Nurse educator · 2025
AI-Powered Virtual Reality Simulation for Clinical Handover Training: A Development Framework.
СтатьяНазвание и аннотация: Перевод в очереди
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Chan Maggie Mee Kie, Sze Ki Cheung Daphne, Ho Ken Hok Man, Ka Shun Hung Carson, Ko Hong Tai Ziv, Wai Hin Wan Abraham, Yiu Cheong Wong Benney, Ka Chun Cheuk Kelvin, Lai Pak Hin, Chan Kin Fung
Аннотация
BACKGROUND: Clinical handover is critical for patient safety in nursing; however, traditional methods often lack immersion, realism, and personalized feedback, which hinders effective student training.
PROBLEM: Nurse educators face technical challenges and limited practical guidance when integrating generative artificial intelligence (GenAI) and virtual reality (VR) into handover education.
APPROACH: This article shares our developmental framework for integration, consisting of a 3-layer architecture: system (ChatGPT integration for adaptive responses), interaction (gamification interface), and presentation (immersive VR with Identification, Situation, Background, Assessment, Recommendation [ISBAR]-based AI avatars modeled after actual instructors).
RESULTS: Pilot testing with undergraduate students showed enhanced authenticity through real-person avatars and real-time ISBAR feedback, with challenges in nonverbal synchronization identified for future improvements.
CONCLUSIONS: This developmental framework and implementation checklist provide nursing educators with systematic guidance for deploying AI-VR technology in clinical handover training, positioning nursing education at the forefront of pedagogical innovation.
PROBLEM: Nurse educators face technical challenges and limited practical guidance when integrating generative artificial intelligence (GenAI) and virtual reality (VR) into handover education.
APPROACH: This article shares our developmental framework for integration, consisting of a 3-layer architecture: system (ChatGPT integration for adaptive responses), interaction (gamification interface), and presentation (immersive VR with Identification, Situation, Background, Assessment, Recommendation [ISBAR]-based AI avatars modeled after actual instructors).
RESULTS: Pilot testing with undergraduate students showed enhanced authenticity through real-person avatars and real-time ISBAR feedback, with challenges in nonverbal synchronization identified for future improvements.
CONCLUSIONS: This developmental framework and implementation checklist provide nursing educators with systematic guidance for deploying AI-VR technology in clinical handover training, positioning nursing education at the forefront of pedagogical innovation.