Generative AI adaptive narratives to enhance nursing diagnostic reasoning: a classroom innovation

BACKGROUND: Nursing students often struggle to apply standardized nursing languages (NANDA-I, NIC, NOC) in a coherent and context-sensitive way. Narrative pedagogy supports clinical reasoning, but traditional patient narratives are static and offer limited variability. Generative artificial intelligence (AI) provides new opportunities to create adaptive, cue-rich simulations grounded in authentic patient experiences. OBJECTIVE: To develop and pilot-test an instructional design using generative AI–enhanced narrative simulations to support undergraduate nursing students’ diagnostic reasoning and NANDA–NIC–NOC linkage. METHODS: A mixed-methods pilot study was conducted with second-year nursing students (N = 46). Authentic coronary patient narratives were transformed into adaptive simulated cases using a structured generative AI pipeline. Students were randomly assigned to a control group (static narrative) or an AI-enhanced group (adaptive narratives). Outcomes included diagnostic accuracy, NIC–NOC coherence, self-efficacy, and qualitative reflections. RESULTS: Students in the AI-enhanced group demonstrated significantly higher diagnostic accuracy, stronger NIC–NOC coherence, and greater self-efficacy than the control group (all p < .001, large effect sizes). Qualitative analysis identified enhanced cue sensitivity, iterative refinement of diagnostic decisions, and increased perceived authenticity as key learning mechanisms. CONCLUSION: Generative AI–enhanced narrative simulation is a feasible and pedagogically valuable approach for strengthening nursing diagnostic reasoning using standardized nursing languages. By introducing controlled narrative variability grounded in real patient experiences, this method supports context-aware and reflective clinical reasoning in undergraduate nursing education. IMPLICATIONS FOR NURSING EDUCATION: Generative AI expands narrative pedagogy by enabling educators to create an unlimited range of realistic, ethically sound and cue-rich scenarios for teaching nursing diagnostic accuracy, clinical reasoning and patient-centred care planning. CLINICAL TRIAL NUMBER: Not applicable.