Ehsan Toofaninejad
1 
, Mahdieh Zangiabadizadeh
2,3, Masomeh Kalantarion
3* , Saeed Latifi
4 1 Department of eLearning in Medical Sciences, School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2 Department of Midwifery, School of Nursing and Midwifery, Islamic Azad University, Kerman, Iran
3 Department of Medical Education, School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran
4 Educational Technology Department, Kharazmi University, Tehran, Iran
Abstract
Effective feedback plays a pivotal role in medical education, bridging the gap between current and desired learner performance. This short communication outlines common types and models of feedback in clinical teaching and explores how artificial intelligence (AI) tools, such as ChatGPT, can complement traditional methods. While AI can offer immediate, data-driven insights, the irreplaceable human element brings contextual awareness and emotional intelligence to feedback processes. We present a practical categorization of feedback types and a comparative overview of ten well-established models. By integrating human expertise with AI-supported systems, educators can enhance formative assessment and foster autonomous, reflective learning. Practical implications are discussed for implementing feedback models in both in-person and digital learning environments.