Extended Reality (XR) - including Virtual Reality (VR), Mixed Reality (MR), and Augmented Reality (AR) - is increasingly used to trial new systems (e.g., surgical VR training platforms, MR industrial maintenance tools, AR indoor navigation) and novel interaction techniques (e.g., hand-gesture control, eye-gaze selection, haptic feedback gloves, redirected walking). Evaluations often rely on questionnaires such as the System Usability Scale (SUS), User Experience Questionnaire (UEQ), NASA Task Load Index (NASA-TLX), and Presence Questionnaire (PQ).
However, XR designers control environmental factors like weather, lighting, and colour - known to affect mood and perception. Identical systems can score higher in sunny, bright scenes and lower in grey, dim settings, leading to false positives or false negatives in results.
This project will systematically investigate how such environmental variables bias questionnaire outcomes. The student will:
- Build controlled XR scenarios with varied environmental cues, applied to identical tasks.
- Recruit participants and collect questionnaire data.
- Analyse the extent to which the environment skews usability, workload, and UX ratings.
Significance
Results will expose hidden biases in XR evaluation, informing guidelines for more reliable and reproducible studies. The findings will be relevant to XR product testing in healthcare, mining, defence, education, and entertainment.
School
Computer Science and Engineering
Research Area
Human-computer interaction (HCI) | Extended reality (XR) | Virtual reality (VR) | Mixed reality (MR) | User experience (UX) | Usability evaluation | Experimental psychology | Perception research
Suitable for recognition of Work Integrated Learning (industrial training)?
No
- Research environment
- Expected outcomes
- Supervisory team
- Reference material/links
The project will be based in the Human-Centred Computing group at UNSW’s School of Computer Science and Engineering. Students will have access to a fully equipped XR lab with VR headsets, MR devices, and high-performance computers. The group offers strong interdisciplinary links with engineering, optometry, and psychology, regular research meetings, and close mentoring from academic and PhD supervisors.
- Identification of how environmental variables in XR (e.g., weather, lighting, colour palette) bias usability, workload, and UX questionnaire results
- Recommendations for reducing bias in XR evaluation protocols to improve reliability and reproducibility
- A complete dataset and statistical analysis demonstrating the magnitude of environmental effects
- A research poster summarising methods, findings, and practical guidelines for XR evaluation
- Student gains in XR development, experimental design, human factors methods, and scientific communication
- A research paper at a top-tier HCI Conference (e.g., ACM CHI, IEEE ISMAR, or IEEE VR)
- Dmitry Alexandrovsky, Susanne Putze, Michael Bonfert, Sebastian Höffner, Pitt Michelmann, Dirk Wenig, Rainer Malaka, and Jan David Smeddinck. 2020. Examining Design Choices of Questionnaires in VR User Studies. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20). Association for Computing Machinery, New York, NY, USA, 1–21. https://doi.org/10.1145/3313831.3376260
- Xia, G., Henry, P., Queiroz, F., & Westland, S. (2021). Effects of coloured lighting in the real world environment and virtual reality. Journal of the International Colour Association , 27, 9-25. https://aic-color.org/resources/Documents/jaic_v27_02.pdf
- Mostafavi, A., Vujovic, M., Xu, T. B., & Hensel, M. (2024). Impacts of Illuminance and Correlated Color Temperature on Cognitive Performance: A VR-Lighting Study. arXiv preprint arXiv:2406.02728.
- A. Naz, R. Kopper, R. P. McMahan and M. Nadin, "Emotional qualities of VR space," 2017 IEEE Virtual Reality (VR), Los Angeles, CA, USA, 2017, pp. 3-11, doi: 10.1109/VR.2017.7892225.
- https://en.wikipedia.org/wiki/Aesthetic%E2%80%93usability_effect
- https://en.wikipedia.org/wiki/Color_psychology