Evaluating Layout Dimensionalities in PC+VR Asymmetric Collaborative Decision Making
Daniel Enriquez, Wai Tong, Chris North, Huamin Qu, Yalong Yang

TL;DR
This study empirically evaluates how different layout dimensionalities in PC and VR devices affect user experience and efficiency in asymmetric data-driven collaboration tasks.
Contribution
It provides new insights into optimal layout dimensionalities for PC and VR in asymmetric collaborative decision-making.
Findings
Preference for PC2D+VR3D layout
PC2D+VR2D led to fastest task completion
Trade-offs discussed for different layout combinations
Abstract
With the commercialization of virtual/augmented reality (VR/AR) devices, there is an increasing interest in combining immersive and non-immersive devices (e.g., desktop computers) for asymmetric collaborations. While such asymmetric settings have been examined in social platforms, significant questions around layout dimensionality in data-driven decision-making remain underexplored. A crucial inquiry arises: although presenting a consistent 3D virtual world on both immersive and non-immersive platforms has been a common practice in social applications, does the same guideline apply to lay out data? Or should data placement be optimized locally according to each device's display capacity? This study aims to provide empirical insights into the user experience of asymmetric collaboration in data-driven decision-making. We tested practical dimensionality combinations between PC and VR,…
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Taxonomy
TopicsVirtual Reality Applications and Impacts · Manufacturing Process and Optimization · Product Development and Customization
