"Nursing handovers" aims to enhance new nursing staff's ISBAR handover communication skills and decision-making abilities in synthesizing critical information. The study employs SVVR technology to design simulated scenarios following patient emergencies and utilizes GAI's real-time simulated dialogue feedback mechanism. This step-by-step approach guides learners in training handover communication techniques and decision-making for synthesizing essential information. Through interactions between new nurses and GAI senior nurses, trainees practice asking questions to gather essential information required during patient transfer handovers, following the ISBAR standard handover protocol.

In busy clinical settings, senior nurses often convey handover techniques verbally during emergencies. This approach yields ineffective and incomplete learning outcomes due to time constraints. Consequently, AI-trained standard senior nurses enable learners to practice wholeheartedly in a safe and secure environment, unrestricted by time or space, with the ability to repeat experiences. Research findings also reveal that learners exhibit a high state of flow and significant acceptance of the game during gameplay, with low levels of anxiety toward the game. This indicates that utilizing generative AI combined with the Standard Senior Nurse to learn shift handover techniques through gameplay effectively assists learners in fulfilling the critical mission of nursing staff—shift handover.