Digital technologies in education: a scientometric analysis of international and Russian research

The article is devoted to forming an idea of global trends in the digitalization of education, allowing to determine the trajectories and prospects of improving the quality of Russian education by evaluating and comparing the international and Russian practices. The authors assume that peer-reviewed scientific publications, as centers of knowledge concentration on the subject, most objectively reflect the existing trends and issues in the field of digitalization of education among researchers. This paper presents the results of a bibliographic data analysis of a selected pool of articles published in peer-reviewed scientific journals on Social and Computer Sciences, in order to explore the most relevant topics of 2021-2023 publications related to the implementation of modern IT technologies in education, through consideration of keywords of selected materials. The data source for the analysis of international studies was ScienceDirect, a full-text database of publications of peer-reviewed open access publications; for the study of Russian trends – the scientific digital library Elibrary.ru, the largest Russian information and analytical portal in the field of science. The data on international studies were processed using the VOSviewer software tool for the construction and visualization of bibliometric networks. The scientometric analysis of bibliographic data of the array of selected publications of the given topic allowed to highlight both the main existing areas of research in the study area and promising ones that need to be studied, as well as to select and form the most significant recommendations for achieving a quality level of education. The study revealed a lag in the formation of media education and augmented reality in the Russian Federation, recognized as promising areas, compared to the international progress. 

1. Janmaijaya M., Shukla A.K., Muhuri P.K., Abraham A. Industry 4.0: Latent Dirichlet Allocation and clustering based theme identification of bibliography. Eng. Appl. Artif. Intell. 2021, 103.

2. Choudhury N., Faisal F., Khushi M. Mining temporal evolution of knowledge graphs and genealogical features for literature-based discovery prediction. Journal of Informetrics, 14 (3) (2020), Article 101057.

3. Clauset A., Larremore D.B., Sinatra R. Data-driven predictions in the science of science. Science, 355 (6324) (2017), pp. 477-480

4. Fortunato S., Bergstrom C.T., Börner K., Evans J.A., Helbing D., Milojević S., Vespignani A. Science of science. Science, 359 (6379) (2018), p. eaao0185

5. Zain, S. Digital transformation trends in education. In Future Directions in Digital Information; Elsevier: Amsterdam, The Netherlands, 2021; pp. 223–234.

6. Nacional’nyj proekt «Obrazovanie». Minprosveshhenija Rossii. URL: https://edu.gov.ru/nationalproject/

7. Informacionnaja platforma «ScienceDirect». URL: www.sciencedirect.com

8. Programmnyj instrument «VOSviewer». URL: https://www.vosviewer.com/

9. Huo C., Ma S., Liu X. Hotness prediction of scientific topics based on a bibliographic knowledge graph. Information Processing & Management 2022, 59 (4).

10. Van Eck, N.J., & Waltman, L. (2014). Visualizing bibliometric networks. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring scholarly impact: Methods and practice (pp. 285-320).

11. Bygstad B., Ovrelid E., Ludvigsen S., Dahlen M. From dual digitalization to digital learning space: Exploring the digital transformation of higher education. Computers & Education, 182 (2022), Article 104463, 10.1016/j.compedu.2022.104463

12. Efimova, E. G. Tendencii cifrovogo razvitija regional’noj sistemy professional’nogo obrazovanija / E. G. Efimova // Ural – XXI vek: makroregion neoindustrial’nogo i innovacionnogo razvitija : Materialy III Mezhdunarodnoj nauchno-prakticheskoj konferencii. V 2-h tomah, Ekaterinburg, 15–16 oktjabrja 2018 goda / Otvetstvennye za vypusk Ja.P. Silin, E.B. Dvorjadkina. Tom 1. – Ekaterinburg: Ural’skij gosudarstvennyj jekonomicheskij universitet, 2018. – S. 127-134. – EDN VPWNPL.

13. Alekseeva, E. N. Razvitie sistemy internet-tehnologij v svete realizacii Bolonskogo soglashenija kak sredstvo sovershenstvovanija kachestva podgotovki v sisteme vysshego professional’nogo obrazovanija / E. N. Alekseeva // . – 2014. – № 4(60). – S. 255-257. – EDN TMQATN.

14. Savina, A. G. Tendencii razvitija sistemy obrazovanija i nauki v uslovijah cifrovizacii obshhestva / A. G. Savina // Cifrovizacija sovremennogo obshhestva: faktory transformacii, problemy i perspektivy : monografija. – Orel : Orlovskij gosudarstvennyj universitet jekonomiki i torgovli, 2019. – S. 27-44. – EDN ZILTNZ.

15. Dneprovskaja, N. V. Ocenka gotovnosti rossijskogo vysshego obrazovanija k cifrovoj jekonomike / N. V. Dneprovskaja // Statistika i Jekonomika. – 2018. – T. 15, № 4. – S. 16-28. – DOI 10.21686/2500-39252018-4-16-28. – EDN XYHITR.

16. Ustjuzhanina, E. V. Cifrovizacija obrazovatel’noj sredy: vozmozhnosti i ugrozy / E. V. Ustjuzhanina, S. G. Evsjukov // Vestnik Rossijskogo jekonomicheskogo universiteta imeni G.V. Plehanova. – 2018. – № 1(97). – S. 3-12. – EDN YSJCMG.