AI Image-Generation as a Teaching Strategy in Nursing Education
Open accessAbstract
Generative artificial intelligence (AI) allows for the transformation of written text into artistic images. Scholars and researchers are beginning to explore the benefits of this technology to improve reflective practices and critical analysis in education. The extent to which AI-generated images can be used to explore cultural stereotypes and mental representations of the nursing profession has not yet been studied. This article describes a case study of using generative-AI images created by Midjourney with undergraduate nursing students to examine their perceptions and fears of the nursing profession. The research explored how students experienced the process of using AI-generated art as a teaching tool to increase their reflections and discussions on professional nursing topics. Images were used to encourage both individual and collaborative reflection and discussion on nursing topics. Results of this qualitative, exploratory study point to therapeutic and technological outcomes of using AI image-generation as a strategy to encourage reflection and discussion on student’s perceptions and fears of the nursing profession. Implications for education and practice are discussed. Keywords- artificial intelligence, image-generation, Midjourney, nursing education
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Integration of text-to-speech and speech-to-text technologies enhances simulation realism by creating more authentic patient interactions and enabling personalised educational opportunities.
“Such integration enhances simulation realism by creating more authentic patient interactions and enabling personalised educational opportunities (Reed and Dodson, 2024; Bumbach et al., 2024; Reed et al., 2023).”
From Patterns, advances, and gaps in using ChatGPT and similar technologies in nursing education: A PAGER scoping review (2025) · cites this paper as Reed et al., 2023
The “Generative AI in Nursing Education” section says educators who understand generative AI can provide personalized learning experiences and mentions virtual simulation. It does not discuss text-to-speech or speech-to-text integration, or show that these technologies make patient interactions more authentic or simulations more realistic. Page numbers were not provided in our copy. (LLM, conf=0.82)
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Prompt engineering when using generative AI in nursing education
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- Authors
- Reed, J., Alterio, B., Coblenz, H., O'Lear, T., & Metz, T.
- Affiliations
- Kent State University (US)
- ORCID
- Reed, Janet
- Venue
- Journal of Interactive Learning Research
- Published
- 2023
- Volume
- 34
- Issue
- 2
- Pages
- 369-399
- ISSN
- 1093-023X (ISSN-L)
- OpenAlex
- W4411076142
- Cited by
- 38
- References
- 1
- Citations by year
- 2026: 14 · 2025: 14 · 2024: 6 · 2023: 4
- FWCI
- 1.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journal of Interactive Learning Research (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Keywords
- generative AI, AI image generation, Midjourney, nursing education, nursing students, reflective practice, collaborative reflection, cultural stereotypes
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