医疗教育由生成性人工智能赋权的大型语言模型.
Tanisha Jowsey1, Jessica Stokes-Parish1, Rachelle Singleton2
1Faculty of Health Sciences and Medicine, Bond University, Robina, Australia.
Trends in molecular medicine
|September 17, 2023
概括
生成型人工智能 (GAI) 大型语言模型 (LLM) 为医学和健康科学教育工作者提供了新的教学工具. 整合这些AI技术可以增强学生的学习能力.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 数字学习技术数字学习技术
背景情况:
- 生成型人工智能 (GAI) 和大型语言模型 (LLM) 是快速发展的应用.
- 越来越多的GAI-LLMs需要在学术环境中进行探索.
- 医学和健康科学 (M&HS) 教育面临着适应新数字工具的挑战.
研究的目的:
- 为整合GAI-LLMs在M&HS学习和教学中提供实用策略.
- 引导教育工作者利用GAI-LLMs来提高学生的数字能力.
- 探索人工智能在现代化健康科学教学中的潜力.
主要方法:
- 审查与教育相关的当前GAI-LLM能力.
- 为M&HS开发教学整合框架.
- 确定在课堂上道德和有效地使用人工智能的最佳实践.
主要成果:
- 具体的,可操作的战略,将GAI-LLMs纳入M&HS课程.
- 关于GAI-LLMs如何支持多样化的学习活动的例子.
- 关于促进学生对人工智能产生的内容进行批判性评估的指导.
结论:
- GAI-LLMs为提高M&HS教育提供了显著的机会.
- 这些工具的战略整合可以有效地提高学生的数字素养.
- 教师在指导在健康科学中负责任地采用人工智能方面发挥着至关重要的作用.
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