Abstract:

Immigration rates are continuously increasing in Europe, and more and more immigrant students have access to the education systems of the host countries. Normally, the share of immigrant students in the total population is higher in developed countries, where opportunities are more abundant. Ensuring equity of educational opportunities within an educational system, despite the heterogeneity of the students in terms of origin and background, has always been among the main aims of policy makers. According to reports of the Organisation for Economic Co-operation and Development (OECD), across OECD countries in 2003 non-immigrant students scored 47 points higher in mathematics than immigrant students; by 2012 that performance difference had shrunk by around 10 score points with immigrant and non-immigrant students scoring equally in several countries. Recent studies also reveal that a factor related to the low performance of immigrant students with respect to natives is a less favourable family background, emphasising the effects of institutions and education policies of the host countries on students’ performance. Therefore, focusing on countries with high percentages of immigrants in their population, traditionally higher than the OECD average across the Programme for International Student Assessment (PISA) cycles, would provide a meaningful insight into how these differences have been formed.
The aim of this study is to provide an in-depth examination of the differences between immigrants and natives in terms of their mathematics performance. Four European countries [Sweden, Denmark, Germany and Belgium (Flemish)] with similarly oriented educational systems, demonstrating common characteristics in terms of their long-lasting high concentrations of immigrant students are investigated. The sample consisted of 22,095 15-year-old students who participated in PISA 2012. The study considers the extent to which students’ immigration status and the language spoken at home contribute to the prediction of their mathematics performance, after controlling for students’ socio-economic status.
For the purposes of the statistical analysis, a three-level multilevel model (1st student, 2nd school, 3rd country) was applied to take into account the clustered nature of the data by inputting variables in more than one levels, acknowledging the fact that students in the PISA sample are nested within schools and only a specific amount of schools are selected in each country. The multilevel model revealed that students’ immigration status and the language spoken at home were statistically significant predictors of their mathematics achievement, even after controlling for their socioeconomic status, which was also statistically significantly related to mathematics performance.
The findings indicated that, although the performance gap between immigrants and native students has significantly decreased over the last years, it still remains an issue, even for traditional immigrant-receiving European countries with high rates of immigrant students. The issue that arises here is how to best support immigrant students who face the multiple disadvantage of socioeconomic deprivation, low education standards in their countries of origin and cultural and language adjustment to the host countries. This is a topic that should draw the attention of policy makers both at national and international level.

Keywords:

Immigrant students, Mathematics achievement, PISA, Multilevel modelling.