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Creating custom GPTs for faculty development: An example using the Johari Window and Crucial Conversation frameworks
Neil Mehta1, Craig Nielsen2, Amy Zack3
1Professor of Medicine and Associate Dean for Curricular Affairs, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University School of Medicine, Cleveland, OH, USA.
None:
Feedback plays a crucial role in the growth and development of trainees, particularly when addressing areas needing improvement. However, faculty members often struggle to deliver constructive feedback, particularly when discussing underperformance. A key obstacle is the lack of comfort many faculty experience in providing feedback that fosters growth. Traditional faculty development programs designed to address these challenges can be expensive and too time-intensive, for busy clinicians.. Generative AI, specifically custom GPT models simulating virtual students and coaches, offers a promising solution for faculty development in feedback training. These AI-driven tools can simulate realistic feedback scenarios using widely accepted educational frameworks and coach faculty members on best practices in delivering constructive feedback. Through interactive, low-cost, and accessible virtual simulations, faculty members can practice in a safe environment and receive immediate, tailored coaching. This approach enhances faculty confidence and competence while reducing the logistical and financial constraints of traditional faculty development programs. By providing scalable, on-demand training, custom GPT-based simulations can be seamlessly integrated into clinical environments, fostering a supportive feedback culture prioritizing trainee development. This paper describes the stepwise process of design and implementation, of a custom GPT-powered feedback training based on an accepted framework. This process can has the potential to transform faculty development in medical education.
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