生成型人工智能对专业素质的影响 医生培训期间的课程和反思文章
Louis William Wang1,2,3,4
1Department of Vascular Medicine, St Vincent's Hospital, Sydney, New South Wales, Australia.
Internal medicine journal
|May 28, 2025
概括
生成型人工智能 (AI) 挑战了医生培训的评估,就像反思论文一样. 基于讨论的活动提供了一个潜在的解决方案,以保障医疗教育的专业发展目标.
科学领域:
- 医学教育 医学教育
- 专业发展专业发展
- 人工智能的人工智能
背景情况:
- 医生培训依赖于专业发展课程,以培养能力和反思.
- 生成型人工智能 (AI) 对传统的评估方法,特别是个人反思论文构成重大威胁.
- 人工智能生成的文章越来越难以检测,危及评估专业素质的完整性.
研究的目的:
- 为应对将人工智能纳入医学教育的挑战,同时保持评估完整性.
- 探索保护专业素质课程免受人工智能产生的内容的策略.
- 为医生实习生确定潜在的替代评估方法.
主要方法:
- 这篇文章回顾了生成AI对医疗教育当前评估实践的影响.
- 它讨论了个人反思论文对人工智能驱动的内容生成的脆弱性.
- 考虑了保护专业发展课程的几种选择.
主要成果:
- 生成型人工智能可以产生高质量的输出,模仿学员创建的反思论文.
- 目前的人工智能检测软件很难有效地识别人工智能生成的内容.
- 维护学习目标需要创新的评估方法.
结论:
- 基于讨论的活动被提出为个人反思文章的可行替代方案.
- 将人工智能融入学习中必须与评估真正的专业发展的需要保持平衡.
- 调整评估策略对于人工智能时代医疗教育的未来至关重要.
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