使用Boyer模型在HPE奖学金中应用AI工具的12个技巧
Jennifer Benjamin1,2, Ken Masters3, Anoop Agrawal4
1Department of Pediatrics, Huffington Department of Education Innovation and Technology, Baylor College of Medicine, Houston, TX, USA.
Medical teacher
|January 10, 2025
概括
人工智能 (AI) 为卫生专业教育提供了强大的工具. 本指南为教育工作者提供了实用技巧,以将AI有意义地整合到教学和学术中,强调对AI成果的批判性评估.
科学领域:
- 健康 职业 教育 教育 专业
- 教育中的人工智能
- 医疗教育 技术 技术 医学教育
背景情况:
- 人工智能 (AI) 融入卫生专业教育需要一个结构化的方法,超越最初的作.
- 教师需要实践指导,帮助他们利用人工智能工具进行日常的教学和学习活动.
- 一个教学框架对于最大限度地发挥AI在教育学术中的潜力至关重要.
研究的目的:
- 为教育工作者提供关于在卫生专业教育中使用人工智能的实用,可操作的建议.
- 展示人工智能如何有效地应用于增强教学和学习.
- 引导人工智能的有意义的整合到教育中的学术活动.
主要方法:
- 这篇文章建议利用博耶的奖学金模型作为人工智能集成的教学框架.
- 它提供了实际的解决方案,并展示了人工智能工具用于教育目的的实用性.
- 该方法的重点是利用人工智能能力用于教学和学习奖学金.
主要成果:
- 人工智能工具可以有效地应用于提高卫生专业教育中的日常教学和学习.
- 博耶模型为最大限度地提高人工智能对教育学术贡献提供了一个强大的框架.
- 实际应用证明了人工智能在推进教育实践中的有用性.
结论:
- 教师应该采用结构化的方法来整合AI,使用Boyer的奖学金模型.
- 对人工智能输出的批判性评估,包括对准确性和幻觉的审查,至关重要.
- 负责任的人工智能使用和避免过度依赖对于教育中的可持续整合至关重要.
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