From foundational concepts and ethical considerations to hands-on strategies for prompting, evaluating outputs, curriculum design, clinical education, and scholarly work, this series will equip participants with practical competencies for responsible and effective AI use. Led by experienced educators and thought leaders in medical education, each monthly session offers actionable insights and tools to help you integrate AI into your teaching, assessment, and professional development. Whether you're just getting started or looking to deepen your expertise, this series offers a supportive and structured path toward AI literacy and leadership.
How has the AI series impacted you?
Session 1: Foundations of Skill-Building with Artificial Intelligence
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Session 2: Prompting for Educators: Effective Communication with AI
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Session 3: Evaluating AI Outputs: Ensuring Accuracy and Relevance
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Session 4: AI for Efficiency and Automation
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Session 5: Using AI with Data and Scholarship
Thursday, September 18
1:00 - 2:00pm ET
Discover how artificial intelligence can elevate your research and scholarship in medical education. This session will explore AI tools for analyzing data, streamlining literature reviews, enhancing academic writing, and visualizing findings. You’ll also learn how to navigate ethical considerations and ensure transparency and attribution in AI-assisted work. Whether you're new to AI or ready to expand your scholarly toolkit, this session offers practical strategies to advance your research with confidence
Objectives:
- Explore AI tools for analyzing and interpreting educational and research data.
- Use AI to streamline literature reviews, data visualization, and academic writing.
- Recognize ethical considerations when using AI for research and scholarly work.
- Practice transparency and attribution for AI contributions in their work.
Presenters
Tonya Anderson, MAEd
Adjunct Professor and Curriculum Development Consultant
Wayne State University
Heather Billings, PhD, MA
Assistant Professor of Medical Education, Director, Faculty Development
Mayo Clinic College of Medicine and Science
Brian Gin, MD, PhD
Associate Professor of Medical Education and Pediatrics
University of Illinois College of Medicine
LaTeesa James, MLIS
Health Sciences Informationist
University of Michigan Library
Melinda Turner, EdD
Director of Faculty Development
Lincoln Memorial University DeBusk College of Osteopathic Medicine
Session 6: Developing AI-Enhanced Curricula
Thursday, October 16
1:00 - 2:00pm ET
Objectives:
- Use AI tools to design curriculum components, including syllabi and learning objectives.
- Integrate AI-generated content into curriculum mapping.
- Evaluate the effectiveness of AI in curriculum development.
- Evaluate the impact of bias and automation on educational equity and fairness.
Session 7: Personalizing Learning with AI
Thursday, November 20
1:00 - 2:00pm ET
Objectives:
- Develop personalized learning activities using AI tools.
- Explore AI applications for virtual simulations and intelligent tutoring.
- Assess the effectiveness of AI-driven personalized learning solutions.
Session 8: AI for Assessment and Evaluation in Medical Education
Thursday, December 18
1:00 - 2:00pm ET
Objectives:
- Use AI to create assessments aligned with learning objectives.
- Analyze assessment results using AI tools to inform instruction.
- Explore AI applications for evaluating narrative data such as SOAP notes.
Session 9: Preparing for AI Integration in Clinical Education
Thursday, January 15
1:00 - 2:00pm ET
Objectives:
- Develop curriculum components on AI’s role in clinical settings.
- Evaluate the ethical and practical considerations of using AI in patient care.
- Create educational resources to explain AI applications to students.
Session 10: Continuous Professional Development in AI: Building a Lifelong Learning Plan
Thursday, February 19
1:00 - 2:00pm ET
Objectives:
- Assess personal AI knowledge gaps and develop a learning plan.
- Explore and share AI-related resources for ongoing professional growth.
- Reflect on AI use in medical education and identify areas for further experimentation.