A Study on the Pathways for Artificial Intelligence to Reconstruct the “Health Assessment” Course from the Perspective of Integration of Industry, Education, and Innovation
Driven by the dual imperatives of national vocational education reform and the “Healthy China” strategy, nursing education is undergoing a fundamental transformation from skill transmission to the cultivation of “digital and intelligent literacy” and innovative competence. Focusing on the core module Health Assessment in vocational undergraduate nursing programs, this paper explores innovative pathways for restructuring the curriculum through artificial intelligence (AI) within the theoretical framework of “integration of industry, education, and innovation.” The study analyzes traditional teaching challenges—clinical practice barriers, unitary assessment methods, and disconnection from industry frontiers—and demonstrates the necessity of AI empowerment. It constructs a tri‑chain synergy model (education chain, industry chain, innovation chain) to guide curriculum reform. Four core pathways are elaborated: reshaping objectives and content, innovating methods and resources, reforming evaluation through data‑driven approaches, and building collaborative platforms with robust mechanisms. Drawing on international trends, the paper also proposes safeguard measures. The research aims to provide a theoretical reference and practical blueprint for the digital transformation of vocational undergraduate nursing education.
[1] Jie MS, 2026, The Theoretical Logic and Practical Pathways for Enhancing Labor Education in Higher Education Institutions through the Integration of Industry and Education. Journal of Ideological and Theoretical Education, 2026(4): 145–153.
[2] Dong RL, Wan QL, Guang LL, et al., 2026, Dynamic Changes and Relationships among AI Literacy, Job Crafting, and Career Growth in New Nurses in the AI Era: A Multicenter Three-wave Longitudinal Study, Nurse Education Today, 2026(167): 107237.
[3] Arrue M, Cariñanos-Ayala S, Zarandona J, 2026, Guided University Debate: Fostering Nursing Students’ Competency Development, Nurse Education Today, 2026(167): 107301.
[4] Nissim Y, Simon E, 2025, The Diffusion of Artificial Intelligence Innovation: Perspectives of Preservice Teachers on The Integration of ChatGPT in Education. Journal of Education for Teaching, 51(2): 381–401.
[5] Cai L, 2025, Exploration and Research on the Integration of Artificial Intelligence and Metacosmos into Innovation and Entrepreneurship Education and the Integration of Industry, Science, Innovation and Education. Applied Mathematics and Nonlinear Sciences, 10(1): 516.
[6] Fung TCJ, Chan SL, Lam CFM, et al., 2025, Effects of Generative Artificial Intelligence (GenAI) Patient Simulation on Perceived Clinical Competency among Global Nursing Undergraduates: A Cross-over Randomised Controlled Trial. BMC Nursing, 24(1): 934.
[7] Sawka D, Kendall M, Diorio M, et al., 2025, Impact of a Preclinical Elective on Medical Student Performance on an Anesthesiology Simulation Scenario. Advances in Medical Education and Practice, 2025(16): 1229–1238.
[8] Lee S, Kim MC, Kim J, 2024, The Status of Interprofessional Education for Healthcare Students in the Republic of Korea: A Scoping Review Focusing on Simulation-based Education. Korean Journal of Medical Education, 36(3): 303–314.
[9] Machry JS, Krzyzewski J, Ward C, et al., 2024, The NICU Tracheostomy Team: Multidisciplinary Collaboration for Improvement in Survival of Complex Patients. Journal of Perinatology, 44(12): 1854–1862.
[10] Cai Y, Lei XP, Zhang Y, et al., 2025, Exploration of Practical Teaching Reform in Pharmacognosy Based on a “Science–Industry–Education” Integrated Practical Teaching Base. Health Vocational Education, 43(3): 49–54.
