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从多维IRT视角检查不同项目的运作

Terry A Ackerman1, Ye Ma2

  • 1The University of Iowa, 8 North Shore Drive, Edwardsville, IL, 62025, USA. tackerman@uiowa.edu.

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概括
此摘要是机器生成的。

差异性项目功能 (DIF) 发生在测试项目测量不同能力时. 本研究使用二维多维物件响应理论 (MIRT) 来分析DIF,考虑复杂的能力分布和问题解决方法.

关键词:
补偿和非补偿的MIRT模型.差异性项目的功能.这是一个多维的IRT.

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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 统计 统计 统计

背景情况:

  • 差异性项目功能 (DIF) 是测试开发中的一个关键分析,在不同组中识别有偏见的项目.
  • 现有研究表明,当项目接触到不同的能力组合时,特别是在不同的组能力分布的情况下,DIF可能会出现.
  • 标准的DIF分析经常忽视潜伏能力的多维性质,可能导致误解.

研究的目的:

  • 通过二维多维物品响应理论 (MIRT) 的镜头来检查差异物品功能 (DIF).
  • 为了说明补偿MIRT模型,项目能力复合表示,以及潜在能力分布对项目参数的影响.
  • 审查忽视维度和应用单维物品响应理论 (IRT) 模型的后果.

主要方法:

  • 使用二维MIRT框架调查DIF,专注于补偿MIRT模型.
  • 从MIRT的角度来看,分析了三种方法来理解DIF:均/非均的DIF与不同的分布,占全部潜伏空间,和基于场景的DIF.
  • 对一维IRT模型对二维潜伏空间的影响进行了分析研究.

主要成果:

  • 估计的项目参数可以根据受试者的潜在能力分布而有所不同.
  • 在IRT模型中忽视维度可能会导致不准确的DIF评估,当潜在的能力是多维的.
  • 考虑完整的潜能空间对于缓解条件方法中的DIF效应至关重要.

结论:

  • 两维的MIRT视角提供了对DIF的更细致的理解,考虑了复杂的能力结构.
  • 不同的能力分布,甚至不同的解决问题的方法可以诱导DIF,即使具有相同的潜在分布.
  • 虽然软件有助于DIF检测,但识别DIF的根本原因需要比统计标记更深入的分析洞察力.