Generating group-level scores under response accuracy-time conditional dependence

IF 3 Q1 EDUCATION & EDUCATIONAL RESEARCH Large-Scale Assessments in Education Pub Date : 2022-06-22 DOI:10.1186/s40536-022-00122-y
Hyo Jeong Shin, Paul A. Jewsbury, Peter W. van Rijn
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Abstract

The present paper investigates and examines the conditional dependencies between cognitive responses (RA; Response Accuracy) and process data, in particular, response times (RT) in large-scale educational assessments. Using two prominent large-scale assessments, NAEP and PISA, we examined the RA-RT conditional dependencies within each item in the measurement model and the structural model. Evidence for RA-RT conditional dependencies was observed in data from both programs, presenting a challenge in incorporating RT to the current operational models in NAEP and PISA that do not account for RA-RT conditional dependencies. However, inclusion of RT in the model had a relatively large contribution to improving the measurement of ability (residual variance decrease of 11% in NAEP and 18% in PISA), in contrast to relatively modest difference in parameter estimation from neglecting the conditional dependencies (e.g., estimated difference on residual variance of 1% in both NAEP and PISA). We conclude that the benefits of incorporating RT in the operational models for large-scale educational assessments may outweigh the costs.

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在反应准确性-时间条件依赖下产生组级分数
本文研究和检验了认知反应(RA;反应准确性)和处理数据,特别是大规模教育评估中的反应时间(RT)。利用NAEP和PISA这两个著名的大规模评估,我们检查了测量模型和结构模型中每个项目中的RA-RT条件依赖关系。在这两个项目的数据中都观察到RA-RT条件依赖性的证据,这对将RT纳入NAEP和PISA当前的操作模型提出了挑战,因为这些模型不考虑RA-RT条件依赖性。然而,在模型中纳入RT对改善能力的测量有相对较大的贡献(NAEP和PISA的残差方差减少了11%和18%),而忽略条件依赖性对参数估计的差异相对较小(例如,NAEP和PISA的残差估计差异均为1%)。我们的结论是,将RT纳入大规模教育评估的操作模型的好处可能超过成本。
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来源期刊
Large-Scale Assessments in Education
Large-Scale Assessments in Education Social Sciences-Education
CiteScore
4.30
自引率
6.50%
发文量
16
审稿时长
13 weeks
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