The higher education space: connecting degree programs from individuals’ choices
Date
2019
Type:
Article
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17 p.
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Abstract
Data on the applicants’ revealed preferences when entering higher education is used
as a proxy to build the Higher Education Space (HES) of Portugal (2008–2015) and
Chile (2006–2017). The HES is a network that connects pairs of degree programs according to their co-occurrence in the applicants’ preferences. We show that both
HES network structures reveal the existence of positive assortment in features such as
gender balance, application scores, unemployment levels, academic demand/supply
ratio, geographical mobility, and first-year drop-out rates. For instance, if a degree
program exhibits a high prevalence of female candidates, its nearest degree programs
in the HES will also tend to exhibit a higher prevalence when compared to the
prevalence in the entire system. These patterns extend up to two or three links of
separation, vanishing, or inverting for increasing distances. Moreover, we show that
for demand/supply ratio and application scores a similar pattern occurs for time
variations. Finally, we provide evidence that information embedded in the HES is not
accessible by merely considering the features of degree programs independently.
These findings contribute to a better understanding of the higher education systems
at revealing and leveraging its non-trivial underlying organizing principles. To the best
of our knowledge, this is the first network science approach for improving decision-making and governance in higher education systems.
Description
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Citation
EPJ Data Science. 8, 39 (2019).
Keywords
Higher education systems, Network science, Computational social sciences