When students enroll in the Doctor of Nurse Anesthesia Practice – Post-Baccalaureate (DNAP) program at the Medical University of South Carolina (MUSC), they enter a learning environment where evidence-based care and emerging technologies intersect.
For Katherine Lowry, DNAP, CRNA, LSSBB, this approach to learning inspired her to reimagine how a foundational chemistry and physics course for first-year students was taught. She partnered with instructional designer Scott Nolt, Ed.D., to explore how artificial intelligence (AI) could strengthen course design while keeping faculty expertise, professional judgment and human connection at the center of the learning experience.
Their approach was practical. Rather than using AI to replace instruction entirely, they used a custom agent to review the course and help identify gaps among learning objectives, course materials and assessments. Lowry and Nolt then drew on their expertise to interpret those findings and determine how best to implement changes in a way to best support students.
The result was a more consistent and interactive course structure. Each module was reorganized into a "Watch, Read, Practice, Discuss, Submit" sequence, giving students a clear path through the material and making expectations easier to understand. Long lectures were broken into focused lessons, while new practice opportunities gave students immediate feedback and additional opportunities to reinforce complex concepts.
The impact was clear. Students responded positively to the redesigned course. Among the 29 students who completed the end-of-course evaluation, both the interactive learning environment and instructor responsiveness received ratings of 4.9 out of 5. Students also reported high levels of engagement, responsiveness and satisfaction, with many praising the course's organization, additional practice opportunities and interactive learning environment. Several students also noted that the reimagined structure helped them better understand expectations and stay connected throughout the course.
For Lowry, this innovative application of AI reflects a larger vision for the future of healthcare education.
"AI works best as a thought partner," she said. "It helps us make better design decisions faster, but the relationships, mentorship and learning experiences remain deeply human."
That mindset is helping shape the Doctor of Nurse Anesthesia Practice – Post-Baccalaureate (DNAP) program student experience at MUSC. By combining emerging technologies with evidence-based teaching practices, faculty are helping prepare future nurse anesthetists to think critically, adapt confidently and lead in a rapidly evolving healthcare landscape.
For students considering MUSC’s DNAP-PB program, this initiative is one example of how faculty are continually exploring new ways to enhance learning, support student success, and prepare for what’s next.
Katie Ennis
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