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School differentiation and its consequences: educational choice and students’ wellbeing

Priority areas of development: sociology
2017

Goal of research was to analyze the processes of emergence and reproduction of the educational differentiation on different levels: at the level of primary education (mutual choice of parents and schools); of secondary and professional education (formation of school climate, risk and aggressive behavior); and tertiary education (main aspects of the formation of motivation and academic achievements of university students).

Methodology.  To evaluate the relations between factors of interest we applied the methods of traditional statistics: OLS regression, robust OLS regression, logistic regression. To reveal the pathways of formation of students’ academic motivation and to prove theoretical assumptions about causality we used structural equation modeling. When we were developing the methodology for the measurement of school climate, we assessed scales’ consistency by factor analysis and item response theory. the qualitative data were openly coded and the nodes were structured hierarchically, but we did not aim to follow the precise procedure of the grounded theory.

Empirical base of research consists of quantitative and qualitative data collected by the Laboratory throughout the previous years and in 2017: (1) survey of 185 parents (for the development of a tool to measure school choice and values of upbringing) and 30 interviews with parents and school representatives about parental school  choice and school differentiation; (2) survey of 249 schools in Kaluga region (27 thousands pupils of 6th-9th grades, in collaboration with the project “Teacher for Russia”); (3) survey of 1500 students of vocational schools and technical colleges in Saint Petersburg (the second and the third waves of the research on adolescents’ health and risk behavior).

Results of research. The analysis of urban data and “digital footprints” reveals that school’s relevance is related to its status (gymnasium, lyceum, schools with advanced curriculum), state exams’ results, and the share of pupils who commute to the school from other districts. The choice of the primary school is quite stable, as 88,5% of 11th grade students have studied in the same school from the first grade.

We have demonstrated that school choice is a two-sided process. On the one hand, schools select families of a matching background by sending them particular signals. We revealed 22 signals which are highly differentiated by school status: schools with standard curriculum are willing to accept everybody, free of charge, and take parental responsibilities of upbringing; gymnasia and lyceums openly talk about barriers and necessity to pay for diverse services.

The analysis of the “digital footprints” reveals that when parents choose a school, they compare educational institutions by two main characteristics: proximity and school type. The results of the interviews and the survey have shown us that parents choose school based on their capitals, and the final decision depends on the difference in the perception of schools and their signals.

The study allowed us identifying the paths of formation of university students’ motivation, and the factors related to their academic achievements. Intrinsic motivation affects student’s self-concept, while extrinsic motivation does not. Previous educational achievements affect the grade for the class; the higher was the previous achievement, the higher is the interest in the class and the higher is student’s valuing of course’s utility for the future career. Student’s achievement rises if both cognitive and “practical” engagement in studying is high. Class attendance has opposite effect on the grades for students of different educational programs. Students get higher grades if they have friends among students; it is best to have friends among the teaching assistants.

We finalized and approved the original methodology for the assessment of socio-psychological climate of the school. We found that school size and social composition are related to a range of school climate characteristics (attitude towards school; attitude towards teachers; aggressive adolescent environment; cyberbullying; the frequency of discipline violation), and, thereby, it should be always taken into account when assessing school climate.

The analysis of the longitudinal data collected in vocational schools and technical colleges reveals that alcohol consumption rates increase during the studying process regardless the characteristics of the educational institution. The aggressive behavior to some extent does depend on the features of the technical college/ vocational school: in some of them this kind of behavior gets widely spread, while in others it is not detected at all, even after controlling for such background factors as gender.

Level of implementation, recommendations on implementation or outcomes of the implementation of the results

Project results were presented on international conferences and seminars in the USA and in Europe (Denver – CHI Conference on Human Factors in Computing Systems, Stockholm – World Anti-Bullying Forum, Oslo – INAS and etc.).

In cooperation with the heads of administration of Kaluga region we conducted a computer-based survey of all the schools in the region. This experience proved the possibility to test schools and students on a large scale. Recently we have reached an agreement with the Moscow region to conduct a similar survey.

The methodology for the assessment of school climate, risk and aggressive behavior was applied in the Kaluga region. For each educational institution in the sample, we prepared an individual report containing the particular school’s results compared to the overall sample’s results. This gives an opportunity to adjust social and educational policies in places. We also provided reports for the Ministry of education and science of Kaluga region, representing the results of the overall sample. Thus, the authorities can form educational and social policy with regard to the results of the studies, and develop certain impact measures, taking into account the peculiarities of schools and localities.

Publications:


Vadim V., Musabirov I., Alexandrov D. A. Studying Patterns of Communication in Virtual Urban Groups With Different Modes of Privacy / Высшая школа экономики. Series SOC "Sociology". 2017. 
Тенишева К. А., Александров Д. А. Неравенство в образовательных успехах и планах школьников: роль миграции, этничности и социального статуса, in: Образование и социальная дифференциация: коллективная монография. Москва : Издательский дом НИУ ВШЭ, 2017. С. 226-247.