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Cited by 22Comics and Graphic NarrativesArtificial Intelligence in Healthcare and EducationArtificial Intelligence in Education

Visual narratives in nursing education: a generative artificial intelligence approach

Tran, Linh Duc, Tung, Neo, Macalinga, Eugene Tordecilla, Tang, Arthur, Woo, Brigitte, Tam, Wilson·2024·Nurse Education in Practice
DOI 10.1016/j.nepr.2024.104079
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Abstract

Aim The aim of this paper is to investigate the incorporation of visual narratives, such as comics and graphics, into nursing education using Generative Artificial Intelligence (GAI) models like DALL-E.Background Visual narratives serve as a powerful method for communicating intricate concepts in nursing education. Despite their advantages, challenges in creating effective educational comics persist due to the need for expertise in graphic design and the associated time and resource constraints.Design This study examines existing literature that highlights the efficacy of visual narratives in education and demonstrates the potential of GAI models, specifically DALL-E, in creating visual narratives for nursing education.Methods We analyze the potential of GAI models, specifically DALL-E, to create visual narratives for educational purposes. This was demonstrated through illustrative examples addressing sensitive topics, illustrating research methodology and designing recruitment posters for clinical trials. Additionally, we discussed the necessity of reviewing and editing the text generated by DALL-E to ensure its accuracy and relevance in educational contexts. The method also considered legal concerns related to copyright and ownership of the generated content, highlighting the evolving legal landscape in this domain.Results The study found that GAI, specifically DALL-E, has significant potential to bridge the gap in creating visual narratives for nursing education. While offering cost-effectiveness and accessibility, GAI tools require careful consideration of challenges such as text-related errors, misinterpretation of user prompts and legal concerns.Conclusions GAI models like DALL-E offer promising solutions for enhancing visual storytelling in nursing education. However, their effective integration requires a collaborative approach, where educators engage with these tools as co-pilots, leveraging their capabilities while mitigating potential drawbacks. By doing so, educators can harness the full potential of GAI to enrich the educational experience for learners through compelling visual narratives.

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Authors
Tran, L. D., Tung, N., Macalinga, E. T., Tang, A., Woo, B., & Tam, W.
Affiliations
  • RMIT Vietnam (VN)
  • The University of Melbourne (AU)
  • National University of Singapore (SG)
Corresponding author
Tang, Arthur
ORCID
Venue
Nurse Education in Practice
Publisher
Elsevier BV
Published
2024-08
Volume
79
Pages
104079
ISSN
1471-5953 (ISSN-L)
DOI
10.1016/j.nepr.2024.104079
OpenAlex
W4400850027
Cited by
22
References
12
Citations by year
2026: 8 · 2025: 10 · 2024: 4
FWCI
87.02
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Nurse Education in Practice (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Comics and Graphic Narratives
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
Keywords
visual narrative, nursing education, generative AI, DALL-E, comics in education, graphic design, copyright
MeSH terms
Artificial Intelligence, Education, Nursing, Humans, Narration

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