Prospects for using neural networks in foreign language classes at higher education institutions

the purpose of the study is to determine the possibilities of using neural networks as an innovative tool for creating educational content and a means of organizing an interactive educational environment in foreign language classes at a university. For a better understanding of the technical aspects of using neural networks in teaching foreign languages, an overview of the main types and architectures of relevant neural networks used for processing natural language is provided. The scientific novelty of this study lies in the fact that it presents for the first time 3 different ways of using neural networks for conducting foreign language classes and preparing for them (personalized learning, automated assessment and involving language assistants). In addition, the results of an experimental study are presented demonstrating the effectiveness, quality, disadvantages and problems of the above methods of using neural networks in the educational process of higher education. The general conclusions emphasize the importance and prospects of using neural networks to improve the teaching of foreign languages in higher education institutions, but also indicate the need for careful preparation and support of teachers and students from both university administration and the state, which is necessary for the successful implementation of these innovations.

neural networks, artificial intelligence, foreign language, personalized learning, automated assessment, language assistants