Abstract
A significant problem with immersive virtual reality (IVR) experiments is the ability to compare research conditions. VR kits and IVR environments are complex and diverse but researchers from different fields, e.g. ICT, psychology, or marketing, often neglect to describe them with a level of detail sufficient to situate their research on the IVR landscape. Careful reporting of these conditions may increase the applicability of research results and their impact on the shared body of knowledge on HCI and IVR. Based on literature review, our experience, practice and a synthesis of key IVR factors, in this article we present a reference checklist for describing research conditions of IVR experiments. Including these in publications will contribute to the comparability of IVR research and help other researchers decide to what extent reported results are relevant to their own research goals. The compiled checklist is a ready-to-use reference tool and takes into account key hardware, software and human factors as well as diverse factors connected to visual, audio, tactile, and other aspects of interaction.
Supported by KOBO Association and XR Lab at PJAIT
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Notes
- 1.
The code was developed by ALLEA—the European Federation of Academies of Sciences and Humanities and more on this can be found here: https://allea.org/code-of-conduct/
- 2.
In our research we observed that dynamic IVR experiences tend to be more immersive with higher refresh rates, which are not critical for non-dynamic HQ IVREs.
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Acknowledgements
We would like to thank Kobo Association and all transdisciplinary experts involved with the HASE research initiative (Human Aspects in Science and Engineering) including XR Lab at PJAIT, VR Lab at IP PAS, EC Lab at SWPS University and LIT of the NIPI.
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Skorupska, K. et al. (2021). All Factors Should Matter! Reference Checklist for Describing Research Conditions in Pursuit of Comparable IVR Experiments. In: Biele, C., Kacprzyk, J., Owsiński, J.W., Romanowski, A., Sikorski, M. (eds) Digital Interaction and Machine Intelligence. MIDI 2020. Advances in Intelligent Systems and Computing, vol 1376. Springer, Cham. https://doi.org/10.1007/978-3-030-74728-2_12
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