参与式共同设计和评估一种新的方法,以生成人工智能集成课程评估在高等教育
Alex F Martin1, Svitlana Tubaltseva2, Anja Harrison1
1Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London WC2R 2LS, UK.
Behavioral sciences (Basel, Switzerland)
|June 26, 2025
概括
教育中的生成人工智能可以增强学习和评估,当被深思熟虑地整合时. 这项研究表明,支架式人工智能使用促进了研究生心理学学生的批判性人工智能素养和道德反思.
科学领域:
- 教育技术的教育技术.
- 教育中的人工智能
- 心理学 教育 教育 心理学 教育
背景情况:
- 生成型人工智能为教育提供了机会,但也引发了关于学术诚信,公平和批判性参与的担忧.
- 人工智能的快速发展需要探索它在高等教育评估中的作用.
研究的目的:
- 为研究生心理学学生共同设计和评估人工智能综合评估,以提高关键人工智能素养.
- 调查人工智能辅助评估方法的可行性,可接受性和感知完整性.
主要方法:
- 一项新的AI综合评估在英国一所大学的心理学课程中共同设计和实施.
- 学生被分为"合规" (人工智能辅助反思) 和"不受限制" (免费使用人工智能) 组.
- 通过重点小组,采访和研讨会收集了定性数据;通过使用适应的标签盲目标记获得的定量数据.
主要成果:
- 将人工智能整合到评估中可以促进学生的技术人工智能流性和批判性道德反思.
- 参与式的共同设计和评估方法被证明是有效的,可转移的,并为教育工作者提供了一个实用的工具包.
- 该研究强调了平衡学术诚信与发展基本的AI相关技能的重要性.
结论:
- 精心设计的AI整合在评估中可以有效地促进关键AI素养和道德参与.
- 共设计方法提供了一个可转移的模型,用于开发真实的评估,反映真实世界的AI使用.
- 教师必须通过平衡技能发展与学术诚信来导航教育中的AI不断发展的格局.
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