在基于问题的学习教程中使用生成式人工智能模拟患者病史采集:混合方法研究

Allison Mool, Jacob Schmid, Thomas Johnston, William Thomas, Emma Fenner, Kevin Lu, Raya Gandhi, Adam Western, Brendan Seabold, Kodi Smith, Zachary Patterson, Hannah Feldt, Daniel Vollmer, Roshan Nallaveettil, Anthony Fanelli, Logan Schmillen, Shelley Tischkau, Anna T. Cianciolo, Pinckney Benedict, Richard Selinfreund
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引用次数: 0

摘要

背景实施基于问题的学习(PBL)的医学教育工作者在模拟病人病例时,努力在真实性和可行性之间取得平衡,旨在激发小组合作讨论,调动学生的临床推理能力,激励自主学习,并促进可操作的科学认识的发展。人工智能(AI)的最新进展为 PBL 中的病人模拟提供了令人兴奋的新潜力
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Generative AI to Simulate Patient History-Taking in a Problem-Based Learning Tutorial: A Mixed-Methods Study
Background Medical educators who implement problem-based learning (PBL) strive to balance realism and feasibility when simulating patient cases, aiming to stimulate collaborative group discussion, engage students’ clinical reasoning, motivate self-directed learning, and promote the development of actionable scientific understanding. Recent advances in generative artificial intelligence (AI) offer exciting new potential for patient simulation in PBL
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