THE USE OF ARTIFICIAL INTELLIGENCE IN TEACHING A COURSE ON TRANSLATING SPECIALIZED TEXTS INTO ENGLISH

Abstract

In the context of rapid technological development and globalization, proficiency in English has become an increasingly important aspect of professional growth and competitiveness in the labor market. One of the key competencies required in many fields is the ability to effectively translate specialized texts. This skill demands not only language proficiency but also an understanding of domain-specific terminology and context. However, as practice shows, students exhibit varying levels of knowledge, skills, and learning needs. The organization of the educational process often fails to address individual strengths, weaknesses, and learning styles, resulting in insufficient adaptation to students' personal needs. This lack of personalization may lead to reduced learning efficiency, necessitating the search for innovative approaches. Among the most relevant is the use of artificial intelligence (AI), which significantly transforms the learning process by opening new opportunities for improving education quality, ensuring individualized approaches, and automating routine tasks. AI enables automatic identification of individual learning needs and provides personalized materials and assignments tailored to the areas requiring the most attention for each student.

The goal of this article is to explore the opportunities and prospects of using artificial intelligence in teaching a course on the translation of specialized texts into English. This includes identifying the advantages, challenges, and limitations, analyzing potential developments, presenting methods and approaches, and assessing the effectiveness of AI compared to traditional teaching methods.

To investigate the use of artificial intelligence (AI) in teaching a course on the translation of specialized texts into English, several intelligent learning systems and tools were selected. The primary platforms utilized in the study included ChatGPT, Google Translate, DeepL Translator, Grammarly, Microsoft Translator, and SDL Trados Studio. The research was conducted in several stages, each involving specific methods and tools for data collection and analysis.

Statistical methods and qualitative analysis were employed to evaluate student feedback and assess the quality of translations. Survey data were analyzed using descriptive statistics to identify general trends and levels of student satisfaction.

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References:

1. Smith, J. (2020). Artificial Intelligence in Education: Enhancing Learning and Teaching. Educational Technology Research and Development, 68 (2): 345-360.
2. Jones, A. (2019). Personalized Learning with AI: Adapting to Student Needs. Journal of Learning Analytics, 6 (1): 23-45.
3. Brown, L. (2018). The Role of AI in Personalized Education. Computers & Education 123: 212-221.
4. Chen, X., Zhang, Y., & Liu, T. (2020). Machine Translation with Neural Networks: A Comprehensive Review. Journal of Artificial Intelligence Research, 68, 123-145. doi:10.1613/jair.1.11853
5. Tsai, C. (2020). The Impact of Artificial Intelligence on Language Learning: A Review. Language Learning & Technology, 24 (3): 35-50. doi:10.1016/j.langtec.2020.08.004
6. Miura, Y., Nakamura, K., & Tanaka, M. (2021). Advancements in Machine Translation: Evaluating the Effectiveness of AI Tools in Educational Contexts. Computers & Education, 164, doi:10.1016/j.compedu.2021.104140