首页> 外文学位 >Investigating differential item function amplification and cancellation in application of item response testlet models.
【24h】

Investigating differential item function amplification and cancellation in application of item response testlet models.

机译:在项目响应测试模型的应用中研究差分项目功能的放大和抵消。

获取原文
获取原文并翻译 | 示例

摘要

Many educational tests use testlets as a way of providing context, instead of presenting only discrete multiple-choice items, where items are grouped into testlets (Wainer & Kiely, 1987) or item bundles (Rosenbaum, 1988) marked by shared common stimulus materials. One might doubt the usual assumption of standard item response theory of local independence among items in these cases. Plausible causes of local dependence might be test takers' different levels of background knowledge necessary to understand the common passage, as a considerable amount of mental processing may be required to read and understand the stimulus, and different persons' learning experiences. Here, the local dependence can be viewed as additional dimensions other than the latent traits. Furthermore, from the multidimensional differential item functioning (DIF) point of view, different distributions of testlet dimensions among different examinee subpopulations (race, gender, etc) could be the cognitive cause of individual differences in test performance. When testlet effect and item idiosyncratic features of individual items are both considered to be the reasons of DIF, it is interesting to investigate the phenomena of DIF amplification and cancellation resulting from the interactive effects of these two factors.; This dissertation presented a study based on a multiple-group testlet item response theory model developed by Li et al. (2006) to examine in detail different situations of DIF amplification and cancellation at the item and testlet level using testlet characteristic curve procedures with signed/unsigned area indices and logistic regression procedure. The testlet DIF model was estimated using a hierarchical Bayesian framework with the Markov Chain Monte Carlo (MCMC) method implemented in the computer software WINBUGS. The simulation study investigated all of the possible conditions of DIF amplification and cancellation attributed to person-testlet interaction effect and individual item characteristics. Real data analysis indicated the existence of testlet effect and its magnitudes of difference on the means and/or variance of testlet distribution between manifest groups imputed to the different contexts or natures of the passages as well as its interaction with the manifest groups of examinees such as gender or ethnicity.
机译:许多教育测试使用睾丸作为提供背景的一种方式,而不是仅呈现离散的多项选择项,而是将这些项分为睾丸(Wainer&Kiely,1987)或以共享的共同刺激材料标记的捆绑物(Rosenbaum,1988)。在这些情况下,人们可能会对标准的项目响应理论关于项目间局部独立性的通常假设表示怀疑。可能导致局部依赖的原因可能是应试者了解共同通行所必需的不同水平的背景知识,因为阅读和理解刺激以及不同人的学习经历可能需要大量的心理处理。在这里,可以将局部依赖性视为潜在特征以外的其他维度。此外,从多维差异项功能(DIF)的角度来看,不同受检者亚人群(种族,性别等)之间睾丸尺寸的不同分布可能是导致测试成绩出现个体差异的认知原因。当个体的睾丸效应和个体特质都被认为是DIF的原因时,研究由这两个因素的交互作用引起的DIF放大和消除现象是很有趣的。本文提出了一种基于Li等人开发的多组睾丸项目反应理论模型的研究。 (2006年)使用带符号/无符号面积指数的loglet特征曲线程序和logistic回归程序详细研究了DIF在项和睾丸级别上放大和消除的不同情况。使用分层贝叶斯框架和在计算机软件WINBUGS中实现的马尔可夫链蒙特卡洛(MCMC)方法,估计了睾丸DIF模型。模拟研究调查了归因于人-睾丸相互作用效应和单个项目特征的DIF放大和消除的所有可能条件。实际数据分析表明,存在睾丸效应及其对量表之间的差异和幅度的影响程度,归因于不同语段或性质的清单组之间的差异和/或差异,以及它与考生的清单组之间的相互作用,例如性别或种族。

著录项

  • 作者

    Bao, Han.;

  • 作者单位

    University of Maryland, College Park.$bMeasurement, Statistics and Evaluation.;

  • 授予单位 University of Maryland, College Park.$bMeasurement, Statistics and Evaluation.;
  • 学科 Education Tests and Measurements.; Statistics.; Psychology Psychometrics.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 209 p.
  • 总页数 209
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 教育;统计学;心理学研究方法;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号