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Published on: December 23, 2025
Designing and evaluating LLM-driven coaching agents for VR public speaking practice
Enyao Chang1, Xiaoping Che2, Jianing Zhang1
1School of Software Engineering, Beijing Jiaotong University, Beijing, China.
Frontiers in Psychology
|July 23, 2026
Summary
Virtual Reality public speaking practice with AI coaching significantly reduced anxiety. Participants in the adaptive coaching group showed lasting improvements in managing public speaking anxiety in VR settings.
Area of Science:
- Human-Computer Interaction
- Virtual Reality Applications
- Artificial Intelligence in Education
Background:
- Virtual Reality (VR) offers immersive public speaking practice but often lacks adaptive coaching.
- Large Language Models (LLMs) present new opportunities for personalized and supportive coaching interactions.
Purpose of the Study:
- To design and evaluate a VR public speaking system using LLM-powered embodied agents for adaptive coaching.
- To assess the impact of personalized, performance-contingent feedback on public speaking anxiety.
Main Methods:
- A randomized controlled study with 120 participants comparing adaptive LLM coaching to generic feedback in VR.
- Utilized automatic speech recognition, speech synthesis, and gaze cues for real-time feedback delivery.
- Assessed anxiety levels through pre/post-speech self-reports and follow-up sessions at one week and one month.
Main Results:
- Adaptive coaching led to greater reductions in self-reported state and public speaking anxiety compared to generic feedback.
- Reduced anxiety levels were maintained at follow-up sessions within the VR environment.
- Qualitative feedback indicated participants found the AI coaches supportive but noted limitations in realism and interaction richness.
Conclusions:
- Embodied LLM-based coaching shows promise for supporting anxiety-aware VR public speaking practice.
- Findings suggest potential for VR-based interventions in managing public speaking anxiety.
- Further research is needed to validate real-world transfer and objective performance improvements.
