Economic inequality and student achievement in reading, mathematics, and science across OECD countries
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In this study, the associations of socioeconomic variables with reading test scores in grade 4 (PIRLS) and with math and science test scores in grades 4 and 8 (TIMSS) were examined across 28 OECD countries. This study adds to the current knowledge base by integrating measures of income inequality, which have been used in a few studies involving test scores, with other socioeconomic variables of interest. Bivariate correlations show that certain socioeconomic measures have stronger relationships with test score inequality than with average test scores: income inequality, gender inequality, and adolescent fertility rates all have significant relationships with test score inequality in reading, math, and science. There are also strong intercorrelations among these three socioeconomic variables. Income inequality is significantly associated with average science test scores in grades 4 and 8, while adolescent fertility rates hold significant relationships with average math and science test scores in both grades. Intercorrelations among the variables show that people who live in a country with high income inequality, and are at the lower end of that country’s income distribution, struggle in ways that people in countries with low income inequality do not. Health insurance and access to health care, paid maternity leave, and preschool education are easier to obtain in countries with lower income inequality. Examination of individual countries gives additional insight into the important role of income inequality. Slovenia, for example, has a relatively low GDP per capita but enjoys good test scores, perhaps because of its low income inequality. Finland, another country with low income inequality, attains PIRLS and TIMSS test scores that are among the highest in the world, in part because of social services that have the effect of further reducing income inequality. The U.S. is something of a puzzle because it has relatively high scores despite substantial inequality. Based on the results of this study and other current research, it seems likely that the U.S. could reduce test score inequality by providing targeted supports to low-income families, effectively reducing income inequality. Such supports may include: 1) installing wraparound services within school settings for low-income families; and 2) substantially expanding preschool access, especially among 3-year-olds.