The evidence of impact and ethical considerations of Multimodal Learning Analytics: A Systematic Literature Review
Abstract
There is a growing interest in the research and use of multimodal data in learning analytics. This paper presents a systematic literature review of multimodal learning analytics (MMLA) research to assess i) the available evidence of impact on learning outcomes in real-world contexts and ii) explore the extent to which ethical considerations are addressed. A few recent literature reviews argue for the promising value of multimodal data in learning analytics research. However, our understanding of the challenges associated with MMLA research from real-world teaching and learning environments is limited. To address this gap, this paper provides an overview of the evidence of impact and ethical considerations stemming from an analysis of the relevant MMLA research published in the last decade. The search of the literature resulted in 663 papers, of which 100 were included in the final synthesis. The results show that the evidence of real-world impact on learning outcomes is weak, and ethical aspects of MMLA work are rarely addressed. We discuss our results through the lenses of two theoretical frameworks for evidence of impact types and ethical dimensions of MMLA. We conclude that for MMLA to stay relevant and become part of mainstream education, future research should directly address the gaps identified in this review.
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Ouhaichi, H., Vogel, B., & Spikol, D. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1356537 · Cited by 15 · see citing works
Suraworachet, W., Villa-Torrano, C., Zhou, Q., Asensio-Pérez, J. I., Dimitriadis, Y. A., & Cukurova, M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86436-1_13 · Cited by 8 · see citing works
Self-citationTowards designing a flexible multimodal learning analytics system
Ouhaichi, H. (2022) · doi:10.24834/isbn.9789178772988 · Cited by 4 · see citing works
Alwahaby, H., & Cukurova, M. (2022) · doi:10.35542/osf.io/4znby · Cited by 4 · see citing works
Self-citationIdentifying Tertiary Level Educators’ Needs and Understanding of the Collaboration Process Analytics
Cukurova, M., Kent, C., & Akanji, A. (2022) · Advances in analytics for learning and teaching · doi:10.1007/978-3-031-06333-6_8 · Cited by 1 · see citing works
Self-citationPreserving Privacy in Multimodal Learning Analytics with Visual Animation of Kinematic Data
Mitri, D. D., Epp, A., & Schneider, J. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-67351-1_45 · Cited by 1 · see citing works
Learning Swedish with AI: Exploring Multimodal Learning Analytics in Spoken Language Acquisition
Ouhaichi, H., Spikol, D., & Vogel, B. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-73538-7_16
- Authors
- Alwahaby, H., Cukurova, M., Papamitsiou, Z., & Giannakos, M.
- Affiliations
- University College London (GB)
- Norwegian University of Science and Technology (NO)
- Publisher
- Center for Open Science
- Published
- 2021-08-23
- OpenAlex
- W4213071674
- Cited by
- 15
- References
- 98
- Citations by year
- 2025: 1 · 2024: 5 · 2022: 8 · 2021: 1
- Type
- posted content
- Language
- en
- Open access
- closed
- Locations
- UCL Discovery (University College London) (submittedVersion)
- EdArXiv (OSF Preprints) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Educational Technology and Pedagogy
- Keywords
- multimodal learning analytics, multimodal data, learning outcomes, impact evidence, ethics of learning analytics, ethical considerations
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