Application of artificial intelligence methods in the formation of individualized learning pathways

The article considers the potential application of artificial intelligence methods within a distance learning management system. A structural framework of an intelligent distance learning management system is presented. The paper identifies key directions for the use of ontological modeling within this system. Approaches to solving the problem of forming individualized learning pathways are analyzed, based on a knowledge graph of an electronic course. Additionally, the study explores the development of vector representations of the knowledge graph and the use of neural networks to analyze learners’ digital footprints. The research objectives include: constructing a knowledge graph for an electronic course; applying vector representations to the vertices and relations of the knowledge graph; and selecting the architecture and structure of a neural network and training it to generate individualized learning pathways. The proposed approach employs a knowledge graph of the electronic course that incorporates both course parameters and data on learners who have completed the course. Representing graph elements as vectors enables the application of machine learning techniques, including neural network models, to the analysis of the subject domain. A methodological example illustrating the implementation of the proposed approach is provided.