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Updated: Feb 4, 2026

Using Learning Outcome Measures to assess Doctoral Nursing Education
Published on: June 21, 2010
Rapid review on GenAI in nursing education
Laura Hinsche1, Martina Hasseler1, Tim Tischendorf2
1Faculty of Healthcare, Ostfalia University of Applied Sciences, Wolfsburg, Germany.
Generative AI (GenAI) offers significant potential for nursing education, enhancing personalized learning and training. However, responsible integration requires curriculum adaptation and teacher training to mitigate risks like bias and knowledge distortion.
Area of Science:
- Nursing Education
- Artificial Intelligence
- Digital Health
Background:
- Generative AI, exemplified by ChatGPT, presents opportunities for nursing education, including personalized learning, simulation, and teaching support.
- Successful integration necessitates addressing ethical concerns, curriculum adjustments, and enhancing digital literacy among educators to prevent knowledge distortion, bias, and educational disparities.
Purpose of the Study:
- To provide a rapid overview of generative AI's role and impact in nursing education.
- To identify key themes, benefits, and challenges associated with implementing generative AI in nursing education.
Main Methods:
- A comprehensive literature search was conducted in PubMed, Embase, CINAHL, and Scopus for publications from 2019-2025.
- Search terms included "generative AI", "ChatGPT", and "nursing". 140 full texts were analyzed following PRISMA guidelines.
Main Results:
- Five thematic areas emerged: nursing education, competence development, skills enhancement, implementation strategies, examination quality, and ethical considerations.
- Generative AI offers dual potential: enriching learning via virtual tutors and exam preparation while demanding critical attention to plagiarism, data bias, and the necessity of human oversight.
Conclusions:
- Adapting curricula and providing targeted teacher training are crucial for the responsible and effective use of generative AI in nursing education.
- A proactive approach to integrating generative AI is recommended over outright prohibition to harness its benefits while managing risks.
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