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PEPCAL: A Heuristic Framework for Teaching Generative AI to Continuing Professional Education Providers and Faculty
Heather MacNeill1, Ken Masters, Jennifer Benjamin
1Dr. MacNeill: Assistant Dean, Clinical Faculty Development, Toronto Metropolitan University, School of Medicine, Toronto, Ontario, Canada, and Professor, Temerty Faculty of Medicine, Department of Medicine, University of Toronto, Toronto, Ontario, Canada. Dr. Masters: Professor of Medical Informatics, Medical Education and Informatics Department, College of Medicine and Health Sciences, Sultan Qaboos University, Sultanate of Oman. Dr. Benjamin: Assistant Dean of CPD, Associate Professor, Pediatrics, Department of Pediatrics, Huffington Department of Education Innovation and Technology, Baylor College of Medicine, and Co-Director for Faculty College Texas Children's Hospital, Houston, TX. Dr. Mehta: Professor of Medicine and Associate Dean for Curricular Affairs, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University School of Medicine, and The Jones Day Endowed, Chair in Medical Education, Cleveland Clinic, Cleveland, OH, and Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH. Dr. Agrawal: Associate Professor in Internal Medicine and Pediatrics, Program Director for the Combined Internal Medicine and Pediatrics Residency Program, Baylor College Medicine, Houston, TX. Dr. Valanci-Aroesty: Consultant for Royal College of Physicians and Surgeons of Canada, Ottawa, Canada.
This article introduces the Pedagogical-Ethical-Preparation-Creative-Administrative-Large Data (PEPCAL) framework to guide educators in using Generative AI (GenAI) for continuing professional development (CPD) and faculty development (FD). PEPCAL offers a structured approach for integrating GenAI responsibly and effectively into educational practices.
Area of Science:
- Medical Education
- Artificial Intelligence in Education
- Health Professions Education
Background:
- Generative AI (GenAI) presents transformative potential for continuing professional development (CPD) and faculty development (FD).
- Educators require practical, theoretically grounded guidance for integrating GenAI into professional learning environments.
- Existing frameworks may not fully address the unique pedagogical and ethical considerations of GenAI in health professions education.
Purpose of the Study:
- To introduce the Pedagogical-Ethical-Preparation-Creative-Administrative-Large Data (PEPCAL) framework.
- To provide a heuristic matrix for CPD/FD leaders to teach about and utilize GenAI effectively.
- To support the responsible and informed adoption of GenAI in health professions education.
Main Methods:
- Development of the PEPCAL framework based on international teaching experience, literature review, and inductive feedback.
- Creation of a heuristic matrix intersecting pedagogical approaches with GenAI applications.
- Application of the framework in training CPD/FD providers for GenAI implementation.
Main Results:
- The PEPCAL framework offers a structured approach to GenAI integration in CPD/FD, covering pedagogical design, ethics, preparation, creative uses, administrative tasks, and data insights.
- Highlights opportunities for GenAI to enhance multimodal learning, curriculum design, feedback, and data-driven decision-making.
- Emphasizes ethical considerations, environmental impact, pedagogical design, and preventing deskilling and burnout.
Conclusions:
- The PEPCAL framework complements existing CPD/FD theories and frameworks.
- It encourages an education-first adoption of GenAI, moving beyond tool-driven experimentation.
- PEPCAL facilitates responsible implementation, evaluation, and refinement of GenAI-enabled CPD/FD, fostering dialogue on sociotechnical issues.
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