Abstract
Purpose: This presentation aims to explore integrating generative AI technology, such as ChatGPT, into nursing education to support curriculum development, enhance student engagement, and improve learning outcomes. This study examines how AI can be incorporated to enrich pedagogical approaches in nursing, ensuring that students are well-prepared for complex, evolving healthcare environments.
Background: As healthcare settings become increasingly technologically advanced, nursing education must evolve to prepare students for ever-changing clinical practice. AI technologies, particularly generative AI models, present significant potential for transforming nursing education by promoting active learning, fostering critical thinking, and enabling personalized learning pathways. However, AI in education poses challenges related to ethical use, clinical judgment development, and dependency concerns.
Methods: This abstract presents a literature review and case studies on the implementation of generative AI in nursing curricula. It covers its role in interactive simulations, case study generation, ethical decision-making exercises, and real-time feedback. We also outline pilot program outcomes, where AI was used to facilitate student engagement, adapt content to individual learning needs, and assess critical thinking.
Findings: The integration of AI-enhanced student engagement, as evidenced by increased participation in simulations and case-based learning activities. It also fostered higher critical thinking as students analyzed AI-generated responses for clinical accuracy. However, ethical considerations around data privacy, dependency on AI, and accuracy of AI responses were noted as areas for improvement.
Implications: AI in nursing education is promising to enhance curriculum delivery, but it requires careful, responsible integration. Nurse educators are encouraged to incorporate AI thoughtfully to improve learning experiences while upholding ethical standards and promoting independent clinical judgment. Future research should focus on the long-term impacts of AI on clinical readiness and best practices for effective, ethically sound AI integration in nursing education.
Notes
References:
Gosak, L., Pruinelli, L., Topaz, M., & Štiglic, G. (2024). The ChatGPT effect and transforming
nursing education with generative AI: Discussion paper. Nurse Education in Practice, 75, 103888–103888. https://doi.org/10.1016/j.nepr.2024.103888.
Montejo, L., Fenton, A., & Davis, G. (2024). Artificial intelligence (AI) applications in
healthcare and considerations for nursing education. Nurse Education in Practice, 80, 104158-. https://doi.org/10.1016/j.nepr.2024.104158.
Stokel-Walker, C., & Van Noorden, R. (2023). The Promise And Peril Of Generative Ai. Nature (London), 614(7947), 214–216. https://doi.org/10.1038/d41586-023-00340-6.
Sun, G. H. (2024). Prompt Engineering for Nurse Educators. Nurse Educator, 49(6), 293–299. https://doi.org/10.1097/NNE.0000000000001705.
Summers, A., Haddad, M. E., Prichard, R., Clarke, K.-A., Lee, J., & Oprescu, F. (2024). Navigating challenges and opportunities: Nursing student’s views on generative AI in higher education. Nurse Education in Practice, 79, 104062-. https://doi.org/10.1016/j.nepr.2024.104062
Sigma Membership
Beta Beta (Houston)
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Other
Keywords:
Curriculum Development, Virtual Learning, Teaching and Learning Strategies, Artificial Intelligence, Nursing Education
Recommended Citation
Alexander, Karen E. and Iheduru-Anderson, Kechi, "Enhancing Nursing Curriculum With AI: Integrating Generative Technology in Nursing Education" (2025). International Nursing Research Congress (INRC). 143.
https://www.sigmarepository.org/inrc/2025/presentations_2025/143
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
Enhancing Nursing Curriculum With AI: Integrating Generative Technology in Nursing Education
Seattle, Washington, USA
Purpose: This presentation aims to explore integrating generative AI technology, such as ChatGPT, into nursing education to support curriculum development, enhance student engagement, and improve learning outcomes. This study examines how AI can be incorporated to enrich pedagogical approaches in nursing, ensuring that students are well-prepared for complex, evolving healthcare environments.
Background: As healthcare settings become increasingly technologically advanced, nursing education must evolve to prepare students for ever-changing clinical practice. AI technologies, particularly generative AI models, present significant potential for transforming nursing education by promoting active learning, fostering critical thinking, and enabling personalized learning pathways. However, AI in education poses challenges related to ethical use, clinical judgment development, and dependency concerns.
Methods: This abstract presents a literature review and case studies on the implementation of generative AI in nursing curricula. It covers its role in interactive simulations, case study generation, ethical decision-making exercises, and real-time feedback. We also outline pilot program outcomes, where AI was used to facilitate student engagement, adapt content to individual learning needs, and assess critical thinking.
Findings: The integration of AI-enhanced student engagement, as evidenced by increased participation in simulations and case-based learning activities. It also fostered higher critical thinking as students analyzed AI-generated responses for clinical accuracy. However, ethical considerations around data privacy, dependency on AI, and accuracy of AI responses were noted as areas for improvement.
Implications: AI in nursing education is promising to enhance curriculum delivery, but it requires careful, responsible integration. Nurse educators are encouraged to incorporate AI thoughtfully to improve learning experiences while upholding ethical standards and promoting independent clinical judgment. Future research should focus on the long-term impacts of AI on clinical readiness and best practices for effective, ethically sound AI integration in nursing education.
Description
This presentation explores generative AI’s role in nursing education. It examines how tools like ChatGPT can enhance curriculum delivery, promote critical thinking, and foster student engagement while highlighting ethical considerations for responsible AI use.