NEPS technical report for mathematics: Scaling results of Starting Cohort 1 for eight-year-old children (wave 9)

NEPS Technischer Bericht für Mathematik: Skalierungsergebnisse der Startkohorte 1 8-Jährige Kinder (Welle 9)

ProjektberichtForschung

Publikationsdaten


VonLara Aylin Petersen, Tanja Kutscher, Tessa Beyer, David Bednorz
OriginalspracheEnglisch
Erschienen in(NEPS Survey Papers; Nr. 111)
Seiten31
Herausgeber (Verlag)Leibniz Institut für Bildungsverläufe, Nationales Bildungspanel
DOI/Linkhttps://doi.org/10.5157/NEPS:SP111:1.0 (Open Access)
PublikationsstatusVeröffentlicht – 05.2024

The National Educational Panel Study (NEPS) aims at investigating the development of

competencies across the whole life span and designs tests for assessing these different

competence domains. To evaluate the quality of the competence tests, a wide range of

analyses based on item response theory (IRT) were performed. This paper describes the data

and scaling procedure for the mathematical competence test for 8-year-old children of

starting cohort 1 (newborns). The mathematics test consists of 20 items that represent

different content areas as well as different cognitive components and use different response

formats. The test was administered to 1,632 students. A partial-credit model was used for

scaling the data. Item fit statistics, differential item functioning, Rasch-homogeneity, and the

test´s dimensionality were evaluated to ensure the quality of the test. The results show that

the test exhibited a good reliability (EAP/PV reliability = .76) and that the items satisfactorily

fitted the model. Furthermore, comparable measurements could be confirmed for different

subgroups. Limitations of the test were some recognizable gaps at the upper end of the scale’s item difficulties. Overall, the results revealed good psychometric properties of the

mathematics test, thus supporting the estimation of a reliable mathematics competence

score. Besides the scaling results, this paper also describes the data available in the Scientific

Use File and provides the R syntax for scaling the data.