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

Published online by Cambridge University Press:  01 January 2025

Yi-Hsuan Lee*
Affiliation:
Educational Testing Service
Alina A. von Davier
Affiliation:
Educational Testing Service
*
Requests for reprints should be sent to Yi-Hsuan Lee, Educational Testing Service, Princeton, NJ, USA. E-mail: YLee@ETS.ORG

Abstract

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.

Information

Type
Original Paper
Copyright
Copyright © 2013 The Psychometric Society

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