The article contains the study results of the problems with the accessibility and safety of educational resources, applications, and tools of distance educational technologies for schoolchildren during the period of distance learning. In the framework of the study, the focus was also on the satisfaction of the subjects of educational relations with the services of providers and the support system for educational institutions during the COVID-19 pandemic in Moscow. The article identifies the key challenge to contemporary education—are schools capable of reworking and integrating all the achievements and breakthroughs of distance learning? The results show that when implementing distance learning, it is necessary to take account of the threats and risks that it entails—(1) the barrier of technological innovation; (2) the barrier of social factors; (3) the barrier to physical and psychological health; (4) the barrier of digital didactics; (5) the barrier of legal regulation; (6) the barrier of an inclusive environment. The study results can become the basis for the preparation of proposals and the development of recommendations to provide access to high-quality education for all schoolchildren in the context of distance learning.

The world we live in today holds some uncertainties. The processes of automation, big data, the digital environment, global crises, and the interconnectedness of international society are changing common technological patterns and the educational system. Among the essential features of competitiveness of teachers in higher education are mobility, digital competencies, adaptability, participation in scientific networks and projects, and continuous acquisition of new technological skills. For this reason, teachers must continuously develop their professional skills to remain competitive and create professionals in higher education. Current conditions are fostering global demand for teachers who produce pedagogical and scientific developments.<br /> This article aims to solve the problem of defining the structure, content, and requirements of scientific and methodological support for higher education teachers’ competitiveness in a digital world in the context of global challenges and risks. Theoretically, the problem is defined by the need for new approaches to explaining the concept of teacher competitiveness and the need to develop a psychological and teaching methodology for training and developing teacher competitiveness. In practice, we conclude that researchers must develop personal, professional, procedural, and technological enhancements to support higher education faculty competitiveness in a digital world.

The transition to digital society is characterised by the development of new methods and tools for big data processing. New technologies have a substantial impact on the education sector. The article represents the results of applying big data to analyse and transform the learning content of Moscow’s schools. The analysis of the school curriculum comprised the following: (a) identifying one-topic lesson scripts, (b) analysing cross-disciplinary connections between subjects, (c) verifying the compliance of the lesson script digital content to the Federal Educational Standards. The analysed material included 36,644 lesson scripts. The analysis has been conducted using specifically designed digital tools featuring data mining algorithms. The article considers the issue of applying data mining algorithms to analyse school curriculum for the improvement of its quality.

This work is aimed at assessment of content quality of lesson scenarios in Moscow e-school, comparison of expert data with the features of application of these scenarios in order to reveal strong points and deficiencies in content of lesson scenarios. The considered lesson scenarios are characterized by high quality of material component of educational content. The lesson scenarios substantiate forms and types of control of educational results. Methodological support of the lessons, differentiation and individualization of the content, existence of nonstandard situations stimulating personal participation of students, instructions for a student have been manifested least in the lesson scenarios. High expert quality appraisals of lesson scenarios mostly do not coincide with the popularity of lesson scenarios among the users.

Network analysis methods are actively used to research the behavior of digital repository users who utilize and create digital objects. At the same time, the research into the collective behavior of a group of participants who are members of the same school is much less common. The library of the Moscow Electronic School is a rather complicated system with multiple roles offered to users. The actors of the repository are teachers, students, parents, and publishers – anyone performing any actions with the objects. In this study, the school is seen as an actor performing actions with objects – lesson scenarios within the Moscow Electronic School repository of digital objects. Within the study, the authors compare the sociograms of schools that unite teachers and the scenarios created by the teachers and divide schools into factions based on network indicators in sociograms. The main method of presenting and analyzing data is network analysis and sociogram creation. The authors identify two types of networks: the network of single participant’s relationships and the network of relationships of teachers from a single school. The authors not only describe the data structure in the Moscow Electronic School system that records the digital trace of every individual and collective user but also create a digital map that reflects the dynamics of actions in the Moscow Electronic School system and identify the indicators that characterize the common activity of key participants. Moreover, the authors identify graph factions for schools that characterize the degree of interaction between teachers: disconnected groups, sparse graphs, crystallization centers, dense graphs.