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Analysing Differential School Effectiveness Through Multilevel and Agent-Based Modelling

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Abstract

During the last thirty years education researchers have developed models for judging the comparative performance of schools, in studies of what has become known as “differential school effectiveness†. A great deal of empirical research has been carried out to understand why differences between schools might emerge, with variable-based models being the preferred research tool. The use of more explanatory models such as agent-based models (ABM) has been limited. This paper describes an ABM that addresses this topic, using data from the London Educational Authority's Junior Project. To compare the results and performance with more traditional modelling techniques, the same data are also fitted to a multilevel model (MLM), one of the preferred variable-based models used in the field. The paper reports the results of both models and compares their performances in terms of predictive and explanatory power. Although the fitted MLM outperforms the proposed ABM, the latter still offers a reasonable fit and provides a causal mechanism to explain differences in the identified school performances that is absent in the MLM. Since MLM and ABM stress different aspects, rather than conflicting they are compatible methods.

Suggested Citation

  • Mauricio Salgado & Elio Marchione & Nigel Gilbert, 2014. "Analysing Differential School Effectiveness Through Multilevel and Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(4), pages 1-3.
  • Handle: RePEc:jas:jasssj:2013-116-2
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    1. Jacob M. Markman & Eric A. Hanushek & John F. Kain & Steven G. Rivkin, 2003. "Does peer ability affect student achievement?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(5), pages 527-544.
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    Cited by:

    1. Matt Kasman & Brynle Owen & Joshua Hayward, 2017. "A Community-based Complex Systems Approach to High School Completion," Systems Research and Behavioral Science, Wiley Blackwell, vol. 34(3), pages 267-276, May.
    2. Clémentine Cottineau, 2022. "Modéliser les inégalités dans l’espace géographique," Post-Print halshs-03801388, HAL.

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