Institute of Education

Publications

• Book

  Abashkin V., Abdrakhmanova G., Demidkina O. V. et al.

  Digital Economy: 2026 : Pocket Data Book

  This pocket data book contains the main indicators reflecting the relevance of digital technologies for enterprises and individuals, the activity of ICT sector enterprises, the infrastructure and personnel of the digital economy.

  The data book includes information of the Russian Federal State Statistics Service (Rosstat), Ministry of Digital Development, Communications and Mass Media of the Russian Federation, European Statistical Office (Eurostat), Organisation for Economic Co-operation and Development (OECD), International Telecommunication Union (ITU), UNESCO, UN Department of Economic and Social Affairs, and results of methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.

  In some cases, the presented data specify those published earlier.

  M.: HSE ISSEK, 2026.

• Article

  Pavliuk D.

  Do thesis topics matter? How thesis topic characteristics relate to doctoral experience and self-confidence in defence

  The literature on doctoral students’ experience rarely examines the importance of thesis topic characteristics, even though this is one of the central decisions both at the start and throughout the doctoral journey. Although studies examine how students choose their thesis topics, there is little research on how different topic characteristics are linked to doctoral experience and potential outcomes. This study addresses the gap using data from a nationwide survey of doctoral students at Russian universities (N = 1,539) and regression analysis. We measure thesis topic characteristics (personal choice, alignment with the supervisor’s research, strong personal interest, and continuation of prior research) and show how they relate to doctoral experience and to confidence in future defence. Strong personal interest emerges as the most consistent predictor across outcomes and is more strongly related to research activities and confidence in defence than topic alignment. Alignment with the supervisor’s research is also positively associated with all outcomes, but usually more weakly. Personal choice matters more selectively for peer, departmental, and international engagement, whereas continuation of prior research is not significant once other characteristics are taken into account. Overall, the findings suggest that motivational mechanisms linked to topic interest are at least as important as resource-related fit and, for several outcomes, may be more influential. We argue that doctoral programmes should support topic selection by combining students’ interests with access to supervision and research support.

  Higher Education. 2026.

• Book chapter

  Dvoretskaya I., Alexey Semenov, Uvarov A.

  Exploring Patterns of Information Literacy Development in Schools: Application of Multilevel Latent Class Analysis to School Students Survey Data

  While the literature on digital transformation in education has searched for evidence based practices to improve ICT uptake in school settings, we know little about how schools differ in their approaches. This study aims to overcome the absence of standardized tools that could help to assess the stages and progress of ICT integration in educational settings. By using the example of information literacy development tasks assignment in classroom, we applied a latent class analysis to the survey data obtained from the monitoring the digital transformation of schools in the 2020–21 academic year. Based on the survey data from monitoring the digital transformation of schools, four types of students’ patterns were identified, depending on the information skills tasks assigned to them by their teachers at school. Based on the distribution of students’ patterns of working with information, three typical patterns of schools were identified with the use of multilevel latent class analysis. This study provides evidence for how the development of information literacy differs across schools contexts. As with advent of digital technologies education becomes data intensive domain, new approaches to the big data analysis are encouraged and it can help educators and education policy makers to improve decision-making.

  In bk.: 26th International Conference, DAMDID/RCDL 2024, Nizhny Novgorod, Russia, October 23–25, 2024, Revised Selected Papers. Data Analytics and Management in Data Intensive Domains. (CCIS, volume 2641). Springer, 2026. P. 253-266.

• Working paper

  Antipkina I., Ivanov A., Guzhelya D.

  Explicit continuum scale format reduces the ceiling effect in self-report questionnaires comparing to Likert response format

  This study presents a methodology for developing a new questionnaire format called explicit continuum scenario scales, in the example of a client focus questionnaire. Elements of the Rasch Guttman scenario scale methodology were used in its development. In three consequent studies, different aspects of the scale functioning were investigated. In Study 1, on the sample of 100 respondents, it was shown that the explicit continuum scale produces reliable results and helps avoid the ceiling effect shown in the Likert response format version of the client focus questionnaire. In Study 2, the scale was administered in a competition environment, in a sample of 735 people. Despite the positive shift of scores, the instrument shows excellent psychometric characteristics and still resists the ceiling effect. In Study 3, new items were included, and the scale was presented in an interactive format. In the sample of 65,000 university students, it demonstrated the robustness of its psychometrics characteristics including dimensionality. The results of the three studies show that the explicit continuum format has the advantage of the stable dimensionality similar to the expanded format and is promising for measurement in social sciences.

  Basic research program. WP BRP. National Research University Higher School of Economics, 2024