Research on Dynamic Adjustment and Curriculum Reconstruction of Nursing Programs in Private Universities Empowered by Artificial Intelligence

Abstract

Objective: Against the backdrop of the “Healthy China” initiative and the digital transformation of higher education, this study addresses the critical disconnect between nursing talent cultivation in private universities and clinical practice demands. It aims to provide theoretical underpinnings and practical pathways for optimizing nursing curriculum systems in this context. Methods: A systematic literature review was conducted, utilizing 87 valid articles selected from Chinese and English databases spanning 2019 to 2025. The review synthesized the current state of artificial intelligence (AI)-empowered nursing education, refined the theoretical construction of a core conceptual framework, and performed a multi-perspective comparative analysis from three dimensions: traditional educational models, AI application strategies, and controlled experimental results. Results: AI technology significantly enhances the alignment between nursing curricula and job requirements, improves students’ clinical practical competencies, and boosts teaching efficiency. Private universities can achieve dynamic curriculum reconstruction by establishing diversified resource support systems, implementing modular curriculum design, and developing intelligent evaluation mechanisms. Conclusion: AI serves as a pivotal enabler for nursing education reform in private universities. Future efforts should focus on standardizing AI nursing education resources and integrating humanistic literacy into technological applications, thereby fostering interdisciplinary nursing professionals competent for the era of smart healthcare.

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