GLOBAL RESEARCH TRENDS IN ARTIFICIAL INTELLIGENCE IN NURSING EDUCATION
DOI:
https://doi.org/10.35631/IJMOE.830032Keywords:
Artificial Intelligence, Nursing Education, StudentsAbstract
Artificial intelligence (AI) has rapidly developed into a disruptive and highly influential force across the domains of healthcare and education, with an expanding role in nursing education where it is increasingly applied to strengthen teaching practices, learning processes, and clinical decision-making competencies. Despite increasing interest, the global research landscape concerning AI in nursing education remains disjointed, with limited consolidation of publication trends, thematic developments, and collaborative patterns. This investigation seeks to deliver an extensive bibliometric examination of global scholarly output on artificial intelligence within nursing education. A systematic retrieval of literature was carried out using the Scopus database, applying an advanced search framework anchored on three principal keywords: “artificial intelligence,” “nursing education,” and “student.” In total, 523 pertinent publications were retrieved and subsequently subjected to analysis. Bibliometric methodologies, comprising Scopus Analyzer, OpenRefine, and VOSviewer, were utilized to facilitate data refinement, descriptive statistical evaluation, and visualization of relational networks. The results demonstrate a marked escalation in publication activity, especially following 2020, with peak contributions observed in 2025 at 38 percent and in 2026 at 29%, signaling a swift and substantial surge in academic engagement within the field. Keyword co-occurrence mapping identifies central conceptual clusters, including artificial intelligence, nursing education, and nursing students, alongside progressively emerging areas such as generative artificial intelligence, ChatGPT, simulation-driven learning environments, and ethical considerations surrounding AI deployment. At the national level, the United States exhibits the highest levels of research productivity, citation impact, and international research collaboration, with notable contributions also originating from Australia, the United Kingdom, and developing research centers across Asia and the Middle East. The most frequently cited studies are largely recent publications, underscoring the continuously evolving and fast-paced nature of this research domain. In summary, artificial intelligence within nursing education has evolved into a rapidly expanding and inherently interdisciplinary area of scholarship, propelled by technological innovation and the escalating need for digital competency in contemporary healthcare education systems. This study offers meaningful insights for researchers, educators, and policymakers in shaping future investigative pathways and implementation strategies.
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