The achievement gap in reading competence: the effect of measurement non-invariance across school types

Autor(es): Rohm, Theresa; Carstensen, Claus H.; Fischer, Luise; Gnambs, Timo

Date: 2021

Pages: p. 1-26

Serie: Large-scale Assessments in Education

Series Volume: 9, 23 (2021)


After elementary school, students in Germany are separated into different school tracks (i.e., school types) with the aim of creating homogeneous student groups in secondary school. Consequently, the development of students’ reading achievement diverges across school types. Findings on this achievement gap have been criticized as depending on the quality of the administered measure. Therefore, the present study examined to what degree differential item functioning affects estimates of the achievement gap in reading competence. Using data from the German National Educational Panel Study, reading competence was investigated across three timepoints during secondary school: in grades 5, 7, and 9 (N=7276). First, using the invariance alignment method, measurement invariance across school types was tested. Then, multilevel structural equation models were used to examine whether a lack of measurement invariance between school types affected the results regarding reading development. Our analyses revealed some measurement non-invariant items that did not alter the patterns of competence development found among school types in the longitudinal modeling approach. However, misleading conclusions about the development of reading competence in different school types emerged when the hierarchical data structure (i.e., students being nested in schools) was not taken into account. We assessed the relevance of measurement invariance and accounting for clustering in the context of longitudinal competence measurement. Even though differential item functioning between school types was found for each measurement occasion, taking these differences in item estimates into account did not alter the parallel pattern of reading competence development across German secondary school types. However, ignoring the clustered data structure of students being nested within schools led to an overestimation of the statistical significance of school type effects.

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