Abstract
Conventional user research with human participants faces significant challenges, including substantial time and resource requirements, and limited scalability. In response, this study presents an efficient, cost-effective workflow driven by large language models (LLMs) for simulating user research with synthetic participants (SPs) at scale. In a case study in design augmented reality for education, SPs' open-ended answers were plausible and comprehensive, yet semi-open and closed items diverged from those of humans. SPs can augment early qualitative work, but cannot replace human studies.
| Original language | English |
|---|---|
| Pages (from-to) | 2601-2610 |
| Number of pages | 10 |
| Journal | Proceedings of the Design Society |
| Volume | 6 |
| Early online date | 2 Jul 2026 |
| DOIs | |
| Publication status | E-pub ahead of print - 2 Jul 2026 |
| Event | 19th International Design Conference, DESIGN 2026 - Dubrovnik, Croatia Duration: 18 May 2026 → 26 May 2026 |
Keywords
- artificial intelligence (AI)
- design research
- large language model (LLM)
- synthetic participants
- user research
ASJC Scopus subject areas
- Software
- Modelling and Simulation
- Computer Science Applications
- Computer Graphics and Computer-Aided Design
Fingerprint
Dive into the research topics of 'Can LLM-driven synthetic participants help user research? A case study in designing augmented reality for education'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS