Keywords
methodological foundations of education
individualization of learning
competency-based approach
digital transformation of education
individual educational pathways
How to Cite
Abstract
Abstract. The article provides a theoretical analysis of the methodological foundations of organizing personalized learning in general secondary education institutions, defining its essence, main principles, and pedagogical conditions for implementation in the modern educational environment. Personalized learning is considered as an integral educational model that involves taking into account students’ individual needs, abilities, interests, and learning goals, ensuring their active subject position and the formation of individual educational pathways.
Based on systematic theoretical analysis, historical-pedagogical review, comparative analysis, and generalization of scientific sources, the study examines the evolution of ideas of educational personalization, from the concepts of individualization and differentiation of learning to modern competency-based, activity-oriented, and digital models of educational process organization. It has been established that the methodological foundation of personalized learning is based on the integration of competency-based, activity-oriented, practice-oriented, evidence-based, and digital approaches.
The article substantiates the importance of formative assessment, mastery learning, pedagogical feedback, and digital technologies as tools for ensuring students’ individual development. At the same time, it is determined that digitalization of education is not an independent condition for personalization but serves as a means of implementing a pedagogically grounded learning model. Particular attention is paid to the challenges of implementing personalized learning in Ukrainian general secondary education institutions, including teachers’ professional readiness, digital inequality, adaptation of international educational models to the national context, and ensuring a safe educational environment.
The study concludes that personalized learning is a promising strategic direction for modernizing general secondary education, contributing to the development of competencies, autonomy, self-regulation, and students’ ability for lifelong learning. Prospects for further research are identified, focusing on the development of practical models of personalization, improvement of teacher training, and exploration of the potential of artificial intelligence and adaptive educational technologies.
References
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Dewey, J. (1938). Experience and education. Macmillan. https://archive.org/details/experienceeducat0000dewe
Guskey, T. R. (2010). Lessons of mastery learning. In J. H. McMillan (Ed.), Formative classroom assessment: Theory into practice (pp. 31–43). Teachers College Press.
Guskey, T. R., & Brookhart, S. M. (2018). What we know about grading: What works, what doesn’t, and what’s next. ASCD.
Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge. https://doi.org/10.4324/9780203887332
Israni, A., Sales, A. C., & Pane, J. F. (2018). Mastery learning in practice: A descriptive analysis of learning systems. arXiv. https://doi.org/10.48550/arXiv.1802.08616
Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall. https://www.scirp.org/reference/referencespapers?referenceid=1223948
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press. https://doi.org/10.1017/CBO9780511815355
Malykhin, O. V., & Cherniuk, A. P. (2026). Conceptual and categorical field of the problem of implementing interactive learning strategies in the professional training of students of philological specialities. Perspectives and Innovations of Science, 9 (39). https://doi.org/10.52058/2786-6165-2025-9(39)-1398-1406
Malykhin, O., Aristova, N., & Dybkova, L. (2025a). Using ai tools for personalising learning in the english language classroom: computer science undergraduate students’ perceptions. Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference, (3), 213-217. https://doi.org/10.17770/etr2025vol3.8536
Malykhin, O., Aristova, N., & Dybkova, L. (2025b). Developing computer science undergraduate students’ communicative and self-expression skills: Digital vs. traditional storytelling methods. Environment. Technology. Resources. Proceedings of the 16th International Scientific and Practical Conference, (3), 219–224. https://doi.org/10.17770/etr2025vol3.8559
Mulder, M. (2017). Competence theory and research: A critical review. In M. Mulder (Ed.), Competence-based vocational and professional education (pp. 107–137). Springer. https://doi.org/10.1007/978-3-319-41713-4_5
OECD. (2005). The definition and selection of key competencies: Executive summary. OECD Publishing. https://www.oecd.org/pisa/definition-selection-key-competencies-summary.pdf
OECD. (2019). OECD Learning Compass 2030: A series of concept notes. OECD. https://www.oecd.org/en/data/tools/oecd-learning-compass-2030.html
Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books. https://archive.org/details/reflectivepracti0000scho
Slavin, R. E. (2002). Evidence-based education policies: Transforming educational practice and research. Educational Researcher, 31(7), 15–21. https://doi.org/10.3102/0013189X031007015
Slavin, R. E. (2008). Evidence-based reform in education: What works and what doesn’t? Educational Researcher, 37(7), 474–479. https://doi.org/10.3102/0013189X08327366
Topuzov, O., Malykhin, O., Onopriienko, O., & Lipchevska, I. (2025). Comparative analysis of the effectiveness of distance and in-person learning of Computer Science within the adaptation cycle of basic secondary education. Information Technologies and Learning Tools, 110(6). https://doi.org/10.33407/itlt.v110i6.6317
UNESCO International Institute for Educational Planning. (2015). Competency-based curriculum and assessment. UNESCO IIEP Learning Portal. https://learningportal.iiep.unesco.org/en/issue-briefs/improve-learning/competency-based-approaches
Bloom, B. S. (1968). Learning for mastery. Evaluation Comment, 1(2), 1–12. https://files.eric.ed.gov/fulltext/ED053419.pdf (in English).
Dewey, J. (1938). Experience and education. Macmillan. https://archive.org/details/experienceeducat0000dewe (in English).
Guskey, T. R. (2010). Lessons of mastery learning. In J. H. McMillan (Ed.), Formative classroom assessment: Theory into practice (pp. 31–43). Teachers College Press (in English).
Guskey, T. R., & Brookhart, S. M. (2018). What we know about grading: What works, what doesn’t, and what’s next. ASCD (in English).
Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge. https://doi.org/10.4324/9780203887332 (in English).
Israni, A., Sales, A. C., & Pane, J. F. (2018). Mastery learning in practice: A descriptive analysis of learning systems. arXiv. https://doi.org/10.48550/arXiv.1802.08616 (in English).
Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall. https://www.scirp.org/reference/referencespapers?referenceid=1223948 (in English).
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press. https://doi.org/10.1017/CBO9780511815355 (in English).
Malykhin, O. V., & Cherniuk, A. P. (2026). Conceptual and categorical field of the problem of implementing interactive learning strategies in the professional training of students of philological specialities. Perspectives and Innovations of Science, 9 (39). https://doi.org/10.52058/2786-6165-2025-9(39)-1398-1406 (in English).
Malykhin, O., Aristova, N., & Dybkova, L. (2025a). Using ai tools for personalising learning in the english language classroom: computer science undergraduate students’ perceptions. Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference, (3), 213-217. https://doi.org/10.17770/etr2025vol3.8536 (in English).
Malykhin, O., Aristova, N., & Dybkova, L. (2025b). Developing computer science undergraduate students’ communicative and self-expression skills: Digital vs. traditional storytelling methods. Environment. Technology. Resources. Proceedings of the 16th International Scientific and Practical Conference, (3), 219–224. https://doi.org/10.17770/etr2025vol3.8559 (in English).
Mulder, M. (2017). Competence theory and research: A critical review. In M. Mulder (Ed.), Competence-based vocational and professional education (pp. 107–137). Springer. https://doi.org/10.1007/978-3-319-41713-4_5 (in English).
OECD. (2005). The definition and selection of key competencies: Executive summary. OECD Publishing. https://www.oecd.org/pisa/definition-selection-key-competencies-summary.pdf (in English).
OECD. (2019). OECD Learning Compass 2030: A series of concept notes. OECD. https://www.oecd.org/en/data/tools/oecd-learning-compass-2030.html (in English).
Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books. https://archive.org/details/reflectivepracti0000scho (in English).
Slavin, R. E. (2002). Evidence-based education policies: Transforming educational practice and research. Educational Researcher, 31(7), 15–21. https://doi.org/10.3102/0013189X031007015 (in English).
Slavin, R. E. (2008). Evidence-based reform in education: What works and what doesn’t? Educational Researcher, 37(7), 474–479. https://doi.org/10.3102/0013189X08327366 (in English).
Topuzov, O., Malykhin, O., Onopriienko, O., & Lipchevska, I. (2025). Comparative analysis of the effectiveness of distance and in-person learning of Computer Science within the adaptation cycle of basic secondary education. Information Technologies and Learning Tools, 110(6). https://doi.org/10.33407/itlt.v110i6.6317 (in English).
UNESCO International Institute for Educational Planning. (2015). Competency-based curriculum and assessment. UNESCO IIEP Learning Portal. https://learningportal.iiep.unesco.org/en/issue-briefs/improve-learning/competency-based-approaches (in English).
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