A new mathematical model helps European regions set suitable targets to close gender gaps in education

(Press-News.org) The gender gap in education doesn’t always disadvantage women. In countries like Estonia, Iceland, or Sweden, women outperform men in key indicators such as tertiary education and lifelong learning. But that, too, is a gender gap. That’s the starting point for researchers at the Miguel Hernández University of Elche (UMH), who have developed a mathematical model to support European education authorities in improving performance and reducing gender disparities, regardless of which group is underperforming.

“In many European countries, women outperform men at every educational level. If we’re serious about equality, we must also address these differences,” explains Inmaculada Sirvent, professor of Statistics and Operations Research at UMH and co-author of the study.

Published in Socio-Economic Planning Sciences, the study analyzes four key indicators used by the European Commission to track access to knowledge: tertiary attainment, adult participation in learning, early leavers from education and training, and the share of young people not in employment, education, or training (NEETs).

One of the study’s most striking findings is that, on average, women outperform men in three of the four indicators. The most significant gap concerns tertiary attainment: 38.5% of women in Europe have completed tertiary education, compared to 32% of men. “This imbalance, even if favorable to women, is still a gender gap—and one the education system can and should help close,” says Sirvent.

Using data from 93 European regions, the model provides tailored improvement targets for each region based on two simultaneous goals: getting closer to best practices and reducing gender disparities for each indicator.

“This bi-objetive approach is the key innovation in our work,” says Sirvent. The model allows decision-makers to prioritize different strategies: for instance, setting closer targets as the result of benchmarking against the most similar peers (even if gender gaps persist), or choosing more ambitious, gender-balanced targets that may require a greater effort.

The methodology is based on Data Envelopment Analysis (DEA), a widely used tool for assessing the relative efficiency of comparable units, such as hospitals, schools, or regions, based on their inputs and outputs. In this case, DEA is adapted to suggest customized educational targets that both improve performance and close gender gaps.

“One of the most striking examples is Estonia, where 54% of women have completed tertiary education, compared to just 31% of men,” notes José L. Ruiz, UMH professor of Statistics and Operations Research and co-author of the study. “Our model shows that Estonia could reduce this gap without significantly burdening its education system.” Similar patterns are seen in Iceland and several regions of Poland, Finland, and Spain. In contrast, some areas of Germany, Switzerland, and Austria still show gender gaps favoring men.

The study is also notable for being the first to apply DEA at a subnational level in the European education context and for incorporating gender equality as a key optimization objective in policy planning.

Sirvent and Ruiz, both affiliated with UMH’s Institute for Operations Research, collaborated with Dovilė Stumbrienė of Vilnius University’s Faculty of Philosophy, who led the research.

Among the study’s limitations, the authors cite the lack of more granular territorial data and the absence of relevant social variables such as socioeconomic background, cultural context, or ethnic diversity. They also note that the indicators used measure educational outcomes but not necessarily access opportunities or conditions within the education system.

The study was funded by the Spanish Ministry of Science and Innovation (PID2021-122344NB-I00), the Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana (PROMETEO/2021/063), and the Research Council of Lithuania (agreement S-PD-22-87).

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