This article provides a comprehensive analysis of modern algorithms aimed at improving the functionality of multimedia educational platforms. The main goal of the study is to identify the potential of methods based on artificial intelligence, learning analytics, and big data to increase the efficiency of educational systems. Special attention is given to adaptive learning systems and recommendation algorithms, as well as their role and advantages in personalizing students’ learning processes. The article also examines the impact of platform algorithms on student motivation, the accessibility of learning materials, and their effectiveness in improving the quality of education. The results demonstrate that these technologies enhance learners’ cognitive engagement, allow for the individualization of educational content, and support the optimization of the learning process. The study also discusses pedagogical and organizational aspects of implementing such technologies. Alongside the benefits of AI-based systems, the challenges and limitations associated with integrating them into the educational environment are highlighted. The authors argue that the development of multimedia platforms should focus not only on technical improvements but also on enhancing educational quality. The article suggests future directions for further personalization of the learning process through the use of virtual advisors, intelligent chatbots, and adaptive assessment systems.

MAKHMUTOV A.N.

Master’s degree student, K.Zhubanov Aktobe regional university, Aktobe, Kazakhstan.

E-mail: ali.makhmutov20@gmail.com, https://orcid.org/0009-0000-8415-4733

KEREYEV A.K.

PhD, associate professor, department of computer science and information technologies, K.Zhubanov Aktobe regional university, Aktobe, Kazakhstan.

E-mail: akereyev@zhubanov.edu.kz, https://orcid.org/0000-0002-8283-5807

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