Published June 8, 2026 | Version v1
Dataset Open

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

Authors/Creators

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

Description

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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Additional details

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
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