GE.GAP-EDU · Gender gap in students’ achievement: the role of social, economic, geographical and cultural variables
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2018-03-01 → 2020-08-29
- EU contribution
- €183,455
- Participants
- 1
- Scheme
- MSCA-IF-EF-ST
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Results in brief
Gender gap in students’ achievement: the role of social, economic, geographical and cultural variables
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).
Data: CORDIS, © European Union
Project objective
The study of academic achievement as function of ‘gender’ has received an increasing interest. Nevertheless, this topic seems still topical, at least for the following reasons: until now, some explanatory variables have been picked out but, probably, further unexplored factors exist; 2) the relationship between those factors has not been disclosed yet, i.e. it is not clear if interaction effects between them exist. In particular, the sectorial literature has investigated gender-related stereotypes’ effects on academic achievement but it has not studied possible interactions between stereotypes and the other variables frequently used to study students’ performance; 3) the inter-national comparison is undoubtedly an adequate method to deepen the study of gender-based gap. Nevertheless, the big international research institutes use national data, and it is clear that, when we use big data (such as national ones), almost automatically, some dangerous compensations occur, leading data to a false medium value. Our approach based also on the intra-national comparison is able to avoid those compensations. In fact, the comparisons between macro-geographical clusters produce better data, i.e. data that reproduce the reality more realistically, with three main consequences: 1) to improve the probability of picking out factors that can explain academic achievement depend on gender variable; 2) to guide local (inter-/national) policies; 3) to produce new data that can be used in future researches. Moreover, also the cross-national comparison (between macro-geographical areas within different Countries) could produce new important data because, through it, some possible “regularities” across different Countries can be disclosed, such as, for example, the same interaction effect between stereotypes and social-economic variables, etc. It could be an interesting headway in the field because it could indicate results that are true independently from specific context.
Original text from CORDIS.
Participants
- THE UNIVERSITY OF MANCHESTER · ManchesterCoordinatorUnited Kingdom
Links
Data: CORDIS, © European Union