Holonomic Approach for Item Response Theory Parameter Estimation

Kazuhisa Noguchi, E. Ito
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Abstract

The IRT (item response theory) is a theory for scoring of tests, and it is used for some test systems such as TOEFL. Classical test scoring is the total of raw scores for each items (questions). On the other hand, IRT can make fine performance finer than the raw score method. IRT is based on the relationship between individual test takers' performances on a test item (question), and the test takers' levels of performance. Even with the same number of correct answers, the IRT score may be different depending on the degree of difficulty of item (question). Computational complexity of parameter estimation of IRT is one of important issue. To solve this issue, we propose a parameter estimation method of IRT using the Holonomic approach. Generate differential equations which solve the likelihood function of IRT. By solving this differential equation, it is able to estimate the ability parameter.
项目反应理论参数估计的完整方法
IRT(项目反应理论)是一种测试评分理论,它被用于一些测试系统,如托福。经典考试分数是每个项目(问题)的原始分数的总和。另一方面,IRT可以获得比原始分数方法更好的性能。IRT是基于个别考生在一个测试项目(问题)上的表现与考生的表现水平之间的关系。即使正确答案的数量相同,IRT的分数也可能因项目(问题)的难易程度而有所不同。IRT参数估计的计算复杂度是其中一个重要问题。为了解决这一问题,我们提出了一种基于完整方法的IRT参数估计方法。生成求解IRT似然函数的微分方程。通过求解该微分方程,可以估计出能力参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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