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Qualitative exploration identifies AI literacy gaps and barriers in nursing students' education, highlighting the need for curriculum improvement.
BACKGROUND: The artificial intelligence (AI) transformation of nursing education hinges on students' AI literacy. This study explores nursing students' AI literacy and utilization barriers in AI-assisted learning. METHOD: A descriptive qualitative design was used. Twenty-six undergraduate nursing students were recruited. Data were collected between May 2024 and January 2025 through individual, in-depth, semistructured interviews. Data analysis followed Clarke and Braun's thematic analysis approach. RESULTS: Five main themes were identified: (1) ambiguous perceptions of AI; (2) adaptive behaviors toward AI technology; (3) ambivalent attitudes toward AI applications; (4) perceived barriers to AI adoption; and (5) expectations of AI integration. CONCLUSION: This qualitative study illuminates the multifaceted landscape of AI literacy and barriers perceived by nursing students, and underscores the need for nursing education to address the AI literacy gaps and overcome adoption barriers. Future research should track the long-term effects of AI literacy on clinical performance and career trajectories.
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Yu et al. (2026) studied this question.
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