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首页> 外文期刊>Journal of psychoeducational assessment >Application of a Cognitive Diagnostic Model to a High-Stakes Reading Comprehension Test
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Application of a Cognitive Diagnostic Model to a High-Stakes Reading Comprehension Test

机译：认知诊断模型在高分阅读理解测试中的应用

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摘要

General cognitive diagnostic models (CDM) such as the generalized deterministic input, noisy, and gate (G-DINA) model are flexible in that they allow for both compensatory and noncompensatory relationships among the subskills within the same test. Most of the previous CDM applications in the literature have been add-ons to simulation studies. Although there are some applications of CDMs such as the Fusion Model and the Rule Space Model to educational assessment data in general and second-language data in particular, there are few studies applying general models such as the G-DINA. The purpose of the present study was to demonstrate the application of the G-DINA to the reading comprehension data of a high-stakes test. To this end, an initial Q-matrix was developed, validated, and cross-validated. The skill profiles of the test takers were estimated using the CDM package in R. Throughout, the process of constructing and validating a Q-matrix was elaborated on, the benefits of general models were emphasized, and implications for research investigating inter-skill relationships were discussed. Finally, suggestions for further research, to better take advantage of the flexibilities of general diagnostic models, were presented.
机译：通用认知诊断模型（CDM）（例如广义确定性输入，噪声和门控（G-DINA）模型）具有灵活性，因为它们允许在同一测试中子技能之间进行补偿性和非补偿性关系。文献中大多数以前的CDM应用程序都是模拟研究的附件。尽管CDM有一些应用，例如融合模型和规则空间模型，可以用于一般教育评估数据，特别是第二语言数据中的教育评估数据，但是很少有研究应用诸如G-DINA的一般模型。本研究的目的是证明G-DINA在高分测验的阅读理解数据中的应用。为此，最初的Q矩阵已开发，验证和交叉验证。使用R中的CDM软件包估算了应试者的技能概况。在整个过程中，详细阐述了构造和验证Q矩阵的过程，强调了通用模型的好处，并且对研究技能间关系的研究意义深远。讨论过。最后，提出了进一步研究的建议，以更好地利用常规诊断模型的灵活性。

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