GENERATIVE NEURAL NETWORKS AND THEIR USE IN THE SYSTEM OF INCLUSIVE EDUCATION (ON THE EXAMPLE OF THE EU COUNTRIES, THE USA AND CANADA)

Kutlikova I., Verezubova N., Kishkinova O.

The study relevance is due to the increasing need to adapt educational systems to the needs of students with special needs and disabilities. The research goal is to analyze the possibilities of using generative neural networks (GenAI) in the system of inclusive education on the example of foreign countries. generative neural networks in education, in particular, for the creation of personalized learning materials, adaptive interfaces and support tools for students with special educational needs. As part of the study of generative neural networks and their application in inclusive education, both theoretical and empirical methods were used. The theoretical analysis included the study of scientific literature, regulations and strategic documents of the EU countries, the USA and Canada related to inclusive education and the use of artificial intelligence. Particular attention was paid to the analysis of works on the architectures of generative neural networks and their adaptation for tasks related to inclusive education. Based on the results, the following conclusions were formulated: generative neural networks have significant potential for improving inclusive education, as the experience of the EU countries, the United States and Canada has shown. In particular, such networks have been successfully used to generate individualized learning materials that take into account different learning styles and specific educational needs.

Keywords:inclusion, education, inclusive environment, generative neural networks, machine learning