Abstract
This study presents the organization and design framework of an asynchronous module designed to develop students’ generative Large Language Models (AI) literacy and critical appraisal skills in the context of clinical research. Using a case study design the module introduces students to the role, value, and limitations of AI in clinical judgment. Microsoft Copilot was selected as the tool due to institutional access and copyright compliance. Students were guided on how to upload content and craft prompts effectively. The module was designed to enable subject matter experts to develop content related to evidence-based healthcare practice combined with the opportunity for students to understand the value, role and limitations of AI in clinical judgment. The design structure included preparing students in effective prompting, a case study and critical appraisal. The development team included the Senior Instructional Designer (ID), Librarian and three additional collaborators representing a total of eleven healthcare practice professionals across medicine and allied health disciplines. The ID played a central role in ensuring the content was presented in a way that was both pedagogically sound and accessible to learners. This study provides detailed insights into the design and offer guidance for adapting it across a wide range of post-secondary educational settings.
Presenters
Rivka MolinskyAssociate Dean of Students and Innovation, School of Health Sciences, Touro University, New York, United States Caelen Wen Xuan Siow
Instructional Designer, School of Health Sciences, Touro University, New York, United States
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
2026 Special Focus—Human-Centered AI Transformations
KEYWORDS
Higher Education, AI, Healthcare
