Evaluation of Abilities by Grouping for Small IRT Testing Systems
Evaluation of Abilities by Grouping for Small IRT Testing Systems
复制标题
小型IRT测试系统分组能力评价
DOI：
10.1109/iiai-aai.2016.50
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
H. Hirose
中科院分区：
文献类型：
--
作者：
Yoshiko Tokusada;H. Hirose
在应用项目反应理论的自适应测试的实际情况下，它是至关重要的，知道适当的问题项目的数量足以指定的准确性。在我们开发的几乎所有的自适应测试系统中，我们都采用少量的试题进行自适应测试，因为太多的试题会使考生感到厌烦或被迫放弃完成测试，尽管可以获得估计的准确性。根据经验，我们将问题的数量设置为5个。但是，问题数量太少会导致对考生能力的估计不准确。在本文中，我们将展示问题的数量如何影响估计的准确性。为了估计的稳定性，我们采用了贝叶斯方法，它可以进行收缩估计。为了使使用的估计有意义，我们建议分组，或分类考生的能力。结果将显示最佳组数。通过模拟研究，我们发现五个问题项目不足以估计考生的真实能力。即使测试是适应性的，也至少需要10个项目。
In applying the adaptive testing equipped with the item response theory to actual cases, it is crucial to know the appropriate number of question items suffice for the specified accuracy. In almost all the systems we have developed so far, we adopt small number of items in a sequence of questions for adaptive testing because too many questions will bore examinees or force to give up completing the tests although estimation accuracy can be obtained. By experience, we set the number of questions to be five. However, too small number of questions will cause less accurate estimates for examinees' abilities. In this paper, we show how the number of questions influences the accuracy of the estimates. For the sake of stable estimation, we made use of Bayes method, which may make shrinkage estimation. In order to make sense to use the estimates, we propose grouping, or classifying to examinees' abilities. The optimal number of groups will be shown as a result. By using simulation studies, we have found that five question items are insufficient to estimate the examinee's true ability. At least ten items are required even if the testing is adaptive.