Research on the experience of utilizing artificial intelligence in nursing learning from the perspective of nursing students – a qualitative study
Abstract Background 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 educati...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-08-01
|
| Series: | BMC Nursing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12912-025-03704-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract Background 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. Methods 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. Results 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. Conclusion 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. |
|---|---|
| ISSN: | 1472-6955 |