Methods for Personalized Student Learning in Modern Educational Space

Authors

  • Iryna Zhukevych Department of English for Humanities, Faculty of Linguistics, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine https://orcid.org/0000-0002-4109-4336
  • Natalia Biriukova Department of English for Humanities, Faculty of Linguistics, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine https://orcid.org/0000-0001-7193-5901

DOI:

https://doi.org/10.46299/j.isjel.20250404.01

Keywords:

personalized learning, modern technologies, adaptive learning, microlearning, individualized learning plans, project-based activities, feedback, gamification, artificial intelligence, differentiated instruction, project-based and problem-based learning

Abstract

This article delves into the concept of personalized learning within the context of contemporary higher education, focusing on its orientation towards individual needs. Thanks to modern technological advancements, including breakthroughs in big data, learning analytics, and the development of intelligent tutoring systems, the potential of personalized learning has significantly expanded. These technologies enable a deep and dynamic adaptation of the educational experience, taking into account each student's unique abilities, learning objectives, and individual preferences. This is a fundamental prerequisite for enhancing the effectiveness and transparency of the educational system. Our research provides a detailed analysis of leading conceptual approaches to personalized learning, specifically adaptive learning, differentiated instruction, project-based and problem-based learning, and competency-based education. We examine a range of specific methods and tools for implementing personalization, including individualized learning paths, differentiation of assignments, mentoring and tutoring, as well as the crucial role of adaptive learning platforms and artificial intelligence. Particular attention is paid to the challenges of implementing personalized learning in higher education institutions. The study identifies significant barriers such as limitations in technological infrastructure, insufficient readiness among faculty, ethical and legal aspects of using big data, systemic conservatism and resistance to change, as well as methodological and financial complexities. Despite these challenges, the substantial benefits of personalized learning are emphasized: it contributes to increased student motivation, improved academic results, the development of self-regulated learning skills, and more effective preparation for the demands of the modern labor market. It is demonstrated that personalized learning is not merely an innovative trend but an imperative, strategic necessity for the contemporary higher education system. Its purposeful and effective implementation will enable higher education institutions not only to align with global educational transformations but also to actively prepare highly qualified specialists who possess adaptability and the capacity for continuous self-development in a dynamic global labor market.

References

Бойченко, Оксана. (2021). Перспективи використання інтелектуальних навчальних систем в закладах освіти. Actual Problems in the System of Education General Secondary Education Institution – Pre-University Training – Higher Education Institution. 74-76. 10.18372/2786-5487.1.15827.

Бондаренко, Л. Ю. (2022). Інтелектуальні системи навчання в освітньому процесі. Розвиток сучасної науки та освіти : реалії, проблеми якості, інновації. ТДАТУ. 429–433. http://elar.tsatu.edu.ua/handle/123456789/16770

Гороховський, О. (2010). Інтелектуальні системи. Навчальний посібник. Вінниця. ВНТУ. 194 с.

Лаптєва, М.В. (2015). Інтелектуальні навчальні системи в практиці підготовки іноземних студентів. Засоби навчальної та науково-дослідної роботи, (45), 35–45. https://doi.org/10.5281/zenodo.56255

Прудка, О.В. (2006). Адаптивні та інтелектуальні системи для дистанційного навчання. Актуальні проблеми економіки, (10), 184–189.

Фендьо, О. (2023). Сучасні онлайн-інструменти для організації інтерактивного навчання. Actual Problems in the System of Education: General Secondary Education Institution – Pre-University Training – Higher Education Institution, (3), 620–632. https://doi.org/10.18372/2786-5487.1.17749

Peter, S.E., Bacon, E., & Dastbaz, M. (2010). Adaptable, personalised e‐learning incorporating learning styles. Campus-Wide Information Systems, 27(2), 91–100. https://doi.org/10.1108/10650741011033062

Zhou, Y. (2025). Machine Learning-Based English Learning Behaviour Pattern Recognition and Personalised Teaching Strategies for College Students. Journal of Combinatorial Mathematics and Combinatorial Computing, 127a, 503–522. https://doi.org/10.61091/jcmcc127a-030

Adams, C. M., Cotabish, A., & Dailey, D. (2021). Differentiated Learning Experiences. У A Teacher's Guide to Using the Next Generation Science Standards with Gifted and Advanced Learners. 44–90. https://doi.org/10.4324/9781003238522-3

Oliveira, J., Panontim, L., Fonseca, V. H., Gonçalves, P., Napoleão, D., & Alcântara, M. (2021). Project-Based Learning. International Journal for Innovation Education and Research, 9(7), 224–237. https://doi.org/10.31686/ijier.vol9.iss7.3244

Permatasari, C. P., Yerizon, Y., Arnawa, I. M., & Musdi, E. (2020a). Improving Students’ Problem-Solving Ability through Learning Tools Based on Problem Based Learning. Journal of Physics: Conference Series, 1554, 012017. https://doi.org/10.1088/1742-6596/1554/1/012017

Oroszi, T. (2020). Competency-Based Education. Creative Education, 11(11), 2467–2476. https://doi.org/10.4236/ce.2020.1111181

Саган, О. В. (2025). Організація персоналізованого навчання за допомогою штучного інтелекту. Collection of Research Papers Pedagogical sciences, (108), 37–43. https://doi.org/10.32999/ksu2413-1865/2024-108-6

Гнатик, К., & Фодор, К. (2023). Особливості застосування сучасних підходів у вивченні іноземних мов. Інноваційна педагогіка, (59), 113–116. https://doi.org/10.32782/2663- 6085/2023/59.23

Dutta, S., Ranjan, S., Mishra, S., Sharma, V., Hewage, P., & Iwendi, C. (2024). Enhancing educational adaptability: A review and analysis of AI-driven adaptive learning platforms. 2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM), 1–5. IEEE. https://doi.org/10.1109/ICIPTM59628.2024.10563448

Дзень, В., Борзов, Ю., & Дзень, Д. (2024). Інтеграція smart-систем в освітнє середовище закладів вищої освіти. Вісник ЛДУБЖД, 30, 56–66. https://doi.org/10.32447/20784643.30.2024.06

Ouyang, F., & Zhang, L. (2024). AI-driven learning analytics applications and tools in computer-supported collaborative learning: A systematic review. Educational Research Review, 44, 100616. https://doi.org/10.1016/j.edurev.2024.100616

Дроздов, Д. А., & Калайда, Н. С. (2025). Машинне навчання та штучний інтелект: можливості та виклики. Радіоелектроніка та молодь у XXI столітті: матеріали 29-го Міжнародного молодіжного форуму, 16–19 квітня 2025 р. (Т. 6, с. 410–412). Харківський національний університет радіоелектроніки. https://openarchive.nure.ua/handle/document/30890

Published

2025-08-01

How to Cite

Zhukevych, I., & Biriukova, N. (2025). Methods for Personalized Student Learning in Modern Educational Space. International Science Journal of Education & Linguistics, 4(4), 1–10. https://doi.org/10.46299/j.isjel.20250404.01

Issue

Section

Theory, practice and methods of education