大型语言模型对医学教育和教学适应的影响
Li Zhui1, Nina Yhap2, Liu Liping3
1Department of Vascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
JMIR medical informatics
|August 1, 2024
概括
大型语言模型 (LLM) 为医学教育提供了显著的好处,包括个性化学习和研究效率. 然而,教育工作者必须指导学生批判性地使用LLM,平衡技术与道德和实践技能.
科学领域:
- 医疗教育 技术 技术 医学教育
- 医疗保健中的人工智能
- 数字学习数字学习
背景情况:
- 像大型语言模型 (LLM) 这样的先进技术的整合正在迅速发展医学教育.
- 士课程提供了在医疗保健行业内彻底改变教学,学习和研究的机会.
研究的目的:
- 探索LLMs对医学教育的多方面的影响.
- 确定与在医疗保健培训中采用LLM相关的潜在好处和固有的挑战.
主要方法:
- 这篇文章提出了一个观点分析.
- 它综合了当前对医学教学中的LLM应用的理解和专家观点.
主要成果:
- 士学位可以提高教学质量,个性化学习,改善临床技能培训,并简化研究.
- 关键的挑战包括信息准确性,过度依赖,缺乏情绪智能以及道德/隐私问题.
结论:
- 有效的LLM整合需要教育领导力,适应性教学策略和培养批判性思维.
- 一种平衡的方法确保医疗保健专业人员在技术上熟练,在道德上有基础,并对未来的挑战有实际技能.
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