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<p>Large language models (LLMs) may be able to deliver interactive case-based content and score student interactions with such cases. In this study, GPT-4o demonstrated a high correlation with expert scorers in the evaluation of medical students’ interactions with cases. A difference between LLM scores and expert scorers was corrected through calibration.</p>

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Use of Large Language Models for Rapid Quantitative Feedback in Case-Based Learning: A Pilot Study

  • 期刊论文

  • 发表日期：

    2025年2月28日

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  • Carolyn Qian,
  • Christina Gao,
  • Sang-O. Park,
  • Haelynn Gim,
  • Kelly Hou,
  • Benjamin Cook,
  • Jasmin Le,
  • Brandon Stretton,
  • John Maddison,
  • Liam McCoy,
  • Rudy Goh,
  • Matthew Arnold,
  • Haatem Reda,
  • Tamara Kaplan,
  • Galina Gheihman,
  • Stephen Bacchi

摘要

Large language models (LLMs) may be able to deliver interactive case-based content and score student interactions with such cases. In this study, GPT-4o demonstrated a high correlation with expert scorers in the evaluation of medical students’ interactions with cases. A difference between LLM scores and expert scorers was corrected through calibration.