Values Clarification Exercises to Prepare Nursing Students for Artificial Intelligence Integration
Open accessAbstract
Artificial intelligence (AI) is rapidly revolutionizing health care and education globally, including nursing practice and education. The responsible utilization of AI in a nursing context requires thoughtful consideration of its alignment with nursing values such as compassionate and patient-centered care provision, and respect for diverse perspectives. Values clarification, a vital teaching strategy in nursing education, can reinforce the foundational values and beliefs that guide nursing practice, thereby facilitating nurses’ critical evaluation of the ethical implications of AI implementation. The early introduction of values clarification into nursing education (a) provides students with a framework to prioritize and reflect on the impact of nursing values on their practice, (b) enables educators to make informed decisions and enhance teaching strategies, (c) contributes to the continual improvement of nursing education programs, and (d) fosters an ethical and values-driven approach to the integration of AI into nursing education and practice. This article examines the integration of values clarification into nursing education, offers strategies for nurse educators to integrate AI into their teaching toolkit effectively and ethically, and addresses concerns regarding potential misuses of AI.
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AI's ability to generate nuanced and complex case studies offers a valuable resource for educators, especially in scenarios where direct clinical experience is limited.
“AI's ability to generate nuanced and complex case studies offers a valuable resource for educators, especially in scenarios where direct clinical experience is limited.1”
From The Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care (2024) · cites this paper as [1]
Section 4.1 (Case-Based Learning Exercises; page not supplied) recommends case studies as a way for nursing educators to engage students in examining AI use. It does not say that AI generates nuanced or complex case studies, or that these are especially useful when direct clinical experience is limited. (LLM, conf=0.78)
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“For example, in a nursing ethics class, students can be presented with a case study involving the use of generative AI for task assignments [11].”
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“By implementing case-based learning exercises, nursing educators can effectively engage students in analyzing real-world scenarios and encourage critical thinking regarding the ethical implications of AI integration in nursing practice [11–13].”
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Self-citation
- Authors
- De Gagne, J. C.
- Affiliations
- School of Nursing, Duke University, Durham, NC 27710, USA
- ORCID
- De Gagne, Jennie C.
- Venue
- International Journal of Environmental Research and Public Health
- Publisher
- MDPI AG
- Published
- 2023-07-20
- Volume
- 20
- Issue
- 14
- Pages
- 6409
- ISSN
- 1660-4601 (ISSN-L)
- PMC
- PMC10379214
- OpenAlex
- W4384932359
- Cited by
- 38
- References
- 6
- Citations by year
- 2026: 8 · 2025: 16 · 2024: 11 · 2023: 3
- FWCI
- 1.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Environmental Research and Public Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › General Health Professions › Ethics in medical practice
- Health Sciences › Nursing › Research and Theory › Nursing education and management
- Keywords
- values clarification, artificial intelligence in nursing, nursing education, nursing values, AI ethics, patient-centered care, compassionate care, nursing faculty, teaching methods, AI misuse, reflective practice
- MeSH terms
- Artificial Intelligence, Curriculum, Delivery of Health Care, Education, Nursing, Humans, Students, Nursing
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