对比不同的 (非) 会计方法,用于快速猜测可信价值估计
Jana Welling1, Eva Zink1, Timo Gnambs1
1Leibniz Institute for Educational Trajectories, Bamberg, Germany.
Educational and psychological measurement
|January 19, 2026
概括
在教育评估中快速猜测可以扭曲能力估计. 响应级和组合模型有效地减轻了这种偏差,提高了大规模评估中群组比较的准确性.
科学领域:
- 教育测量的教育测量.
- 心理测量 心理测量 心理测量
- 进行大规模评估.
背景情况:
- 大规模评估为教育政策提供了信息,但可以受到动机等非能力因素的影响.
- 快速猜测,是一种减少动机的形式,可以扭曲能力估计和小组比较.
- 目前解决快速猜测的方法主要集中在点估计上,忽视了潜在变量研究.
研究的目的:
- 为了量化偏差,快速猜测引入了使用可信价值估计的组比较.
- 引入和评估用于处理可信价值估计过程中的快速猜测的新方法.
- 为了比较不同的模型在快速猜测会计中的表现.
主要方法:
- 一个模拟研究比较四个模型:基线 (没有纠正),人级纠正,响应级纠正 (项目响应时间) 和综合方法.
- 在不同的快速猜测场景下,对组比较中的偏差分析.
- 经验验证使用来自德国大规模评估的数据 (N = 478).
主要成果:
- 响应级和组合模型在计算快速猜测方面表现优异.
- 仅仅在个人层面进行校正不足以减轻快速猜测的扭曲效应.
- 该研究成功地证明了所有评估方法的实际适用性.
结论:
- 建议采用响应级和组合建模策略,以便在快速猜测的情况下准确估计能力.
- 未来的研究应该专注于改进这些方法,以进一步提高大规模评估中的能力估计.
- 准确的能力估计对于公平有效的教育政策和决策至关重要.
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