This advanced workshop focuses on implementing AI across core educational functions in health professions education, with emphasis on creating pedagogically sound, authentic artifacts. Through guided hands-on activities, participants will transform teaching materials, redesign assessments, and leverage AI for data-informed decision-making while maintaining educational integrity and academic rigor.

This workshop incorporates the latest developments in AI applications for health professions education, including expanded coverage of agentic AI workflows, enhanced learning analytics capabilities, and low-code AI solutions for educators. Previous 2025 attendees will benefit from new case scenarios, updated assessment frameworks that address evolving academic integrity challenges, and emerging best practices in AI-enhanced curriculum design.

Content Areas:

• Optimizing teaching with AI (content transformation, interactive learning design)
• Enhancing assessment with AI (authentic assessment design, rubric development, feedback generation)
• Data-informed decision-making and learning analytics
• Emerging applications: Agentic AI, machine learning, and low-code solutions
• Hands-on artifact creation with implementation planning

Deliverables: Participants leave with tangible artifacts (transformed learning activity, assessment items, data analysis report) created during the session.

Instructional Methods: Guided hands-on activities using participants' own educational materials, collaborative problem-solving sessions, case scenario analysis, implementation planning exercises, and peer feedback on created artifacts.

Learning Objectives
 

1. Transform traditional educational materials into interactive, AI-enhanced learning experiences using structured workflows that maintain pedagogical soundness and academic rigor.
2. Design authentic assessments that leverage AI capabilities while addressing academic integrity concerns, including development of rubrics and AI-driven feedback mechanisms.
3. Apply AI tools to analyze qualitative and quantitative educational data, generating actionable insights for curriculum enhancement and program improvement.
4. Create implementation-ready artifacts (transformed learning activities, assessment items, or data analysis reports) tailored to their specific institutional contexts.
5. Evaluate emerging AI applications (including agentic AI and machine learning) for their potential impact on teaching, assessment, and educational decision-making in health professions education.

Target Audience: Health professions educators, curriculum designers, and academic leaders with basic AI experience (or Workshop 1 completion) seeking to implement advanced AI applications in teaching, assessment, and educational analytics.