Name
Enhancing Accessibility and Engagement in Medical Immunology through
Universal Design for Learning (UDL) Strategies
Date & Time
Sunday, June 7, 2026, 4:57 PM - 5:12 PM
Location Name
Oglethorpe G
Speakers
Authors
Veronica Able-Thomas, MS, University of South Carolina School of Medicine Greenville; Department of Biomedical Sciences.
Jennifer T. Grier, PhD, University of South Carolina School of Medicine Greenville; Department of Biomedical Sciences
Presentation Topic(s)
Technology and Innovation
Description
PURPOSE
Accessibility is an important consideration for course resources in medical
education. Proper implementation of Universal Design for Learning (UDL)
strategies have the potential to increase content accessibility and provide
academic benefits to numerous of medical students. This study evaluated the
application of (UDL) strategies into medical immunology content within a
Foundations of Medicine 2 (FOM2) course. The primary purpose was to determine
the extent to which UDL-informed redesign, specifically AI-assisted
alternative text (alt-text) for images, impacted student engagement and
learning outcomes. Secondary aims included assessing the feasibility of
technology-supported alt-text generation and understanding student
perceptions of UDL-inclusive course components.
METHODS
A mixed-methods research design was used with IRB approval. Two AI
platforms Chat GPT and Claude were used to generate alt-text for images within
lecture slides. Quantitative measures included descriptive analyses to
determine efficiency of producing slides with accurate alt-text. Following
course completion, enrolled students received an optional post-course survey
to assess engagement, usefulness, and overall perceptions of alt-text within
lectures.
RESULTS
The post-course survey showed that ~33% of responding students reported
viewing the alt-text. Of those that did view the alt-text, more than 90% of
respondents felt that alt-text provided either good or great clarification of
the images; the majority found the alt-text to be very helpful or extremely
helpful as a study tool. Use of AI-assisted alt-text creation proved feasible,
requiring ~37-77 seconds per image for alt text generation and proofing.
Efforts to further streamline the process are ongoing.
CONCLUSIONS
This study provides evidence of the positive impact of UDL implementation
within medical immunology education. These findings can inform best practices
to enhance accessibility and support diverse learners in content-dense
curricula. UDL-based redesign with AI-integration offers a feasible and
broadly applicable model for integration of inclusive teaching strategies
across medical education.
Accessibility is an important consideration for course resources in medical
education. Proper implementation of Universal Design for Learning (UDL)
strategies have the potential to increase content accessibility and provide
academic benefits to numerous of medical students. This study evaluated the
application of (UDL) strategies into medical immunology content within a
Foundations of Medicine 2 (FOM2) course. The primary purpose was to determine
the extent to which UDL-informed redesign, specifically AI-assisted
alternative text (alt-text) for images, impacted student engagement and
learning outcomes. Secondary aims included assessing the feasibility of
technology-supported alt-text generation and understanding student
perceptions of UDL-inclusive course components.
METHODS
A mixed-methods research design was used with IRB approval. Two AI
platforms Chat GPT and Claude were used to generate alt-text for images within
lecture slides. Quantitative measures included descriptive analyses to
determine efficiency of producing slides with accurate alt-text. Following
course completion, enrolled students received an optional post-course survey
to assess engagement, usefulness, and overall perceptions of alt-text within
lectures.
RESULTS
The post-course survey showed that ~33% of responding students reported
viewing the alt-text. Of those that did view the alt-text, more than 90% of
respondents felt that alt-text provided either good or great clarification of
the images; the majority found the alt-text to be very helpful or extremely
helpful as a study tool. Use of AI-assisted alt-text creation proved feasible,
requiring ~37-77 seconds per image for alt text generation and proofing.
Efforts to further streamline the process are ongoing.
CONCLUSIONS
This study provides evidence of the positive impact of UDL implementation
within medical immunology education. These findings can inform best practices
to enhance accessibility and support diverse learners in content-dense
curricula. UDL-based redesign with AI-integration offers a feasible and
broadly applicable model for integration of inclusive teaching strategies
across medical education.
Presentation Tag(s)
Student Presentation