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.
Session 1: Foundations of Skill-Building with Artificial Intelligence
Thursday, May 15
1:00 - 2:00pm ET
Curious about AI but not sure where to start? This session lays the groundwork for building your confidence and skill with artificial intelligence in medical education. We’ll break down essential concepts like machine learning, natural language processing, and data pipelines in clear, practical terms. You'll get comfortable with key terminology, explore the differences between AI and Generative AI (GenAI), and discuss ethical guidelines for responsible AI use in academic settings. You’ll also have the opportunity to self-assess your current AI competency and set goals for growth. Whether you’re a beginner or looking to solidify your foundation, this session will equip you with the knowledge you need to move forward with confidence.
Presenter:
John Lowry, Ph.D.
Associate Professor of Education, Director of Faculty Development
Central Michigan University College of Medicine
Objectives:
- Explain the fundamental concepts of AI, including machine learning, natural language processing, and data pipelines.
- Define key AI terminology relevant to medical education.
- Compare AI and Generative AI (GenAI).
- Identify ethical considerations and guidelines for AI use in academia.
- Self-assess AI competency in medical education
Session 2: Prompting for Educators: Effective Communication with AI
Thursday, June 26
12:00 - 1:00pm ET
Ready to unlock the true potential of AI in your work as a medical educator? It all starts with knowing how to ask the right questions. In this lively, hands-on session, you'll discover practical frameworks like TRACI, CREATE, and RHODES that can help you craft smarter prompts and get better, more reliable results from AI tools. We'll dive into what shapes AI outputs—like bias, data quality, and prompt structure—and practice techniques to sharpen your communication for different educational tasks. Along the way, we'll tackle common pitfalls and ethical challenges, including how to spot misinformation and bias in AI responses. Walk away with easy-to-use strategies that will boost your AI fluency and immediately enhance your teaching, assessment, and scholarship.
Presenters
Larry Hurtubise, PhD
Curriculum and Instruction Consultant
Michael V. Drake Institute for Teaching and Learning
The Ohio State University
Stacey Pylman, PhD
Associate Professor & Director of CME
Office of Medical Education Research and Development (OMERAD)
Michigan State University College of Human Medicine
Emily Rush, PhD
AI Education Specialist
Center for Teaching Excellence and Innovation
Rush University
Objectives:
- Apply effective prompting frameworks (e.g., TRACI, CREATE, RHODES) to interact with AI tools.
- Identify factors that influence AI output quality, such as bias and data input quality.
- Develop refined prompts to achieve task-specific outputs.
- Recognize ethical risks such as AI-generated misinformation and biased content.
Session 3: Evaluating AI Outputs: Ensuring Accuracy and Relevance
Thursday, July 17
1:00 - 2:00pm ET
Objectives:
- Analyze AI outputs to determine alignment with educational goals.
- Check AI outputs for accuracy, correctness, and relevance against credible sources.
- Triangulate results across multiple AI tools.
- Recognize ethical risks such as AI-generated misinformation and biased content.
Session 4: AI for Efficiency and Automation
Thursday, August 21
1:00 - 2:00pm ET
Objectives:
- Identify AI tools that can streamline administrative and teaching tasks in medical education.
- Automate repetitive processes using AI for scheduling, document summarization, and data organization.
- Evaluate the effectiveness and ethical implications of AI-driven automation in education.
Session 5: Using AI with Data and Scholarship
Thursday, September 18
1:00 - 2:00pm ET
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.
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.