NEURAL NETWORK MACHINE TRANSLATION IN FOREIGN LANGUAGE TEACHING IN TECHNICAL UNIVERSITY

Background. Mass usage of neural-network machine translation services by students of technical universities when studying foreign languages leads to the necessary changes in the working programme content and teaching instruments. Such a perspective causes ambiguous response among educators, which makes this problem relevant under the conditions of digital transformation of higher education. Purpose. The authors aim to provide the results of a theoretical and empirical study of how the participants of the foreign language teaching and learning process respond to the mass implementation of neural network machine translators. Materials and methods. Materials for this article are obtained by the method of questionnaire survey, which is conducted among instructors and students of Novosibirsk technical universities in 2024. For a deeper understanding concerning the attitude of respondents to the implementation of neural network machine translation apps in the teaching and learning process, retrospective conversations with students and semi-formalised interviews with instructors of Foreign Language Departments are conducted. Results. The findings suggest a predominantly positive attitude of the instructors and students of Novosibirsk technical universities to the implementation of neural network machine translation services in teaching and learning foreign languages. Although there is a tendency to use such services to translate large pieces of their own texts, many students are focused on analysing the quality and editing their translates. The instructors, in their turn, note that neural network machine translators do not solve the problem of linguistic difficulties, especially when translating industry-specific texts. However, they find no reason to ban their students from using neural network machine translation services in classroom and extracurricular activities. Moreover, the instructors emphasise that the use of these instruments should be taught on purpose. Taking into account the respondents’ opinions, the authors offer to add a separate module devoted to the proper use of neural network machine translation services to the working programmes, which will contribute to the development of students’ critical thinking when solving academic, professional and research tasks.