Analyzing Multimodal Multichannel Data about Self-Regulated Learning with Advanced Learning Technologies: Issues and Challenges
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Recent developments in multimodal data collection, learning analytics, and AI afford opportunities to improve the assessment of processes.
“Recent developments in multimodal data collection, learning analytics, and AI afford opportunities to improve the assessment of processes.”
From Assessment in the age of artificial intelligence (2022) · cites this paper as Azevedo & Gašević, 2019
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Vision, challenges, roles and research issues of Artificial Intelligence in Education
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Self-citationAssessment in the age of artificial intelligence
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Järvelä, S., Nguyen, A., & Hadwin, A. (2023) · British Journal of Educational Technology · doi:10.1111/bjet.13325 · Cited by 342 · see citing works
Molenaar, I. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100070 · Cited by 217 · see citing works
Molenaar, I., Mooij, S. D., Azevedo, R., Bannert, M., Järvelä, S., & Gašević, D. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107540 · Cited by 217 · see citing works
Self-citationGuo, L. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12650 · Cited by 141 · see citing works
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Self-citationTowards investigating the validity of measurement of self-regulated learning based on trace data
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Self-citationViberg, O., Wasson, B., & Kukulska-Hulme, A. (2020) · Australasian Journal of Educational Technology · doi:10.14742/ajet.6494 · Cited by 58 · see citing works
“…are largely based on the examination of students’ log data from learning management systems, which provide a limiting view of individuals’ SRL. Azevedo and Gasevic (2019) stressed that “analyses of multimodal multichannel SRL process data can significantly augment advanced learning…”
BackgroundTemporal Assessment of Self-Regulated Learning by Mining Students’ Think-Aloud Protocols
Lim, L., Bannert, M., van der Graaf, J., Molenaar, I., Fan, Y., Kilgour, J., Moore, J., & Gašević, D. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.749749 · Cited by 44 · see citing works
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System design for using multimodal trace data in modeling self-regulated learning
Cloude, E. B., Azevedo, R., Winne, P. H., Biswas, G., & Jang, E. E. (2022) · Frontiers in Education · doi:10.3389/feduc.2022.928632 · Cited by 23 · see citing works
Self-citationWhen Can AI Models Explain Learning? Validity Criteria for AI as Cognitive Models in Education
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A Conceptual Framework to Integrate Research Programs on Self-Regulation in Education
Wortha, F., Gerjets, P., Azevedo, R., Bernacki, M., Brucker, B., Bühler, B., Ehlis, A.-C., Kasneci, E., Miyake, A., Murayama, K., et al. (2026) · Educational Psychology Review · doi:10.1007/s10648-026-10196-7
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- Authors
- Azevedo, R., & Gašević, D.
- Affiliations
- University of Central Florida (US)
- Monash University (AU)
- Corresponding author
- Azevedo, Roger
- Gašević, Dragan
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 96
- Pages
- 207-210
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W2942629971
- Cited by
- 345
- References
- 0
- Citations by year
- 2026: 79 · 2025: 65 · 2024: 47 · 2023: 48 · 2022: 50 · 2021: 29 · 2020: 23 · 2019: 4
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers in Human Behavior (publishedVersion)
- HAL (submittedVersion)
- Funders
- Economic and Social Research Council (ES/S015701/1)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- student self-regulation, advanced learning technologies, intelligent tutoring systems, serious games, immersive virtual learning environments, hypermedia, eye tracking, log analysis, physiological signals, facial expression analysis, think-aloud, educational data mining, metacognition, emotional processing, social processes, adaptive scaffolding, real-time feedback, conceptual understanding
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