Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jul 13, 2026

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task
07:08

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task

Published on: December 5, 2025

Artificial Intelligence in Narrative Feedback Analysis for Competency-Based Medical Education: A Review.

Sameer Asim Khan1, Jamal Taiyara1, Nabil Zary2

  • 1College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai Health, Dubai, United Arab Emirates.

Studies in Health Technology and Informatics
|May 17, 2025
PubMed
Summary

Related Concept Videos

Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Personalize and Advance Your Education with PAVE: A Precision Education Initiative.

Studies in health technology and informatics·2026
Same author

Design, implementation, and evaluation of IIIDDS: a structured WhatsApp case-discussion curriculum in undergraduate radiology education.

Frontiers in medicine·2026
Same author

Development of entrustable professional activities for competency-based prosthodontic specialty training programmes.

Journal of dentistry·2026
Same author

Influence of marital pressures and cultural constructs on females (IMPACT-F): a global study of female medical students and doctors.

BMC medical education·2026
Same author

Investigating organizational resilience in a medicine and health sciences university in United Arab Emirates.

PloS one·2025
Same author

Editorial: Navigating complexity in postgraduate/graduate health professions education: innovative pedagogical approaches and assessment strategies.

Frontiers in medicine·2025

Artificial Intelligence (AI) and Natural Language Processing (NLP) can analyze vast amounts of narrative feedback in Competency-Based Medical Education (CBME). AI offers efficient data analysis, reducing educator workload and enhancing feedback evaluation for medical students.

Area of Science:

  • Medical Education
  • Artificial Intelligence
  • Natural Language Processing

Background:

  • Competency-Based Medical Education (CBME) produces extensive qualitative narrative feedback.
  • Traditional analysis methods struggle with the scale and complexity of CBME feedback data.
  • There is a need for advanced analytical tools to manage and interpret this data.

Purpose of the Study:

  • To explore the applications of Artificial Intelligence (AI), specifically Natural Language Processing (NLP), in analyzing medical student performance feedback within CBME.
  • To assess the impact and challenges of implementing AI for feedback analysis in CBME.
  • To review existing literature on AI-driven feedback analysis in medical education.

Main Methods:

  • A comprehensive literature search was conducted using PubMed and Google Scholar.
Keywords:
Artificial intelligencecompetency-based medical educationfeedbackmedical educationnatural language processingqualitative analysis

Related Experiment Videos

Last Updated: Jul 13, 2026

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task
07:08

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task

Published on: December 5, 2025

  • Studies meeting specific inclusion criteria were identified and analyzed.
  • The review synthesized findings on AI applications, benefits, and limitations in CBME feedback analysis.

    • Main Results:

    • AI, particularly NLP, can automate theme extraction from narrative feedback.
    • AI tools can significantly reduce the workload for educators managing feedback.
    • AI enhances the efficiency and effectiveness of evaluating medical student performance feedback.
    • Challenges include contextual understanding limitations and the necessity of human oversight.

    Conclusions:

    • AI holds transformative potential for analyzing feedback in Competency-Based Medical Education.
    • Effective integration of AI requires addressing current challenges and ensuring human oversight.
    • Further research is needed to optimize AI tools for educational workflows in CBME.