Learning outcomes: school and family factors

Child development is an important predictor of later life course achievements including academic and labour market success, and in recent years increasing attention has focused on the relationship between child development and life course trajectories in low and middle-income countries. This study uses data from the first wave of the Chinese Family Panel Study (CFPS) collected in 2010 to examine the relationship between parental labour migration and educational outcomes for youth. The historically uneven development across China has contributed to differentials between the urban and rural populations. Labour migration may contribute to decreasing these inequalities. The paper examines the contribution of parental labour migration to explaining variation in three educational outcomes, school pacing, math and verbal achievement. Multivariate regression models are estimated to examine the contribution of individual, household and community characteristics to explaining variation in the outcomes measures highlight the relationships between migration, residence and Hukou. First, the urban Hukou advantage is not universal with observed differences only for language scores. Second, youth living in rural households with one or more migrant parents are more likely to have higher math scores compared to youth in other rural households.

Do parents invest more in sons than in daughters in rural China with strong tradition of son preference and differentiate the educational outcomes across children within families? Prior research suggests that girls have lower educational attainment than boys across families in China. However, existing research primarily relies on sample from urban families with only one child and pays little attention to rural families, normally have more than one child. In addition, sample from one child family is hard to know how parents allocate resources within families, since the only child expectably receives all the resources, but the rural child has to compete with their siblings. Therefore, we have little knowledge about gender differences in educational outcomes in rural China and how parents allocate the resource across children
This research aims to explore the gender differences in educational outcomes and how parents allocate resources within families in rural China by using unique sibling data from the Gansu Survey of Children and Families (GSCF). Preliminary suggests that there is no difference in educational attainment, but sons outscore their sisters in test scores. The next step of this research is going to explore how parental investment reinforces the gender differences in educational performance.

The study aims to explore educational performances of children in the primary grades in Andhra Pradesh, India. For this, the study uses data from the Young Lives research. The study used bi-variate analysis to examine the status of educational performances of children; and logistic regression analysis to find out factors responsible for school performances. Educational performances have been examined using the Peabody Picture Vocabulary Test results separately for reading, writing and mathematical abilities. The preliminary analysis shows that large percentage of boys and girls are not able to read and write in the primary grades. But, their mathematical abilities are relatively better than reading and writing. The logistic regression analysis results show that along with other variables boys with reference to girls; standard BMI of children with reference to low BMI; children getting mid-day meal in schools with reference to not getting; economic activities of children with reference to not working children ; and children in grade 2 and 3 with reference to grade1 are statistically significant predictors for better reading, writing and mathematical abilities. Mother’s education, middle and rich class are also important determinants of reading and writing.

This paper studies the effect of private tutoring on academic achievement and educational inequality in Korea. Korea has the largest system of private tutoring in the world along with outstanding performance on international academic tests, such as the PISA. Korea's school system is characterized by limited school choice and low variation in quality and curricula across schools, which provides incentive to use private tutoring for additional educational investment. Out of concerns that wealthier families can choose more and better tutoring, the government enacted various forms of regulation on the tutoring market. This paper seeks to estimate the effect of private tutoring on academic achievement and to evaluate the impacts of a range of government policies. It develops and estimates a dynamic discrete choice model of private tutoring and self-study decisions using panel data from the 2005 to 2011 waves of the Korea Education Longitudinal Study. The data follow 7th graders annually until one year after high school graduation and contain detailed information on private tutoring use and test scores.

This paper primarily examines the interrelationships connecting family background and students’ academic attainment. Based on the questionnaire survey conducted in 6 senior high schools in Harbin, the capital of Heilongjiang Province in northeast China, the sample consists of 2028 senior high school freshman.The findings suggest that the differentiation of social stratification between families in senior high school education is embodied in student’s academic attainment. The advantaged classes (such as the administrator group, the middle- manager group, and professionals and technicians group) contain significantly larger resources in economic capital, cultural capital, and parents’ emotional involvement in education than the disadvantaged (such as blue-collar worker group, skilled industrial worker group, and peddler group), which indirectly affects students’ performance in exams. A further analysis indicates the way how family structured variables, including family’s cultural capital, economic capital affect the academic achievement. Besides, this paper explores the extent to which family process variables, including parental educational expectation, family interaction, parents’ emotional engagement in education, and behavior supervision, have power to predict academic achievement between different classes.