为学习而设计的程序性评估:为学习目的而设计的程序性评估:AMEE指南编号. 第174章 在这里
Dario Torre1, Lambert Schuwirth2
1University of Central Florida College of Medicine, Orlando, FL, USA.
Medical teacher
|October 5, 2024
概括
学习的程序性评估 (PAL) 使用结构化数据收集来增强学习. 本指南阐明了PAL术语,学习过程,有效性和未来的AI整合在评估中.
科学领域:
- 教育评估的教育评估
- 学习科学 学习科学
背景情况:
- 课程性学习评估 (PAL) 是一种不断发展的教育方法.
- 它涉及专门用于增强学习的评估数据的结构化收集.
研究的目的:
- 提供关于PAL的关键方面的建议.
- 为了澄清术语,并概述指导学习过程.
- 检查AI的有效性和未来方向,包括AI的作用.
主要方法:
- 审查程序性评估的演变.
- 学习过程的概要 (分布式学习,交叉学习,超越学习,通过测试增强的学习).
- 从程序视角分析有效性和未来的AI机会.
主要成果:
- 澄清PAL术语及其历史发展.
- 确定主要的学习流程,这些流程为PAL设计提供了信息.
- 了解有效性的不断变化的性质以及人工智能对评估的影响.
结论:
- PAL提供了一个结构化的框架,用于利用评估数据来改善学习.
- 了解学习过程和有效性对于有效的PAL实施至关重要.
- 人工智能为评估的未来带来了重大机遇和挑战.
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