Abstract
Problem: Artificial intelligence (AI) has driven a global change in nursing education and is becoming more prevalent worldwide. Integrating AI into nursing education could revolutionize the preparation of future nurses and equip them with the necessary knowledge and skills related to AI. However, the existing literature on the intersection of nursing education and artificial intelligence is sparse, consisting primarily of commentaries, editorials, and opinion articles. To our knowledge, there is a notable gap in the comprehensive review that systematically synthesizes the current use of AI in nursing education.
Purpose: The aim of this systematic review was to synthesize the body of research on the current utilization of AI in nursing education to comprehensively understand the application of AI in the field of nurse education.
Search Strategy: This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic search of PubMed, Scopus, Education Resources Information Centre, and CINHAL Plus Full Text was conducted to identify studies published between 2019 and 2024 that aimed to investigate the body of research on AI in nursing education. The following Key terms were used to identify relevant studies: “artificial intelligence” OR “AI” AND “nursing” OR” nurses” OR “nursing education”.
Results of literature search: All identified references were stored in Zotero. A total of 573 Articles were identified from databases. Among them,85 duplicates were removed, and 488 articles underwent eligibility screening. After abstract/full-text screening,15 articles met the inclusion and exclusion criteria.
Synthesis of Evidence: The studies included in the review were synthesized to produce four themes pertaining to AI in nursing education: AI-driven decision-making, virtual reality and simulation, academic writing skills, and personalized learning.
Implications for Practice: This systematic review provides valuable insights into the current utilization of AI in nursing education, which provides a potential path to enhance critical thinking abilities and improve clinical competency for complex nursing procedures. Collaboration among educators and AI developers can improve learning outcomes for nursing students. Nursing educators can guard and guide the use of AI technology. Despite the applications of AI, AI in nursing education remains in its infancy, and further exploration and research in these areas is needed.
Sigma Membership
Non-member
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Systematic Review
Research Approach
N/A
Keywords:
Teaching and Learning strategies, Virtual Learning, Artificial Intelligence, AI, AI Utilization in Nursing Education
Recommended Citation
Almutairi, Rayhanah R., "A Systematic Review of Artificial Intelligence and Nursing Education: What Do We Know?" (2025). International Nursing Research Congress (INRC). 75.
https://www.sigmarepository.org/inrc/2025/presentations_2025/75
Conference Name
36th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Seattle, Washington, USA
Conference Year
2025
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
A Systematic Review of Artificial Intelligence and Nursing Education: What Do We Know?
Seattle, Washington, USA
Problem: Artificial intelligence (AI) has driven a global change in nursing education and is becoming more prevalent worldwide. Integrating AI into nursing education could revolutionize the preparation of future nurses and equip them with the necessary knowledge and skills related to AI. However, the existing literature on the intersection of nursing education and artificial intelligence is sparse, consisting primarily of commentaries, editorials, and opinion articles. To our knowledge, there is a notable gap in the comprehensive review that systematically synthesizes the current use of AI in nursing education.
Purpose: The aim of this systematic review was to synthesize the body of research on the current utilization of AI in nursing education to comprehensively understand the application of AI in the field of nurse education.
Search Strategy: This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic search of PubMed, Scopus, Education Resources Information Centre, and CINHAL Plus Full Text was conducted to identify studies published between 2019 and 2024 that aimed to investigate the body of research on AI in nursing education. The following Key terms were used to identify relevant studies: “artificial intelligence” OR “AI” AND “nursing” OR” nurses” OR “nursing education”.
Results of literature search: All identified references were stored in Zotero. A total of 573 Articles were identified from databases. Among them,85 duplicates were removed, and 488 articles underwent eligibility screening. After abstract/full-text screening,15 articles met the inclusion and exclusion criteria.
Synthesis of Evidence: The studies included in the review were synthesized to produce four themes pertaining to AI in nursing education: AI-driven decision-making, virtual reality and simulation, academic writing skills, and personalized learning.
Implications for Practice: This systematic review provides valuable insights into the current utilization of AI in nursing education, which provides a potential path to enhance critical thinking abilities and improve clinical competency for complex nursing procedures. Collaboration among educators and AI developers can improve learning outcomes for nursing students. Nursing educators can guard and guide the use of AI technology. Despite the applications of AI, AI in nursing education remains in its infancy, and further exploration and research in these areas is needed.
Description
Artificial intelligence (AI) has driven a global change in nursing education and is becoming more prevalent worldwide. Integrating AI into nursing education could revolutionize the preparation of future nurses and equip them with the necessary knowledge and skills related to AI.