MedED-AI #118 Epoch "Revolutionizing Feedback and Coaching in Medical Education: The Role of AI and Emotional Intelligence"

Attending a workshop on feedback and coaching in medical education was an enriching experience during phase 1 training day at UOB. It highlighted the critical role feedback plays in fostering growth and guiding learners toward achieving their full potential. As I reflect on these learnings, a pivotal question arises: How can Artificial Intelligence (AI) enhance the effectiveness of feedback and coaching in medical education?

Benefits of Integrating AI in Feedback and Coaching

1. Personalized Feedback: AI tools can analyze individual student performance and provide detailed, tailored feedback. For example, an AI system could review a student’s clinical notes or simulated patient interactions and highlight specific areas for improvement while suggesting actionable steps.
2. Real-time Insights: With AI-powered tools, educators can offer immediate feedback during practical sessions or assessments, enabling students to reflect and adjust their approach promptly.
3. Data-Driven Coaching: AI can collect and analyze longitudinal data, such as patterns in clinical reasoning or procedural skills, to identify strengths and weaknesses. This data empowers coaches to guide learners more effectively toward holistic improvement.
4. Enhanced Emotional Intelligence in Coaching: AI can assist coaches by identifying non-verbal cues or language patterns that indicate student emotions, helping educators adjust their approach and foster a supportive learning environment.
5. Consistency and Accessibility: AI ensures that feedback is consistent, unbiased, and accessible at any time. It can act as a supplementary tool for learners who may need additional support outside scheduled coaching sessions.

Challenges of Integrating AI in Feedback and Coaching

1. Over-reliance on Technology: There is a risk of students and educators becoming overly dependent on AI, potentially diminishing the value of human connection and empathy in coaching relationships.
2. Limited Contextual Understanding: While AI can analyze data, it may struggle to fully comprehend the nuances of clinical situations or the complex interpersonal dynamics of medical education.
3. Ethical Concerns: AI systems require access to sensitive student performance data, raising concerns about privacy and data security.
4. Emotional Intelligence Development: Effective coaching often relies on the emotional intelligence of educators. AI may assist in identifying emotions but cannot replace the human ability to respond empathetically and build trust.
5. Training and Adaptation: Both students and educators will require training to effectively use AI tools, which could be a significant time and resource investment.

Conclusion

Integrating AI into feedback and coaching practices in medical education offers immense potential to enhance learning experiences. However, it also necessitates careful consideration of ethical, emotional, and practical challenges. As coaching evolves with AI, educators must focus on blending the strengths of technology with human-centered approaches to maintain the emotional intelligence essential for meaningful mentorship.

Huang, H., & Lin, H. C. (2024). ChatGPT as a life coach for professional identity formation in medical education. Educational Technology & Society, 27(3), 374-389.

Randhawa, G. K., & Jackson, M. (2020, January). The role of artificial intelligence in learning and professional development for healthcare professionals. In Healthcare management forum (Vol. 33, No. 1, pp. 19-24). Sage CA: Los Angeles, CA: SAGE Publications.

Bachkirova, T., & Kemp, R. (2024). ‘AI coaching’: democratising coaching service or offering an ersatz?. Coaching: An International Journal of Theory, Research and Practice, 1-19.

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#MedicalEducation #Feedback #Coaching #ArtificialIntelligence #EmotionalIntelligence #EdTech #ProfessionalDevelopment