MONITORING MACHINE-TRANSLATION DEPENDENCE IN THE ONLINE TRAINING OF FUTURE PHILOLOGISTS

The objective of this article is to examine the most effective and expedient methods for identifying instances of hidden machine translation (MT) usage by student translators in their translation assignments and examinations. Additionally, the article aims to propose a system of incentives to reduce students' reliance on MT. This initiative was prompted by the recognition that the advancement of students' translation proficiency necessitates the balanced development of both their technological competence and their creative abilities. Method. A mixed-methods study was conducted with 34 undergraduate philology students at the V.N. Karazin Kharkiv National University. The study was part of a course on legal translation. Throughout the semester, the students' translation assignments and examinations were evaluated using a computer program designed to identify indications of MT. The extent of MT was considered in the assessment of the aforementioned translations, using a scale developed specifically for this purpose. Findings. The results substantiate the assertion that the proposed methodology serves to curtail students' reliance on MT, while simultaneously fostering the growth of their creative abilities within the context of translation. By the conclusion of the semester, the proportion of matches between the majority of the students' target texts and their MT counterparts had decreased to levels typically observed in texts translated without the use of MT. Implications for Research and Practice. The proposed methodology has the potential to be employed in online translation courses with the objective of reducing students' reliance on MT. Further research could be conducted to investigate the applicability of this methodology in different educational settings.