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STFM Podcast October 2025 Episode

The October 2025 episode of the STFM Podcast is titled "Learning After Training: The Master Adaptive Learner Framework" and features Lou Edje, MD, MHPE. Listen on this page below or through a streaming platform.

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Today’s residents will still be practicing in 2060. Given that medical knowledge increases at lightning speed, educators must prepare learners for a future that demands constant innovation when faced with practice challenges. In this episode, Lou Edje, MD, MHPE, introduces the Master Adaptive Learner Framework and demonstrates how to use it with medical students, residents, and chief residents. Dr Edje shares strategies to help learners overcome barriers to learning, to “fail forward” productively, and to acquire habits supportive of a lifetime of Master Adaptive Learning.Hosted by Omari A. Hodge, MD, and Jay-Sheree Allen Akambase, MDCopyright © Society of Teachers of Family Medicine, 2025Resources:

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Resources

Fostering the Development of Master Adaptive Learners - On-Demand CBME Faculty Development Webinars, Webinar #11
Training Future Family Physicians to Become Master Adaptive Learners - Fam. Med.
Master Adaptive Learning in Faculty Development with Drew M. Keister, MD - The STFM Podcast September 2024
STFM Competency-Based Medical Education Toolkit for Residency Programs

Lou Edje, MD, MHPE

Dr Edje is a board-certified family physician, chair of the family medicine review committee of the Accreditation Council for Graduate Medical Education, and chair of the nominating committee of the American Medical Association’s Council on Medical Education. She was on the writing group for the new requirements for family medicine training in the United States. She is an Executive Leadership in Academic Medicine alumna who was the Ohio Academy of Family Physicians 2012 Family Physician of The Year. She was a recipient of the 2022 Dr. Martin Luther King, Jr. Humanitarian Award from the University of Cincinnati and the Distinguished Humanitarian Alumni Award from Michigan Medicine. She started at Michigan State University at age 16 where she received a bachelor of science degree in physiology. She was president of her medical school student body at the University of Michigan Medical School (UMMS) then completed her family medicine training, with honors, followed by 13 years in private practice and health system leadership. She subsequently returned to her residency program to serve as program director for 7 years. She has since founded two family medicine residency programs. Dr Edje has a masters in health professions education from the University of Michigan. As senior associate dean for medical education at UMMS, she supports the medical education of 680 medical students, 1300 house officers, and 3000 faculty as well as medical education at the Ann Arbor VA. Her interests include mitigating bias in assessment, master adaptive learners, and medical education policy.

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STFM's AI Assistant is designed to help you find information and answers about Family Medicine education. While it's a powerful tool, getting the best results depends on how you phrase your questions. Here's how to make the most of your interactions:

1. Avoid Ambiguous Language

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Example:

Instead of: "Can you help me with that?"

Try: "Can you help me update our Family Medicine clerkship curriculum?"

Why this is important: Ambiguous language can confuse the AI, leading to irrelevant or unclear responses. Clear references help the chatbot understand exactly what you're asking.

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Instead of: "What resources does STFM provide?"

Try: "I'm a new program coordinator for a Family Medicine clerkship. What STFM resources are available to help me design or update clerkship curricula?"

Why this is better: Providing details about your role ("program coordinator") and your goal ("design or update clerkship curricula") gives the chatbot enough context to offer more targeted information.

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Instead of: "How can I improve my program?"

Try: "As a program coordinator for a Family Medicine clerkship, what resources does STFM provide to help me improve student engagement and learning outcomes?"

Why this is important: Including relevant details helps the AI understand your specific situation, leading to more accurate and useful responses.

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If you move to a completely new topic and the chatbot doesn't recognize the change, click the Clear Chat History button and restate your question.

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Why this is important: Resetting ensures the AI does not carry over irrelevant information, which could lead to confusion or inaccurate answers.

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Include Background Information: The more context you provide, the better the chatbot can understand and respond to your question.

Example:

Instead of: "What are the best practices?"

Try: "In the context of Family Medicine education, what are the best practices for integrating clinical simulations into the curriculum?"

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Break Down Complex Queries: If you have multiple questions, ask them separately.

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Instead of: "What are the requirements for faculty development, how do I register for conferences, and what grants are available?"

Try: Start with "What are the faculty development requirements for Family Medicine educators?" Then follow up with your other questions after receiving the response.

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"What type of membership is best for me?"

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Good Prompt

"I'm the chair of the Department of Family Medicine at a major university, and I plan to retire next year. I'd like to stay involved with Family Medicine education. What type of membership is best for me?"

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STFM Podcast October 2025 Episode

Listen to All Episodes

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Lou Edje, MD, MHPE

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AI Chatbot Tips

Tips for Using STFM's AI Assistant

1. Avoid Ambiguous Language

Example:

2. Use Specific Terms

Example:

3. Don't Assume the AI Knows Everything

Example:

4. Reset if You Change Topics

5. Provide Enough Context

Example:

6. Ask One Question at a Time

Example:

Examples of Good vs. Bad Prompts

Bad Prompt

Good Prompt

Double Check Important Information

Technical Limitations

STFM AI Assistant