在助产士教育中整合创造性人工智能:平衡创新,道德和学术诚信
Megan Koontz1, Stefanie Podlog2
1President, Midwives College of Utah, Salt Lake City, Utah.
Journal of midwifery & women's health
|September 11, 2025
概括
大型语言模型 (LLM) 为高等教育提供了新的工具,但偏见和学术诚信等伦理问题需要谨慎管理. 在助产计划中负责任的整合平衡了创新与保持教育标准和公平.
科学领域:
- 高等教育 高等教育
- 健康 职业 教育 教育 专业
- 人工智能的人工智能
背景情况:
- 大型语言模型 (LLM) 正在通过学习,管理和研究工具改变高等教育.
- 整合LLM提出了包括偏见,错误信息和学术诚信在内的伦理挑战.
- 助产士教育正在探索LLM应用程序的影响和负责任的使用.
研究的目的:
- 探索LLM在助产士高等教育中的不断变化的作用.
- 确定负责LLM整合的伦理考虑和策略.
- 为在专业健康教育中利用LLM工具提供一个框架.
主要方法:
- 审查LLM能力和高等教育的伦理问题.
- 来自美国助产计划的案例研究见解.
- 分析教师发展战略,课堂应用和政策更新.
主要成果:
- LLM 具有显著的潜力,可以增强学习和简化助产士教育中的任务.
- 关键的挑战包括减轻偏见,防止抄袭和培养批判性思维.
- 负责任的融合需要教师培训,学生指导和政策调整.
结论:
- 当有思想地整合时,LLM可以成为助产士高等教育中的有价值的工具.
- 保持学术标准,公平和批判性思维至关重要.
- 负责使用LLM的可复制框架可以指导专业健康教育计划.
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