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Modeling Growth With Adaptive Longitudinal Large‐Scale Assessments LSA NELS

Author(s):
Qian, Jiahe
Publication Year:
2018
Report Number:
RR-18-34
Source:
ETS Research Report
Document Type:
Report
Page Count:
17
Subject/Key Words:
Multidimensional Item Response Theory (MIRT), Longitudinal Data, Large-Scale Assessments (LSA), Adaptive Testing, National Educational Longitudinal Study of 1988 (NELS), Growth Modeling, Growth Patterns, Assessment Design, Reading Assessment

Abstract

The 2‐parameter logistic multidimensional item response theory (MIRT) model was employed to model growth for the National Education Longitudinal Study of 1988 (NELS:88). The 3 measurement waves of NELS:88 (base year, first follow‐up, and second follow‐up) represented 3 dimensions. The inquiry aimed to improve modeling performance growth based on examinees' responses to the test items in each wave, with item location parameters set to be invariant across the 3 waves (instead of using item changes) and the latent mean of the first wave set to 0. The yielded scores of 3 waves were thus placed on approximately the same scale; the changes of the scores across waves could be measured. Moreover, the growth models for longitudinal data were improved by using auxiliary information such as gender, race, school location, and parents' education. In the study, the results of the growth pattern were compared with those yielded by the Embretson models.

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