Background: Novice nurses often struggle with prioritizing care in complex environments. While Virtual Reality (VR) offers immersive training, traditional VR often lacks dynamic interaction and personalized feedback. Furthermore, effective simulation requires not just technological practice but also structured pedagogical reflection.

Objectives: This study aims to develop a high-fidelity, AI-enhanced VR training module for nursing prioritization. The module design integrates the Tanner Clinical Judgment Model, expert clinical experience, and advanced interactive technologies.

Methods: A comprehensive instructional design approach was adopted. The scenario content was synthesized from longitudinal field observations of 15 support groups for new nurses and the expert consensus of researchers with 20 years of combined educational experience. The scenario flowchart and user interface (UI) prototypes were created using Figma to visualize the user experience (UX). The gamification design incorporates Generative AI to drive dynamic interactions with virtual family members and voice recognition technology to assess therapeutic communication.

Results: The developed VR module features a gamified structure with leveling and scoring systems. Key design elements include: (1) "Call-out" Scaffolding: Real-time prioritization provided upon learners’ hesitation; (2) AI-Driven Interaction: GenAI powers voice-based family interruptions to challenge learners; and (3) Hybrid Debriefing Model: The simulation concludes with a quantitative performance report followed by in-person debriefing and retry mechanisms to effectively reinforce learning.

Conclusion: This study presents an innovative AI-enhanced hybrid simulation framework. By combining VR and GenAI scalability with human insight, this design addresses both decision-making and communication skills as core competencies for nursing prioritization.

Authors:
Hao-Yuan Chang, National Taiwan University, Taiwan
Shih-Jou Chen, National Taiwan University, Taiwan
Hsiao-Ling Yang, National Taiwan University, Taiwan
Cheng-Fang Yang, National Taiwan University, Taiwan
Ya-Ling Tzeng, China Medical University, Taiwan

About the Presenter(s)
Dr. Hao-Yuan Chang is a Nursing Associate Professor at National Taiwan University, specializing in women’s health and nurse retention. Her research integrates GenAI into biostatistics and develops VR curriculum design to advance nursing pedagogy.

Connect on ResearchGate
https://www.researchgate.net/profile/Hao-Yuan-Chang

See this presentation on the full schedule – Tuesday Schedule

Bookmark