Practice-informed Patterns for Organising Large Groups in Distributed Mixed Reality Collaboration
Emily Wong, Juan Sánchez Esquivel, Jens Emil Grønbæk, Germán Leiva, Eduardo Velloso
TL;DR
The paper addresses scaling distributed mixed reality collaboration from dyads to large groups across dissimilar spaces by engaging collaboration designers (CDs) to reimagine MR collaboration spaces. It uses a four-part expert workshop—MR technology probe, semi-structured interviews, speculative low-fidelity prototyping, and validation—to derive a set of design principles and eight Blended Collaboration Patterns (BCP) for blended f-formations and place-making in MR. The major contributions are a practice-informed design framework, eight scalable MR interaction patterns, and theoretical implications for f-formations and space-place relationships, offering a blueprint for distributed MR collaboration at scale. It highlights the need to consider multiple vantage points beyond the first-person perspective and to develop evaluation tools for real-world, large-scale MR collaboration scenarios.
Abstract
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.
