你的课程是否符合GenAI的要求? 一种用于GenAI影响评估的方法和一个案例研究
Remco Jongkind1, Erik Elings1, Erik Joukes2
1Teaching and Learning Centre, Amsterdam UMC Location AMC, Amsterdam, North Holland, 1105AZ, The Netherlands.
MedEdPublish (2016)
|March 13, 2026
概括
生成性AI (GenAI) 对教育评估构成风险. 一种新的方法评估了GenAI对评估有效性和学习成果的影响,导致64%的评估和36%的学习成果进行了调整.
科学领域:
- 医疗信息学 医疗信息学
- 教育技术的教育技术
- 教育中的人工智能
背景情况:
- 生成型人工智能 (GenAI) 在教育中既带来了机遇,也带来了风险,特别是在评估有效性和学习成果方面.
- 学生使用像ChatGPT这样的GenAI工具可能会破坏传统的评估方法.
- 需要一个系统的方法来评估和解决GenAI对教育课程的影响.
研究的目的:
- 提出一种广泛适用的方法来确定在GenAI的背景下评估的有效性.
- 评估学生使用GenAI对学习成果的影响.
- 为决定是否改变评估格式和/或学习成果提供一个框架.
主要方法:
- 开发了一种五步方法,并应用于医疗信息学课程.
- 与教师合作分析课程评估计划.
- 根据GenAI影响评估,调整课程评估和学习成果.
主要成果:
- 57%的评估,特别是在书面和编程方面,存在有效性和相关性降低的风险.
- GenAI对有效性的影响与评估的内容和结构有关,而不是复杂性.
- 64%的受影响评估的格式被调整,而36%的学习成果被改变.
结论:
- 大多数评估都受到GenAI的影响,需要对评估或学习成果进行调整.
- 开发的方法和案例研究为教育机构解决GenAI挑战提供了蓝图.
- 调整评估或学习成果对于在GenAI时代保持教育诚信至关重要.
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