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Monitoring Scale Scores over Time via Quality Control Charts, Model-Based Approaches, and Time Series Techniques

机译:通过质量控制图,基于模型的方法和时间序列技术来监控时间尺度上的分数

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摘要

Maintaining a stable score scale over time is critical for all standardized educational assessments. Traditional quality control tools and approaches for assessing scale drift either require special equating designs, or may be too time-consuming to be considered on a regular basis with an operational test that has a short time window between an administration and its score reporting. Thus, the traditional methods are not sufficient to catch unusual testing outcomes in a timely manner. This paper presents a new approach for score monitoring and assessment of scale drift. It involves quality control charts, model-based approaches, and time series techniques to accommodate the following needs of monitoring scale scores: continuous monitoring, adjustment of customary variations, identification of abrupt shifts, and assessment of autocorrelation. Performance of the methodologies is evaluated using manipulated data based on real responses from 71 administrations of a large-scale high-stakes language assessment.
机译:随着时间的推移,保持稳定的分数等级对于所有标准化的教育评估都至关重要。用于评估规模漂移的传统质量控制工具和方法要么需要特殊的等值设计,要么可能过于费时而无法定期进行操作测试,因为该测试在主管部门与其评分报告之间的时间间隔很短。因此,传统方法不足以及时捕获异常的测试结果。本文提出了一种用于评分监测和评估规模漂移的新方法。它涉及质量控制图,基于模型的方法和时间序列技术,以适应以下监视标度得分的需求:连续监视,调整习惯变化,识别突然变化以及评估自相关。方法的效果是根据71个主管部门进行的大规模高水平语言评估的真实答复,使用操纵数据进行评估的。

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