Artificial intelligence (AI) is reshaping education, but existing AI application frameworks cannot be effectively applied to nursing education, which is defined by its focus on practical skills and clinical judgment. This study aims to address this gap by synthesizing literature on current educational AI application frameworks to propose a dedicated AI application framework for nursing education, grounded in the core nursing competency model of Knowledge, Attitude, and Skills (KAS) to guide curriculum design. A systematic search was conducted in PubMed, Embase, Web of Science, and CNKI to identify literature on educational AI application frameworks. The search strategy combined controlled vocabulary and free-text keywords, adapted to the indexing structure of each database. Reference lists of eligible studies and relevant articles were manually screened to supplement the electronic search. The search was updated to March 2026. The study systematically screened the initial 1750 retrieved documents, ultimately including 23 studies for analysis. The included publications spanned the years 2022 to 2026 and covered 15 countries worldwide. Through in-depth analysis of these documents, the study identified and synthesized an AI application framework for nursing education comprising three major dimensions: knowledge, attitudes, and skills. This framework encompasses 12 key sub-dimensions, providing detailed guidance for curriculum design in nursing education, and is proposed for an AI application framework tailored to nursing education. The potential of AI in nursing education is transformative. To fully unlock this potential and ensure responsible application, existing research should focus on empirically validating the proposed framework through empirical studies, exploring adaptive implementation strategies for resource-constrained settings, and developing educators’ AI application capabilities.
Xiang et al. (Wed,) studied this question.