Periodic Reporting for period 1 - GE.GAP-EDU (Gender gap in students’ achievement: the role of social, economic, geographical and cultural variables)
Berichtszeitraum: 2018-03-01 bis 2020-02-29
Mathematical competence is a key competence, considered necessary for personal development and fulfillment. Educational stratification precedes later social stratifications, and inequality of social opportunities is strongly related to inequality of educational opportunities. Therefore, exploring factors affecting inequalities in learning math is a priority for an equitable educational policy agenda.
The study of gender differences in math has received increasing attention over time but the literature is not yet conclusive and, to some extent, even contradictory across cultures and geographies. In fact, gender differences vary by country, with sharp variations, for example, among European countries: on average, girls living in the North of the EU perform better than boys in all subjects, whereas girls living in the South underperform boys in scientific subjects. Such evidence supports the hypothesis that gender differences in math are mainly related to the (sociocultural and economic) context and where students live rather than individual, or genetic differences. But precisely how culture and geography are significant is still an open question.
We contribute to this knowledge gap by exploring the association between differences in students’ achievement and the gendered, sociocultural places students’ experience, at both national and regional levels.
The study of gender differences at regional level is not new in the literature but previous studies have used a number of different tools to measure sociocultural environmental factors, and thus comparability of results across such studies is limited. In our study, we developed and validated a new measure to capture and synthesize sociocultural factors (and in particular people’s perceptions’ of gendered roles) we showed to be related to gender differences in math. The use of the same tool in different countries and regions enables valid comparisons and allowed us to draw an updated map of educational inequalities at different levels of locality in Europe.
This measure enabled us to further evaluate the association between gender differences in math and gender attitudes at different cultural locations, with clear implications for policy-makers (as educational policy needs to explicitly account for sociocultural locales in order to be effective); practitioners (as they need to be aware of the strength of the association between local sociocultural factors and students’ learning outcomes); and, educational and social research (with the new, updated and replicable measures validated across all European countries and regions enabling comparability of results across cultures and geographies and thus contributing to understandings of educational inequality).
The study of gender differences in math has received increasing attention over time but the literature is not yet conclusive and, to some extent, even contradictory across cultures and geographies. In fact, gender differences vary by country, with sharp variations, for example, among European countries: on average, girls living in the North of the EU perform better than boys in all subjects, whereas girls living in the South underperform boys in scientific subjects. Such evidence supports the hypothesis that gender differences in math are mainly related to the (sociocultural and economic) context and where students live rather than individual, or genetic differences. But precisely how culture and geography are significant is still an open question.
We contribute to this knowledge gap by exploring the association between differences in students’ achievement and the gendered, sociocultural places students’ experience, at both national and regional levels.
The study of gender differences at regional level is not new in the literature but previous studies have used a number of different tools to measure sociocultural environmental factors, and thus comparability of results across such studies is limited. In our study, we developed and validated a new measure to capture and synthesize sociocultural factors (and in particular people’s perceptions’ of gendered roles) we showed to be related to gender differences in math. The use of the same tool in different countries and regions enables valid comparisons and allowed us to draw an updated map of educational inequalities at different levels of locality in Europe.
This measure enabled us to further evaluate the association between gender differences in math and gender attitudes at different cultural locations, with clear implications for policy-makers (as educational policy needs to explicitly account for sociocultural locales in order to be effective); practitioners (as they need to be aware of the strength of the association between local sociocultural factors and students’ learning outcomes); and, educational and social research (with the new, updated and replicable measures validated across all European countries and regions enabling comparability of results across cultures and geographies and thus contributing to understandings of educational inequality).
We used data collected by the European Values Survey (EVS - statistically representative both at national and at different levels of regionality) to validate a new gender attitudes measure across all European countries including items not previously used for such measures (e.g. perceptions of single motherhood, conceived as a woman’s elective choice). By using a new combination of items, we managed to capture meanings of masculinity and femininity in different cultures, across European countries comparatively but also within each of them at different levels of regionality. Then, we explored the association between gender attitudes and gender differences in math (measured via OECD-PISA data) across all European countries and regions by employing multilevel regression analysis.
Results from our analyses showed that gender attitudes sharply vary by country and region, and that such sub-national variation is often larger than that between countries. This confirmed well-established perceptions (e.g. people living in southern Italy show more traditional gender attitudes than those living in the North), but also demonstrated huge variability of gender attitudes in countries like Finland, one of the most gender equal countries in Europe when the ranking is based on national aggregates.
Our results, also confirmed our main hypothesis that gender differences in math are associated with the perceptions of gender and gendered roles in the locality, and in particular that gender differences in math attainment are greater in more traditional cultures (where women’s life is mainly focused on looking after home and children). The idea underlying such findings is well known: people’s attitudes towards gender shape students’ learner identity, and so their learning practices. In other words, living in more traditional places (where caring roles and private life is deemed more appropriate for women whereas participating in public life is deemed more appropriate for men), involves a culture that creates a contradiction between ‘female identity’ and ‘mathematics identity’. This can explain why girls may disengage from math and other scientific disciplines considered relevant for public life.
Finally, we developed a new, updated index to measure gender gaps in the key sectors of social life (economy, politics, health and education) and validated it at both national and regional level. We reviewed both the theoretical and methodological literature about gender (in)equality. Then we revised the set of indicators used to measure gender inequalities in order to account for the empowerment of women over time.
Results from our analyses showed that gender attitudes sharply vary by country and region, and that such sub-national variation is often larger than that between countries. This confirmed well-established perceptions (e.g. people living in southern Italy show more traditional gender attitudes than those living in the North), but also demonstrated huge variability of gender attitudes in countries like Finland, one of the most gender equal countries in Europe when the ranking is based on national aggregates.
Our results, also confirmed our main hypothesis that gender differences in math are associated with the perceptions of gender and gendered roles in the locality, and in particular that gender differences in math attainment are greater in more traditional cultures (where women’s life is mainly focused on looking after home and children). The idea underlying such findings is well known: people’s attitudes towards gender shape students’ learner identity, and so their learning practices. In other words, living in more traditional places (where caring roles and private life is deemed more appropriate for women whereas participating in public life is deemed more appropriate for men), involves a culture that creates a contradiction between ‘female identity’ and ‘mathematics identity’. This can explain why girls may disengage from math and other scientific disciplines considered relevant for public life.
Finally, we developed a new, updated index to measure gender gaps in the key sectors of social life (economy, politics, health and education) and validated it at both national and regional level. We reviewed both the theoretical and methodological literature about gender (in)equality. Then we revised the set of indicators used to measure gender inequalities in order to account for the empowerment of women over time.
Our contribution to the study of gender differences in math is two-fold: (i) by analyzing the most recent secondary educational data sets (collected in 2017 by OECD-PISA), we confirmed results from some previous studies claiming that sociocultural contextual factors impact learning outcomes by gender, and provided a measure of the association between them across European cultures comparatively; (ii) we developed a new, updated measure of gender attitudes and validated it across European countries and regions thus guaranteeing results comparability; (iii) we studied factors affecting gender differences in math at different levels of regionality and proved that looking at more local levels is necessary in order to understand the role of sociocultural contextual factors on gender differences and thus to properly inform educational policy and practice.
In addition, we developed a new index of gender gaps in the key sectors of social. Most of the previous indices have been developed to measure gender gaps in both industrialized and not industrialized countries, thus including a number of indicators (such as for example sex birth ratio or equal civil rights), more useful to capture gender inequality in some less industrialized countries than in the western world.
In addition, we developed a new index of gender gaps in the key sectors of social. Most of the previous indices have been developed to measure gender gaps in both industrialized and not industrialized countries, thus including a number of indicators (such as for example sex birth ratio or equal civil rights), more useful to capture gender inequality in some less industrialized countries than in the western world.