Other Titles
How AI Can Enhance Clinical Education [Title Slide]
Other Titles
PechaKucha Presentation
Abstract
Background: Generative AI is transforming clinical nursing education, highlighting the urgent need to train nurse educators with the knowledge, tools, and confidence for practical use. AI tools are quickly impacting content, student preparation, and teaching methods, creating both opportunities and challenges. AI offers both advantages and obstacles in clinical content creation; however, advantages do not replace nursing experience. Due to its rapid integration into education, many educators remain cautious about responsible implementation because of ethical concerns.
Purpose: This study examines changes in participant knowledge and confidence in the use of AI tools in clinical education among clinical nurse educators from eight states in the Southeast following a clinical instructor education workshop. This workshop explored AI's role in clinical nursing education, practical applications, risks, opportunities, and ethical considerations.
Method: A workshop on AI tools was conducted for educators from both academic and practice settings. A retrospective pre-post- survey assessed changes in confidence and the integration of AI into clinical education practice. Interactive and engaging learning methods guided participants on the core principles of creating and implementing personal objective AI tools. AI tools were compared, helping participants better understand the specific uses of the different AI tools introduced and discussed.
Results: Participants (n=41) reported a statistically significant (p < 0.05) increase in knowledge and confidence in ethically integrating AI tools into practice, as well as an increase in confidence regarding implementing AI into current clinical education practices.
Implications: AI can enhance clinical judgment, critical thinking, and patient-centered care. Using AI technologies such as simulation, adaptive quizzing, evaluation creation, concept mapping, and decision-support tools can boost clinical judgment. Incorporating these into clinical nursing education supports competency-based training and prepares nurses for technology-driven healthcare.
Notes
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CAPES Academy Project is supported by the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) as part of an award totaling $3,923,812. with 0% financed with non-governmental sources. Award number T1QHP47312.
References:
Jallad, S. T., Alsaqer, K., Albadareen, B. I., & Al-maghaireh, D. (2024). Artificial intelligence tools utilized in nursing education: Incidence and associated factors. Nurse Education Today, 142, N.PAG. https://doi-org.proxy.library.emory.edu/10.1016/j.nedt.2024.106355
Jiang, Z., Liu, Q., Jiang, N., Ning, M., & Yu, Q. (2025). Artificial Intelligence Literacy and Its Associated Factors Among Nursing Students. Nurse Educator, 50(6), E378–E383. https://doi-org.proxy.library.emory.edu/10.1097/NNE.0000000000001989
Labrague, L. J., & Sabei, S. A. (2025). Integration of AI-Powered Chatbots in Nursing Education: A Scoping Review of Their Utilization, Outcomes, and Challenges. Teaching & Learning in Nursing, 20(1), e285–e293. https://doi-org.proxy.library.emory.edu/10.1016/j.teln.2024.11.010
Olla, P., Wodwaski, N., & Long, T. (2025). Beyond the Bot: A Dual-Phase Framework for Evaluating AI Chatbot Simulations in Nursing Education. Nursing Reports, 15(8), 280. https://doi-org.proxy.library.emory.edu/10.3390/nursrep15080280.
Qutishat, M., Al-Hadidi, M., Shakman, L., Shdefat, A. A.-, Ghunaimi, A.-A. A.-, & Al-Barwani, S. S. (2025). Benefits, challenges, and future recommendations in the integration of artificial intelligence in nursing education: A scoping review. Teaching & Learning in Nursing, 20(4), e1315–e1323. https://doi-org.proxy.library.emory.edu/10.1016/j.teln.2025.05.016.
Sigma Membership
Alpha Epsilon
Lead Author Affiliation
Emory University, Atlanta, Georgia, USA
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Retrospective
Research Approach
Quantitative Research
Keywords:
Continuing Education, Faculty Development, Teaching and Learning Strategies, Advances in Education, Generative Artificial Intelligence
Recommended Citation
Woods, Elizabeth L.; Clement, Desiree Mullis; Pampuri, Kandice; Pustinger, Maggie; and Phan, Quyen, "Generative AI in Nursing Education: Opportunities, Challenges and Educator Preparedness" (2026). International Nursing Research Congress (INRC). 148.
https://www.sigmarepository.org/inrc/2026/presentations_2026/148
Conference Name
37th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Toronto, Ontario, Canada
Conference Year
2026
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. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Date of Issue
2026-08-12
Generative AI in Nursing Education: Opportunities, Challenges and Educator Preparedness
Toronto, Ontario, Canada
Background: Generative AI is transforming clinical nursing education, highlighting the urgent need to train nurse educators with the knowledge, tools, and confidence for practical use. AI tools are quickly impacting content, student preparation, and teaching methods, creating both opportunities and challenges. AI offers both advantages and obstacles in clinical content creation; however, advantages do not replace nursing experience. Due to its rapid integration into education, many educators remain cautious about responsible implementation because of ethical concerns.
Purpose: This study examines changes in participant knowledge and confidence in the use of AI tools in clinical education among clinical nurse educators from eight states in the Southeast following a clinical instructor education workshop. This workshop explored AI's role in clinical nursing education, practical applications, risks, opportunities, and ethical considerations.
Method: A workshop on AI tools was conducted for educators from both academic and practice settings. A retrospective pre-post- survey assessed changes in confidence and the integration of AI into clinical education practice. Interactive and engaging learning methods guided participants on the core principles of creating and implementing personal objective AI tools. AI tools were compared, helping participants better understand the specific uses of the different AI tools introduced and discussed.
Results: Participants (n=41) reported a statistically significant (p < 0.05) increase in knowledge and confidence in ethically integrating AI tools into practice, as well as an increase in confidence regarding implementing AI into current clinical education practices.
Implications: AI can enhance clinical judgment, critical thinking, and patient-centered care. Using AI technologies such as simulation, adaptive quizzing, evaluation creation, concept mapping, and decision-support tools can boost clinical judgment. Incorporating these into clinical nursing education supports competency-based training and prepares nurses for technology-driven healthcare.
Description
Generative AI is quickly reshaping clinical nursing education, offering new possibilities while introducing emerging challenges for educators. This study assessed shifts in AI-related knowledge and confidence among 41 participants following an AI-focused workshop. Integrating AI-driven simulations, student preparation tools, and decision-support platforms can strengthen clinical judgment, critical thinking, and competency-based learning for the next generation of nurses.