Abstract
ABSTRACT A hallmark of English higher education (HE) over the last twenty years has been policies seeking to increase provider competition and student choice. Central to this has been student funding policy changes, leading to rising college costs. This article asks if prospective HE students’ concerns about college costs and the financial strategies they anticipate using because of them, widen or limit their choice of HE institution and subject of study. It calls on the findings from a nationally representative survey of 1,374 English college applicants and uses latent class analysis to develop a typology of students’ planned financial coping mechanisms: Minimizing costs; Managing costs and maximizing returns; and No financial concerns; which prove to be socially stratified. Minimizing costs students are the most disadvantaged and adopt mechanisms which constrain their choices of where and what to study, unlike students in the other groups. Thus, government policies aimed at improving student choice potentially have the opposite effect for the most disadvantaged, perpetuating existing inequalities in access to, and the experience of, HE.
Highlights
Recent higher education (HE) policies in England have sought to promote student choice and provider competition. Central to this are cost-sharing policies, especially higher tuition repaid via student loans, which transfer more of the costs of HE from government to students
We develop a typology of students’ financial coping mechanisms based on their anticipated actions aimed at minimizing, managing, and maximizing their HE study costs and derived from students’ answers to a survey question about what they planned to do because of the costs
Latent class analysis (LCA) estimates two parameters: a) the probability of a particular observed response l conditional on latent class membership; b) the probability of being in a specific latent class k (Finch & Bronk, 2011) In Mplus v8.3, which we used, the estimation of these parameters is done through Maximum like lihood estimation (MLE) via the Estimation-Maximization algorithm, and model fit is assessed through the adjusted Bayesian Information Criterion, the Akaike Information Criterion, the Log-likelihood test, and the boot strapped Lo-Mendel-Rubin adjusted Log-likelihood ratio test’s (LRT) p-value for k-1 classes(Nylund et al, 2007)
Summary
Recent higher education (HE) policies in England have sought to promote student choice and provider competition Central to this are cost-sharing policies, especially higher tuition repaid via student loans, which transfer more of the costs of HE from government to students. These policies are intended to empower students to make better choices, and to motivate institu tions to address student concerns because they are a revenue source (Callender & Dougherty, 2018). These policies have led to rising college costs and student loan debt. It assesses how these can influence students’ choice of HE institution and subject of study, by developing a typology of the
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