Tepla, O., & Dubrovina, I.
(2026).
Large language models in training of philologists and translators.
Humanities Studios: Pedagogy, Psychology, Philosophy,
14(2),
32-47.
https://doi.org/10.31548/hspedagog/2.2026.32
Digitisation of the education sector has modernised the need to determine the impact of large language models based on artificial intelligence on the professional training of philologists and translators. Use of these technologies has significantly modified the content and structure of educational components, the methodology for developing translation competence, and the requirements for modern translators in line with market needs. The study aimed to analyse the role of the use of large language models based on artificial intelligence in the professional training of future philologists and translators. The methodological basis of the scientific research was the methods of critical analysis of scientific sources on the subject under study and comparison of educational practices. The results of the research showed that the use of large language models for teaching foreign languages and translation contributed to the personalisation of learning, improved the accuracy and quality of translation, self-education of students, the development of their critical thinking and the automation of the process of assessing their performance. At the same time, a range of challenges and risks were identified in the application of these technologies in the educational process: inaccurate translation, direct dependence on technical infrastructure, non-compliance with the principles of academic integrity, and insufficient effectiveness in the formation of translation competence, especially general educational background knowledge. The study also established that the effectiveness of using large language models largely depends on the level of digital literacy of students and pedagogical support for their application in the educational process. The need to develop skills for the responsible and ethical use of artificial intelligence tools as part of the professional training of future translators has been emphasised. The practical significance of the conclusions is determined by the identification of ways to integrate large language models into the professional training of future philologists and translators
digital competence; information technology; neural machine translation; translation studies; critical thinking; educational process; artificial intelligence