Data analysis indicates distance is a predictor of students’ intentions to attend university, net of selected demographic and socio-economic variables. This report applies statistical modelling and geo-mapping to existing data, contributing to current literature as well as indicating an ongoing advancement from discrete categorisation to continuous measures of students’ distance from higher education providers.
We know that geography matters in relation to participation in higher education. Both the 2008 Bradley Review (Commonwealth of Australia) and the 2010 Inquiry into the Extent and Nature of Disadvantage and Inequity in Rural and Regional Victoria (Victoria Parliament Rural and Regional Committee), observed that regional students were under-represented in higher education when compared to their urban peers. Indeed, data from the Department of Education Employment and Workplace Relations in 2010 shows that the participation rates of students from regional and remote areas actually deteriorated between 2005 and 2010.
While we know that geography is linked to disadvantage, we do not fully understand the processes through which this disadvantage arises. The reasons for the differences in participation highlighted in both the Bradley Review and the Victorian Parliamentary Inquiry varied pointing to a complexity of factors, operating in interconnected ways. Context is critical. For example, Alloway and Dalley-Trim reported that while youth living in rural areas were commonly interested in pursuing higher education following completion of secondary school, barriers to participation limited their propensity to act on this interest. The barriers include attachment to home, desire to remain close to family and friends and the cost of studying away from home. In a similar refrain, Marks et al. found attitudes, motivations and aspirations as important influences in the decision to attend university. These non-cognitive dispositions towards participating in university are developed and influenced by local social and cultural networks and values.
In part, the lower aspirations that are identified in some of the research as a barrier to participation could be a result of regional and remote students (and/or their teachers) understanding the difficulties they face attending higher education and, as a result, lowering their expectations of achievement. Whatever the case, the evidence is conclusive: students living in regional and remote areas perform less well in secondary education and, even after accounting for this lower success in school, they are less likely to progress to university than their metropolitan peers.
As noted above, one challenge in identifying the mechanisms through which this disadvantage develops is that the barriers to progression are likely to vary, and they are likely to change over time and space. In this respect, we know from research in vocational education in Australia that some groups of people suffer from multiple barriers to progression in education and the labour market. McVicar and Tabasso’s research addresses the accumulative effect of students from poorer backgrounds, and from regional areas, and a non-dominant ethnicity that helps explain their difficulties progressing in VET. James at al. and Parker et al. noted that similar observations apply to participation in higher education.
This report aims to assess if geographical location and other background factors linked to achievement (such as socio-economic status [SES]) predict students’ intentions to enrol in higher education.
The research attempts to answer two key questions:
- Is distance from a university, net of other factors, a predictor of students’ intentions to attend university?
- What are the implications of this study in relation to policies regarding the presence of regional universities in Australia?
The research involves two distinct phases of analysis. Phase One draws upon data gathered in a related project by Cooper and uses mapping software to create a continuous measure (e.g. kilometres) of students’ distance from a university as opposed to a relatively limited number of discrete categories (e.g. metropolitan, remote). Continuous measures may increase understanding of how factors, such as geographical location, impact participation and access to higher education. In Phase Two, we explore the same issue with the Longitudinal Surveys of Australian Youth (LSAY) data from the 2009 (Yr09) cohort (Department of Education and Training).
Key findings and recommendations
While factors are likely to be complex and interwoven, even when controlling for the effect of SES, this report finds geographical location to be a significant predictor of students’ intentions to study at university. These findings are consistent with other research, and highlight the ongoing importance of access to universities in regional and remote Australia.
Conclusions and considerations for policy
Access to services is a persistent challenge in regional and remote Australia, as smaller populations make it difficult to offer the range of services (e.g. healthcare, education) that are available in metropolitan areas. As a result, people either travel long distances to access such services or go without. Increased access to higher education in regional and remote Australia is one component of a multi-faceted approach to tackling the economic, information, class and geographical barriers that commonly impact students’ participation. Universities in regional and remote Australia are uniquely positioned to contribute to the economic, social, cultural fabric of their region. An important element of improved access includes a regional network of universities that offer a wide range of courses that appeal to students’ diverse desires and/or capabilities. Faced with ever tightening budgets, innovative solutions are urgently needed in order to improve access to university education for regional and remote Australia.
Within the ever growing area of geo-mapping techniques, researchers are encouraged to consider variables like the Nearest University Measure (NUM) used in this report. Continuous measures (e.g. kilometres), as opposed to discrete categories (e.g. metro, remote) may increase understanding of how factors, such as geographical location, may impact participation and access to education and other services. While the continuous measures used in Phase One did not significantly predict students’ intentions to enrol at university, the high risk of sample bias and a number of statistical issues prevented clear conclusions. Future research may apply the same techniques used in Phase One on a larger, more representative sample. An ever growing list of geo-mapping techniques and software is enabling new ways for researchers to report and analyse trends, correlations and possible relationships.