Empowered Yet Uneasy: AI Augmented Pedagogy in Nursing Education

Janet M. Reed, PhD, RN, CMSRN

The surge of artificial intelligence (AI), particularly generative AI, is reshaping how we think, write, teach, and learn. For nurse educators, this shift presents both profound opportunities and intimidating challenges. In many respects, nursing education resembles the “Wild West” with rapid innovation outpacing policy, practice, and pedagogical consensus among faculty. This paper explores (1) how AI is transforming education, (2) how nurse educators are responding emotionally and pragmatically, (3) the promises AI may hold for alleviating educator burdens, and (4) the urgent need for institutional and national guidance. When nurse educators engage proactively, transparently, and ethically as co-navigators of this evolving landscape in higher education, they foster trust and help shape a culture of integrity and adaptability.

Artificial intelligence, and particularly generative models, have proliferated dramatically in the past few years, altering how knowledge is produced, disseminated, and consumed. In the educational sphere, AI tools can generate text, summarize complex content, suggest revisions, create test items, and even simulate dialogues or patient care scenarios (Samala et al., 2024). The implications for teaching and learning are vast: educators and learners alike must reconsider traditional roles of content creation, assessment, and mentorship. In nursing education, AI is being used to create realistic patient simulations, develop personalized learning experiences, and provide personalized feedback to students (Dodson et al., 2025; Reed & Dodson, 2024). For instance, the University of California San Francisco’s School of Nursing recently integrated generative AI into its simulation lab, where students practice patient interactions with AI-driven avatars capable of emotional and verbal responses with diverse patient groups (Miller, 2025). Similarly, at Kent State University, we are piloting AI-based virtual patients to improve therapeutic communication, decrease anxiety, and improve student noticing skills (Reed et al., 2025). Such technologies can transform both what students learn and how they learn.

Spectrum of Readiness

Many educators have expressed a mix of emotions and attitudes about AI. Although many recognize the potential benefits, they often experience uncertainty and nervousness about ethical concerns and the rapid pace of change concurrent with perceived inadequate institutional support (Buele & Llerena-Aguirre, 2025). The rapid proliferation of new AI tools has sparked diverse reactions ranging from excitement about innovation to fear of academic dishonesty. Faculty at multiple universities have reported feeling overwhelmed by constant technological changes, noting AI’s potential dehumanization of pedagogy and adverse effects on students (Abdelaal & Al Sawi, 2024). Concerns about plagiarism, deskilling, and misinformation are common, leading many nursing faculty to resist pedagogical changes (Chan et al., 2025). One educator shared with me that students in her class began submitting essays that were “too polished,” prompting suspicion of AI-generated writing. Another reported students using AI to draft care plans that lacked contextual nuance or patient-centered focus. These examples illustrate fears that AI could erode students’ capacity for critical thinking. Some faculty fear that in their pursuit of expediency, students’ attention spans are shrinking, whereas other students refuse AI altogether for moral and environmental objections. Moreover, since AI models can generate inaccurate or biased information, educators must help students develop workplace skills of being able to critically evaluate for credibility and bias in AI outputs (Srinivasan et al., 2024).

While apprehension is widespread, many educators are discovering AI’s ability to reduce administrative burden and enhance creativity for themselves and their students. For example, some nursing faculty use ChatGPT to draft exam questions for NCLEX preparation, but maintaining faculty oversight is essential (Hargett et al., 2025). Adaptive tutoring systems can identify when a student struggles with dosage calculations or ethical reasoning and provide targeted feedback. In simulation settings, AI chatbots can role-play patients with specific conditions, ensuring consistency and standardization while allowing students to practice communication skills safely (Chan et al., 2025). If educators can reframe their thinking about AI and see it as a tool to increase their own efficiency, rather than seeing it as just one more thing to learn and do, then they may be able to regain time for mentoring and fostering innovation with students. This human-centered focus aligns with nursing’s ethical foundation and professional identity, emphasizing that technology should augment not replace the human connection in education.

Policy and Guidance Void

Despite widespread adoption of AI tools, many universities still lack clear policies to govern ethical use. A recent analysis found that fewer than 40% of higher education institutions had formal guidelines for AI integration in teaching (Ghimire & Edwards, 2024). This absence creates confusion about acceptable use, student disclosure, and evaluation standards. Nursing programs in particular face unique ethical concerns because of their emphasis on patient safety and integrity. The recently released AI Vision Statement from the National League for Nursing (NLN, 2025) repeatedly emphasizes the need to urgently establish AI governance, ethical oversight, and policy frameworks. The document calls for: National AI literacy and competency standards, institutional data governance, shared accountability frameworks, faculty development, and curricular innovation in AI. Similarly, the American Nurses Association (ANA) in its 2022 position statement on the ethical use of AI, calls for nurses to be involved at interdisciplinary tables to advocate for regulatory guidelines to hold developers morally accountable. Helping to guide and mold more ethical AI systems corresponds to the nurse’s ethical duty to minimize harm to patients.

As AI begins influencing how nurses make clinical decisions and document with new ambient technologies, educators need clear frameworks for ensuring future nurses can accurately verification, cross-examine, and be accountable for AI decisions to ensure patient safety. The American Association of Colleges of Nursing (AACN) has encouraged faculty to model transparent AI use and incorporate AI literacy into professional development, but no standardized national policy yet exists. Decision trees, ethical checklists, and discipline-specific policies are urgently needed. It is recommended for faculty to use tiers of transparency and explicit classroom policies requiring disclosure when AI tools are used (Yan et al., 2024). Transparency represents a pedagogical and ethical commitment rather than merely a technical requirement; adopting such standards offers nursing programs a foundational pathway toward greater integrity and innovation.

Educators Must Steward Ethical AI Use

Nurse educators should model and steward ethical AI use with courage and humility. First, educators can model engagement and lifelong learning by participating in continuous professional learning about AI’s capabilities and limitations. This might include participating in interdisciplinary committees or collaborating with computer science colleagues to develop context-appropriate AI literacy modules relevant to nursing practice. Second, educators should always model transparency in their own AI use. When faculty use AI for drafting course materials or grading support, they should acknowledge it to students. For example, an assignment co-drafted using AI might include the statement: “This document was reviewed with the assistance of [Name AI tool with version] for clarity and grammar.” Transparency fosters trust and teaches students ethical standards for AI use. Third, nurse educators should facilitate open, grace-filled discussions about AI with students acknowledging its benefits while naming its pitfalls. These conversations can help students develop discernment, empathy, and integrity in their future practice. More collaborative, interdisciplinary research is needed to test LLM tools in authentic educational environments, iterate ethically, and ensure alignment with pedagogical goals: always keeping a human-centered approach (Yan et al., 2024). Finally, educators must advocate for institutional and national policies that balance innovation with accountability.

In conclusion, nurse educators today stand at the frontier of AI’s educational revolution. The pace of change evokes both excitement and trepidation. While the risks of deskilling, bias, and ethical ambiguity are real, the opportunities for improved efficiency, creativity, and personalized learning are equally profound. By embracing AI with transparency, critical reflection, and humanity, nurse educators can shape a future where technology enhances rather than diminishes the human art of caring. While AI may help impart knowledge to students, only a nurse educator can show empathy in real human experiences to provide the mentorship needed for students to develop into future nurse leaders to shape the utilization of AI in our world.

References

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