Identifying significant indicators using LMS data to predict course achievement in online learning
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
When the continuous assessment process of a course drastically changes, adding or reducing the number of activities or the typology of the exercises included, the GAR model is invalid because the historical data will be useless to predict learners' performance according to the new assessment model.
“When the continuous assessment process of a course drastically changes, adding or reducing the number of activities or the typology of the exercises included, the GAR model is invalid because the historical data will be useless to predict learners' performance according to the new assessment model.”
From Experiences in the use of an adaptive intelligent system to enhance online learners' performance: a case study in Economics and Business courses (2021) · cites this paper as You 2016
Cites
Motivational and self-regulated learning components of classroom academic performance.
Pintrich, P. R., & De Groot, E. V. (1990) · Journal of Educational Psychology · doi:10.1037/0022-0663.82.1.33 · Cited by 8,332 · see citing works
Sun, P.-C., Tsai, R. J., Finger, G., Chen, Y.-Y., & Yeh, D. (2008) · Computers & Education · doi:10.1016/j.compedu.2006.11.007 · Cited by 2,726 · see citing works
(1993) · Cited by 1,939 · see citing works
Learning analytics: drivers, developments and challenges
Ferguson, R. (2012) · International Journal of Technology Enhanced Learning · doi:10.1504/ijtel.2012.051816 · Cited by 1,357 · see citing works
Improving online learning: Student perceptions of useful and challenging characteristics
Song, L., Singleton, E. S., Hill, J. R., & Koh, M. H. (2004) · The Internet and Higher Education · doi:10.1016/j.iheduc.2003.11.003 · Cited by 1,132 · see citing works
Constructivism and computer‐mediated communication in distance education
Jonassen, D., Davidson, M., Collins, M., Campbell, J., & Haag, B. B. (1995) · American Journal of Distance Education · doi:10.1080/08923649509526885 · Cited by 1,117 · see citing works
Construct validation of a strategy model of student self-regulated learning.
Zimmerman, B. J., & Martinez-Pons, M. (1988) · Journal of Educational Psychology · doi:10.1037/0022-0663.80.3.284 · Cited by 1,064 · see citing works
Let’s not forget: Learning analytics are about learning
Gašević, D., Dawson, S., & Siemens, G. (2015) · TechTrends · doi:10.1007/s11528-014-0822-x · Cited by 1,049 · see citing works
Mining LMS data to develop an “early warning system” for educators: A proof of concept
Macfadyen, L. P., & Dawson, S. (2010) · Computers & Education · doi:10.1016/j.compedu.2009.09.008 · Cited by 1,045 · see citing works
Mega, C., Ronconi, L., & De Beni, R. (2014) · Journal of Educational Psychology · doi:10.1037/a0033546 · Cited by 1,007 · see citing works
Development of achievement motivation
(2002) · Choice Reviews Online · doi:10.5860/choice.40-1049 · Cited by 812 · see citing works
Understanding procrastination from a self-regulated learning perspective.
Wolters, C. A. (2003) · Journal of Educational Psychology · doi:10.1037/0022-0663.95.1.179 · Cited by 679 · see citing works
The Development of Academic Self-Regulation
Pintrich, P. R., & Zusho, A. (2002) · Elsevier eBooks · doi:10.1016/b978-012750053-9/50012-7 · Cited by 539 · see citing works
Academic Analytics: A New Tool for a New Era.
Campbell, J. P., DeBlois, P. B., & Oblinger, D. G. (2007) · Educational Review · Cited by 505 · see citing works
Puzziferro, M. (2008) · American Journal of Distance Education · doi:10.1080/08923640802039024 · Cited by 480 · see citing works
Predictors for Student Success in an Online Course
Yükseltürk, E., & Bulut, S. (2007) · Cited by 445 · see citing works
An overview of learning analytics
Clow, D. (2013) · Teaching in Higher Education · doi:10.1080/13562517.2013.827653 · Cited by 436 · see citing works
Early Alert of Academically At-Risk Students: An Open Source Analytics Initiative
Jayaprakash, S. M., Moody, E. W., Lauría, E. J. M., Regan, J. R., & Baron, J. D. (2014) · Journal of Learning Analytics · doi:10.18608/jla.2014.11.3 · Cited by 424 · see citing works
Tracking student behavior, persistence, and achievement in online courses
Morris, L. V., Finnegan, C., & Wu, S.-S. (2005) · The Internet and Higher Education · doi:10.1016/j.iheduc.2005.06.009 · Cited by 424 · see citing works
Issues in the Measurement of Metacognition
Schraw, G. J., & Impara, J. C. (2000) · Cited by 407 · see citing works
Electronic collaborators: learner-centered technologies for literacy, apprenticeship, and discourse
(1999) · Choice Reviews Online · doi:10.5860/choice.37-0448 · Cited by 400 · see citing works
Procrastination, participation, and performance in online learning environments
Michinov, N., Brunot, S., Bohec, O. L., Juhel, J., & Delaval, M. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.07.025 · Cited by 394 · see citing works
Huang, S., & Fang, N. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.08.015 · Cited by 374 · see citing works
Current state and future trends
Dawson, S., Gašević, D., Siemens, G., & Joksimovíc, S. (2014) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2567574.2567585 · Cited by 328 · see citing works
Using learning analytics to predict (and improve) student success: a faculty perspective
Dietz-Uhler, B. L., & Hurn, J. E. (2013) · Cited by 316 · see citing works
Examining trace data to explore self-regulated learning
Hadwin, A. F., Nesbit, J. C., Jamieson‐Noel, D., Code, J., & Winne, P. H. (2007) · Metacognition and Learning · doi:10.1007/s11409-007-9016-7 · Cited by 279 · see citing works
Wang, A. Y., & Newlin, M. H. (2002) · Computers in Human Behavior · doi:10.1016/s0747-5632(01)00042-5 · Cited by 257 · see citing works
Supporting Self-Regulation in Student-Centered Web-Based Learning Environments
Dabbagh, N. H., & Kitsantas, A. (2004) · International journal on e-learning · Cited by 255 · see citing works
The Impact of Online Graduate Students' Motivation and Self-Regulation on Academic Procrastination
Rakes, G. C., & Dunn, K. E. (2010) · Cited by 229 · see citing works
You, J. W., & Kang, M. (2014) · Computers & Education · doi:10.1016/j.compedu.2014.04.018 · Cited by 225 · see citing works
Self-citationProcrastination in Online Courses: Performance and Attitudinal Differences
Elvers, G. C., Polzella, D. J., & Graetz, K. (2003) · Teaching of Psychology · doi:10.1207/s15328023top3002_13 · Cited by 146 · see citing works
Procrastination in a distance university setting
Klingsieck, K. B., Fries, S., Horz, C., & Hofer, M. (2012) · Distance Education · doi:10.1080/01587919.2012.723165 · Cited by 136 · see citing works
The skinny on big data in education: Learning analytics simplified
Reyes, J. A. (2015) · TechTrends · doi:10.1007/s11528-015-0842-1 · Cited by 135 · see citing works
Examining the Effect of Academic Procrastination on Achievement Using LMS Data in E-Learning.
You, J. W. (2015) · Educational Technology & Society · Cited by 133 · see citing works
Self-citationData for free: Using LMS activity logs to measure community in online courses
Black, E. W., Dawson, K., & Priem, J. R. (2008) · The Internet and Higher Education · doi:10.1016/j.iheduc.2008.03.002 · Cited by 118 · see citing works
Student Alienation, Academic Achievement, and WebCT Use.
Johnson, G. M. (2005) · Cited by 117 · see citing works
Promoting Academic Motivation and Self-Regulation: Practical Guidelines for Online Instructors
Artino, A. R. (2008) · TechTrends · doi:10.1007/s11528-008-0153-x · Cited by 115 · see citing works
Larusson, J. A., & White, B. (2014) · Springer eBooks · doi:10.1007/978-1-4614-3305-7 · Cited by 91 · see citing works
Self-Regulatory Behavior Influences in Distance Learning
King, F. B., Harner, M. J., & Brown, S. W. (2000) · International journal of instructional media · Cited by 74 · see citing works
Tuckman, B. W. (2005) · Psychological Reports · doi:10.2466/pr0.96.3c.1015-1021 · Cited by 74 · see citing works
Access Patterns of Online Materials in a Blended Course
Asarta, C. J., & Schmidt, J. R. (2012) · Decision Sciences Journal of Innovative Education · doi:10.1111/j.1540-4609.2012.00366.x · Cited by 72 · see citing works
Detecting the Learner's Motivational States in An Interactive Learning Environment
Qu, L., & Johnson, W. L. (2005) · Cited by 68 · see citing works
Student Hits in an Internet‐Supported Course: How Can Instructors Use Them and What Do They Mean?
Dan, A. (2003) · Decision Sciences Journal of Innovative Education · doi:10.1111/j.1540-4609.2003.00016.x · Cited by 67 · see citing works
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Pistilli, M., USA, L. '. L. A. A. K. C. 2. 2. I. I., & Association for Computing Machinery-Digital Library (2014) · doi:10.1145/2567574 · Cited by 65 · see citing works
Designing Learning Analytics Experiences
Pardo, A. (2014) · Springer eBooks · doi:10.1007/978-1-4614-3305-7_2 · Cited by 58 · see citing works
Joo, Y. J., Joung, S., & Kim, J. (2012) · Interactive Learning Environments · doi:10.1080/10494820.2012.745421 · Cited by 56 · see citing works
A Study of Online Exams Procrastination Using Data Analytics Techniques
Levy, Y. M., & Ramim, M. M. (2012) · Interdisciplinary Journal of e-Skills and Lifelong Learning · doi:10.28945/1730 · Cited by 53 · see citing works
Models of Asynchronous Computer Conferencing for Collaborative Learning in Large College Classes
(2012) · Routledge eBooks · doi:10.4324/9780203053805-17 · Cited by 22 · see citing works
Jo, I., & Kim, Y. (2013) · Cited by 17 · see citing works
Early Participation in Asynchronous Writing Environments and Course Success
Warnock, S., Bingham, K., Driscoll, D., et al. (2012) · Online Learning · doi:10.24059/olj.v16i1.178 · Cited by 8 · see citing works
"Relationships between e-Learning Strategies and Learning Achievement"
Lee, I. (2002) · Journal of Educational Technology · doi:10.17232/kset.18.2.51 · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Aldowah, H., Al-Samarraie, H., & Fauzy, W. M. (2019) · Telematics and Informatics · doi:10.1016/j.tele.2019.01.007 · Cited by 564 · see citing works
Learning Management System (LMS) Use with Online Instruction
Bradley, V. M. (2020) · International Journal of Technology in Education · doi:10.46328/ijte.36 · Cited by 349 · see citing works
Prediction of students’ early dropout based on their interaction logs in online learning environment
Mubarak, A. A., Cao, H., & Zhang, W. (2022) · Interactive Learning Environments · doi:10.1080/10494820.2020.1727529 · Cited by 170 · see citing works
An early feedback prediction system for learners at-risk within a first-year higher education course
Baneres, D., Rodriguez, M. E., & Serra, M. (2019) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2019.2912167 · Cited by 128 · see citing works
Paulsen, L., & Lindsay, E. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12401-4 · Cited by 111 · see citing works
Examining the use of prompts to facilitate self-regulated learning in Massive Open Online Courses
Wong, J., Baars, M., de Koning, B. B., & Paas, F. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106596 · Cited by 88 · see citing works
Investigating temporal access in a flipped classroom: procrastination persists
AlJarrah, A., Thomas, M. K., & Shehab, M. (2018) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-017-0083-9 · Cited by 86 · see citing works
Using trace data to enhance Students' self-regulation: A learning analytics perspective
Ye, D., & Pennisi, S. (2022) · The Internet and Higher Education · doi:10.1016/j.iheduc.2022.100855 · Cited by 69 · see citing works
Guerrero-Roldán, A.-E., Rodríguez-González, M. E., Bañeres, D., Elasri-Ejjaberi, A., & Cortadas, P. (2021) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-021-00271-0 · Cited by 50 · see citing works
A SYSTEMATIC REVIEW OF THE TENDENCIES IN THE USE OF LEARNING MANAGEMENT SYSTEMS
ALTINPULLUK, H., & KESIM, M. (2021) · Turkish Online Journal of Distance Education · doi:10.17718/tojde.961812 · Cited by 49 · see citing works
Wang, Q., & Mousavi, A. (2023) · British Journal of Educational Technology · doi:10.1111/bjet.13282 · Cited by 38 · see citing works
Learning Analytics Lens: Improving Quality of Higher Education
Hooda, M. (2020) · International Journal of Emerging Trends in Engineering Research · doi:10.30534/ijeter/2020/24852020 · Cited by 30 · 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
Bond, M., Viberg, O., & Bergdahl, N. (2023) · LAK23: 13th International Learning Analytics and Knowledge Conference · doi:10.1145/3576050.3576085 · Cited by 8 · see citing works
Aida, S. (2023) · Education Sciences · doi:10.3390/educsci13101005 · Cited by 8 · see citing works
Mumcu, B. B., & Çebi, A. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00537-x · Cited by 7 · see citing works
“The use of such log data allows for a concrete assessment of students’ behavior on online learning platforms (You, 2016).”
- Authors
- You, J. W.
- Affiliations
- Gachon University (KR)
- Corresponding author
- You, Ji Won
- ORCID
- You, Ji Won
- Venue
- The Internet and Higher Education
- Publisher
- Elsevier BV
- Published
- 2016-04
- Volume
- 29
- Pages
- 23-30
- ISSN
- 1096-7516 (ISSN-L)
- OpenAlex
- W2183210442
- Cited by
- 388
- References
- 51
- Citations by year
- 2026: 29 · 2025: 17 · 2024: 30 · 2023: 42 · 2022: 64 · 2021: 53 · 2020: 57 · 2019: 41 · 2018: 27 · 2017: 17 · 2016: 11
- FWCI
- 27.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Internet and Higher Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Education › Online and Blended Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Keywords
- learning management system data, student self-regulation, university students, online learning
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