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DOI: 10.15507/1991-9468.030.202602.346-369

UDC 37.013:004.9

 

From Individualization to Personalization of Education: Theoretical Aspects and Practical Implementation Based on Artificial Intelligence Solutions

Sergey D. Karakozov
Dr.Sci. (Ped.), Professor, Director of the Institute of Mathematics and Informatics, Moscow Pedagogical State University (1, bld. 1 Malaya Pirogovskaya St., Moscow 119435, Russian Federation), ORCID: https://orcid.org/0000-0001-8151-8108, Scopus ID: 57208902502, SPIN-code: 7462-2637, This email address is being protected from spambots. You need JavaScript enabled to view it.

Natalia I. Ryzhova
Dr.Sci. (Ped.), Professor, Leading Researcher of the Laboratory for the Study of Modern Trends in Education Development, Federal State University of Education (10A, bld. 2 Radio St., Moscow 105005, Russian Federation), ORCID: https://orcid.org/0000-0002-5868-8157, Scopus ID: 57211411898, SPIN-code: 6382-1690, This email address is being protected from spambots. You need JavaScript enabled to view it.

Evgeniia A. Samokhvalova
Senior Lecturer of the Chair of Applied Informatics in Education, Moscow Pedagogical State University (1, bld. 1 Malaya Pirogovskaya St., Moscow 119435, Russian Federation), ORCID: https://orcid.org/0000-0002-4882-4020, SPIN-code: 7543-4906, This email address is being protected from spambots. You need JavaScript enabled to view it.

Ilya B. Gosudarev
Cand.Sci. (Ped.), Associate Professor of the Chair of Software Engineering and Computer Technology, ITMO University (49 Kronverkskii Prospekt, Saint Petersburg 197101, Russian Federation), ORCID: https://orcid.org/0000-0003-4236-5991, Scopus ID: 57192154325, SPIN-code: 9554-8251, This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract
Introduction. The digital transformation of education necessitates a rethinking of fundamental pedagogical concepts. The traditional distinction between individualization and personalization of learning requires conceptualization in light of the development of artificial intelligence technologies. The aim of this study is to define a conceptual framework for analyzing the transition from individualization to personalization of learning under the influence of artificial intelligence technologies and to establish the feasibility of achieving true personalization in its philosophical and pedagogical sense using modern systems.
Materials and Methods. The study is based on an interdisciplinary approach. Methods of conceptual, comparative, and systemic analysis are applied. A review of international (Squirrel AI Learning, Carnegie Learning, Knewton) and Russian (Contribution to the Future, university systems) adaptive learning platforms is conducted. Aspects of personalization models, the role of the student and teacher, the flexibility of educational trajectories, and the results achieved are considered. The empirical part consisted of a cross-sectional descriptive and analytical survey of 191 teachers and university professors conducted between October 6 and 27, 2025, at Moscow Pedagogical State University.
Results. Artificial intelligence technologies significantly expand the practical possibilities of an individualized approach, but the personalization they enable remains limited. Current systems primarily adapt the format, pace, and sequence of instruction while maintaining consistent goals. Full personalization, which involves student participation in goal setting and co-creation of the educational trajectory, remains under-utilized. A practical need for a methodology for applying artificial intelligence based solutions to achieve individualization and personalization of learning was identified. Artificial intelligence should be viewed as a new educational environment. True personalization requires changes in pedagogical design, ensuring the transparency of algorithms, and active student participation in goal setting.
Conclusion. The study opens up prospects for developing a theory of digital subjectivity and integrating the humanistic goals of education with the capabilities of technologies artificial intelligence. The results are significant for the academic community, digital education specialists, and educational platform developers.

Keywords: personalized learning, individualized learning, adaptive learning systems, digital transformation of education, personalized AI-based platforms, digital didactics, learner-centered education

Conflict of interest: The authors declare no conflict of interest.

For citation: Karakozov S.D., Ryzhova N.I., Samokhvalova E.A., Gosudarev I.B. From Individualization to Personalization of Education: Theoretical Aspects and Practical Implementation Based on Artificial Intelligence Solutions. Integration of Education. 2026;30(2):346–369. https://doi.org/10.15507/1991- 9468.26302.346-369

Authors’ contribution:
S. D. Karakozov – oversight and leadership responsibility for the research activity planning and execution.
N. I. Ryzhova – formulation of overarching research goals and aims.
E. A. Samokhvalova – specifically visualization.
I. B. Gosudarev – verification as a part of the activity or separate, of the reproducibility of results experiments and other research outputs.

Availability of data and materials. The datasets used and/or analysed during the current study are available from the authors on reasonable request.

All authors have read and approved the final manuscript.

Submitted 02.02.2026;
revised 02.03.2026;
accepted 10.03.2026.

 

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