Commuting to School: A New Spatial Interaction Modelling Framework for the Education Sector

The education sector in England and Wales is becoming increasingly data rich, with the regular collection of the Pupil Level Annual School Census (PLASC) and school preference information, together with the compilation of school performance league tables. However, it is also a rapidly changing environment both in terms of demographic demand as well as policy responses from Government. The latest policy documents require that local education authorities provide fair and equitable admissions policies for all, while at the same time limiting the number of surplus school places. Moreover, funding has to be targeted appropriately in the face of significant changes in the complexion and number of state educated school pupils. Therefore, it is crucial for education planners to be able to interpret the large quantities of data collected each year into valuable intelligence to support planning and decision making. This chapter explores the use of classic spatial interaction models with journey to school data for the purpose of school network planning for the city of Leeds. The limitations associated with the application of spatial interaction models in the education sector will be discussed, and modifications to the computational form will be explored using a genetic algorithm. Spatial interaction models representing pupils from different socio-demographic backgrounds will be calibrated and incorporated into an overarching logic model called the Spatial Education Model (SEM). Finally, the SEM will be used to forecast pupil numbers attending schools in the study area up to the year 2013. DOI: 10.4018/978-1-61520-755-8.ch016