Preview

Informatics and education

Advanced search

Adaptive models of distance learning in professional education: Integration of information technologies and methodological approaches

https://doi.org/10.32517/0234-0453-2025-40-4-63-75

Abstract

Current trends in education digitalization require a fundamental rethinking of methodological approaches to organizing professional education. The study aims to develop an integrated distance learning model that combines adaptive technologies with methodological principles of professional training. The methodology is based on systematic analysis of empirical data from 1247 participants in the educational process from 18 professional educational organizations during 2023-2024. Methods of regression analysis, clustering, machine learning, and statistical modeling were applied to identify patterns of distance learning effectiveness. Results demonstrate predictive accuracy of 89.4 % in predicting academic results. Cluster analysis identified four typological groups of students: “High-adaptive”, “Moderate- adaptive”, “Traditionalists”, and “Technophobes”. The theoretical significance of the study lies in creating a conceptual framework for designing adaptive educational systems of professional orientation. The practical value is determined by the possibility of scaling the proposed solutions in the professional education system to improve the quality of specialist training in the digital economy.

About the Authors

M. V. Kozhevnikov
South Ural State Humanitarian and Pedagogical University
Russian Federation

Michail V. Kozhevnikov, Doctor of Sciences (Philology),
Professor at the Department ofTrainingTeachers of Professional Education and Subject Methods, Professional Pedagogical Institute

Chelyabinsk



N. Yu. Korneeva
South Ural State Humanitarian and Pedagogical University
Russian Federation

Natalia Yu. Korneeva, Candidate of Sciences (Education),
Docent, Head of the Department of Training Teachers of Professional Education and Subject Methods, Professional Pedagogical Institute

Chelyabinsk



O. Yu. Leushkanova
South Ural State Humanitarian and Pedagogical University
Russian Federation

Olga Yu. Leushkanova, Candidate of Sciences (Education), Associate Professor at the Department of Training Teachers of Professional Education and Subject Methods, Professional Pedagogical Institute

Chelyabinsk



N. V. Uvarina
South Ural State Humanitarian and Pedagogical University
Russian Federation

Natalia V. Uvarina, Doctor of Sciences (Education), Professor, Professor at the Department of Training Teachers of Professional Education and Subject Methods, Professional Pedagogical Institute

Chelyabinsk



E. V. Gnatyshina
South Ural State Humanitarian and Pedagogical University
Russian Federation

Ekaterina V. Gnatyshina, Doctor of Sciences (Education),
Docent, Head of the Department of Pedagogy and Psychology

Chelyabinsk



References

1. Klarin M. V., Moldovanu M. B. Educational design models in distant and blended instruction: a didactical analysis. Education and Society. 2020;(4(123)):2634. (In Russian.) EDN: ZXGJQW.

2. Zhutova V. A., Sidunova G. I. Models of distance learning application in higher education. Arkhivarius. 2021;7(4(58)):2126. (In Russian.) EDN: PBPESX.

3. Tarasov O. V. Adaptive technologies in distance learning: Modern approaches and perspectives. Modern Science: Actual Problems of Theory and Practice. Series: Natural and Technical Sciences. 2024;(7):147151. (In Russian.) EDN: JVDOGG.DOI: 10.37882/22232966.2024.7.37.

4. Mian Ya., Khalid F., Qun A., Ismail S. Learning analytics in education, advantages and issues: A systematic literature review. Creative Education. 2022;13:29132920. DOI: 10.4236/ce.2022.139183.

5. Revunova L. N. Problems of effective interaction of teachers and students in the conditions of distance learning. Vestnik GSU. 2021;(5):2329. (In Russian.) EDN: GSCSPT.

6. Parmenova N. V. Going the distance: Effective instruction using distance learning technology. The World of Science, Culture and Education. 2023;(1(98)):215218. (In Russian.) EDN: HPHFQM. DOI: 10.24412/199154972023198215218.

7. Yinzhou P. The model of formation of competence of social interaction in the conditions of distance learning in the chinese audience of students. Education Management Review. 2023;(5(63)):133139. (In Russian.) EDN: ILSQOJ. DOI: 10.25726/t671159483602i.

8. Radygina E. G. Building an effective model of distance learning organization. Scientific and Methodological Electronic Journal “Koncept”. 2022;(2):1023. (In Russian.) EDN: HDRRBE. DOI: 10.24412/2304120X202211007.

9. du Plooy E., Casteleijn D., Franzsen D. Personalized adaptive learning in higher education: A scoping review of key characteristics and impact on academic performance and engagement. Heliyon. 2024;10(21):e39630. DOI:10.1016/j. heliyon.2024.e39630.

10. Reda Al. H., Demidov A. S. Effective data transmission algorithms for distance learning. Computational Nanotechnology. 2021;8(4):1927. (In Russian.) EDN: FYSOCA. DOI: 10.33693/2313223X2021841927.

11. Shamsutdinova T. M. Formation of individual educational trajectory in adaptive learning management systems. Open Education. 2021;25(6):3644. (In Russian.) EDN: YPLVRY. DOI: 10.21686/18184243202163644.

12. Patarakin E. D., Salimullin K. D. Transfer of skills in modeling complex adaptive systems to the design of pedagogical. MCU Journal of Informatics and Informatization of Education. 2025;(1(71)):115129. (In Russian.) EDN: OBTOMN. DOI: 10.24412/207290142025171115129.

13. Fomina T. A., Novikova G. M. Designing an adaptive interface of an information system for support of educational institution's activities. Vestnik Altaiskoi akademii ekonomiki i prava. 2020;(61):125133. (In Russian.) EDN: JNQYHT. DOI: 10.17513/vaael.1174.

14. Khoang K. K., Avksentieva E. Yu., Fedosov Yu. V. Forming an individual trajectory of teaching computeraided design by means of an intelligent adaptive system. Ergodesign. 2021;(1(11)):4148. (In Russian.) EDN: YMPWRB. DOI: 10.30987/26584026202114148.

15. Yordanova S. T., Slavov M. N., StoitsevaDeliche va D. R. Design and genetic algorithms based optimisation of industrial adaptive PID FLC system of liquid level. Mecha tronics, Automation, Control. 2023;24(4):181189. EDN: LIRYSW. DOI: 10.17587/mau.24.181189.

16. Kazakova V. N., Karyukina M. V. Case technology in the implementation of the distance learning model. Uchenye zapis ki ISGZ. 2019;17(1):248254. (In Russian.) EDN: ZQXAHB.

17. Poletaykin A. N., Shevtsova Yu. V., Podkolzin V. V., Strukova E. G. Mathematical model of quality assessment of contact work in elearning based on webinars. Informatics and Education. 2019;34(7):4253. (In Russian.) EDN: HPHFQM. DOI: 10.32517/0234045320193474253.

18. Starygina S. D., Nuriev N. K., Pechenyi E. A., Obadi A. A. M. Designing smart educational systems with digital technologies. Educational Technologies & Society. 2019;22(3):5466. (In Russian.) EDN: BFPEFH.

19. Oleshkevich D. V., Filimonyuk L. A. Design of the individual educational route of young teachers in the system of additional vocational education. Problems of Modern Pedagogical Education. 2021;(723):251254. (In Russian.) EDN: WPOVIT.

20. Razumovskiy V. A. The peculiarities of designing the heterogeneous educational systems in the context of the development of the information society. Izvestia of the Volgograd State Pedagogical University. 2023;(7(180)):4048. (In Russian.) EDN: OTCBZZ.

21. Starygina S. D. Designing cyberphysical educational systems. Matematicheskie metody v tekhnologiyakh i tekh nike. 2024;(122):7982. (In Russian.) EDN: IGDHVD.

22. Vogel S., Rudolf S. Complex system design with design languages: Method, applications and design principles. Ontology of Designing. 2018;8(3(29)):323346. (In Russian.) EDN: YTBTTV. DOI: 10.18287/22239537201883323346.


Review

For citations:


Kozhevnikov M.V., Korneeva N.Yu., Leushkanova O.Yu., Uvarina N.V., Gnatyshina E.V. Adaptive models of distance learning in professional education: Integration of information technologies and methodological approaches. Informatics and education. 2025;40(4):63-75. (In Russ.) https://doi.org/10.32517/0234-0453-2025-40-4-63-75

Views: 12


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 0234-0453 (Print)
ISSN 2658-7769 (Online)