Assessment of Nursing Skill and Knowledge of ChatGPT, Gemini, Microsoft Copilot, and Llama: A Comparative Study
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Abstract Introduction Artificial intelligence (AI) has emerged as a transformative force in healthcare. This study assesses the performance of advanced AI systems—ChatGPT-3.5, Gemini, Microsoft Copilot, and Llama 2—in a comprehensive 100-question nursing competency examination. The objective is to gauge their potential contributions to nursing healthcare education and future potential implications. Methods The study tested four AI systems (ChatGPT 3.5, Gemini, Microsoft Copilot, Llama 2) with a 100-question nursing exam in February of 2024. A standardized protocol was employed to administer the examination, covering diverse nursing competencies. Questions derived from reputable clinical manuals ensured content reliability. The AI systems underwent evaluation based on accuracy rates. Results Microsoft Copilot demonstrated the highest accuracy at 84%, followed by ChatGPT 3.5 (77%), Gemini (75%), and Llama 2 (68%). None achieved complete accuracy on all questions. Each of the AI systems has answered at least one question that only they got correctly. Conclusion The variations in AI answers underscore the significance of selecting appropriate AI systems based on specific application requirements and domains, as no singular AI system consistently surpassed others in every aspect of nursing knowledge.
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AI tools are becoming more common in nursing education for academic writing, clinical case analysis, simulation learning, and exam preparation.
“These tools are becoming more common in nursing education to help in academic writing, analysis of clinical cases, simulation learning, and preparation taking exams [2].”
From HOW AI TOOLS (LIKE CHATGPT/GEMINI) AFFECT CRITICAL THINKING IN NURSING STUDENTS. A SYSTEMATIC REVIEW (2026) · cites this paper as [2]
Cites
Ray, P. P. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.04.003 · Cited by 2,463 · see citing works
The state of artificial intelligence in nursing education: past, present, and future directions
De Gagne, J. C. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20064884 · Cited by 191 · see citing works
Taira, K., Itaya, T., & Hanada, A. (2023) · JMIR Nursing · doi:10.2196/47305 · Cited by 76 · see citing works
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Comparative analysis of ChatGPT and Gemini (Bard) in medical inquiry: a scoping review
Fattah, F. H., Salih, A. M., Salih, A. M., Asaad, S. K., Ghafour, A. K., Bapir, R., Abdalla, B. A., Othman, S., Ahmed, S. M., Hasan, S. J., et al. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1482712 · Cited by 50 · see citing works
HOW AI TOOLS (LIKE CHATGPT/GEMINI) AFFECT CRITICAL THINKING IN NURSING STUDENTS. A SYSTEMATIC REVIEW
Din, A. L. (2026) · Journal of Medical & Health Sciences Review · doi:10.65035/650ytk03 · Cited by 1 · see citing works
- Authors
- Hiwa, D. S., Abdalla, S. S., Muhialdeen, A. S., Hamasalih, H. M., & Karim, S. O.
- Affiliations
- University of Sulaimani (IQ)
- ORCID
- Dilan S. Hiwa
- Venue
- Barw Medical Journal
- Publisher
- Barw Medical Journal
- Published
- 2024-05-07
- ISSN
- 2960-1959 (ISSN-L)
- OpenAlex
- W4397000090
- Cited by
- 10
- References
- 3
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 2
- FWCI
- 0.95
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Barw Medical Journal (publishedVersion, cc-by-nc-nd)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- large language models, ChatGPT, Gemini, Microsoft Copilot, Llama 2, nursing knowledge assessment, nursing education, artificial intelligence in healthcare
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