Jul 2026· The Journal of Nursery Education· pp.
1-10
· 1 citation· 34 references
Medicine
TL;DR
A concise, nursing faculty-centered AI development checklist for responsible AI integration in teaching and assessment and simplifies steps for understanding new technologies, adds to research on competencies, and improves instructional efficiency is provided.
Abstract
Background
Artificial intelligence (AI) is increasingly available to faculty and students, yet adoption remains uneven. Faculty report uncertainty about capabilities, limitations, and ethical boundaries, and lack time for integration, while institutions grapple with policy, privacy, and equity concerns. The purpose of this article is to provide a concise, nursing faculty-centered AI development checklist for responsible AI integration in teaching and assessment.
Method
AI implementation guidance was synthesized into a five-step checklist for faculty AI competency development.
Results
The checklist converts exploratory evidence into a logical faculty development plan, emphasizing practical steps that reduce cognitive load, standardize expectations, and support equitable access to enable rapid adoption and consistent implementation for individuals, programs, and institutions.
Conclusion
With a concise evidence-based checklist, nurses can achieve the benefits of AI while advancing equity and preserving the human-centered core of the nursing profession. This checklist simplifies steps for understanding new technologies, adds to research on competencies, and improves instructional efficiency.
Current evidence indicates that AI can support learning, clinical reasoning, documentation, patient monitoring, decision support, workflow efficiency, and personalized education; however, evidence from real-world nursing settings remains less mature than technological development.
Natasha Mohit Mahajan· International Journal of Nur...· 0 citations
BACKGROUND
Artificial intelligence (AI) is rapidly transforming nursing and health professions education. Although these technologies offer opportunities for innovation, they also raise concerns related to professional identity, ethical judgment, depersonalization, and burnout.
METHOD
This conceptual article synthesi...
Bonnie Soik· The Journal of Nursery Educa...· 0 citations
Despite widespread adoption of artificial intelligence (AI), behavioral health practitioners often feel ill-prepared to use the technologies in their clinical services. While, graduate school has been identified as an optimal time to introduce AI-related topics, to date, literature on the integration of AI-focused...
Jonathan G. Perle· Mental Health and Digital Te...· 0 citations
12 practical tips for educators and curriculum designers that provide a coherent, learner-centered scaffold to help educators worldwide prepare learners for AI-augmented practice are translated.
Diego F. Niño, K. Masters, Rakesh Patel et al.· Medical Teacher· 0 citations
This commentary proposes a context-sensitive implementation framework for responsible AI integration in medical student education in Somalia and comparable low-resource settings that prioritizes faculty oversight, academic integrity, patient confidentiality, multilingual verification, local clinical validation, low-ban...
Mohamed Mohamud Ali, Abdullahi Abdirahman Omar· Advances in Medical Educatio...· 0 citations
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