Enhancing learning outcomes through AI-driven simulation in nursing education: a systematic review

Abstract

Artificial intelligence (AI) is increasingly integrated into simulation-based nursing education to enhance scalability, personalisation, and interactivity. This review systematically examined the impact of AI-driven simulations on learning outcomes in nursing education. Method This systematic review adhered to PRISMA guidelines and included empirical studies published between 2015 and 2025. A comprehensive search was conducted across six databases, and study quality was appraised using RoB 2, ROBINS-I, JBI, and MMAT tools. Methodological heterogeneity precluded meta-analysis; findings were instead synthesised through deductive categorisation to ensure a structured and critical integration. Results Sixteen studies met the inclusion criteria. AI-driven simulations were associated with improved communication, clinical reasoning, knowledge acquisition, self-efficacy, and empathy. Most studies reported high levels of learner satisfaction and engagement. However, limitations included challenges in interpreting nuanced emotional cues, limited cultural adaptability of AI systems, and technological constraints affecting responsiveness. Conclusions AI-driven simulation supports the development of diverse learning outcomes in nursing education. Further research is needed to explore long-term effects and optimise implementation strategies.