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School Class Composition and Student Development in Cognitive and Non-Cognitive Domains: Longitudinal Analyses of Primary School Students in Germany

Abstract

The paper discusses whether and how social and ethnic school class composition may affect students’ cognitive and non-cognitive development over time. High-performing students, who often tend to come from more privileged backgrounds, may provide opportunities for weaker students to enhance their competence development and serve as role models for behavior appropriate to the school setting. In contrast, a higher share of children with a migration background at a school or in a school class may lead teachers to lower their requirements to adapt to the level of the non-native speakers’ language skills. Moreover, a higher proportion of immigrants in a class increases children’s opportunities and incentives to use their language of origin in and around school. To test these different hypotheses, we analyze panel data on the impact of school class composition on students’ changes in cognitive and non-cognitive outcomes, namely vocabulary, numeracy, and effort. The data are derived from the BiKS project (Educational Processes, Competence Development and Selection Decisions in Preand Elementary School Age) and have been collected in two German states since 2006. The panel study provides detailed information on almost 2,400 students from over 150 classes and includes assessment tests, student’s and teacher’s questionnaires, and telephone interviews with parents. The major result is that school class composition has little to no effect if initial measures on vocabulary, numeracy or effort are taken into account. This means, that if we shift from a purely cross-sectional to a value-added model from grade 3 to 4. One exception is the negative correlation between the share of migrants in a class and the individual progress in numeracy.

Keywords

  • Competence development
  • Peer effects
  • Immigrant segregation
  • Elementary school
  • Value-added models

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Notes

  1. 1.

    Advantaged neighbors can also have positive effects since they can provide more information, including, for instance, about job opportunities. This has been researched in labor market studies, where weak ties are especially relevant (Granovetter 1973). In a neighborhood where almost everyone is unemployed, there is hardly anyone who can tell other people about a job or trainee position, or who can recommend a person to the head of a company (Wilson 1987). For educational careers, information on the supply and quality of different schools might also be important for the decision-making.

  2. 2.

    A third important factor regarding the language acquisition of non-natives is efficiency, which depends mainly on intellectual capacities and age at immigration. We ignore these aspects in the discussion, as both characteristics are individual-specific and almost all of today’s elementary school children with a migration background were born in Germany or arrived in Germany before school enrolment.

  3. 3.

    Only North Rhine-Westphalia has eliminated restriction in elementary school choice.

  4. 4.

    BiKS is the acronym for the German title “Bildungsprozesse, Kompetenzentwicklung und Selektionsentscheidungen im Vor- und Grundschulalter”, which means in English “Educational Processes, Competence Development and Selection Decisions in Pre- and Elementary School Age”.

  5. 5.

    Another advantage of experiments is that the range, the “strength” of the treatment effect can be administered. For e.g., in observational education studies we often have classes with no to some students with migration background, but only a few classes with (nearly) all students having this characteristic. If there are threshold effects starting at a higher proportion of students with migration background, the effects would not be discovered if the sample consists (almost) only of classes below such a threshold.

  6. 6.

    ‘Trivial’ because in the case of real cross-sectional data, regressing a student variable (level 1) on means of this variable for each school class in a hierarchical linear model results in completely explained variance at level 2. In the ‘constant only model,’ the variance at level 2 is based on the different means of the dependent variable per school class and the total average between all school classes. As students’ effort in grades 3 and 4 correlates, the aggregate measure of grade 3 should significantly correlate with students’ efforts in grade 4, too.

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Acknowledgments

The chapter is the result of work undertaken as part of the Subproject 7 of the research group BiKS (‘Bildungsprozesse, Kompetenzentwicklung und Selektionsentscheidungen im Vor- und Grundschulalter’—Educational Processes, Competence Development and Selection Decisions in Pre- and Elementary School Age) based at the University of Bamberg, Germany. It is funded by grants from the Deutsche Forschungsgemeinschaft (German Research Foundation), project number BL 381/7-2.

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Schneider, T. (2013). School Class Composition and Student Development in Cognitive and Non-Cognitive Domains: Longitudinal Analyses of Primary School Students in Germany. In: Windzio, M. (eds) Integration and Inequality in Educational Institutions. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6119-3_8

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