The issue of segregation in education can be (and has been) examined from both the individual level (e.g., parent surveys, choice analysis, etc.) or from macro-level statistics (e.g., changes in segregation level, region, city or national level). The uniqueness of a complexity science approach is the ability to connect these two levels and perhaps demonstrate that seemingly innocuous changes in individual behaviour or societal context can lead to drastic change in macro level dynamics. To be specific, by a complex systems approach we intend a combination of theoretical agent-based modelling of school choice dynamics, coupled with empirical spatial data and school choice data, both to calibrate and to test model outcomes.

The proposed research aims to uncover the dynamics of school choice and resulting patterns of school segregation by assuming a multi-dimensional approach to segregation. The research consists of two parts: The first will particularly look into patterns and trends of segregation that lie at the different intersections of class and ethnicity, with a special focus on differences within highly educated groups and of intersections of migrational background, income and educational attainment. This will lead to new multi-dimensional measures (macro) of segregation which can be used to assess current segregation and also assess the validity of the model (see below).

The second part of the research will develop an agent-based model of school choice and school allocation that will enable us to study how potential disruptions (policy interventions, demographic scenarios) affect choice and resulting patterns of school segregation. This model will focus on how parental choice and school allocation mechanisms (centralised vs. non-centralised) impact the level of segregation in different neighbourhoods. With a validated model the inspectorate will be able to test potential policies and assess their relative impact on segregation.