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Navigating the Artificial Intelligence Integration Challenge: One Nursing School's Journey From Uncertainty to
Shawna S Mudd1, Leigh Montejo, Jihane Frangieh
1Author Affiliations: Johns Hopkins School of Nursing, Baltimore, Maryland (Drs. Mudd, Montejo, Frangieh, Capello, Lukkahatai, Aryal, Zhang, and Moore).
Nurse Educator
|June 22, 2026
Summary
Nursing programs can integrate artificial intelligence (AI) using a framework-based approach. This strategy addresses stakeholder needs and builds essential AI literacy for future practice.
Area of Science:
- Nursing Education
- Artificial Intelligence
- Digital Health Literacy
Background:
- Artificial intelligence (AI) is rapidly advancing in education and healthcare.
- Nursing programs are exploring AI to enhance professional knowledge and practice readiness.
- There is a need for clear, pedagogically sound guidance for AI integration in nursing schools.
Purpose of the Study:
- To develop systematic, discipline-specific frameworks for AI utilization in nursing education.
- To provide guidance for foundational AI literacy and pedagogical alignment.
- To support the integration of AI into nursing curricula and assessments.
Main Methods:
- Nursing faculty and staff reviewed AI literacy frameworks.
- A phased implementation plan was developed for AI integration.
- Existing AI use frameworks were adapted for nursing education.
Main Results:
- The Digital Education Council AI Literacy Framework was selected and adapted.
- AI integration requires discipline-specific adaptation and diverse perspectives.
- Complementary frameworks and iterative interpretation are crucial for developing AI competencies.
Conclusions:
- Framework-based approaches help nursing programs manage diverse stakeholder perspectives.
- These approaches establish a foundation for intentional AI literacy and integration.
- This strategy supports the development of scholarly, research, and clinical decision-making skills through AI.
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