LAVR @ LAK25


Learning Analytics from Virtual Reality (LAVR)

March 04, 2025, 13:30-17:00, Dublin, as part of LAK25 conference

The use of immersive virtual reality (VR) in educational settings is growing. Thanks to rich sensory data that can be collected from VR applications, this presents many opportunities for learning analytics (LA). Building on the successful first LAVR workshop, held within LAK24 in Kyoto, the workshop aims to continue conversations and bring together researchers and practitioners working on topics on the intersection of learning analytics and immersive virtual reality in educational settings. Overall, it aims to advance research on the potential and challenges of rich sensory data generated from VR for learning purposes. The workshop strives to better understand how LA can improve the future design of educational VR applications. Therefore, we call for contributions on the role of LA in foundational research about the VR infrastructure and its multimodal analytics; VR for asynchronous learning experiences; and VR for synchronous learning and teaching.

Topics of interest

  • Objective vs subjective data analysis
  • Effective visualization of data coming from VRs
  • Privacy and security concerns of using LA from VR in education
  • Challenges of algorithmic biases and unintended consequences of LA in VR
  • Scalability, availability, and shareability aspects of LA for VRs
  • Data preparation and challenges of VR for LA (e.g. multiple sensor merging)
  • Student/teacher acceptance and perception of using VR for LA
  • LA for the design of VR environments and learning experiences
  • LA for performance measurement and evaluation of learning in/with VR
  • LA for improving inclusion, equity, and diversity in VR learning environments
  • LA for supporting individualized learning processes in VR environments
  • LA for enabling and enhancing collaborative learning in VR environments
  • LA for supporting the integration of VR in hybrid learning environments
  • LA for empowering instructors in VR learning environments
  • LA for supporting the integration of Generative AI in VR learning environments
  • LA for educational 360-degree videos

    • General info

    Until recently, virtual reality with head-mounted displays was confined only to research laboratories. However, thanks to advances in technology and falling prices (Goswami, 2023), it has now become affordable (the head-mounted display can be purchased for a similar price to a mobile phone), allowing a significant increase in the number of people using VR.

    Following the general trends, there is a growing interest in education to explore the possibilities of VR in the classroom (McGrath et al., 2023). The data collected from various sensors from these devices present a rich information source for learning analytics. Yet, despite the growing interest in VR and its convergence with learning analytics, the number of papers reporting its opportunities for learning analytics is very scarce (Jiang et al., 2024).

    However, it is evident that an increasing number of VR applications, as well as VR experiences integrated with learning analytics, are emerging from technology companies specializing in VR development (Dwivedi et al., 2022). Claims about the benefits of combining VR and learning analytics lack details of standards, best practices, and academic rigor. Such reports are also almost non-existent (Hwang & Chien, 2022).

    As Kukulska-Hulme et al. (2023) mention, apart from the potential of VR, the challenges in education include technical, accessibility issues or privacy and security concerns. These concerns also apply to learning analytics. The richness of the data generated from VR sensors poses additional challenges to data engineering, as well as new challenges for privacy. For example, a recent study on 55,000+ users found that the motion data from 100 seconds in a game could identify a user with 94.33% accuracy (Nair et al., 2023).

    In addition to the lack of rigorous and public studies, the fact that most research is reported by companies raises some additional issues about the unethical use of learning analytics. These include automated decision-making (performance) enabled by massive data collection without critical evaluation of the underlying collected training data used to develop these models (Carter & Egliston, 2023). Nonetheless, ongoing advancements in ethical standards and transparency guidelines are driving improvements in the responsible use of learning analytics in educational technologies (Sakr & Abdullah, 2024).

    Following the successful first LAVR workshop, held within LAK24 in Kyoto, this workshop aims to serve as a Learning Analytics for Virtual Reality (LAVR) forum for bringing together researchers and practitioners working on topics on the intersection of learning analytics and (immersive) virtual reality in educational settings. Overall, the LAVR workshop aims to advance research on the potential and challenges of rich sensory data generated from VR for learning purposes. Ultimately, we strive to better understand how LA can improve the future design of educational VR applications. Therefore, we call for contributions on the role of LA in foundational research about the VR infrastructure and its multimodal analytics; VR for asynchronous as well as synchronous learning experiences. Although being primarily focused on VR, we are encouraging submission of other eXtended Reality (XR) technologies such as Augmented Reality (AR), Mixed Reality (MR), Haptics, Wearables, etc.

    Workshop goals

    The objectives of the workshop are as follows:
  • bring together researchers and practitioners to discuss what possibilities and challenges enable VR for learning analytics,
  • uncover the emerging trends for this research through both the discussion and a keynote presentation,
  • establish links between the VR for education and the Learning Analytics community.

    • Submissions

    • The accepted papers will be submitted to CEUR Workshop proceedings (CEUR-WS) similarly as the workshops at LAK24 As such, authors have to comply with the CEUR template.
      • Use the one-column version in the zip archive - CEUR-Template-1col.odt for Word-based submission and sample-1col.tex for LaTeX.
      • There is also a CEUR template for Overleaf.
    • Participants are asked to submit the following paper types:
      • Full papers (10-12 pages) describing research with stated methodology and positioned in state-of-the art.
      • Short papers (5-9 pages) more novel work, might be narrower in scope or work-in-progress that is likely to generate discussions at the workshop between the participants.
      • Position papers (5-6 pages) introducing new points of view in the workshop topics or summarising the experience of a group in the field, also welcome practitioner reports describing experience or challenges of using and implementing analytics in virtual reality in education.
      Further, based on the feedback from last year, we accept project and demo submissions to strengthen the link between research and practitioners. These have lower requirements without the need for rigorous evaluation required for research papers. As such they do not meet the requirements for publishing in CEUR proceedings. Those will be given space to present at the workshop, the short contribution will be published on this website and the publications server of the RWTH Aachen University. Your contribution will be assigned a stable address and can be viewed worldwide and reliably cited.
      • Project description (1-2 pages) in their initial stages that can demonstrate their innovative potential for further analytics
      • Demos (1-2 pages + video) showcasing the combined potential of VR and analytics.
    • The submissions should be done using EasyChair system using the link below.
    • Each of the submitted papers will be reviewed by at least two members of the Program Committee. The review process is single-blind (i.e., reviewers' identities are not disclosed to the authors). There is no need to anonymise your submission.

    Submit paper

    *All submissions should be made through Easychair

    Important dates

    • 09 Oct 2024: Workshop calls for participation announced
    • 04 Dec 2024: Workshop papers submission deadline
    • 20 Dec 2024: Notifications sent out
    • 08 Jan 2025: Camera-ready version of papers

    Organisation

    Martin Hlosta   Ivan Moser  

    IFeL, Swiss Distance University of Applied Science, Switzerland

    Amir Winer   Nitza Geri  

    Open University of Israel, Israel

    Birte Heinemann   Sergej Görzen  

    RWTH Aachen, Germany

    Umesh Ramnarain   Christo van der Westhuizen   Mafor Penn  

    University of Johannesburg, South Africa

    Programme Committee.

    • Geoffray Bonnin, Université Lorraine, France
    • Herman Myburgh, University of Johannesburg
    • Tanya Nazaretsky, EPFL, Swiss Federal Institute of Technology Lausanne, Switzerland
    • Ofir Turel, University of Melbourne, Australia
    • Mamta Shah, Elsevier, USA
    • Egon Werlen, IFeL, Swiss Distance University of Applied Science, Switzerland
    • Qi Zhou, University College London, UK
    • ...to be added continuously

    Program

    • 13:30 - 13:40 Ice-breaker and Introductions
    • 13:40 - 14:10 Keynote + Q&A
    • 14:10 - 16:00 Presentation of the papers (+ small break) - including showcasing the demo of the VR application
    • 16:00 - 16:50 Group activity - Group discussion activity
    • 16:50 - 17:00 Summary & Conclusions

    Registration

    The registration for the workshop will be managed via the LAK25 registration system, we will update the website once the registration opens.

    Contact

    Contact

    In case of any questions regarding the workshop, please contact : Martin Hlosta   and Amir Winer   and mark the subject as LAVR25.

    Venue

    The workshop will be in conjunction with the 15th Learning Analytics and Knowledge ConferenceLAK25 Conference.

    References

    Carter, M., & Egliston, B. (2023). What are the risks of virtual reality data? Learning analytics, algorithmic bias and a fantasy of perfect data. New media & society, 25(3), 485-504. https://doi.org/10.1177/14614448211012794

    Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., ... & Wamba, S. F. (2022). Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 66, 102542. https://doi.org/10.1016/j.ijinfomgt.2022.102542

    Goswami, R. (2023, March 4). Meta announces big price cuts for its VR headsets. CNBC. https://www.cnbc.com/2023/03/03/meta-quest-pro-vr-headset-gets-price-cut.html

    Hwang, G. J., & Chien, S. Y. (2022). Definition, roles, and potential research issues of the metaverse in education: An artificial intelligence perspective. Computers and Education: Artificial Intelligence, 3, 100082. https://doi.org/10.1016/j.caeai.2022.100082

    Iop, A., El-Hajj, V. G., Gharios, M., de Giorgio, A., Monetti, F. M., Edström, E., ... & Romero, M. (2022). Extended reality in neurosurgical education: A systematic review. Sensors, 22(16), 6067. https://doi.org/10.3390/s22166067

    Jiang, Z., Zhang, Y., & Chiang, F. K. (2024). Meta‐analysis of the effect of 360‐degree videos on students' learning outcomes and non‐cognitive outcomes. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13464

    Kukulska-Hulme, A., Bossu, C., Charitonos, K., Coughlan, T., Deacon, A., Deane, N., Ferguson, R., …, & Whitelock, D. (2023). Innovating Pedagogy 2023: Open University Innovation Report 11. Milton Keynes: The Open University.

    McGrath, O., Hoffman, C., & Dark, S. (2023). Future Prospects and Considerations for AR and VR in Higher Education Academic Technology. Owen McGrath, Chris Hoffman, and Shawna Dark, 'Future Prospects and Considerations for AR and VR in Higher Education Academic Technology, 'EDUCAUSE Review. https://ssrn.com/abstract=4431134

    Nair, V., Guo, W., Mattern, J., Wang, R., O'Brien, J. F., Rosenberg, L., & Song, D. (2023). Unique identification of 50,000+ virtual reality users from head & hand motion data. arXiv preprint arXiv:2302.08927.

    Sakr, A., & Abdullah, T. (2024). Virtual, augmented reality and learning analytics impact on learners, and educators: A systematic review. Education and Information Technologies, 1-50.‏ https://doi.org/10.1007/s10639-024-12602-5