(2023):
Intersectional inequalities in academic achievement in primary and secondary education from a cross-country perspective.
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Led by the University of Luxembourg, the PIONEERED project brought together a team of researchers from across Europe to delve into the complexities of educational (in-)equality across various contexts. This collaborative effort aimed to understand the factors shaping access to and participation in education, while acknowledging the multifaceted nature of inequalities and the need for tailored solutions.
The partner institutions, including the MZES, followed a multi-phase approach, reviewing existing research, analysing policies, and assessing educational inequality across the participating countries. Through several work packages, they identified effective policies and practices based on evidence from policy reports, research publications, and key stakeholders involved in the policy or practice implementation. This work culminated in a comprehensive database of educational policies, a valuable resource for future research and policy development.
In one work package, we examined how educational inequalities vary across stages of the education system (primary, secondary, and tertiary) and between countries. Focussing on intersectional inequalities by migration background, gender, and socioeconomic status (SES) in reading and mathematics, we analysed data from PIRLS 2016, TIMSS 2019, and PISA 2015 and 2018. Our findings revealed significant intersectional disparities that vary by country and increase at the secondary level. In mathematics, intersectional inequalities are more linked to gender, while in reading, having a migration background plays a larger role. Using a two-step multilevel approach, we found greater scholastic gaps at the secondary level that are linked to tracking, nuanced effects of government spending on high-SES immigrant students at the primary level, and better performance among migrants in countries with a high proportion of high-SES immigrants.
Our team also examined the often-overlooked aspect of participation in shadow education (SE). Using TIMSS 2019 and PISA 2012 data from European countries, we explored how social background, gender, and migration status influence participation in mathematics SE. The findings reveal that at the primary level, migrant girls from socioeconomically disadvantaged families are most likely to participate in SE, while native boys from advantaged backgrounds are least likely. At the secondary level, migrant girls show the highest SE participation rates across all socioeconomic backgrounds. Our research challenges the view that SE is primarily driven by high socioeconomic status, highlighting unique participation patterns among migrant girls.