At the beginning of the year 2020 the world community faced the emergence of Coronavirus infection. The governments of different countries reacted to the spread of the pandemic by introducing restrictive measures that also affected the education sector. In order to reduce the rate of COVID-19 cases, many countries took a decision to close schools and switch to distance learning that exacerbated the problem of the digital divide in the world. According to UNESCO, more than 800 million learners did not have access to a personal computer, more than 700 million students lacked Internet access. Moreover, teachers had an insufficient level of training for using digital educational resources and delivering the online education effectively. The listed problems posed a threat to ensuring educational continuity during a difficult epidemiological situation and led the countries to take certain measures to level it, such as additional funding to support schools and provide resources for students from vulnerable groups, development of digital educational platforms and resources, as well as programs of methodological training for teachers.

In Russia, in response to the pandemic, the government decided to close schools and switch to a distance format like a big part of European countries. This measure was introduced in densely populated regions, as well as in regions with the highest incidence rates. In late March-early April 2020, the government recommended Russian schools to provide a possibility of organizing a two- or three-week holiday in order to provide opportunities for students and teachers to prepare for subsequent distance learning. However, this measure was not sufficient to close the large gap in the level of technological and methodological readiness of various regions, and, as a result, to smooth out the problem of digital inequality.

In this paper we analyzed data on the schools’ transfer to a distance format on the Russian regions data for the 2016-21 years. This paper aims to answer the following question: what is the relationship of successful transfer to remote format, measured through the share of students on distance learning, with school financial and digital resources, advanced curricula, and teachers’ professional characteristics under taken local political measures?

The analysis was carried out in three stages. First, regional cases of educational policies under COVID-19 situation were analyzed and systematized. Second, the regional differences in the technological readiness for the transfer to the distant format were shown using the methods of descriptive statistics.Third, fixed effects of schools’ resources and teachers’ characteristics on the share of students on distance learning were analyzed. All indicators of digital resources and school characteristics were logarithmized to normalize their distributions. Thus, at these stages, log-linear relationships between variables were analyzed. The total sample was 425 observations for 85 Russian regions over 5 years.

The situation that has developed over several waves of education modernization has led to the fact that at the time of the start of the coronavirus pandemic in 2020, the technological readiness of schools for the transfer to distance learning varied greatly depending on the region. Despite the obvious pandemic challenges, there still are some regions where the share of students on distance learning is minimal - less than 0.1%. In addition, educational policies and decisions taken by regional authorities during the pandemic varied greatly. The differences were related to the level of methodological and technical support provided to teachers and students, as well as the decisions on the format of classes, the duration of holidays, the dates of the end of the school year and the methods of final assessment. The results of fixed effects analysis showed that the key predictor of such transfer in primary school is school funding, however, in the senior grades its importance decreases. Also, schools with advanced curriculum turned out to be more successful in the transfer to that new format of education. Then, regions with a large presence of teachers with secondary vocational education and lower qualifications are in a more vulnerable situation. Moreover, higher pedagogical education of teachers in some cases gives a negative effect - this may indicate that graduates of pedagogical universities are less ready to implement and use digital tools than specialists of other profiles who have decided to teach at school. The results obtained open prospects for further research on the digital divide in education. It is shown that decision-making policies regarding the education system in a pandemic may differ not only between countries, but also within them. In the case of decentralized education systems, such differences can overlap and exacerbate the existing digital inequality.

DiMaggio, P., & Hargittai, E. (2001). From the ‘digital divide’to ‘digital inequality’: Studying Internet use as penetration increases. Princeton: Center for Arts and Cultural Policy Studies, Woodrow Wilson School, Princeton University, 4(1), 4-2. De Haan, J. (2004). A multifaceted dynamic model of the digital divide. It & Society, 1(7), 66-88. Hindman, D. B. (2000). The rural-urban digital divide. Journalism & Mass Communication Quarterly, 77(3), 549-560. Jung, J. Y., Qiu, J. L., & Kim, Y. C. (2001). Internet connectedness and inequality: Beyond the “divide”. Communication research, 28(4), 507-535. Volchenko, O. V. (2016). Dynamics of the digital divide in Russia. Monitoring public opinion: Economic and social changes, (5 (135)). (In Russ.) Rykov, Y., Nagornyy, O., & Koltsova, O. (2017, June). Digital inequality in Russia through the use of a social network site: A cross-regional comparison. In International Conference on Digital Transformation and Global Society (pp. 70-83). Springer, Cham. Uvarov, A. Yu., Gable, E., Dvoretskaya, I. V., Zaslavsky, I. M., Karlov, I. A., Mertsalova, T. A., & Frumin, I. D. (2019). Difficulties and prospects of digital transformation of education. (In Russ.) Havenson, T. E., & Chirkina, T. A. (2018). Effectively maintained inequality. Economic Sociology, 19(5). (In Russ.) Kosyakova, Y., Yastrebov, G., Yanbarisova, D., & Kurakin, D. (2016). Reproduction of social inequality in the Russian educational system. Journal of Sociology and Social Anthropology, 19(5). (In Russ.)