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Aspiration, Attainment and Success: An Agent-Based Model of Distance-Based School Allocation

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Abstract

In recent years, UK governments have implemented policies that emphasise the ability of parents to choose which school they wish their child to attend. Inherently spatial school-place allocation rules in many areas have produced a geography of inequality between parents that succeed and fail to get their child into preferred schools based upon where they live. We present an agent-based simulation model developed to investigate the implications of distance-based school-place allocation policies. We show how a simple, abstract model can generate patterns of school popularity, performance and spatial distribution of pupils which are similar to those observed in local education authorities in London, UK. The model represents ‘school’ and ‘parent’ agents. Parental ‘aspiration’ to send their child to the best performing school (as opposed to other criteria) is a primary parent agent attribute in the model. This aspiration attribute is used as a means to constrain the location and movement of parent agents within the modelled environment. Results indicate that these location and movement constraints are needed to generate empirical patterns, and that patterns are generated most closely and consistently when schools agents differ in their ability to increase pupil attainment. Analysis of model output for simulations using these mechanisms shows how parent agents with above-average " but not very high " aspiration fail to get their child a place at their preferred school more frequently than other parent agents. We highlight the kinds of alternative school-place allocation rules and education system policies the model can be used to investigate.

Suggested Citation

  • James Millington & Tim Butler & Chris Hamnett, 2014. "Aspiration, Attainment and Success: An Agent-Based Model of Distance-Based School Allocation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(1), pages 1-10.
  • Handle: RePEc:jas:jasssj:2012-132-2
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    Cited by:

    1. Connie H. Wang & Bin-Tzong Chie & Shu-Heng Chen, 2017. "Transitional student admission mechanism from tracking to mixing: an agent-based policy analysis," Evolutionary and Institutional Economics Review, Springer, vol. 14(1), pages 253-293, June.
    2. Shu-Heng Chen & Connie Houning Wang & Weikai Chen, 2017. "Matching Impacts of School Admission Mechanisms: An Agent-Based Approach," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(2), pages 217-241, March.

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