Artificial Intelligence in Nursing Education: A Bibliometric Analysis
Xiaoyue Yu, Weizhen Wu, Jun Ni, Zhifeng Lin
TL;DR
This paper analyzes the growing role of artificial intelligence in nursing education using bibliometric methods to identify trends and key contributors.
Contribution
The study provides novel insights into AI's integration in nursing education through a comprehensive bibliometric analysis.
Findings
430 publications were identified, with the US and China as the main contributors.
Nurse Education Today and Nurse Education in Practice were the most significant journals.
Trending topics included technology, educational programs, and simulation.
Abstract
The swift advancement of artificial intelligence (AI) has significantly impacted multiple industries. The prospects of AI within nursing education are especially promising, as it presents avenues for enhancing the preparation of forthcoming nursing practitioners in a constantly changing healthcare landscape. We employed VOSviewer, CiteSpace, and the Bibliometrix R package to effectively visualize the bibliometric findings. A total of 430 publications were identified. The predominant sources of these publications were the United States of America and China, while the National University of Singapore emerged as the foremost contributor. The journals that provided the most substantial input in this area included Nurse Education Today and Nurse Education in Practice. Furthermore, keywords showed significant citation bursts and trending topics, such as technology, educational programs, and…
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Simulation-Based Education in Healthcare · E-Learning and COVID-19