Modelling the Effects of Pupil Mobility and Neighbourhood on School Differences in Educational Achievement
Traditional studies of school differences in educational achievement use multilevel modelling techniques to take into account the nesting of pupils within schools. However, educational data are known to have more complex non-hierarchical structures. The potential importance of such structures is apparent when considering the impact of pupil mobility during secondary schooling on educational achievement. Movements of pupils between schools suggest that we should model pupils as belonging to the series of schools attended and not just their final school. Since these school moves are strongly linked to residential moves, it is important to additionally explore whether achievement is also affected by the history of neighbourhoods lived in. Using the national pupil database (NPD), this paper combines multiple-membership and cross-classified multilevel models to simultaneously explore the relationships between secondary school, primary school, neighbourhood and educational achievement. The results show a negative relationship between pupil mobility and achievement, the strength of which depends greatly on the nature and timing of these moves. Accounting for pupil mobility also reveals that schools and neighbourhoods are more important than shown by previous analysis. A strong primary school effect appears to last long after a child has left that phase of schooling. The additional impact of neighbourhoods, on the other hand, is small. Crucially, the rank order of school effects across all types of pupils is sensitive to whether we account for the complexity of the multilevel data structure.
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- Stephen Machin & Shqiponja Telhaj & Joan Wilson, 2006.
"The Mobility of English School Children,"
CEE Discussion Papers
0067, Centre for the Economics of Education, LSE.
- Harvey Goldstein & Simon Burgess & Brendon McConnell, 2007. "Modelling the effect of pupil mobility on school differences in educational achievement," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 941-954.
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