This immersive, hands-on workshop prepares participants to leverage Generative AI (GAI) tools in medical education. Through faculty-guided practice and collaborative learning, participants develop critical skills needed to evaluate, implement, and responsibly apply LLMs in their teaching practices.

This workshop is designed for medical science educators, curriculum designers, and academic leaders who have started exploring AI in their workflows. Whether you're relatively new to AI or have been using it regularly, this session will help you advance your skills in enhancing teaching, assessment, and data-informed decision-making in medical education. Ideal for those who have basic familiarity with AI tools and want to expand their capabilities – from those who have just begun experimenting to those ready to explore more advanced applications.

Key Learning Objectives:

• Understanding LLM Capabilities and Limitations: Participants will explore the current capabilities, strengths, and limitations of LLMs, pinpointing key areas where these models excel and where challenges like biases and training data constraints emerge.
• Practical Application and GAI Tool Evaluation: Through structured comparative analysis, participants evaluate six leading GAI tools, using established rubrics and matrices to assess their capabilities. Working in teams, participants engage in hands-on exercises. Using carefully selected use cases, participants analyze varied AI outputs to understand each model's distinct strengths and limitations. This systematic approach enables participants to make informed decisions about which tools best suit their specific instructional needs.
• Advanced Prompting Techniques: Participants master iterative prompting strategies to enhance AI output quality and relevance, with special attention to MSE applications. This includes exploring AI agents, Custom AI Tools and emerging autonomous capabilities.
• Critical Evaluation Framework: Using established frameworks, participants develop skills to assess AI-generated content reliability and accuracy, ensuring appropriate implementation in educational settings.
• Ethical and Responsible Use: Throughout the workshop, participants engage with ethical considerations through targeted vignettes and real-world scenarios, examining issues such as academic integrity, data privacy, and the distinctions between open and closed AI systems.

This workshop combines pre-course preparation, hands-on practice, and post-workshop resources to support ongoing implementation. Participants should have basic experience with 1-2 GAI applications and an interest in expanding their knowledge of common GAI applications in medical education. The workshop emphasizes immediate practical application while preparing participants for emerging trends in AI development and integration.

A comprehensive resource guide and follow-up opportunities support participants in addressing implementation challenges and sharing success stories in their specific contexts.

Workshop Schedule:

• 8:00 - 8:15 (15 min) Welcome and Workshop Overview
• 8:15 - 8:45 (30 min) Understanding LLM Capabilities and Limitations
• 8:45 - 9:15 (30 min) Systematic GAI Tool Evaluation
• 9:15 - 9:30 (15 min) Coffee Break and Informal Discussion
• 9:30 - 10:00 (30 min) Mastering Advanced Prompting
• 10:00 - 10:30 (30 min) Critical Validation and Evaluation of AI outputs
• 10:30 - 11:00 (30 min) Ethical and Responsible Use of AI