Participation in higher education: A geodemographic perspective on the potential for further expansion in student numbers

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Higher education in England has expanded rapidly in the last ten years with the result that currently more than 30 per cent of young people go on to university. Terms of use: Documents in EconStor may

Geodemographics and spatial interaction: an integrated model for higher education

“…The origin estimates for the spatial interaction model therefore comprised 150 * 7 variables (1,050). This additional disaggregation of the supply population by OAC aims to capture heterogeneity in HE participation behaviours, which are known to stratify geodemographic clusters (see Batey et al 1999;Singleton 2010). The demand capacity for each (university) destination in the model was estimated from the HESA data as the sum frequency of students with English domicile within each HE institution.…”

“…There is currently considerable interest in the use of these classifications in public sector service delivery applications. This ''renaissance of geodemographics'' (Longley 2005) includes examples from policing (Ashby and Longley 2005), health (Aveyard et al 2002) and education (Batey et al 1999;Singleton 2010;Tonks and Farr 2003).…”

“…Our motivation for this work is that, despite a growth in the absolute numbers of students attending HE over recent years, differentials in the rates of participation between societal groups have remained persistently uneven (Comptroller and Auditor General 2008). Within the geography and GIS literature, inequality in HE access has been examined separately using both spatial interaction (Wilson 2000) and geodemographic approaches (Batey et al 1999;Singleton 2010). However, hitherto, there has not been a unified framework within which the relative benefits of both traditions can be maximised.…”

Data mining course choice sets and behaviours for target marketing of higher education

“…Geodemographic classifi cations link to applicants using their home address, and assign labels and descriptions that represent the aggregate characteristics of the neighbourhood in which they live. Although used prevalently in the commercial sector, 47,48 these types of classifi cation have only recently experienced a renaissance for public sector service delivery, 49 with demonstrated applications in education, 9,25 health, 50 local government 51 and policing. 52 The geodemographic classifi cation used for this analysis is the free National Statistics Output Area Classifi cation (OAC).…”

“…Knowledge of differences in HE participation rates between societal groups has a lengthy history, 15 -18 and a comprehensive review of those changes in policy that have aimed to support a more egalitarian system can be seen elsewhere. 19,20 HE participation has been shown to stratify across a variety of segments, including ethnicity, 21,22 gender and social class, 23,24 neighbourhood type, 25,26 parental education 27 and schooling. 28 However, despite this extensive research and signifi cant government funding interventions, a recent National Audit Offi ce report highlights that some groups still remain signifi cantly under-represented.…”