Project Lead: Anuja Doshi, Oral Biological and Medical Sciences
Co Lead: HsingChi von Bergmann
Project Description
This project will explore the use of Generative AI (GenAI) and Large Language Models (LLMs) in Case-Based Learning (CBL) to enhance student engagement, critical thinking, and clinical reasoning skills in dental education. By adapting to each student’s responses, we expect the LLMs to foster richer and more diverse discussions during CBL sessions. A pre-post and crossover design will be used to measure improvements in students’ critical thinking, clinical reasoning, and engagement. Overall, the project aims to establish a sustainable, scalable model for interactive, adaptive GenAI-enhanced learning in the Faculty of Dentistry, aligning with UBC’s strategic goals for transformative education.
Research Questions
- How does the integration of GenAI/LLMs into Case-Based Learning (CBL) impact students’ clinical reasoning, critical thinking, and engagement compared to traditional CBL methods?
- Can AI-generated clinical cases promote greater consistency and calibration among faculty, ensuring standardized delivery of CBL sessions across different instructors?
- What are the best practices for designing, implementing, and sustaining AI-enhanced CBL that aligns with the goals of equitable, inclusive, and innovative dental education?