“ADAPTIVE EDUCATIONAL PLATFORMS: LEVERAGING ARTIFICIAL INTELLIGENCE FOR PERSONALIZED STUDENT LEARNING AND EVALUATION”.

Authors

  • M. Alibekova Lecturer, Department of Computer Engineering and Digital Technologies, Andijan Branch of Kokand University, Uzbekistan.

DOI:

https://doi.org/10.55640/

Keywords:

Artificial intelligence, Student knowledge assessment, Adaptive learning, Personalized learning paths, Educational technologies, Online learning platform.

Abstract

This article examines how a platform was developed to assess student knowledge and create personalized learning paths using artificial intelligence (AI). During the study, students took tests to measure their starting knowledge, and AI algorithms used these results to build adaptive learning paths. The findings showed a significant increase in students' knowledge and a greater mastery of weaker topics. The article explains the platform's structure, how it works, test results, and the effectiveness of its personalized learning paths. It also discusses possible future uses. The research confirms that AI technologies are effective in online and distance education.

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References

1.Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, Ray. (1995). Cognitive Tutors: Lessons Learned. Journal of the Learning Sciences, 4(2), 167–207. https://doi.org/10.1207/s15327809jls0402_2

2.Chen, Y. (2025). Evaluation of the impact of AI-driven personalized learning platform on medical students’ learning performance. Frontiers in Medicine, 12, 1610012. https://doi.org/10.3389/fmed.2025.1610012

3.Yaseen, H., Mohammad, A. S., Ashal, N., Abusaimeh, H., Ali, A., & Sharabati, A.-A. A. (2025). The Impact of Adaptive Learning Technologies, Personalized Feedback, and Interactive AI Tools on Student Engagement: The Moderating Role of Digital Literacy. Sustainability, 17(3), 1133. https://doi.org/10.3390/su17031133

4.Chen, Y. (2025). Evaluation of the impact of AI-driven personalized learning platform on medical students’ learning performance. Frontiers in Medicine, 12, 1610012. https://doi.org/10.3389/fmed.2025.1610012

5.Tan, L. Y., Hu, S., Yeo, D. J., & Cheong, K. H. (2025). Artificial intelligence-enabled adaptive learning platforms: A review. Computers and Education: Artificial Intelligence, 9, 100429. https://doi.org/10.1016/j.caeai.2025.100429

6.Khine, M. S. (2024). Using AI for Adaptive Learning and Adaptive Assessment. In M. S. Khine (Ed.), Artificial Intelligence in Education (pp. 341–466). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-9350-1_3

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Published

2026-06-08

Issue

Vol. 5 No. 6 (2026): Journal of Multidisciplinary Sciences and Innovations

Section

Articles

License

Creative Commons License

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

Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.

How to Cite

“ADAPTIVE EDUCATIONAL PLATFORMS: LEVERAGING ARTIFICIAL INTELLIGENCE FOR PERSONALIZED STUDENT LEARNING AND EVALUATION”. (2026). Journal of Multidisciplinary Sciences and Innovations, 5(6), 477-482. https://doi.org/10.55640/

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