Increasing the Consequential Validity of Reading Assessment Using Dynamic Measurement Modeling: A Comment on Dumas and McNeish (2017)

Abstract

Dynamic measurement modeling (DMM) has been shown to improve the consequential validity of longitudinal mathematics assessment in the Early Childhood Longitudinal Study-Kindergarten (ECLS-K) database. Here, the authors demonstrate the capability of DMM to similarly improve the consequential validity of ECLS-K reading assessment through the estimation of student-specific learning capacities and growth parameters for reading.

Keywords

achievement gap longitudinal studies psychometrics reading social class

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