Towards an Understanding of Distributed Asymmetric Collaborative Visualization on Problem-solving

PubDate: Feb 2023

Teams: HKUST；Carnegie Mellon University；Virginia Tech

Writers: Wai Tong, Meng Xia, Kam Kwai Wong, Doug A. Bowman, Ting-Chuen Pong, Huamin Qu, Yalong Yang

PDF: Towards an Understanding of Distributed Asymmetric Collaborative Visualization on Problem-solving

Abstract

This paper provided empirical knowledge of the user experience for using collaborative visualization in a distributed asymmetrical setting through controlled user studies. With the ability to access various computing devices, such as Virtual Reality (VR) head-mounted displays, scenarios emerge when collaborators have to or prefer to use different computing environments in different places. However, we still lack an understanding of using VR in an asymmetric setting for collaborative visualization. To get an initial understanding and better inform the designs for asymmetric systems, we first conducted a formative study with 12 pairs of participants. All participants collaborated in asymmetric (PC-VR) and symmetric settings (PC-PC and VR-VR). We then improved our asymmetric design based on the key findings and observations from the first study. Another ten pairs of participants collaborated with enhanced PC-VR and PC-PC conditions in a follow-up study. We found that a well-designed asymmetric collaboration system could be as effective as a symmetric system. Surprisingly, participants using PC perceived less mental demand and effort in the asymmetric setting (PC-VR) compared to the symmetric setting (PC-PC). We provided fine-grained discussions about the trade-offs between different collaboration settings.