Harnessing the potential of large language models in medical education: promise and pitfalls
Abstract Objectives To provide balanced consideration of the opportunities and challenges associated with integrating Large Language Models (LLMs) throughout the medical school continuum. Process Narrative review of published literature contextualized by current reports of LLM application in medical...
Gespeichert in:
Veröffentlicht in: | Journal of the American Medical Informatics Association : JAMIA 2024-02, Vol.31 (3), p.776-783 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Abstract
Objectives
To provide balanced consideration of the opportunities and challenges associated with integrating Large Language Models (LLMs) throughout the medical school continuum.
Process
Narrative review of published literature contextualized by current reports of LLM application in medical education.
Conclusions
LLMs like OpenAI’s ChatGPT can potentially revolutionize traditional teaching methodologies. LLMs offer several potential advantages to students, including direct access to vast information, facilitation of personalized learning experiences, and enhancement of clinical skills development. For faculty and instructors, LLMs can facilitate innovative approaches to teaching complex medical concepts and fostering student engagement. Notable challenges of LLMs integration include the risk of fostering academic misconduct, inadvertent overreliance on AI, potential dilution of critical thinking skills, concerns regarding the accuracy and reliability of LLM-generated content, and the possible implications on teaching staff. |
---|---|
ISSN: | 1067-5027 1527-974X 1527-974X |
DOI: | 10.1093/jamia/ocad252 |