The article analyses, with reference to English, the impact of digital learning tools on translation quality and on the professional competence of trainee translators. The relevance of the study stems from the rapid entry of computer-assisted translation systems, neural machine translation and AI-based assistive tools into the educational process, while it remains insufficiently described how exactly these tools affect translation quality and which components of competence they develop or weaken. The aim of the research is to classify types of digital tools, to determine the effect of each on translation quality, and to relate them to the components of established competence models. The material comprises a corpus of scholarly sources on translation competence theory, the didactics of translation technology and machine translation post-editing. Descriptive, comparative-analytical and structural-functional methods were applied, together with content analysis of the sources. Five types of digital tools were identified, and for each a quality effect and a risk zone are described. Three principal risks were established: the flattening of style, over-reliance on the tool, and the false confidence produced by fluent machine output. On this basis a three-stage methodological model and assessment criteria are proposed. The practical value of the study lies in the applicability of the model to the design of translation curricula and teaching materials.

digital learning tools, translation quality, professional competence, computer-assisted translation, neural machine translation, post-editing, didactics of translation technology, English.

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