In defence of targeting? The Open University's Community Partnerships Programme

Allen, Meg

doi:10.5456/wpll.12.s.138

Cited by 1 publication

(2 citation statements)

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“…The parental education level is frequently examined, whether in relation to more educated parents seeking to gain educational advantage (Chesters, 2015 ), particularly through choosing schools outside their immediate locale (Allen, 2010 ; Rees et al, 2007 ; Warrington, 2005 ), or to determine its effect on educational attainment of their children (Cigan, 2014 ; Marcenaro-Gutierrez et al, 2007 ; Nguyen, 2016 ). A related variable often explored is the type of school attended with Manley and Johnston ( 2014 ) demonstrating that schools such as grammar schools that select pupils bases on academic ability perform better than both comprehensive and secondary modern schools who in turn outperform 6th form colleges.…”

Section: Methodsmentioning

confidence: 99%

“…Closely related to the questions around homogeneity is the modifiable areal unit problem (MAUP), as boundaries such as the MSOA are artificially created to support data collection and/or administrative tasks rather than reflecting real life (Harrison & Hatt, 2010 ; Harrison & McCaig, 2015 ; Singleton, 2010 ). As noted by Burrows and Bradshaw ( 2001 , p.1347) “Wards are not neighbourhoods”, and as a consequence no matter what dataset, scale, or boundaries are used for targeting “all are flawed in some way” (Allen, 2010 , p.140).…”

Section: Introductionmentioning

confidence: 99%

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Creating a Composite Index to Target Recruitment of UK Students from Areas of Low Participation in Higher Education

Bell

Burns

2021

Appl. Spatial Analysis

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This research presents a framework through which a new Higher Education Access and Deprivation (HEAD) composite index was created to assist UK universities in efficiently recruiting and supporting students from areas with traditionally low engagement rates in higher education. The index was designed to be easily adaptable by university staff to suit their own work priorities and/or an institution’s strategic requirements by utilising open socio-demographic data and construction techniques that require minimal technical statistical skills. Although Cornwall was used as the study area in this research, this index has been designed such that it can be readily applied elsewhere. Two differently weighted models were created using the framework – one with equal weights and the other based on the frequency the constituent indicators appeared in the reviewed academic literature. Both models were mapped across Cornwall, identifying areas of deprivation at a finer resolution than under the current widely used Participation of Local Areas (POLAR) methodology. The weighted model performed marginally better than both the equal weighted model and the current POLAR methodology when validated against external data, and additionally it worked well in both rural and urban environments leading to it being selected as the new HEAD index. The HEAD index maps smaller scale areas of deprivation than previously available, and by enabling users to investigate the underlying socio-demographic characteristics of an area, it also allows universities to create interventions, support, and policies that best targets the students they aim to recruit and teach.

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