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Abstract
<jats:p>This paper provides an in-depth investigation into the development of an adaptive educational process management algorithm based on artificial intelligence technologies. Given the diversity in students' initial knowledge levels, cognitive assimilation rates, and learning engagement, the need for personalized education is increasingly growing. The study proposes a multi-stage management algorithm based on the collection, processing, and analysis of multidimensional student parameters, including test results, practical assignments, independent study, attendance, LMS platform activity, and task completion efficiency. Through the integration of machine learning models, the student's knowledge level is dynamically classified, and tailored learning resources are generated. The algorithm operates on the principle of a continuous feedback loop.</jats:p>