Number
810
Name
Utilization of AI Tools in Health Sciences Education at ETSU
Date & Time
Monday, June 8, 2026, 6:00 PM - 7:30 PM
Location Name
Oglethorpe Ballroom
Speakers
Authors
Kinner Flaglor, ETSU Quillen College of Medicine
Mark Hernandez, PhD, ETSU Quillen College of Medicine Department of Medical Education
Paul Monaco, PhD, ETSU Quillen College of Medicine Department of Medical Education
Antonio Rusinol, ETSU Quillen College of Medicine Department of Medical Education
Presentation Topic(s)
Technology and Innovation
Description
PURPOSE
AI's introduction into health sciences education has shifted learning
across multiple disciplines. Previous studies show that students and faculty
recognize AI's utility in healthcare and their careers but lack knowledge for
effectively integrating it into professional activities. Health science
educators suggest adding AI education into existing curricula, particularly
as AI may improve health equity. This is especially important at East
Tennessee State University (ETSU), which serves rural regions with
historically poor health outcomes.
METHODS
An IRB approved mixed-methods study was conducted from May to July 2025
using surveys completed by students, faculty, and residents across medicine,
pharmacy, physical therapy, health sciences, and graduate medical education
at ETSU.
RESULTS
114 complete responses were received (24 clinical science faculty, 11 basic
science faculty, 9 other faculty, 14 pre-clerkship students, 9 clerkship
students, 4 pre-clerkship pharmacy students, 4 clerkship pharmacy students,
15 undergraduate health sciences students, 17 graduate health sciences
students, and 7 residents). No significant differences in AI usage or
attitudes were found. Respondents acknowledged AI's importance, though
familiarity and usage varied widely. ChatGPT was the most recognized tool,
both free and subscription-based, with OpenEvidence and Gemini as other
frequently mentioned free assistants, and Claude among subscription models.
Qualitative analysis revealed that faculty and residents held mixed feelings
toward AI, while students showed polarized responses – either wholly positive
or negative. Many responses addressed AI's impact on critical thinking and
environmental effects.
CONCLUSION
Students demonstrated less nuanced AI opinions, viewing LLMs as entirely
positive or negative, while career-advanced respondents showed more balanced
perspectives, recognizing both benefits and limitations. No significant
demographic differences emerged, likely reflecting small sample sizes within
each group. Survey findings informed planning for a faculty workshop on AI
applications in health sciences education.
AI's introduction into health sciences education has shifted learning
across multiple disciplines. Previous studies show that students and faculty
recognize AI's utility in healthcare and their careers but lack knowledge for
effectively integrating it into professional activities. Health science
educators suggest adding AI education into existing curricula, particularly
as AI may improve health equity. This is especially important at East
Tennessee State University (ETSU), which serves rural regions with
historically poor health outcomes.
METHODS
An IRB approved mixed-methods study was conducted from May to July 2025
using surveys completed by students, faculty, and residents across medicine,
pharmacy, physical therapy, health sciences, and graduate medical education
at ETSU.
RESULTS
114 complete responses were received (24 clinical science faculty, 11 basic
science faculty, 9 other faculty, 14 pre-clerkship students, 9 clerkship
students, 4 pre-clerkship pharmacy students, 4 clerkship pharmacy students,
15 undergraduate health sciences students, 17 graduate health sciences
students, and 7 residents). No significant differences in AI usage or
attitudes were found. Respondents acknowledged AI's importance, though
familiarity and usage varied widely. ChatGPT was the most recognized tool,
both free and subscription-based, with OpenEvidence and Gemini as other
frequently mentioned free assistants, and Claude among subscription models.
Qualitative analysis revealed that faculty and residents held mixed feelings
toward AI, while students showed polarized responses – either wholly positive
or negative. Many responses addressed AI's impact on critical thinking and
environmental effects.
CONCLUSION
Students demonstrated less nuanced AI opinions, viewing LLMs as entirely
positive or negative, while career-advanced respondents showed more balanced
perspectives, recognizing both benefits and limitations. No significant
demographic differences emerged, likely reflecting small sample sizes within
each group. Survey findings informed planning for a faculty workshop on AI
applications in health sciences education.
Presentation Tag(s)
Student Presentation