Research Article

Does equating matter in value-added models?

Volume: 7 Number: 4 October 31, 2018
TR EN

Does equating matter in value-added models?

Abstract

The purpose of this study was to examine the effect of equated and non-equated data on value-added assessment analyses. Several models have been proposed in the literature to apply the value-added assessment approach. This study compared two different value-added models: the unadjusted hierarchical linear model and the generalized persistence model. The former model assumes equated tests while the latter one relaxes this assumption. Two different data sets (equated and non-equated) were analyzed with both models. Value-added estimates for both models based on a statewide examination (equated) and a countrywide examination (non-equated) data were generally consistent. School rankings showed differences between the two models. The practical implication of this study is that although there were small differences in school rankings, a model requiring an equating assumption can be applied to a non-equated data set in a case when equating between test forms is not possible.

Keywords

References

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Details

Primary Language

English

Subjects

Studies on Education

Journal Section

Research Article

Publication Date

October 31, 2018

Submission Date

September 1, 2018

Acceptance Date

October 6, 2018

Published in Issue

Year 2018 Volume: 7 Number: 4

APA
Şen, S., Terzi, R., Yıldırım, İ., & Cohen, A. (2018). Does equating matter in value-added models? Turkish Journal of Education, 7(4), 186-195. https://doi.org/10.19128/turje.456656

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