C., & McIsaac, M. S. (1999). Factors influencing interaction in an online course. American Journal of Distance Education, 13(3), 22-36.
- West, R. E., Waddoups, G., & Graham, C. R. (2006). Understanding the experiences of instructors as they adopt a course management system. Educational Technology Research and Development, 55(1), 1-26. https://doi.org/10.1007/s11423-006-9018-1 · DOI
Cited by
Sorted by citations
Engagement in Online Learning: Student Attitudes and Behavior During COVID-19
Hollister, B., Nair, P., Hill-Lindsay, S., & Chukoskie, L. (2022) · Frontiers in Education · doi:10.3389/feduc.2022.851019 · Cited by 317 · see citing works
Engaging with assessment: Increasing student engagement through continuous assessment
Holmes, N. (2018) · Active Learning in Higher Education · doi:10.1177/1469787417723230 · Cited by 150 · see citing works
Unpacking student engagement in higher education learning analytics: a systematic review
Bergdahl, N., Bond, M., Sjöberg, J., Dougherty, M., & Oxley, E. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00493-y · Cited by 138 · see citing works
Rodriguez-Triana, M. J., Prieto, L. P., Holzer, A., & Gillet, D. (2020) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2020.2995557 · Cited by 33 · see citing works
Modelling adult learners’ online engagement behaviour: proxy measures and its application
Wong, A., & Chong, S. (2018) · Journal of Computers in Education · doi:10.1007/s40692-018-0123-z · Cited by 23 · see citing works
- Authors
- Beer, C., Clark, K., & Jones, D.
- Affiliations
- Central Queensland University (AU)
- Venue
- ASCILITE Publications
- Publisher
- Open Access Publishing Association
- Published
- 2010-12-01
- Volume
- 2010
- Issue
- 1
- Pages
- 75-86
- ISSN
- 2653-665X (ISSN-L)
- OpenAlex
- W2260563388
- Cited by
- 169
- References
- 1
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 6 · 2023: 11 · 2022: 11 · 2021: 27 · 2020: 11 · 2019: 5 · 2018: 16 · 2017: 15 · 2016: 12 · 2015: 13 · 2014: 16 · 2013: 5 · 2012: 11
- FWCI
- 14.83
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- ASCILITE Publications (publishedVersion, cc-by)
- Acquire (CQUniversity) (submittedVersion)
- Figshare (submittedVersion)
- ASCILITE - Australian Society for Computers in Learning in Tertiary Education Annual Conference
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Social Sciences › Education › Online and Blended Learning
- Keywords
- student engagement, virtual learning environments, Moodle, engagement metrics, online learning, user behavior data, teaching and learning quality
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
