The Application of Generative Artificial Intelligence in Designing Simulation-based Teaching Cases for ICU Specialized Nurses: A Randomized Controlled Trial

Abstract :

Introduction: The intensive care unit is a complex environment, requiring nurses with advanced clinical skills and decision-making abilities. Simulation-based education is essential for enhancing these skills, but traditional case design is time-consuming and heavily reliant on educator expertise. Generative Artificial Intelligence (Generative AI) presents an opportunity to automate and streamline case design. This study evaluates the effectiveness of Generative AI in designing simulation-based teaching cases for ICU nurses.

Methods: A randomized controlled trial was conducted with 40 ICU nurses, randomly assigned to either the experimental group (n = 20), using Generative AI for case design, or the control group (n = 20), using traditional methods. Outcomes measured included case design time, learner satisfaction, and expert-rated case quality across 7 dimensions. Statistical analyses included t-tests and Mann-Whitney U tests, with significance set at p < 0.05.

Results: The experimental group significantly reduced case design time (56.20 ± 9.35 minutes vs. 181.35 ± 22.13 minutes, p < 0.01) and achieved higher learner satisfaction (median 10 vs. 9, p < 0.01). No significant differences were observed in case quality for “clarity of objectives,” “realism,” and “evaluation design” (p > 0.05). However, the experimental group scored lower in “scenario logic” (p = 0.024), “intervention feasibility” (p = 0.001), “material completeness” (p = 0.010), and “difficulty alignment” (p = 0.003).

Conclusion: Generative AI enhances simulation case design efficiency and learner satisfaction.While AI-generated cases match human-designed cases in certain aspects, they underperform in areas requiring clinical rigor and practical relevance. Further optimization of AI-generated content is needed for high-quality cases.

Please include a short summary of your presentation that highlights why an attendee would want to participate in your session.: Join our session to explore how Generative AI can revolutionize simulation-based case design for ICU nurses training.We'll showcase how AI significantly enhances design efficiency and learner satisfaction while discussing key areas where human oversight is still essential. Discover how this cutting-edge technology can transform nursing education.