The DOI matches its Crossref record; 57 of the 59 references it cites were found in a registry or an index.
In search for the most informative data for feedback generation: Learning analytics in a data-rich context
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In the citing paper
“Examples of popular LMS include Moodle, WebCT, Blackboard, and Sakai (Tempelaar et al., 2015).”
From Using information and communication technology (ICT)-based data systems to support teacher data-driven decision-making: Insights from the literature (2013–2023) (2024) · cites this paper as Tempelaar et al., 2015
In the citing paper
“This data type is one of the most commonly employed in LA studies (Azcona et al., 2019; Tempelaar et al., 2015).”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Tempelaar et al., 2015
In the citing paper
“Our review suggests that assessment data mostly serve educators with evidence-based formative and summative assessment (e.g. Choi & Cho, 2020; Tempelaar et al., 2015).”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Tempelaar et al., 2015
In the citing paper
“Methods used to support feedback include predictive modelling (Azcona et al., 2019; Tempelaar et al., 2015), classifi cation (Baneres et al., 2019), clustering (Lim, Gasevic, et al., 2021; Tempelaar et al., 2018; Tsai et al., 2021), Bayesian network analysis (Choi & Cho, 2020), natural language processing (Perikos et al., 2017), process mining (Sedrakyan et al., 2016), relationship mining (T”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Tempelaar et al., 2015
Citations
Cites
Visible learning: a synthesis of over 800 meta‐analyses relating to achievement
Carter, M. (2009) · Educational Psychology · doi:10.1080/01443410903415150 · Cited by 7,696
(2008) · Cited by 6,939
Handbook of educational psychology
(1997) · Choice Reviews Online · doi:10.5860/choice.34-3084 · Cited by 4,850
Handbook of Research on Educational Communications and Technology
(2013) · Routledge eBooks · doi:10.4324/9781410609519 · Cited by 2,744
Pekrun, R., Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2011) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2010.10.002 · Cited by 2,248
Handbook of Research on Educational Communications and Technology
Jonassen, D. H., Spector, M. J., Driscoll, M., Merrill, M. D., van Merriënboer, J. J. G., & Driscoll, M. P. (2008) · Routledge eBooks · doi:10.4324/9780203880869 · Cited by 1,692
Aligning assessment with long‐term learning
Boud, D. J., & Falchikov, N. (2006) · Assessment & Evaluation in Higher Education · doi:10.1080/02602930600679050 · Cited by 1,516
Learning Analytics: The Emergence of a Discipline
Siemens, G. (2013) · American Behavioral Scientist · doi:10.1177/0002764213498851 · Cited by 1,284
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
Micheletta, S. (2013) · Form re - Open Journal per la formazione in rete · doi:10.13128/formare-13251 · Cited by 1,016
(2012) · DSpace (Open University in the Netherlands) · Cited by 754
Martin, A. J. (2006) · British Journal of Educational Psychology · doi:10.1348/000709906x118036 · Cited by 739
Vermunt, J. D. H. M. (1996) · Higher Education · doi:10.1007/bf00129106 · Cited by 684
The regulation of constructive learning processes
Vermunt, J. D. H. M. (1998) · British Journal of Educational Psychology · doi:10.1111/j.2044-8279.1998.tb01281.x · Cited by 658
Credé, M., & Niehorster, S. (2012) · Educational Psychology Review · doi:10.1007/s10648-011-9184-5 · Cited by 607
Bienkowski, M. A., Feng, M., & Means, B. (2012) · Cited by 586
Ferguson, R., & Shum, S. B. (2012) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2330601.2330616 · Cited by 553
A Structural Equation Model of Predictors for Effective Online Learning
Marks, R. B., Sibley, S. D., & Arbaugh, J. B. (2005) · Organizational Behavior Teaching Review · doi:10.1177/1052562904271199 · Cited by 499
An overview of learning analytics
Clow, D. (2013) · Teaching in Higher Education · doi:10.1080/13562517.2013.827653 · Cited by 436
Agudo-Peregrina, Á. F., Iglesías-Pradas, S., Conde, M. Á., & Hernández-García, Á. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.05.031 · Cited by 425
Shum, S. B., & Ferguson, R. (2012) · Cited by 399
Feedback Strategies for Interactive Learning Tasks
Narciss, S. (2007) · doi:10.4324/9780203880869.ch11 · Cited by 389
Schmidt, H. G., van der Molen, H. T., Winkel, W. T., & Wijnen, W. (2009) · Educational Psychologist · doi:10.1080/00461520903213592 · Cited by 383
Baker, R. S. (2010) · Elsevier eBooks · doi:10.1016/b978-0-08-044894-7.01318-x · Cited by 311
Lehmann, T., Hähnlein, I. S., & Ifenthaler, D. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.07.051 · Cited by 282
A Study of the Relationship between Student Social Networks and Sense of Community.
Dawson, S. (2008) · Adelaide Research & Scholarship (AR&S) (University of Adelaide) · Cited by 231
Teaching and Learning in Technology-Rich Environments
Lajoie, S. P., & Azevedo, R. (2015) · Routledge eBooks · doi:10.4324/9780203874790.ch35 · Cited by 206
Learning dispositions and transferable competencies
Shum, S. B., & Crick, R. D. (2012) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2330601.2330629 · Cited by 202
The role of academic motivation in Computer-Supported Collaborative Learning
Rienties, B., Tempelaar, D. T., den Bossche, P. V., Gijselaers, W., & Segers, M. S. R. (2009) · Computers in Human Behavior · doi:10.1016/j.chb.2009.05.012 · Cited by 198
Self-citationSuthers, D. D., Vatrapu, R., Medina, R., Joseph, S., & Dwyer, N. (2007) · Computers & Education · doi:10.1016/j.compedu.2006.10.007 · Cited by 197
Visualising the invisible: a network approach to reveal the informal social side of student learning
Hommes, J. E., Rienties, B., de Grave, W. S., Bos, G. M. J., Schuwirth, L., & Scherpbier, A. J. J. A. (2012) · Advances in Health Sciences Education · doi:10.1007/s10459-012-9349-0 · Cited by 188
Self-citationWolff, A., Zdráhal, Z., Nikolov, A., & Pantucek, M. (2013) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2460296.2460324 · Cited by 187
Dataset-Driven Research to Support Learning and Knowledge Analytics
Verbert, K., Manouselis, N., Drachsler, H., & Duval, E. (2012) · DSpace (Open University in the Netherlands) · Cited by 166
Narciss, S., & Huth, K. (2006) · Learning and Instruction · doi:10.1016/j.learninstruc.2006.07.003 · Cited by 162
Tempelaar, D. T., Niculescu, A., Rienties, B., Gijselaers, W., & Giesbers, B. (2011) · The Internet and Higher Education · doi:10.1016/j.iheduc.2011.10.003 · Cited by 153
Self-citationOpening Learning Management Systems to Personal Learning Environments
García‐Peñalvo, F. J., Alier, M., Casany, M. J., & Conde, M. Á. (2020) · RECERCAT (Consorci de Serveis Universitaris de Catalunya) · doi:10.3217/jucs-017-09-1222 · Cited by 151
System, scholar or students? Which most influences online MBA course effectiveness?
Arbaugh, J. B. (2014) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12048 · Cited by 111
Nijhuis, J. F. H., Segers, M. S. R., & Gijselaers, W. (2007) · Learning and Instruction · doi:10.1016/j.learninstruc.2007.01.009 · Cited by 100
Pedro, M. S., Baker, R. S., Gobert, J. D., Montalvo, O., & Nakama, A. (2011) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-011-9101-0 · Cited by 97
Nistor, N., Baltes, B., Dascălu, M., Mihailă, D., Smeaton, G. L., & Trăușan-Matu, Ș. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.10.051 · Cited by 96
Conde, M. Á., García‐Peñalvo, F. J., Conde, M. J. R., Alier, M., & García‐Holgado, A. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.05.023 · Cited by 78
Sadler, R. (2004) · Griffith Research Online · Cited by 77
Formative assessment and learning analytics
Tempelaar, D. T., Heck, A., Cuypers, H., van der Kooij, H., & van de Vrie, E. (2013) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2460296.2460337 · Cited by 75
Self-citationThe attainment of White and ethnic minority students in distance education
Richardson, J. T. E. (2011) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2010.534767 · Cited by 60
Analyzing the students’ behavior and relevant topics in virtual learning communities
Tobarra, L., Robles-Gómez, A., Ros, S., Hernández, R., & Caminero, A. C. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.10.001 · Cited by 59
Human–computer interaction in evolutionary visual software analytics
González-Torres, A., García‐Peñalvo, F. J., & Therón, R. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2012.01.013 · Cited by 38
Self- regulation and motivation in computer- supported collaborative learning environments
Järvelä, S., Hurme, T.-R., & Järvenoja, H. (2010) · doi:10.4324/9780203847817-28 · Cited by 37
Who Profits Most from Blended Learning?
Tempelaar, D. T., Rienties, B., & Giesbers, B. (2009) · Industry and Higher Education · doi:10.5367/000000009789346130 · Cited by 26
Self-citationOblinger, D. G. (2012) · Educational Review · Cited by 26
Optimising New Modes of Assessment: In search of Qualities and Standards
Segers, M. S. R., Dochy, F. J. R. C., & Cascallar, E. C. (2003) · Kluwer Academic Publishers eBooks · doi:10.1007/0-306-48125-1 · Cited by 21
Rienties, B., Tempelaar, D. T., Giesbers, B., Segers, M. S. R., & Gijselaers, W. (2012) · Interactive Learning Environments · doi:10.1080/10494820.2012.707127 · Cited by 19
Self-citationTempelaar, D. T., Kuperus, B. T. A., Cuypers, H., van der Kooij, H., van de Vrie, E., & Heck, A. (2012) · RUSC Universities and Knowledge Society Journal · doi:10.7238/rusc.v9i1.1272 · Cited by 17
Self-citationOblinger, D. G. (2012) · Educational Review · Cited by 16
Rienties, B., Nanclares, N. H., Hommes, J. E., & Veermans, K. (2013) · Springer eBooks · doi:10.1007/978-3-319-01940-6_7 · Cited by 16
Self-citationDesigning and testing visual representations of draft essays for higher education students
Whitelock, D. M., Field, D., Pulman, S., Richardson, J. T. E., & Labeke, N. V. (2014) · Open Research Online (The Open University) · Cited by 16
Kim, H. S., & Chun, E. Y. (1999) · Journal of Educational Technology · doi:10.17232/kset.15.1.133 · Cited by 15
Dossier “Mathematical e-Learning”
Juan, A. A., Sánchez, M. A. H., Cuypers, H., & Loch, B. (2012) · RUSC Universities and Knowledge Society Journal · doi:10.7238/rusc.v9i1.1431 · Cited by 9
Flagged first, then by citations
2 of the 59 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- Rienties, 2012, A dynamic analysis of social interaction in Computer Mediated Communication; a preference for autonomous learning, Interactive Learning Environments
- Rienties, B., Slade, S., Clow, D., Cooper, M., & Ferguson, R. (submitted for publication). Risks and ethical concerns of Learning Analytics: a state-of-the-art review.
- Siemens, 2013, Improving the quality of productivity of the higher education sector: Policy and strategy for systems-level deployment of learning analytics, Solar Research
Cited by
Sorted by citations
van Dijck, J., Poell, T., & de Waal, M. (2018) · doi:10.1093/oso/9780190889760.001.0001 · Cited by 2,951
The current landscape of learning analytics in higher education
Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.07.027 · Cited by 766
Predicting academic performance of students from VLE big data using deep learning models
Waheed, H., Hassan, S., Aljohani, N. R., Hardman, J., Alelyani, S., & Nawaz, R. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.106189 · Cited by 676
Designing educational technologies in the age of AI: A learning sciences‐driven approach
Luckin, R., & Cukurova, M. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12861 · Cited by 694
Rajabalee, Y. B., & Santally, M. I. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10375-1 · Cited by 484
Metadata
- Authors
- Tempelaar, D. T., Rienties, B., & Giesbers, B.
- Affiliations
- Maastricht University (NL)
- The Open University (GB)
- Erasmus University Rotterdam (NL)
- Corresponding author
- Tempelaar, Dirk T.
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2015-06
- Volume
- 47
- Pages
- 157-167
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W1994211543
- Cited by
- 449
- References
- 59
- Citations by year
- 2026: 33 · 2025: 22 · 2024: 25 · 2023: 31 · 2022: 40 · 2021: 51 · 2020: 44 · 2019: 53 · 2018: 60 · 2017: 43 · 2016: 36 · 2015: 10
- FWCI
- 44.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers in Human Behavior (publishedVersion)
- Open Research Online - ORO (The Open University) (acceptedVersion)
- Research Publications (Maastricht University) (submittedVersion)
- Funders
- Dutch SURF
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Education › Online and Blended Learning
- Keywords
- learning analytics, learning dispositions, formative assessment, virtual learning environments, student performance prediction, underachieving students, blended learning, problem-based learning, e-tutorials, feedback generation
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