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Detecting Person Heterogeneity in a Large-Scale Orthographic Test Using Item Response Models

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Algorithms from and for Nature and Life

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Abstract

Achievement tests for students are constructed with the aim of measuring a specific competency uniformly for all examinees. This requires students to work on the items in a homogenous way. The dichotomous logistic Rasch model is the model of choice for assessing these assumptions during test construction. However, it is also possible that various subgroups of the population either apply different strategies for solving the items or make specific types of mistakes, or that different items measure different latent traits. These assumptions can be evaluated with extensions of the Rasch model or other Item Response models. In this paper, the test construction of a new large-scale German orthographic test for eighth grade students is presented. In the process of test construction and calibration, a pilot version was administered to 3,227 students in Austria. In the first step of analysis, items yielded a poor model fit to the dichotomous logistic Rasch model. Further analyses found homogenous subgroups in the sample which are characterized by different orthographic error patterns.

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Notes

  1. 1.

    The test was constructed for the Austrian National Educational Standards which is a governmental project of the Austrian Federal Ministry for Education, Arts and Culture. By order of the Ministry the construction for the pilot version of the orthographic test was conducted by the Center of Testing and Consulting at the Faculty of Psychology, University of Vienna.

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Authors and Affiliations

  1. Faculty of Psychology, Department of Psychological Assessment and Applied Psychometrics, University of Vienna, Vienna, Austria

    Christine Hohensinn, Klaus D. Kubinger & Manuel Reif

Authors
  1. Christine Hohensinn
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  2. Klaus D. Kubinger
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  3. Manuel Reif
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Corresponding author

Correspondence to Christine Hohensinn .

Editor information

Editors and Affiliations

  1. University of Essex Department of Mathematical Sciences, Colchester, United Kingdom

    Berthold Lausen

  2. Ghent University Department of Marketing, Ghent, Belgium

    Dirk Van den Poel

  3. University of Marburg Databionics, FB 12, Marburg, Germany

    Alfred Ultsch

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Hohensinn, C., Kubinger, K.D., Reif, M. (2013). Detecting Person Heterogeneity in a Large-Scale Orthographic Test Using Item Response Models. In: Lausen, B., Van den Poel, D., Ultsch, A. (eds) Algorithms from and for Nature and Life. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-00035-0_33

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