Skills diagnosis using IRT-Based continuous latent trait models
Skills diagnosis using IRT-Based continuous latent trait models
复制标题
DOI：
10.1111/j.1745-3984.2007.00041.x
复制
发表时间：
2007-12-01
影响因子：
1.3
通讯作者：
Stout, William
中科院分区：
文献类型：
--
作者：
Stout, William
本文总结了技能诊断的连续潜在特质IRT方法，并用项目反应函数(IRFs)建立了具有代表性的连续潜在特质模型。首先，较为详细地介绍了几种基本的基于IRT的连续潜在特质方法。然后对估计、模型检验和评估评分方面进行了简要的总结。最后，简要介绍了加州大学伯克利分校基于多维Rasch模型的中学科学嵌入式评估项目的一个重要应用。
This article summarizes the continuous latent trait IRT approach to skills diagnosis as particularized by a representative variety of continuous latent trait models using item response functions (IRFs). First, several basic IRT-based continuous latent trait approaches are presented in some detail. Then a brief summary of estimation, model checking, and assessment scoring aspects are discussed. Finally, the University of California at Berkeley multidimensional Rasch-model-grounded SEPUP middle school science-focused embedded assessment project is briefly described as one significant illustrative application.