Intelligent Data Processing Technologies as a Basis for Modeling Digital Avatars in the Educational Environment

Objective. To substantiate the conceptual foundations for creating digital avatars in the educational environment based on intelligent data collection and processing technologies. Methods. Integration of sensor technologies, IoT, Big Data, machine learning algorithms, comparative analysis of physical and analytical modeling approaches. Results. It is shown that combining physical modeling and data analytics enables the development of flexible and adaptive digital avatars reflecting individual user behavior. Scientific novelty. The study proves that exclusively analytical models are insufficient and that integrated modeling provides a holistic behavioral simulation. Practical significance. The proposed approach can be applied in digital university ecosystems, distance learning platforms, and educational analytics research to enhance personalization and learning efficiency.