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Social inequality, factors of education quality at school and students’ choices of educational trajectories

Priority areas of development: sociology, humanitarian

Goal of research:

Track 1. To analyze the dynamics of PIRLS, TIMSS and PISA results of students from different social groups and territories.

Track 2. To analyze characteristics of math teachers, their beliefs and the ways they implement a differentiated approach in teaching in the context of unequal access to educational resources.

Track 3. To analyze institutional and individual factors and their relationship to students’ academic outcomes and students’ choices of educational trajectory.


Track 1. Descriptive analysis of educational results of students from different social groups in the 2000s. Quantitative analysis with the D Duncan index were used to estimate  educational inequality and segregation of students. The results of Russia were compared with other countries.

Track 2. We implemented analysis of a series of interviews based on the grounded theory approach [Glaser, Strauss 1968]. We also did ethnographic analysis of math lessons video records giving an interpretation to the role-play interaction schemes between teachers and students, to the students involvement and class climate. Finally, to study math teachers’ attitudes and teaching practices in the 11th grade we used a quantitative analysis, in particular an order logit regression.

Track 3. To assess the relationship between the practices parents used to teach children to read and students’ reading literacy in the primary school we used linear (OLS), logistic and ordinal logit regression. The analysis was conducted on the full sample of students and on  the sub-samples by mother education levels. School climate factors in the upper grades were studied with the use of confirmatory factor analysis (CFA) and item response theory (IRT). Students’ educational trajectories, as well as the factors related to affluent students’ achievements were estimated with logistic regression and decomposition analysis. And finally we used descriptive analysis to compare the dynamics of students’ trajectories after the 9th grade in different regions of Russia.

Empirical base of research:

Track 1. The work is based on the data from PIRLS, TIMSS and PISA studies for Russia and other countries collected in the 2000s.

Track 2. We used the data of the study "Trajectories in Education and Careers" (http://trec.hse.ru/) (HSE), as well as data of 30 semi-structured interviews with high schools math teachers. These interviews were conducted in nine Russia’s regions.

Track 3. We used PIRLS data, data from the longitudinal project "Trajectories in Education and Career", as well as information from open state sources of Rosstat and EMISS, EISOD of the Ministry of Education and Science of Russia and the portal "Statistics of Russian Education" were used.

Results of research:

Track 1. The dynamics of the results of the students from different social groups is estimated. There has been a slight improvement in the results of Russian schoolchildren and a decrease in social and territorial inequalities during the 15 years of observation. However, these changes do not apply to all subject areas. This can be explained by the improvement in the results of the students from low cultural capital families living in small towns and rural areas. The achievement scores of students from families with higher cultural capital living in large cities did not show any significant growth. The same time schools in Russia became more segregated in the period from 2003 to 2012. The comparison with other countries confirmed the tendency of increasing segregation.

Track 2. Different aspects of the differentiated approach in math teaching were analyzed.First, we found out what categories teachers use to differentiate students and how they work with different groups of children. Two models of categorization - exclusive and inclusive ones were described. Second, we explored the students and teachers’ involvement during math lessons. The math lessons video records show how the ways teachers involve students affects their access to educational resources in class. A quantitative analysis of the teachers’ survey shows that the practices of the differential approach are not related to teachers’ characteristics such as routine seeking, years of work experience, qualification, education etc. Third, we analyzed teachers 'views on their role in expanding or restricting students' access to educational resources. Two fundamentally different perceptions of the teacher’ role were described. Some teachers don’t  consider themselves responsible for students’ academic failure. Others understand clearly the locus of their responsibility for every student academic results.

Track 3.  Mechanisms of social inequality at different levels of school were described.In primary school, inequality of educational results in reading is associated with parental teaching before school age. Teaching strategies vary in families with different levels of cultural capital. These strategies have different effects. In the most difficult situation are the kids in low cultural capital families, that do not attend kindergarten. Inequality in educational results in the first grade is not compensated by the end of primary school.Analysis of educational results in the middle and high school revealed a group of low performing students from families with high socio-economic status (SES). In this case, factors of failure are similar across academically ‘weak’ groups of students: low expectations from the teachers, the location of school in the rural areas, the disadvantaged social context of a school, unfavorable school climate. On the other hand, in high school, the relationship between the components of the school climate and the educational achievements of schoolchildren is weak. Academic expectations of teachers are positively correlated with the results of students with high SES only. There is a significant negative relationship between the feeling of alienation students have and their educational performance.By the end of the middle and high school, inequality correlates with the choice of the further educational trajectory. Socio-economic status of the family is more important at the end of the 9th grade. Students from families with high SES choose an academic trajectory while the majority of low SES students choose professional education track. Students who continue their education in the 10 and 11th grades will enter the university with a high probability. At the same time, universities prefer high SES to lower SES students, even if their academic achievements are the same. That confirms the maintained inequality theory.The observed evidences of educational inequality have a regional specificity, weakening or strengthening the actions of the above-described mechanisms. For example, regions with large university centers are characterized by a high proportion of students who embark on an academic track after the 9th grade. In other types of regions vocational school programs are more popular.


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