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Related Experiment Video

Updated: Jul 16, 2026

Step By Step: Microsurgical training method combining two nonliving animal models
05:25

Step By Step: Microsurgical training method combining two nonliving animal models

Published on: May 9, 2015

AI-Generated Microlearning for Plastic Surgery Residency: Single-Arm Pre-Post Feasibility Study.

Marius Drysch1, Sonja Verena Schmidt1, Felix Reinkemeier1

  • 1Department of Plastic Surgery, BG University Hospital Bergmannsheil Bochum, Bochum, North Rhine-Westphalia, Germany.

JMIR Medical Education
|July 14, 2026
PubMed
Summary

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Artificial intelligence (AI)-generated microlearning modules are feasible and acceptable for surgical training, showing preliminary improvements in resident confidence and knowledge. This study provides effect size estimates for future randomized trials.

Area of Science:

  • Medical Education
  • Artificial Intelligence in Healthcare
  • Surgical Training

Background:

  • Surgical residency training faces challenges with increasing knowledge demands and limited learning time.
  • Microlearning offers a flexible educational approach for busy clinical schedules.
  • Large language models (LLMs) present opportunities for scalable educational content generation, but their use in surgical training is underexplored.

Purpose of the Study:

  • To assess the feasibility and acceptability of AI-generated microlearning modules for plastic surgery residents.
  • To evaluate the quality of AI-generated content through faculty assessment.
  • To estimate the preliminary impact on residents' self-perceived knowledge and confidence.

Main Methods:

  • A 12-week single-arm pilot study involving 11 plastic surgery residents.
Keywords:
artificial intelligencefeasibility studiesgraduate medical educationlarge language modelsmicrolearningmultiple-choice questionsplastic surgery

Related Experiment Videos

Last Updated: Jul 16, 2026

Step By Step: Microsurgical training method combining two nonliving animal models
05:25

Step By Step: Microsurgical training method combining two nonliving animal models

Published on: May 9, 2015

  • Development of six microlearning modules using Google Gemini 2.5 Pro.
  • Content selection based on board-certified plastic surgeon evaluations using a 5-dimension rubric; biweekly module release.
  • Assessment of acceptability, faculty ratings, psychometrics, and pre-post changes in self-perceived knowledge and confidence.

    • Main Results:

    • High resident acceptability (median ≥5/7) and high faculty-rated content quality (mean 4.68/5).
    • Significant improvement in composite self-perceived confidence (d=0.65, P=.047) and medium effect for knowledge (d=0.71, P=.09).
    • Largest gains observed in hand surgery knowledge (d=1.48) and confidence (d=1.41).

    Conclusions:

    • AI-generated microlearning modules are feasible and acceptable in plastic surgery residency.
    • High-quality content was achieved, with residents demonstrating engagement and improved confidence.
    • The intervention integrated well into existing educational structures, providing data for future trial design.