Song Dan, Zhang Panpan, Zhu Yuyun, Qi Shutong, Yang Yajuan, Gong Lili, Zhou Lihua
School of Nursing, Anhui Medical University, No.81 Meishan Road, Shushan District, Hefei, Anhui 230032, PR China.
Dentistry Center, The First Affiliated Hospital of the University of Science and Technology of China (Anhui Provincial Hospital), No.17 Lujiang Road, Luyang District, Hefei, Anhui 230001, PR China.
Nurse Educ Pract. 2025 Sep 3;88:104549. doi: 10.1016/j.nepr.2025.104549.
This study aimed to explore the effects of interactive teaching strategies based on generative artificial intelligence (GenAI) under the guidance of outcome-based education (OBE) theory on higher-order thinking skills (HOTS) and artificial intelligence (AI) literacy of undergraduate nursing students.
Recently, GenAI-assisted teaching has been widely recognised as a trend in nursing education reform. HOTS and AI literacy are important for nursing students in the era of artificial intelligence. However, studies on the use of GenAI to enhance the HOTS and AI literacy of undergraduate nursing students are limited.
A quasi-experimental study.
Based on OBE theory, interactive teaching strategies using GenAI were introduced into a nursing course. Overall, 132 third-year nursing undergraduates enrolled in this course were randomly divided into experimental (n = 66) and control groups (n = 66).
After completing the course, the HOTS scores of nursing undergraduates (P = 0.018) and AI literacy (P < 0.001) in the experimental group were significantly better than those in the control group. There was a significant difference in the HOTS scores (P < 0.001) and AI literacy (P < 0.001) between the experimental group before and after the course.
GenAI-assisted teaching could help nursing undergraduates improve their HOTS and AI literacy. As an important auxiliary teaching tool, GenAI should be integrated into other nursing courses and widely applied in nursing education in the future.
