Lei Pengding, Duo Edward N, Gao Yazhuo, Zhu Xuehua
School of Nursing, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.
BMC Nurs. 2025 Aug 12;24(1):1062. doi: 10.1186/s12912-025-03704-7.
Artificial intelligence (AI) is increasingly transforming the methods of educational delivery and knowledge acquisition within the nursing discipline. This study aims to explore the experiences of undergraduate nursing students regarding the integration of AI into nursing education and to improve learning outcomes and AI effectiveness.
A qualitative descriptive study was utilized using semi-structured interviews. Twenty-one undergraduate nursing students were selected using the purposive sampling method. The interview data were collected and analyzed using the conventional content analysis method.
Five main themes and thirteen sub-themes emerged from the data analysis: functional experiences with AI, content-related experiences, performance-related experiences, attitudes toward AI and its behavioral impact, and considerations of academic ethics.
AI-assisted instruction is an emerging trend in nursing education. To optimize its effectiveness, efforts should focus on improving learning outcomes, acknowledging AI as a supplementary tool, managing content-related risks, enhancing the technical performance of AI platforms, addressing issues of overreliance while integrating traditional and modern approaches, and strengthening academic integrity measures to mitigate ethical risks.
人工智能（AI）正日益改变护理学科的教学方法和知识获取方式。本研究旨在探讨本科护理专业学生在将人工智能融入护理教育方面的经历，并提高学习成果和人工智能的有效性。
采用半结构化访谈进行定性描述性研究。采用目的抽样法选取21名本科护理专业学生。访谈数据采用传统内容分析法进行收集和分析。
数据分析得出五个主要主题和十三个子主题：人工智能的功能体验、与内容相关的体验、与表现相关的体验、对人工智能的态度及其行为影响，以及学术伦理考量。
人工智能辅助教学是护理教育中的一个新兴趋势。为了优化其有效性，应努力提高学习成果，将人工智能视为一种辅助工具，管理与内容相关的风险，提高人工智能平台的技术性能，在整合传统和现代方法时解决过度依赖问题，并加强学术诚信措施以降低伦理风险。
