Abstract:
All schools operate in an educational context, which means broadly a structure that is determined by the local Education Department or Authority that, amongst others, supplies resources for improvement processes and sets educational goals (Creemers, 2007). Beyond this, each school has an individual school context which relates mostly to the local community and the potential student intake and hence, the locally available cultural capital of students (Bourdieu, 1977).
This study aims to group schools to school clusters within which more transition activity occurs compared to adjacent school clusters (so-called school markets). A stochastic network approach is used to define the boundaries of school markets based on student transitions (Krivitsky & Handcock, 2008). This approach is different from other approaches more commonly used to group schools to school markets according to administrative boundaries, or areas of responsibility of municipal authorities, or based on the location of schools in space by taking into account travel costs (time or distance) between place of residence and school location.
Exemplary analysis was conducted for the German metropolis Hamburg where approximately 200,000 students attend school. Data modelling is based on student register data of Hamburg’s Department of Education and covers all student transitions in the summer of 2014 from primary schools to secondary schools, and includes all school types and all educational sectors. Using this approach, 14 school markets were unveiled.
Relying on transition data has the benefit of reflecting the reality of student movement and is not based on artificial boundaries which may lead to arbitrary findings. Applying this methodology enables identification and monitoring of social stratification and segregation between and within school markets during the school choice process. In particular, the role of place, school type and school sector can be taken into account. Furthermore, the local appropriateness of provided school types and the impact of curricular (e.g. languages) and extracurricular activities (e.g. Student Exchange Programs, Choir/Music Bands, Sport Teams) of schools on school choice behaviour could be examined. Such findings in turn could provide a lever to address the risk of the formation of so-called ghetto-schools that are likely to occur in environments where open school choice policies are promoted.
These insights may facilitate further research into the influence of contextual factors, which locally impact school choice behaviours and which might be amenable to a school’s administrative staff to achieve educational goals, while overcoming the trade-off between social inclusion and improving academic performance.
This study aims to group schools to school clusters within which more transition activity occurs compared to adjacent school clusters (so-called school markets). A stochastic network approach is used to define the boundaries of school markets based on student transitions (Krivitsky & Handcock, 2008). This approach is different from other approaches more commonly used to group schools to school markets according to administrative boundaries, or areas of responsibility of municipal authorities, or based on the location of schools in space by taking into account travel costs (time or distance) between place of residence and school location.
Exemplary analysis was conducted for the German metropolis Hamburg where approximately 200,000 students attend school. Data modelling is based on student register data of Hamburg’s Department of Education and covers all student transitions in the summer of 2014 from primary schools to secondary schools, and includes all school types and all educational sectors. Using this approach, 14 school markets were unveiled.
Relying on transition data has the benefit of reflecting the reality of student movement and is not based on artificial boundaries which may lead to arbitrary findings. Applying this methodology enables identification and monitoring of social stratification and segregation between and within school markets during the school choice process. In particular, the role of place, school type and school sector can be taken into account. Furthermore, the local appropriateness of provided school types and the impact of curricular (e.g. languages) and extracurricular activities (e.g. Student Exchange Programs, Choir/Music Bands, Sport Teams) of schools on school choice behaviour could be examined. Such findings in turn could provide a lever to address the risk of the formation of so-called ghetto-schools that are likely to occur in environments where open school choice policies are promoted.
These insights may facilitate further research into the influence of contextual factors, which locally impact school choice behaviours and which might be amenable to a school’s administrative staff to achieve educational goals, while overcoming the trade-off between social inclusion and improving academic performance.