Chapter ХІV. Modeling the efficiency of ai-based adaptive learning

Pashchenko, Oleksandr (orcid.org/0000-0003-3296-996X), Koroviaka, Yevhenii (orcid.org/0000-0002-2675-6610), Kirin, Roman (orcid.org/0000-0003-0089-4086) and Khomenko, Volodymyr (orcid.org/0000-0002-3607-5106) (2025) Chapter ХІV. Modeling the efficiency of ai-based adaptive learning (1). ІЦО НАПН України, м. Київ, Україна. ISBN 978-617-8330-53-8

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Abstract

The rapid advancement of artificial intelligence (AI) has significantly influenced various sectors, including education. AI-driven adaptive learning systems offer personalized educational experiences by analyzing students’ learning patterns and adjusting content accordingly. This study focuses on developing a mathematical model for AI-based adaptive learning, incorporating machine learning techniques such as Bayesian Knowledge Tracing (BKT) and reinforcement learning to assess knowledge levels, predict learning trajectories, and optimize content delivery. The research includes computational modeling to evaluate the effectiveness of adaptive learning compared to traditional methods. The findings indicate that AI-based adaptive learning improves knowledge retention, accelerates time-to-mastery, and enhances student engagement through personalized content adaptation. By integrating real-time feedback mechanisms and predictive analytics, this model demonstrates the potential of AI to revolutionize modern education, making learning more efficient and student-centered. The study’s outcomes provide valuable insights for educators and policymakers seeking to implement AI-driven adaptive learning systems in educational institutions.

Item Type:	Book
Additional Information:	Pashchenko Oleksandr, Koroviaka Yevhenii, Kirin Roman, Khomenko Volodymyr. Chapter ХІV. Modeling the efficiency of ai-based adaptive learning. Artificial Intelligence in Education. Part 1 : Monograph / [Collective of authors]; edited by Iatsyshyn A. – Kyiv : IDE NAES Ukraine, 2025. Pp. 202-213. ISBN 978-617-8330-53-8
Keywords:	AI in education, adaptive learning, machine learning, Bayesian Knowledge Tracing, personalized learning.
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education > 378 Higher education. Universities. Academic study
Divisions:	Institute for Digitalisation of Education > Generic resouse
Depositing User:	д.пед.н. Анна Яцишин
Date Deposited:	06 Jan 2026 14:48
Last Modified:	08 Jan 2026 10:51
URI:	https://lib.iitta.gov.ua/id/eprint/748072

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