Development of mixed distribution item response models for the analysis of cross-classified multirater data and their application in teaching evaluation research (MixIRT-CCM)

开发用于分析跨分类多评估者数据的混合分布项目响应模型及其在教学评估研究中的应用（MixIRT-CCM）

• 批准号: 405463675
• 负责人: Professor Dr. Tobias Koch, Ph.D.
• 金额: --
• 依托单位: Psychologische Hochschule Berlin gGmbH (PHB)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/405463675?language=en
• 关键词: Development; mixed; distribution; item; response

The aim of the project is to extend measurement models of item response theory (IRT models) to the analysis of cross-classified multirater (CCM) data including latent classes (mixture components) or multiple measurement waves (longitudinal designs). The project builds on current research findings in the area of multimethod change measurement (e.g., Koch, 2013, Holtmann, 2017) and mixture IRT modeling for hierarchical data structures (e.g., Kelcey, McGinn, & Hill, 2014, Wang, 2011) and seeks to extend these new modeling approaches to so-called CCM measurement designs. The development of such models is of high scientific and practical interest, as CCM data are found in many areas of psychology and empirical educational research, particularly in the area of teaching evaluation research. The newly developed models are applied to teaching evaluation data in order to take a closer look at the convergent and discriminant validity of teaching evaluations at higher education institutions. In addition, the statistical performance of the models is investigated in Monte Carlo simulation studies.

该项目的目的是将项目反应理论的测量模型（IRT模型）扩展到包括潜在类别（混合成分）或多重测量波（纵向设计）在内的交叉分类多重评分者（CCM）数据的分析。该项目建立在多方法变化测量领域的现有研究成果（例如，Koch, 2013, Holtmann, 2017）和分层数据结构的混合IRT建模（例如，Kelcey, McGinn, & Hill, 2014, Wang, 2011）的基础上，并寻求将这些新的建模方法扩展到所谓的CCM测量设计。这些模型的发展具有很高的科学和实用价值，因为CCM数据在心理学和实证教育研究的许多领域都有发现，特别是在教学评估研究领域。将新建立的模型应用到教学评价数据中，以进一步研究高校教学评价的收敛效度和判别效度。此外，在蒙特卡罗仿真研究中对模型的统计性能进行了研究。