Adaptive management of educational system personalization based on multidimensional data

The article analyzes the possibilities of using predictive analytics as the basis for building adaptive management of a data-based educational system (Data-Driven education). Theoretical and methodological aspects of the possibility of integrating machine learning algorithms into the educational process are considered. Key benefits of integrating predictive analysis and adaptive management have been identified, as well as ethical, technical and methodological limitations of their use in the educational process. It is shown that neural network models act as a technological core of training based on multidimensional data, providing the ability to process and analyze multidimensional educational data in real time. The authors emphasize the need to adapt successful predictive analytics and adaptive management practices to improve the effectiveness.