Work

Blending human and AI-powered feedback models in medical education: A practical overview

Year: 2025

Type: article

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.

Source: Research and Development in Medical Education

DOI: 10.34172/rdme.025.33353

Authors: Ehsan Toofaninejad, Mahdieh Zangiabadizadeh, Masomeh Kalantarion, Saeed Latifi

Institutions: Shahid Beheshti University, Shahid Beheshti University of Medical Sciences, Islamic Azad University Kerman, Kharazmi University

Language: English

Topic: Innovations in Medical Education

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Quality education

Open Access status: diamond

Funder: Shahid Beheshti University of Medical Sciences