Undermatch in higher education: prevalence, drivers and outcomes
It is widely known that there are substantial socio-economic gaps in students’ likelihood of attending higher education. However, we also know that students from disadvantaged backgrounds are less likely to attend a high status university than their richer counterparts, even when they have similar A level grades. This has important implications for disadvantaged students’ future earnings and employment prospects, and hence for equity and social mobility.
This project will produce the first UK-based research on this so-called phenomenon of ‘undermatch’ – where a student’s academic credentials would allow them to access a university that is more selective than the one they actually attend. Evidence suggests that this is a significant issue in the US, with over 40% of students undermatching in their post-secondary choice. However, we have little idea of the scale of the issue in the UK.
The project also aims to advance the international literature on the topic by introducing a novel new approach to estimating undermatch, highlighting the likely biases in existing methods.
The researchers will use linked administrative data and the new Next Steps longitudinal survey to document the extent of undermatch. They will explore which types of students are most likely to undermatch, according to their socio-economic status, characteristics, subject studied and school attended. They will also consider the potential implications for undermatch of the use of predicted rather than actual A-level grades in the university application process, by using AS-levels as a proxy for predicted grades.
Finally, the researchers will document the association between undermatch and future outcomes. This will allow them to investigate whether students who undermatch are less likely to achieve a good degree, and whether they underperform in the labour market.
Overall, this project aims to make a substantial contribution to our understanding of access and entry to higher education.
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