Multimodal Learning Analytics Using Wearable Devices in Immersive Virtual Reality Learning Environments: A Systematic Review on Learning Indicators and Ethical Considerations

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This systematic literature review explores the application of multimodal learning analysis (MMLA), with physiological signals collected through wearable devices as the primary data source, in immersive virtual reality (IVR) learning environments. By examining 78 peer-reviewed articles published over the past nine years (2016-2024), the paper addresses two core research questions in IVR learning environments: 1) What are the main multimodal learning indicators? 2) What are the ethical considerations associated with multimodal learning analysis? The findings indicate that cognitive indicators are dominant, while studies on emotional and affective learning indicators remain scarce. Real-time monitoring of cognitive load and dynamic task adjustment mechanisms have yet to be fully implemented, suggesting future research on the design of adaptive learning tasks. Additionally, the review calls for improvements in both technological and ethical frameworks to address issues related to privacy, transparency, and fairness. By reviewing and summarizing current research advancements, this paper offers valuable insights into future research and practice of MMLA in IVR learning environments.

Original languageEnglish
Title of host publicationProceedings - 25th IEEE International Conference on Advanced Learning Technologies, ICALT 2025
EditorsMaiga Chang, Scott Chen, Rita Kuo, Demetrios Sampson, Ahmed Tlili, Pei-Shu Tsai
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages96-100
Number of pages5
ISBN (Electronic)9798331565305
DOIs
Publication statusPublished - 2025
Event25th IEEE International Conference on Advanced Learning Technologies, ICALT 2025 - Hybrid, Changhua, Taiwan, Province of China
Duration: 14 Jul 202517 Jul 2025

Publication series

NameProceedings - 25th IEEE International Conference on Advanced Learning Technologies, ICALT 2025

Conference

Conference25th IEEE International Conference on Advanced Learning Technologies, ICALT 2025
Country/TerritoryTaiwan, Province of China
CityHybrid, Changhua
Period14/07/2517/07/25

Keywords

  • Immersive Virtual Reality
  • Multimodal Learning Analytics
  • Wearable Devices

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