Understanding undergraduate nursing students’ learning journeys with artificial intelligence: a journey mapping study

Abstract

As artificial intelligence (AI) becomes increasingly embedded in healthcare, nursing education faces growing expectations to prepare students with AI literacy. However, nursing students often encounter cognitive, emotional, and practical challenges when learning AI, and their learning experiences across the educational trajectory remain insufficiently understood. This study employed journey mapping to explore how undergraduate nursing students experience learning AI over time. A qualitative descriptive design was used. Seventeen undergraduate nursing students from four universities in different regions were purposively recruited between March and September 2025. Semi-structured interviews were conducted and analyzed using content analysis. A journey map was developed to integrate students’ learning tasks, emotional trajectories, barriers, and needs across different stages of AI learning. The AI learning journey was characterized by four stages: Initial Contact and Curiosity, Learning and Confusion, Integration and Anxiety, and Internalization and Confidence. Across these stages, students experienced distinct and evolving challenges. Early learning was characterized by limited relevance and fragmented exposure to AI concepts. Subsequent stages involved cognitive overload, theory–practice gaps, ethical uncertainty, and career-related anxiety, while later stages highlighted the need for feedback, institutional support, and opportunities for innovation and professional identity consolidation. Journey mapping revealed the dynamic and stage-specific nature of nursing students’ AI learning experiences. These findings highlight the importance of stage-sensitive educational approaches that combine early cognitive guidance, scaffolded technical learning, ethical reflection, and innovation-oriented support to strengthen AI education in undergraduate nursing programs.

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