Using AI as a Teaching Partner (Not a Threat)

Jacklyn DelPrete
Jan 19
4 min read

Artificial intelligence (AI) continues to spark strong reactions in nursing education—especially among NP faculty who are deeply committed to clinical reasoning, ethical practice, and professional formation. While some see opportunity, others understandably worry about shortcuts, erosion of rigor, and loss of faculty authority.

Here’s the reframe that matters most: AI is not here to replace NP faculty—it’s here to support them.

When used intentionally and transparently, AI can function as a teaching partner, improving efficiency, consistency, and instructional design while leaving judgment, evaluation, and mentorship exactly where they belong—with faculty.

Below are practical, real-world ways NP faculty can use AI to enhance teaching without compromising rigor, integrity, or professional standards.

Is AI a threat to NP education?

NP education is not content delivery—it’s professional formation. Faculty are responsible for shaping safe, competent, and ethical practitioners, so hesitation around AI is both reasonable and responsible.

Common concerns include:

Students outsourcing thinking instead of developing it
Faculty worry that AI-generated responses may bypass the cognitive work required for clinical reasoning, synthesis, and decision-making.
Loss of academic rigor
There’s fear that assignments may become superficial if AI produces polished but shallow responses.
Inaccurate or unsafe clinical information
AI can generate confident-sounding but incorrect content, which is especially concerning in advanced practice education.
Blurred lines around authorship and academic integrity
Without clear expectations, both students and faculty may struggle to define what constitutes acceptable use.

These concerns don’t mean AI has no place in NP education—they mean AI must be used with structure, intention, and faculty oversight.

Reframing AI: From Shortcut to Support Tool

A helpful mental shift is to stop treating AI as something fundamentally different from other academic tools faculty already use.

AI is comparable to:

A test item bank, which still requires faculty vetting and alignment
A writing center tutor, which supports but does not replace student effort
A simulation pre-brief, which prepares students for deeper learning
A clinical reasoning worksheet, which scaffolds thinking without doing it for the learner

AI does not “think.” It responds to prompts. That means faculty remain in full control of:

Learning objectives
Prompt design and constraints
Evaluation criteria
Clinical and ethical standards

Used this way, AI becomes an extension of faculty expertise—not a competitor.

Practical Ways NP Faculty Can Use AI (Right Now!)

1. Drafting Case Studies and Clinical Scenarios

AI is particularly effective for generating starting points for teaching materials, especially when time is limited.

AI can help draft:

SOAP note scenarios for practice documentation
Unfolding case studies that evolve across a module
Differential diagnosis exercises tied to common presentations
Population health or systems-based vignettes

These drafts save time by reducing the “blank page” problem, especially for faculty managing multiple courses or large enrollments.

Note: You determine clinical relevance, increase complexity, align with evidence-based guidelines, and incorporate nuance that reflects real NP practice. The final product is still unmistakably faculty-driven.

2. Creating Practice Questions

AI can assist with generating questions designed for learning, not grading.

Useful applications include:

Low-stakes quizzes to reinforce key concepts
Certification-style practice questions
Knowledge checks embedded in modules
Discussion prompts linked to readings or clinical scenarios

This is particularly helpful in asynchronous courses, where frequent engagement opportunities matter.

Note: You review for accuracy, adjust difficulty, remove flawed distractors, and ensure alignment with course outcomes. AI speeds up question generation—but faculty ensure quality and rigor.

3. Supporting Feedback Efficiency

One of the most practical uses of AI is in drafting feedback language—especially for recurring issues faculty see semester after semester.

AI can help generate:

Common feedback phrases for writing, SOAP notes, or case studies
Rubric-aligned feedback templates
Growth-oriented language for students who are struggling

This can significantly reduce feedback fatigue in large or writing-heavy courses.

Note:You decide what feedback is appropriate, personalize it, and add clinical insight. AI supports efficiency—but your judgment shapes the message.

4. Teaching Clinical Reasoning With AI

Let's be honest: AI is not going anywhere. Students and practicing clinicians are using it. Rather than trying to police AI use, many faculty are finding success by bringing AI into the learning process explicitly. Let's teach students how to properly use and critique AI instead.

Structured transparency assignments might include:

Asking students to generate differential diagnoses with AI and then critique them using clinical guidelines
Identifying where AI recommendations lack nuance or miss key safety considerations
Revising an AI-generated plan of care to meet NP-level standards

These activities shift the focus from answer generation to evaluation, reasoning, and professional judgment. Students will practice higher-order thinking instead of passive consumption.

5. Faculty Workflow Support (The Hidden Benefit!)

Beyond student-facing applications, AI can meaningfully support faculty workload—an often overlooked benefit.

AI can assist with:

Lesson and module planning outlines
Drafting weekly announcements or reminders
Summarizing discussion board themes
Translating objectives into student-friendly language

This is not about doing less as an educator—it’s about protecting cognitive bandwidth so faculty can focus on mentoring, scholarship, and meaningful teaching interactions.

Setting Clear Boundaries for Ethical Use

AI works best in environments with clear expectations. Some examples are:

Including a syllabus statement outlining acceptable and unacceptable AI use
Clearly distinguishing between brainstorming/support and final submission
Requiring disclosure or citation when AI is used
Designing assignments that assess reasoning, reflection, and application—not just written output

Clarity benefits everyone: students know what’s expected, and faculty maintain academic integrity without constant policing.

What AI Cannot Replace in NP Education

No matter how advanced AI becomes, there are aspects of NP education it simply cannot replicate.

AI cannot: