The role of neural networks in the development of communicative competence of technical science students

Communicative competence has a significant impact on the successful integration of a modern specialist into the professional environment, so its development is one of the priority tasks of educational institutions. At the current stage of modern technological development, AI tools based on neural network models have considerable potential to cope with this task, but for the most effective realization of this potential, it is necessary to create a methodology for their application. This study contributes to the development of the methodology for the application of neural network technologies in the educational process in order to improve the quality of professional training of specialists. The scientific novelty of the work consists in a comprehensive analysis of the effectiveness of applying neural network models to the development of the main components of communicative competence and types of speech activity, taking into account the specific characteristics of students. The following methods were used in the research: content analysis of scientific publications, technical specifications of applications, and reviews of experts and users of software products; pedagogical observation (evaluating how students used neural network technologies in the educational process); online survey (questionnaire) of students to identify their attitude towards the capabilities of AI tools and to collect information on the experience of using neural networks for the development of communicative competence. This research may be of interest to university teachers and researchers dealing with the application of neural network technologies and AI tools. The results of the work can be used in teaching foreign languages at universities to improve the quality of communicative competence development, as well as for the development of educational programs and assessment tools in relevant disciplines.