혼합연구를 이용한 간호 시뮬레이션 수업에서의 생성형 인공지능 활용경험

Exploring the Use of Generative Artificial Intelligence in Nursing Simulation Courses: A Mixed-Methods Study

Purpose: This study aims to explore the significance and impact of generative artificial intelligence (AI) in nursing simulation courses, enhance its application potential, and propose effective ethical strategies for using AI. Methods: Convergent parallel mixed-methods approach was employed to investigate AI usage patterns among nursing students during simulation classes and qualitatively examine their attitudes toward AI. Results: Among AI-related questions, “priority in nursing and my role in simulation” had the highest term frequency-inverse document frequency(TF-IDF) value of 8.358, The term frequency(TF) of “medication” was the highest at 36, its TF-IDF value was 4.464. Qualitative analysis revealed that the use of AI in simulation classes is inevitable, necessitating separate guidelines for AI use and the development of tailored instructional designs. AI has demonstrated positive effects in nursing simulation courses, such as personalized learning support, real-time feedback provision, improved accessibility, and the promotion of creative problem-solving. Conversely, limitations, including increased AI dependency, decreased critical thinking skills, widening digital disparity among individuals, and data privacy issues, were noted. Conclusion: Clear usage guidelines, ethical education, and the cultivation of critical AI literacy are essential for effectively using AI in nursing simulation courses. This approach explicitly states that AI should be used as a supplementary knowledge tool, -not as a substitute for nurses, roles or decision-making,- and continuous oversight is necessary.