在双参数物流模型下进行在线项目校准的复合最佳设计
1School of Education, Jiangxi Normal University, Nanchang, China.
Applied psychological measurement
|January 31, 2025
概括
本研究介绍了一种复合最佳设计,用于在计算机化测试中高效校准项目参数. 与现有设计相比,这种新方法可以提高估计项目难度和歧视参数的准确性.
科学领域:
- 心理测量 心理测量 心理测量
- 教育测量教育的测量
- 统计建模 统计建模
背景情况:
- 项目响应理论 (IRT) 模型对于分析测试数据至关重要.
- 项目参数的有效校准对于计算机化适应性测试 (CAT) 中准确的能力估计至关重要.
- 现有的设计可能无法最佳地平衡不同项目参数的估计.
研究的目的:
- 提出一种新的组合最佳设计,以高效地同时校准项目难度和歧视参数.
- 在双参数后勤 (2PL) 模型中,以适应性优化对具有挑战性的参数的估计.
- 评估拟议设计的性能与D-最佳和随机设计相比.
主要方法:
- 开发一个复合的最佳设计,结合两个最佳性标准.
- 使用验收概率来生成优化项目参数的设计点.
- 模拟研究和真实数据分析以评估参数恢复.
主要成果:
- 复合最佳设计在恢复歧视和难度参数方面表现出卓越的性能.
- 在模拟和真实数据分析中表现优于D-最佳和随机设计.
- 有效地平衡了难以估计的参数的优化.
结论:
- 拟议的组合最佳设计为IRT中的项目参数校准提供了更有效,更准确的方法.
- 这种方法提高了在计算机化测试中的项目参数估计的精度.
- 为提高教育和心理评估的质量提供了有价值的工具.
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