This hands-on workshop guides participants through advanced applications of Generative AI (GAI) in teaching and assessment, emphasizing practical implementation and ethical considerations.

This workshop is designed for health professions educators (HPE), curriculum designers, and academic leaders who are interested in leveraging generative AI to enhance teaching, assessment, and data-informed decision-making while addressing the practical and ethical challenges of integrating AI into HPE. Ideal for those who have experience with AI tools or have completed introductory AI training and want to expand their expertise.

Key Learning Objectives:

• Introduction to the Workshop and AI Vision: Participants will discuss the overarching goals of AI in HPE, reviewing and reflecting on the AI vision presented to establish a shared foundation for integrating AI in their respective programs.
• Optimizing Teaching with GAI: Participants actively engage with GAI tools to transform and enhance their educational materials through guided, hands-on activities. Using their own course content, they explore techniques for converting traditional lectures into interactive learning experiences, developing dynamic clinical case scenarios with branching decision points, and creating multimedia resources that accommodate diverse learning styles. Practical exercises focus on analyzing content structure, applying AI-assisted transformation techniques, designing scaffolded learning pathways, and generating complementary study materials—all while maintaining educational integrity and academic rigor. Throughout these activities, participants address implementation challenges and develop practical strategies for successful integration within their specific institutional contexts.
• Enhancing Assessment with GAI: Participants engage in practical exercises focused on designing and redesigning assessments leveraging AI, while emphasizing authenticity and academic integrity. Participants will create assessment items, develop rubrics, and deliver AI-driven feedback, ensuring that AI-generated assessments remain authentic, targeted, and ethical. Special emphasis is placed on transforming traditional assessments into authentic evaluation methods that remain relevant and reliable in an AI-enhanced learning environment.
• Data-Informed Decision-Making and Emerging AI Applications: Participants work with sample datasets to explore advanced AI applications in learning analytics and other emerging AI applications in HPE. Through hands-on exercises using simulated qualitative and quantitative performance data, they learn to harness AI tools for data organization, visualization, and analysis to generate actionable insights for curriculum enhancement. The activities emphasize responsible data handling and the ethical use of AI for performance analysis.
• Conclusion and Takeaways: The workshop concludes with a reflective session where participants share key insights, discuss future goals, and solidify their understanding of integrating AI into educational and assessment practices.

These workshops equip participants with practical competencies to optimize teaching, enhance assessment integrity, and use AI to support evidence-based decision-making in educational settings. This workshop provides the participants with direct experience in applying more advanced GAI applications to teaching and assessment processes using hands-on exercises to enable each person to experience different AI product functionalities, including best practices, implementation processes, and transferable uses. Workshop attendees are expected to have ongoing experience using multiple GAI applications. They may also be interested in enhancing their ability and knowledge to serve as a GAI resource faculty member in their organization.

Workshop Schedule:

• 12:30 - 12:35 (5 min) Introduction to the Workshop and AI Vision
• 12:35 - 1:30 (55 min) Optimizing Teaching with GAI
• 1:30 - 1:45 (15 min) Coffee Break
• 1:45 - 2:40 (55 min) Optimizing Assessment with GAI
• 2:40 - 3:20 (40 min) Concurrent Sessions
  • Track A: Data Analysis in HPE
  • Track B: Emerging Topics (Content to be determined based on participant interests and emerging trends)
• 3:20 - 3:30 (10 min) Conclusion and Takeaways