Authors
- Vishnevskaya Ekaterina M. PhD (Pedagogy)
- Ivanova Anna M. PhD (Philology)
Annotation
This paper explores the challenges associated with natural language processing using software programs that employ generative artificial intelligence algorithms. The authors analyze the automated process of written translation facilitated by these software products and examine the implications of such automation for the training of would-be translators, particularly in the context of enhancing their digital competencies. The study underscores the necessity of equipping students with the ability to consciously select and implement diverse information technologies throughout all phases of their professional endeavors. Furthermore, the research explores the phenomenon of text comprehension from multiple perspectives, including hermeneutics, psychology, linguistic didactics, as well as cognitive and computational linguistics. The authors investigate the underlying causes of errors made by students during the post-editing of machine translation outputs generated by neural machine translation (NMT) systems and large language models (LLMs). The methodological approach employed in this study encompasses analysis, synthesis, modeling, and comparative methods, thereby facilitating a comprehensive interpretation of the collected empirical data. The results indicate notable distinctions between machine translation and conventional professional translation, particularly highlighting the limitations in full text comprehension that stem from extralinguistic factors, including background knowledge, pragmatics, and axiology. Despite the substantial advancements in text analysis introduced by neural machine translation systems, the post-translation editing process remains a crucial final step. These
findings emphasize the importance of incorporating post-editing training into the curricula of aspiring translators to better prepare them for the practical use of machine translation in real-world scenarios.
How to link insert
Vishnevskaya, E. M. & Ivanova, A. M. (2025). COMPREHENSION AS A DIALOGUE WITH THE TEXT: GENERATIVE ARTIFICIAL INTELLIGENCE IN TRANSLATION TRAINING Bulletin of the Moscow City Pedagogical University. Series "Pedagogy and Psychology", 2 (58), 190. https://doi.org/10.24412/2076-913X-2025-258-190-202
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