The effectiveness of Artificial Intelligence (AI) in learning outcomes of nursing students : A meta-analysis of randomized controlled trials (RCTs)
Background Artificial intelligence (AI) has the potential to revolutionize nursing education by enhancing learning experiences and educational outcomes. While researchers have investigated the usefulness of AI-based technology in nursing education, a systematic review emphasising randomised contro...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
American Institute of Mathematical Sciences
2025
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/49763/1/STEM%20Education%20Manuscript.pdf http://ir.unimas.my/id/eprint/49763/ https://www.aimspress.com/aimspress-data/steme/2025/4/PDF/steme-05-04-026.pdf |
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| Summary: | Background
Artificial intelligence (AI) has the potential to revolutionize nursing education by enhancing learning experiences and educational outcomes. While researchers have investigated the usefulness of AI-based technology in nursing education, a systematic review emphasising randomised controlled trials (RCTs) is required to provide solid evidence to address educators' scepticism of its application. In this review, we provide evidence-based insights from RCTs to guide nursing educators and policymakers in enhancing educational practices.
Objective
To evaluate the effectiveness of AI-based technology applications on nursing students' learning outcomes in terms of knowledge level.
Design
Meta-Analysis of randomised controlled trials (RCTs).
Database Sources
A thorough electronic database search included Scopus, Pubmed, CINAHL, and Google Scholar. The search started on January 15, 2023 and ended on May 31, 2023 as sufficient research was identified. This review was supplemented by manual searches of reference lists from relevant articles to ensure comprehensiveness, following the inclusive and exclusive criteria.
Review Methods
PRISMA 2020 guidelines were adopted in this SLR. The CASP RCT Checklist was used to examine the quality of the study. Two reviewers collaborated to enhance the quality of the screened studies. Any discrepancies were resolved through discussion and consultation with a third reviewer, which was not utilised because no discrepancies were observed.
Results
The five RCT studies met the inclusion criteria and were included in this SLR for critical analysis. Three major themes were formulated based on the main objective, namely cognitive, psychomotor, and affective. Overall, further analysis of the three major themes established a total of 6 sub-themes, namely knowledge level, cognitive load, skills performance, anxiety, satisfaction, and confidence. The use of AI had a positive, small, and statistically insignificant effect on knowledge level, as evident from the meta-analysis. A review of the article also indicated positive effects of AI on skill performance, satisfaction, and confidence, whereas it reduced cognitive load and anxiety.
Conclusion
The meta-analysis provides solid evidence-based insights into the effectiveness of AI in nursing education. It advances nursing education by guiding nurse educators, policymakers, and future researchers in maximising the benefits of AI in delivering safe, efficient, and highest-quality nursing care. |
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