The higher education space

connecting degree programs from individuals’ choices

Research output: Contribution to journalArticle

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.

Original languageEnglish
Article number39
JournalEPJ Data Science
Volume8
Issue number1
DOIs
Publication statusPublished - 1 Dec 2019

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Higher Education
Education
Revealed Preference
Governance
Unemployment
Drop out
Network Structure
Decision making
Decision Making
Entire
Tend

Keywords

  • Computational social sciences
  • Higher education systems
  • Network science

Cite this

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title = "The higher education space: connecting degree programs from individuals’ choices",
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.",
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The higher education space : connecting degree programs from individuals’ choices. / Candia, Cristian; Encarnação, Sara; Pinheiro, Flávio L.

In: EPJ Data Science, Vol. 8, No. 1, 39, 01.12.2019.

Research output: Contribution to journalArticle

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AU - Candia, Cristian

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