Ethical considerations of undergraduate nursing students using artificial intelligence for learning: A qualitative study.

Background

Artificial intelligence technology is rapidly penetrating the field of nursing education, and students are widely using AI tools in their learning process. As a result, the ethical issues thus raised are drawing increasing attention.

Objective

This study aims to explore nursing undergraduates' ethical experiences in AI-assisted learning, such as academic integrity, privacy protection, and learning fairness.

Methods

This descriptive qualitative study was conducted at a university in Eastern China. Purposive sampling was used to recruit 21 undergraduate nursing students across all four academic years. Data were collected through semi-structured interviews from December 2025 to February 2026. Thematic analysis was performed following Braun & Clarke's six-step framework.

Results

4 themes and 13 sub-themes were identified. Students' trust in AI varied along a spectrum from complete reliance to deep skepticism. While some students proactively protected privacy and verified AI-generated information through systematic cross-checking, others showed indifference or a lack of verification due to limited motivation or access. Perceptions of fairness were diverse, ranging from viewing AI as an equal-opportunity tool to concerns about resource disparities between free and paid platforms. Despite AI's efficiency, a recurring theme among participants was the irreplaceable value of face-to-face interpersonal communication with teachers and peers.

Conclusion

This single-center qualitative study offers contextual insights into nursing students' ethical experiences with AI-assisted learning. These insights may inform the development of AI ethics curricula and institutional guidance, while further research is needed to explore transferability across diverse settings and to evaluate the effectiveness of educational interventions.