Teaching agricultural university students a professional foreign language using technological solutions based on artificial intelligence

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Importance. The use of artificial intelligence (AI)-based technological solutions for specific aspects of a foreign language or types of speech activity is currently one of the most relevant vectors in the development of foreign language teaching methodology. The rapidly growing body of research by domestic and international scientists, dedicated to determining the linguodidactic potential of specific AI tools and step-by-step teaching methodologies, provides a necessary scientific foundation for creating models of systematic and comprehensive foreign language instruction based on AI. This involves integrating students’ language work with AI into traditional teaching. The aim of the study is to develop a methodology for comprehensive teaching of professional foreign language to students of an agricultural university using AI-based technological solutions.

Materials and Methods. The study is conducted at Voronezh State Agrarian University named after Emperor Peter the Great. The participants are first-year students enrolled in the degree program 35.03.06 – “Agricultural Engineering”. In the control group (N = 38), a traditional methodology for teaching professional foreign language is used, based on the principles of Language for Specific Purposes with elements of Content and Language Integrated Learning. In the experimental group (N = 38), in addition to the traditional methodology, students engaged in practice with AI-based technological solutions. This practice took place outside of class hours. Mathematical processing of the results is performed using Student’s t-test method.

Results and Discussion. The experimental study confirmed the effectiveness of the author’s methodology for teaching professional foreign language to agricultural university students by supplementing traditional instruction with extracurricular practice using AI-based technological solutions. Statistical analysis of the results at the control stage revealed the effectiveness of the innovative method across all five diagnostic indicators: acquisition of professional vocabulary (t = 3.43 at p ≤ 0.05), mastery of grammatical structures (t = 2.91 at p ≤ 0.05), further reading skills’ development (t = 2.91 at p ≤ 0.05), oral dialogic speech (t = 3.95 at p ≤ 0.05), written monologic speech (t = 3.68 at p ≤ 0.05).

Conclusion. The novelty of the study lies in the development and validation of a comprehensive methodology for teaching professional foreign language to agricultural university students using AI-based technological solutions. The prospects of the research are that its results can be utilized in designing models for integrated foreign language instruction for students of both linguistic and non-linguistic degree programs and specialties.

作者简介

T. Baydikova

Voronezh State Agrarian University named after Emperor Peter the Grea

编辑信件的主要联系方式.
Email: november22@rambler.ru
Tatiana V. Baydikova, Cand. Sci. (Education), Associate Professor of Russian and Foreign Languages Department1 Michurina St., Voronezh, 394087 俄罗斯联邦

A. Solomatina

Voronezh State Agrarian University named after Emperor Peter the Grea

Email: asyachge@mail.ru
Anna G. Solomatina, Cand. Sci. (Education), Associate Professor of Russian and Foreign Languages Department1 Michurina St., Voronezh, 394087 俄罗斯联邦

参考

  1. Kuzminov Ya.I., Kruchinskaya E.V., Gruzdev I.A., Naumov A.A. (2025). Falling behind and getting ahead: stu-dent use of generative ai in education. Vysshee obrazovanie v Rossii = Higher Education in Russia, vol. 34, no. 6, pp. 9-35. (In Russ.) http://doi.org/10.31992/0869-3617-2025-34-6-9-35, https://elibrary.ru/rxdtxq
  2. Sysoyev P.V. (2023). Artificial intelligence in education: awareness, readiness and practice of using artificial intelligence technologies in professional activities by university faculty. Vysshee obrazovanie v Rossii = Higher Education in Russia, vol. 32, no. 10, pp. 9-33. (In Russ.) https://doi.org/10.31992/0869-3617-2023-32-10-9-33, https://elibrary.ru/tzytkm
  3. Zhang W., Cai M., Lee H., Evans R., Zhu C., Ming C. (2024). AI in medical education: global situation, effects and challenges. Education and Information Technologies, vol. 29, pp. 4611-4633. https://doi.org/10.1007/s10639-023-12009-8, https://elibrary.ru/rdfanm
  4. Chan K., Zary N. (2019). Applications and challenges of implementing artificial intelligence in medical educa-tion: integrative review. JMIR Medical Education, vol. 5, no. 1, art. 13930. http://doi.org/10.2196/13930
  5. Feuerriegel S., Shrestha Y.R., von Krogh G., Zhang C. (2022). Bringing artificial intelligence to business man-agement. Nature Machine Intelligence, vol. 4, no. 7, pp. 611-613. http://doi.org/10.1038/s42256-022-00512-5, https://elibrary.ru/nblvwj
  6. Kock Zj., Salinas-Hernández U., Pepin B. (2025). Engineering students’ initial use schemes of ChatGPT as an instrument for learning. Digital Experiences in Mathematics Education, no. 11, pp. 192-218. http://doi.org/10.1007/s40751-025-00169-w, https://elibrary.ru/ereabf
  7. Sysoyev P.V., Evstigneev M.N. (2025). Integration of artificial intelligence technologies in language and methodological pre-service teachers' training. Yazyk i kul’tura = Language and Culture, no. 69, pp. 204-219. (In Russ.) http://doi.org/10.17223/19996195/69/10, https://elibrary.ru/guzvbi
  8. Waisberg N., Hudek A. (2021). AI for Lawyers: How Artificial Intelligence is Adding Value, Amplifying Exper-tise, and Transforming Careers. Hoboken, Wiley Publ., 208 p.
  9. Gavrilov M.V. (2024). Stages of teaching law students to draft international legal documents in English based on artificial intelligence tools. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov Universi-ty Review: Series Humanities, vol. 29, no. 4, pp. 985-998. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-4-985-998, https://elibrary.ru/jakhgc
  10. Sysoyev P.V., Kharin V.V., Gavrilov M.V. (2024). Method of teaching law students to draft international legal documents based on artificial intelligence tools as part of an integrated course. Yazyk i kul’tura = Language and Culture, no. 67, pp. 272-289. (In Russ.) https://doi.org/10.17223/19996195/67/15, https://elibrary.ru/rfqxpk
  11. Sysoyev P.V., Gavrilov M.V., Bulochnikov S.Yu. (2025). Matrix of technical solutions based on artificial intel-ligence in the professional training of future lawyers. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 30, no. 2, pp. 336-351. (In Russ.) https://doi.org/10.20310/1810-0201-2025-30-2-336-351, https://elibrary.ru/mcjcfz
  12. Johnson D.M., Doss W., Estepp C.M. (2024). Agriculture students’ use of generative artificial intelligence for microcontroller programming. Natural Sciences Education, no. 53, art. e20155. https://doi.org/10.1002/nse2.20155, https://elibrary.ru/xocqpp
  13. Bernetti I., Borghini T., Capecchi I. (2024). Integrating virtual reality and artificial intelligence in agricultural planning: insights from the V.A.I.F.A.R.M. application. Extended Reality. XR Salento 2024. Lecture Notes in Computer Science, vol. 15027. Springer, Cham. https://doi.org/10.1007/978-3-031-71707-9_28
  14. Tokmakova Yu.V., Saenko E.S. (2025). The use of corrective feedback from generative artificial intelligence in teaching a professional foreign language to students of an agricultural university. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 30, no. 1, pp. 50-66. (In Russ.) https://doi.org/10.20310/1810-0201-2025-30-1-50-66, https://elibrary.ru/gsffpp
  15. Baidikova T.V. (2025). Professional thesaurus formation of agricultural university students in the process of speech practice with artificial intelligence tools. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 30, no. 2, pp. 352-363. (In Russ.) https://doi.org/10.20310/1810-0201-2025-30-2-352-363, https://elibrary.ru/wlwxbx
  16. Lew R. (2024). Dictionaries and lexicography in the AI era. Humanities and Social Sciences Communications, no. 11, art. 426. https://doi.org/10.1057/s41599-024-02889-7, https://elibrary.ru/tjflvw
  17. Tangpijaikul M. (2025). Exploring the lexical approach for vocabulary learning through AI-driven feedback. LEARN Journal: Language Education and Acquisition Research Network, no. 18 (1), pp. 1015-1038. https://doi.org/10.70730/SFNP1171, https://elibrary.ru/tjflvw
  18. Kharlamenko I.V. (2024). Artificial intelligence to assist foreign language teacher in working on lexical skills. Inostrannye yazyki v shkole = Foreign Languages at School, no. 3, pp. 55-60. (In Russ.) https://elibrary.ru/pxxouk
  19. Klochikhin V.V., Polyakov O.G. (2023). Artificial intelligence technologies: corpus analysis tools in foreign language teaching. Inostrannye yazyki v shkole = Foreign Languages at School, no. 3, pp. 24-30. (In Russ.) https://elibrary.ru/bdttfe
  20. Klochikhin V.V. (2023). Methodological model of teaching collocational competence based on corpora. Voprosy metodiki prepodavaniya v vuze = Teaching Methodology in Higher Education, vol. 12, no. 2, pp. 24-36. (In Russ.) https://doi.org/10.57769/2227-8591.12.2.02, https://elibrary.ru/vtitrn
  21. Avramenko A.P., Akhmedova A.S., Bulanova E.R. (2023). Chatbot technology as a means of forming foreign language grammatical competence in self-study. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 28, no. 2, pp. 386-394. (In Russ.) https://doi.org/10.20310/1810-0201-2023-28-2-386-394, https://elibrary.ru/abfjqp
  22. Lobeeva P.I. (2023). The didactic potential of using chatbots in teaching and learning English phrasal verbs. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humani-ties, vol. 28, no. 6, pp. 1467-1476. (In Russ.) https://doi.org/10.20310/1810-0201-2023-28-6-1467-1476, https://elibrary.ru/fmyeoc
  23. Cherkasova E.A. (2024). An experiment on the differentiated teaching of English grammar to students at a technical university through educational interaction with a chatbot based on generative AI. Vestnik Tam-bovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 29, no. 5, pp. 1239-1247. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-5-1239-1247, https://elibrary.ru/cqsvks
  24. Adamopoulou E., Moussiades L. (2020). An overview of chatbot technology. Artificial Intelligence Applica-tions and Innovations, vol. 584, pp. 373-383. https://doi.org/10.1007/978-3-030-49186-4_31
  25. Han D. (2020). The effects of voice-based AI chatbots on Korean EFL middle school students’ speaking competence and affective domains. Asia-pacific Journal of Convergent Research Interchange, vol. 6, issue 7, pp. 71-80. https://doi.org/10.47116/apjcri.2020.07.07, https://elibrary.ru/oaepoq
  26. Kim H.S., Cha Y., Kim N.Y. (2021). Effects of AI chatbots on EFL students’ communication skills. Korean Journal of English Language and Linguistics, vol. 21, pp. 712-734. https://doi.org/10.15738/kjell.21..202108.712
  27. Çakmak F. (2022). Chatbot-human interaction and its effects on EFL students’ L2 speaking performance and speaking anxiety. Novitas-ROYAL (Research on Youth and Language), vol. 16 (2), pp. 113-131.
  28. Avramenko A.P., Tarasov A.A. (2023). Artificial intelligence speech recognition technologies for the develop-ment of speaking skills within the unified state exam preparation. Inostrannye yazyki v shkole = Foreign Lan-guages at School, no. 3, pp. 60-67. (In Russ.) https://elibrary.ru/jqzchv
  29. Sysoyev P.V., Filatov E.M. (2023). Method of the development of students’ foreign language communication skills based on practice with a chatbot. Perspektivy nauki i obrazovaniya = Perspectives of Science and Educa-tion, no. 3 (63), pp. 201-218. (In Russ.) https://doi.org/10.32744/pse.2023.3.13, https://elibrary.ru/fjyhew
  30. Sorokin D.O. (2024). The use of voice assistants for the development of foreign language oral communication skills. Inostrannye yazyki v shkole = Foreign Languages at School, no. 3, pp. 73-77. (In Russ.) https://elibrary.ru/rfmsmk
  31. Filatov E.M. (2024). Development of students’ foreign language communicative skills based on the Charac-ter.AI web application. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 29, no. 5, pp. 1248-1260. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-5-1248-1260, https://elibrary.ru/ncusck
  32. Park J. (2019). An AI-based English grammar checker vs. human raters in evaluating EFL learners’ writing. Multimedia-Assisted Language Learning, vol. 22, no. 1, pp. 112-131. http://doi.org/10.15702/mall.2019.22.1.112
  33. Perdana I., Farida M. (2019). Online grammar checkers and their use for EFL writing. Journal of English Teach-ing, Applied Linguistics, and Literatures, vol. 2, no. 2, pp. 67-76. http://doi.org/10.20527/jetall.v2i2.7332
  34. Manap M.R., Ramli N.F., Kassim A.A.M. (2019). Web 2.0 automated essay scoring application and human ESL essay assessment: a comparison study. European Journal of English Language Teaching, vol. 5, no. 1, pp. 146-162. http://doi.org/10.5281/zenodo.3461784
  35. Guo K., Wang D. (2023). To resist it or to embrace it? Examining ChatGPT’s potential to support teacher feed-back in EFL writing. Education and Information Technologies, pp. 1-29. http://doi.org/10.1007/s10639-023-12146-0, https://elibrary.ru/uafcwb
  36. Sysoyev P.V., Filatov E.M. (2024). Method of teaching students’ foreign language creative writing based on evaluative feedback from artificial intelligence. Perspektivy nauki i obrazovaniya = Perspectives of Science and Education, no. 1 (67), pp. 115-135. (In Russ.) https://doi.org/10.32744/pse.2024.1.6, https://elibrary.ru/tmstly
  37. Sysoyev P.V., Filatov E.M., Khmarenko N.I., Murunov S.S. (2024). Teacher vs artificial intelligence: a compari-son of the quality of feedback provided by a teacher and generative artificial intelligence in assessing students’ creative writing. Perspektivy nauki i obrazovaniya = Perspectives of Science and Education, no. 5 (71), pp. 694-712. (In Russ.) https://doi.org/10.32744/pse.2024.5.41, https://elibrary.ru/xzgvgm
  38. Sysoyev P.V. (2025). Personalized learning based on artificial intelligence: how ready are modern students for new educational opportunities. Vysshee obrazovanie v Rossii = Higher Education in Russia, vol. 34, no. 2, pp. 51-71. (In Russ.) https://doi.org/10.31992/0869-3617-2025-34-2-51-71, https://elibrary.ru/weagvq
  39. Sysoyev P.V., Filatov E.M., Evstigneev M.N., Polyakov O.G., Evstigneeva I.A., Sorokin D.O. (2024). A matrix of artificial intelligence tools in pre-service foreign language teacher training. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 29, no. 3, pp. 559-588. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-3-559-588, https://elibrary.ru/jazkme

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