The integration of generative artificial intelligence in nursing education from 2020 to 2025: A bibliometric analysis

Abstract

Generative artificial intelligence (AI), particularly large language models such as Chat Generative Pre-Trained Transformer (ChatGPT), is rapidly transforming higher education, including nursing. This study mapped global research trends on the integration of generative AI in nursing education using a bibliometric approach. Articles indexed in Scopus between 2020 and 2025 were retrieved with keywords related to generative AI, ChatGPT, and nursing education. A total of 149 English-language journal articles were analyzed, and bibliometric visualization was conducted using VOSviewer version 1.6.20 to examine publication patterns, leading authors, journals, institutions, countries, and thematic clusters. Results showed a steady rise in publications, with significant growth in 2023–2024 following the widespread adoption of ChatGPT. The most prolific author is from Taipei Medical University, while Nurse Education in Practice was the top journal with 13 articles and 113 citations. Taipei Medical University and NUS Yong Loo Lin School of Medicine were the most productive institutions, and the United States led in overall output and international collaborations. Keyword analysis revealed four thematic clusters: technological foundations, pedagogical applications, competency and critical thinking, and nursing informatics. Generative AI in nursing education is an emerging field, and future research should address policy, long-term outcomes, and institutional adoption to ensure responsible integration.

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