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While it has been shown that university attendance is strongly predicted by parental education, we know very little about why some potential 'first in family' or firstgeneration students make it to university and others do not. This paper looks at the role of non-cognitive skills in the university participation of this disadvantaged group in England. We find that conditional on national, high-stakes exam scores and various measures of socioeconomic background, having higher levels of non-cognitive skills, specifically locus of control, academic self-concept, work ethic, and self-esteem, in adolescence is positively related to intergenerational educational mobility to university. Our results indicate that having higher non-cognitive skills helps potential first in family university students to compensate for their relative disadvantage, and they are especially crucial for boys. The most important channel of this relationship seems to be through educational attainment at the end of compulsory schooling.

While it has been shown that university attendance is strongly predicted by parental education, we know very little about why some potential 'first in family' or first-generation students make it to university and others do not. This paper looks at the role of non-cognitive skills in the university participation of this disadvantaged group in England. We find that conditional on national, high-stakes exam scores and various measures of socioeconomic background, having higher levels of non-cognitive skills, specifically locus of control, academic self-concept, work ethic, and self-esteem, in adolescence is positively related to intergenerational educational mobility to university. Our results indicate that having higher non-cognitive skills helps potential first in family university students to compensate for their relative disadvantage, and they are especially crucial for boys. The most important channel of this relationship seems to be through educational attainment at the end of compulsory schooling.

There has been much interest across the social sciences in the link between young people's socioemotional (non-cognitive) skills and their educational achievement. But much of this research has focused upon the role of the Big Five personality traits. This paper contributes new evidence by examining two inter-related non-cognitive factors that are rarely studied in the literature: ambition and drive. We use unique survey-administrative linked data from England, gathered in the lead-up to high-stakes compulsory school exams, which allow us to control for a rich set of background characteristics, prior educational attainment and, unusually, school fixed effects. Our results illustrate substantial gender and immigrant gaps in young people's ambitiousness, while the evidence for socio-economic differences is more mixed. Conversely, we find a strong socioeconomic gradient in drive, but no gender gap. Both academically ambitious and driven teenagers achieve grades around 0.37 standard deviations above their peers, even controlling for prior academic attainment and school attended.

Additional file 1: Table S1. Descriptive statistics for the countries included in the PISA sample. Table S2. Correlations between country-level physical activity outcomes and country-level factors. Table S3. Mean, Median, and SD in physical activity outcomes by country. Table S4. Frequencies of physical activity outcomes by country. Table S5. Tabulations of physical activity outcomes by gender. Table S6. Tabulations of physical activity outcomes by wealth (top and bottom quintile). Table S7. Correlations between socioeconomic disparities in physical activity and income inequality. Figure S1. A flow chart showing derivation of the analytical sample. Figure S2. Gender disparities in adolescents’ (95% CI) physical activity: in school and out of school. Figure S3A. Forest plot of gender differences in physical activity outcomes (vigorous activity outside of school). Figure S3B. Forest plot of gender differences in physical activity outcomes (moderate activity outside of school). Figure S3C: Forest plot of gender differences in physical activity outcomes (in school activity). Figure S4. Socioeconomic (wealth-based) disparities in adolescents’ (95% CI) physical activity: in school and out of school among males. Figure S5. Socioeconomic (wealth-based) disparities in adolescents’ (95% CI) physical activity: in school and out of school among females. Figure S6A. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (vigorous activity outside of school), among males. Figure S6B. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (moderate activity outside of school), among males. Figure S6C. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (in school activity), among males. Figure S7A. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (vigorous activity outside of school), among females. Figure S7B. Forest plot of socioeconomic (wealth) differences in physical activity out-comes (moderate activity outside of school), among females. Figure S7C. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (in school activity), among females.

Additional file 1: Table S1. Descriptive statistics for the countries included in the PISA sample. Table S2. Correlations between country-level physical activity outcomes and country-level factors. Table S3. Mean, Median, and SD in physical activity outcomes by country. Table S4. Frequencies of physical activity outcomes by country. Table S5. Tabulations of physical activity outcomes by gender. Table S6. Tabulations of physical activity outcomes by wealth (top and bottom quintile). Table S7. Correlations between socioeconomic disparities in physical activity and income inequality. Figure S1. A flow chart showing derivation of the analytical sample. Figure S2. Gender disparities in adolescents’ (95% CI) physical activity: in school and out of school. Figure S3A. Forest plot of gender differences in physical activity outcomes (vigorous activity outside of school). Figure S3B. Forest plot of gender differences in physical activity outcomes (moderate activity outside of school). Figure S3C: Forest plot of gender differences in physical activity outcomes (in school activity). Figure S4. Socioeconomic (wealth-based) disparities in adolescents’ (95% CI) physical activity: in school and out of school among males. Figure S5. Socioeconomic (wealth-based) disparities in adolescents’ (95% CI) physical activity: in school and out of school among females. Figure S6A. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (vigorous activity outside of school), among males. Figure S6B. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (moderate activity outside of school), among males. Figure S6C. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (in school activity), among males. Figure S7A. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (vigorous activity outside of school), among females. Figure S7B. Forest plot of socioeconomic (wealth) differences in physical activity out-comes (moderate activity outside of school), among females. Figure S7C. Forest plot of socioeconomic (wealth) differences in physical activity outcomes (in school activity), among females.