Practice-informed Patterns for Organising Large Groups in Distributed Mixed Reality Collaboration

要旨

Collaborating across dissimilar, distributed spaces presents numerous challenges for computer-aided spatial communication. Mixed reality (MR) can blend selected surfaces, allowing collaborators to work in blended f-formations (facing formations), even when their workstations are physically misaligned. Since collaboration often involves more than just participant pairs, this research examines how we might scale MR experiences for large-group collaboration. To do so, this study recruited collaboration designers (CDs) to evaluate and reimagine MR for large-scale collaboration. These CDs were engaged in a four-part user study that involved a technology probe, a semi-structured interview, a speculative low-fidelity prototyping activity and a validation session. The outcomes of this paper contribute (1) a set of collaboration design principles to inspire future computer-supported collaborative work, (2) eight collaboration patterns for blended f-formations and collaboration at scale and (3) theoretical implications for f-formations and space-place relationships. As a result, this work creates a blueprint for scaling collaboration across distributed spaces.

著者
Emily Wong
The University of Melbourne, Melbourne, Victoria, Australia
Juan Sánchez Esquivel
Aarhus University, Aarhus, Denmark
Germán Leiva
Aarhus University, Aarhus, Denmark
Jens Emil Sloth. Grønbæk
The University of Melbourne, Melbourne, Victoria, Australia
Eduardo Velloso
University of Melbourne, Melbourne, Victoria, Australia
論文URL

https://doi.org/10.1145/3613904.3642502

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Working Practices and Tools C

313B
5 件の発表
2024-05-13 23:00:00
2024-05-14 00:20:00