Mathematics Achievement in Secondary Education

A user seeks to investigate whether migration background is associated with differences in mathematics achievement among secondary education students in Hungary using the STRIDE map.

Use Case 1 with evidence from Hungary

User Task

A user seeks to investigate whether migration background is associated with differences in mathematics achievement among secondary education students in Hungary using the STRIDE map. The platform provides access to comparative data on student performance across countries and population groups, enabling the exploration of disparities linked to demographic characteristics.

Step 1: Identifying subgroup differences

According to the visualization, students in Hungary generally perform differently depending on migration background, but the pattern is not consistent over time. While in most years students without a migration background outperform those with a migration background, this relationship is reversed in 2015 and 2023 when students with a migration background achieve higher average mathematics scores.

The longitudinal trend shows that the performance of students with a migration background is more volatile, with a sharp decline in earlier years followed by a marked increase around 2015, and subsequent fluctuations. In contrast, students without a migration background exhibit a more stable trajectory over time. By the most recent year, the difference between the two groups appears relatively small, suggesting partial convergence despite earlier disparities.

Step 2: Cross-Country Comparison

The user expands the view to include multiple countries by examining the bar chart. The system enables comparison of Hungary with countries such as Austria, Finland and Sweden, where migration-related differences in mathematics performance appear more pronounced, as well as with countries such as Ireland, Cyprus and Malta, where the gap between groups is smaller.

This comparison allows the user to assess how the magnitude of inequalities associated with migration background varies across national contexts. Hungary appears to fall in an intermediate position, with a small disparity compared to other countries for 2023.

Step 3: Linking Inequality Patterns to Reforms

The system overlays reforms occurring in the same period and the respective educational level aligned with the timeline. The user can click on the reform lines to access details-on-demand (e.g., policy aim, coverage, etc.)

By examining the timeline, the user identifies several reforms in Hungary during the observed period, including the Conditionality of family allowance upon school attendance (2010), the Centralisation of the school system (2012), and the Introduction of State-funded study halls (2019). These reforms are displayed alongside the evolution of mathematics performance for students with and without a migration background.

While the timeline enables the user to visually align reforms with changes in performance trends, the platform does not provide evidence to establish any causal relationship between these reforms and the observed differences in mathematics achievement. Moreover, based on the available reform descriptions, these policies primarily focus on reducing early school leaving, improving system-wide equity, and supporting disadvantaged students more broadly, rather than explicitly targeting students with a migration background

Click the image to watch the study in the Interactive Map.

This case study is written by: Interactive Map Support Team

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