AI summary · arXiv: 2302.01966v1 · cs.HC

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

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

Original paper · DOI Submitted to arXiv on 03 Feb. 2023 11 pages, 12 figures, accepted at IEEE VR 2023 License: NONEXCLUSIVE-DISTRIB 1.0

The essentials

  • The paper presents empirical knowledge of user experience for collaborative visualization in a distributed asymmetrical setting through controlled user studies.
  • The study explores scenarios where collaborators use different computing environments in different places and investigates the use of VR head-mounted displays in an asymmetric setting for collaborative visualization.
  • A formative study was conducted with 12 pairs of participants who collaborated in asymmetric (PC-VR) and symmetric settings (PC-PC and VR-VR).
  • Based on key findings, the authors improved their asymmetric design and another ten pairs of participants collaborated with enhanced PC-VR and PC-PC conditions in a follow-up study.
  • A well-designed asymmetric collaboration system could be as effective as a symmetric system.
  • Participants using PC perceived less mental demand and effort in the asymmetric setting (PC-VR) compared to the symmetric setting (PC-PC).
  • The research provides valuable insights into how collaborative visualization can be used effectively in distributed asymmetrical settings, highlighting the importance of designing systems that can accommodate various computing devices while maintaining effectiveness.
  • Designers should consider incorporating VR head-mounted displays into their systems to enhance collaboration experiences.
  • Overall, this paper contributes to our understanding of how technology can support problem solving through collaborative visualization in distributed teams, emphasizing the need for careful consideration when designing such systems so that users can benefit from enhanced collaboration experiences without sacrificing effectiveness or efficiency.

Key points written by AI: they may contain errors, check them against the paper.

AI-generated keywords: Collaborative Visualization Distributed Asymmetrical Settings Virtual Reality Mental Demand Problem-Solving

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  • Original abstract
This paper, authored by Wai Tong, Meng Xia, Kam Kwai Wong, Doug A. Bowman, Ting-Chuen Pong, Huamin Qu and Yalong Yang, presents empirical knowledge of the user experience for using collaborative visualization in a distributed asymmetrical setting through controlled user studies. The study explores scenarios where collaborators have to or prefer to use different computing environments in different places and investigates the use of Virtual Reality (VR) head-mounted displays in an asymmetric setting for collaborative visualization. To gain an initial understanding and better inform the designs for asymmetric systems, the authors conducted a formative study with 12 pairs of participants who collaborated in asymmetric (PC-VR) and symmetric settings (PC-PC and VR-VR). Based on key findings and observations from this first study, they improved their asymmetric design. Another ten pairs of participants then collaborated with enhanced PC-VR and PC-PC conditions in a follow-up study. The authors 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). They provided fine-grained discussions about the trade-offs between different collaboration settings. This research provides valuable insights into how collaborative visualization can be used effectively in distributed asymmetrical settings. It highlights the importance of designing systems that can accommodate various computing devices while maintaining effectiveness. The findings also suggest that designers should consider incorporating VR head-mounted displays into their systems to enhance collaboration experiences. Overall, this paper contributes to our understanding of how technology can support problem solving through collaborative visualization in distributed teams. It emphasizes the need for careful consideration when designing such systems so that users can benefit from enhanced collaboration experiences without sacrificing effectiveness or efficiency.

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