The effectiveness of adaptive learning systems based on artificial intelligence in STEM disciplines

- Коршевнюк, Т. В. (orcid.org/0000-0003-0430-5808) and Берестовой, І.О. (orcid.org/0000-0002-3843-570X) (2026) The effectiveness of adaptive learning systems based on artificial intelligence in STEM disciplines Педагогічна Академія: наукові записки (29). ISSN 2786-9458

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Abstract

The purpose of the article is to generalize the mechanisms underlying the functioning of artificial intelligence-based adaptive learning systems in STEM disciplines, to determine their impact on learning outcomes, and to identify the main limitations of their pedagogical application. Methods. The methodological basis of the study included the analysis, comparison, generalization, and systematization of contemporary scholarly publications on adaptive learning, intelligent tutoring systems, personalized educational environments, and the use of artificial intelligence in STEM education. An analytical approach was applied to interpret the results, enabling comparisons of different scholarly positions, identification of recurring patterns, and determination of the conditions under which adaptive systems demonstrate the highest effectiveness. Results. The analysis showed that the effectiveness of adaptive systems is determined not by the mere use of artificial intelligence, but by the precision with which diagnostic, corrective, and explanatory functions are integrated within a unified learning environment. The most significant mechanisms of action of adaptive learning systems based on artificial intelligence are diagnosing knowledge gaps among education seekers, adapting the sequence and complexity of tasks to individual capabilities and needs, providing personalized feedback, and generating analytical data for teachers. The most pronounced effect was observed in STEM disciplines characterized by a clear logical sequence and a high degree of interdependence among topics, primarily in mathematics, programming, and related fields. The generalization of the results demonstrated that artificial intelligence-based adaptive learning systems primarily improve the accuracy of task performance, enhance the quality of mastering basic concepts, promote more consistent learning progress, and enable timely correction of typical errors. At the same time, it was found that their impact on motivational indicators and overall engagement is less pronounced than on mastery of learning material and the development of practical skills. Conclusions. Artificial intelligence-based adaptive learning systems should be regarded as an effective tool for enhancing STEM education, provided that their implementation is methodologically sound and pedagogically controlled. The practical value of such systems lies in combining personalization, timely adjustment of the learning trajectory, and the provision of analytical tools that support teachers in the pedagogical guidance of learning. Prospects for further research include a more in depth study of the long-term impact of adaptive systems across different STEM disciplines, comparisons of their effectiveness at different levels of education, and analyses of the ethical and organizational conditions of their use.

Item Type:	Article
Keywords:	personalized learning, intelligent educational systems, educational analytics, individual educational trajectory, mathematics education, programming, digital pedagogy.
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 > 004.9 Application-oriented computer-based techniques Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education > 37.01/.09 Special auxiliary table for theory, principles, methods and organization of education > 37.02 General questions of didactics and method Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 37 Education > 373 Kinds of school providing general education Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 5 Мathematics. natural sciences
Divisions:	Institute of Pedagogics > Department of Biological, Chemical and Physical Education
Depositing User:	лаборант Аліна Хилько
Date Deposited:	25 May 2026 11:36
Last Modified:	25 May 2026 11:36
URI:	https://lib.iitta.gov.ua/id/eprint/749234

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