Practice-informed Patterns for Organising Large Groups in Distributed Mixed Reality Collaboration
<|reference_start|>Practice-informed Patterns for Organising Large Groups in Distributed Mixed Reality Collaboration: 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.<|reference_end|>
@article{wong2024practice-informed,
    title={Practice-informed Patterns for Organising Large Groups in Distributed
  Mixed Reality Collaboration},
    author={Emily Wong, Juan S'anchez Esquivel, Jens Emil Gr{o}nb{ae}k,
  Germ'an Leiva, Eduardo Velloso},
    journal={CHI '24, Proceedings of the CHI Conference on Human Factors in
  Computing Systems, May 11-16 2024, Honolulu, HI, USA},
    year={2024},
    doi={10.1145/3613904.3642502},
    archivePrefix={arXiv},
    eprint={2405.04873},
    primaryClass={cs.HC}
}