How artificial intelligence (AI) supports nursing education: profiling the roles, applications, and trends of AI in nursing education research (1993–2020)

ABSTRACT

This study provides research-based evidence to profile: (1) the roles of artificial intelligence in nursing, (2) its research applications, and (3) the research trends for future study. On the basis of the PRISMA statement, a series of AI and nursing education related keywords from the literature were used to retrieve high-quality journal articles from the Web of Science. A total of 112 AI-supported nursing education research articles were analyzed based on a three-dimensional framework, including interaction (e.g. the roles of AI, types of AI systems), research (e.g. methods and fields), and performance (e.g. research groups and measurement foci). The results revealed that AI played a primary role in profiling and prediction in nursing research (63%), and the most used AI system in nursing was intelligent agents (53%). The quantitative approach (87%) was the dominant research method, and the most relevant studies concerned health and medicine (92%). Regarding sample and measurement matters, patients and medical staff (75%) were the two primary research samples, and the performance evaluation of AI-related tools and systems (90%) was the core measurement focus. Additional content analysis across the three research interests was performed and discussed. Directions for future studies are provided.

KEYWORDS:

• Artificial intelligence (AI)
• nursing education
• applications
• trends
• systematic review

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethical approval

This study was a retrospective bibliometric analysis focusing on analyzing the published articles. No clinical trials were conducted in this study.

Additional information

Funding

This study is supported in part by the Ministry of Science and Technology, Taiwan, under contract numbers MOST 109-2511-H-011-002-MY3, and MOST 109-2511-H-130-002.

Notes on contributors

Gwo-Jen Hwang

Gwo-Jen Hwang, Ph.D., is a chair professor at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology. His research interests include mobile learning, digital game-based learning, flipped classroom and AI in education.

Kai-Yu Tang

Kai-Yu Tang, Ph.D., is an assistant professor at the Graduate Institute of Library & Information Science, National Chung Hsing University. His research interests include mobile commerce, social network analysis, and computational thinking.

Yun-Fang Tu

Yun-Fang Tu, Ph.D., is an assistant professor of educational technology at the Department of Library and Information Science, Research and Development Center for Physical Education, Health, and Information Technology, Fu Jen Catholic University. Her research interests include digital library, mobile and ubiquitous learning.