The use of artificial intelligence in teaching English to students of non-linguistic specialties with varying levels of language proficiency
The article is devoted to the study of the application of artificial intelligence (AI) technologies for developing oral speech skills in English among non-philology students with varying levels of language proficiency. The aim of this research is to demonstrate specific ways to integrate generative neural networks into the educational process based on the textbook "English Language. Country Studies" for the Geography Faculty of Lomonosov Moscow State University, which contains rich and informative material about different countries, their geography, history, and traditions. The methodologies for generating, simplifying, and editing texts on specified topics (using texts about China as an example) with the help of neural networks for levels from A1 to B1 are examined, as well as ways to create accompanying didactic materials (for example, lists of key vocabulary). The methodology of the research is based on linguistic analysis of practical experience in using AI for adapting educational materials. It is shown that AI allows for the effective creation and adaptation of authentic texts corresponding to the language level of students, which helps to overcome difficulties in preparing oral presentations. The use of AI in teaching stimulates speech production, increases the independence and motivation of learners, enabling them to become active participants in the learning process, create interesting texts in English, and make presentations in classes. The results are applicable in the practice of teaching foreign languages in non-linguistic universities for personalizing learning and developing speech skills. The novelty lies in the development and testing of specific algorithms for students to work with AI for adapting country studies content, which expands the didactic potential of traditional textbooks and contributes to the formation of readiness for intercultural communication.
Authors
- Irina Oks
- А. В. Комарова
Publication Details
- Journal
- Litera
- Published
- 2025-10-01
- DOI
- https://doi.org/10.25136/2409-8698.2025.10.76463
- Primary Topic
- Innovations in Education and Learning Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00