XSynth: GenAI-Empowered Shared Mental Model Building for Conceptual Design Collaboration in Extended Reality

要旨

Effective conceptual design collaboration requires teams to build shared mental models (SMMs). Although Extended Reality (XR) technologies support design collaboration, they often lack structured cognition support for such alignment. To address this, we conducted this research within the sandbox of automotive design, and firstly identified key cognitive challenges in its collaboration. We then developed XSynth, a GenAI-powered XR system grounded in Concept–Knowledge Theory. XSynth scaffolds designers’ reasoning, externalizes individual mental models as knowledge graphs, and merges them into a unified graph to facilitate SMMs building. We evaluated XSynth in a within-subject experiment containing 10 design teams (N=30) using mixed-method approach. Results showed that XSynth significantly reduced workload, enhanced creativity support, strengthened perceived SMMs, and improved design performance. This research contributes to HCI by introducing the design and implementation of a theory-grounded, GenAI-powered, XR-based cognition support tool. It also offers empirical evidence into the effectiveness of XSynth, and design implications for future cognition support tools in collaborative settings.

著者
Yaning Li
Northeastern University , Boston, Massachusetts, United States
Shumin Li
Politecnico di Milano , Milan, Italy
Ziyao He
Northeastern University, Boston, Massachusetts, United States
Dakuo Wang
Northeastern University, Boston, Massachusetts, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Designing XR Interaction

P1 - Room 118
7 件の発表
2026-04-16 20:15:00
2026-04-16 21:45:00