Purpose: Family medicine education demands innovative approaches to enhance competency-based learning, faculty efficiency, and quality improvement. This session explores AI-powered tools, specifically ChatGPT, to streamline didactic development, improve feedback delivery, and support scholarship—ultimately enhancing resident performance and patient care.
Relevance to ABFM Goals: This session aligns with ABFM’s mission by integrating AI to:
Enhance CBME & Milestone Assessment via AI-generated case-based learning. Improve Faculty Development & Efficiency by reducing content creation burden. Support Research & QI through AI-assisted literature reviews and manuscript editing. Advance Lifelong Learning with personalized AI-driven self-assessment tools. Methods & Engagement: This interactive 60-minute session includes: ✔ AI-driven case-based learning to enhance engagement. ✔ AI-powered feedback tools for structured, competency-based evaluations. ✔ AI-assisted research and QI strategies to boost academic productivity. ✔ Small-group discussions on AI implementation in residency programs.
Outcomes: Attendees will leave with actionable AI strategies to improve education, enhance faculty efficiency, and support ABFM-aligned QI initiatives—helping programs "work smarter, not harder" with AI.
Learning Objectives:
Demonstrate how AI-powered tools like ChatGPT can enhance competency-based education by creating engaging, interactive didactic materials for family medicine training.
Utilize AI to deliver structured, competency-based feedback that improves mentorship, enhances evaluation efficiency, and supports resident learning outcomes.
Integrate AI-driven strategies into research and quality improvement initiatives to streamline academic productivity, improve scholarly output, and align with ABMS goals for continuous learning and assessment.
