Russian lessons for foreigners: tools of artificial intelligence or the art of technology?

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Abstract

The relevance of the research lies in the necessity of including new technologies (in particular, generative artificial intelligence) in the process of language education in order to adapt students and teachers to new conditions of the information environment, to master new skills and abilities, to improve the quality of education. The highly productive value of generative artificial intelligence for teaching Russian as a foreign language at the level of professional education in higher education is emphasised. The aim of the research is to reveal the learning potential of generative artificial intelligence, which is achieved by applying the following methods: modelling of the learning process with the use of generative artificial intelligence; observation; generalisation of experience and forecasting of students’ achievements with regard to the development of linguistic and communicative competence, as well as flexible skills in academic and subsequent professional activities; linguodidactic analysis; descriptive method. The materials of the work have a pronounced practice-oriented character, as they represent a set of tasks and exercises, composed (performed) with the use of systems based on generative artificial intelligence (Gemini (Bard), Kandinsky, GPTchat (OpenAI), Perplexity, Shedevrum). The tasks are aimed at developing linguistic, communicative, professional, ICT-competences, as well as cognitive (analytical, generative and other) and creative abilities, and other flexible skills (Soft Skills) relevant for academic and further professional activities in the language being learnt (here - Russian as a foreign language). The limitations of generative artificial intelligence in terms of understanding the nuances of linguistic-cultural, social, emotional-psychological, stylistic context, which determines the role of the teacher in the learning process, are noted. We emphasise not so much mentoring, but rather cooperative-activity functions of the teacher, who simultaneously learns together with his students by accessing a resource that is gigantic in terms of information volume and technological capabilities, and directs, supervises, and corrects the activity of generative artificial intelligence and students. The prospects of the research are outlined, which imply the expansion of generative artificial intelligence technology possibilities in language education.

About the authors

Elena V. Dziuba

Peter the Great St. Petersburg Polytechnic University

Author for correspondence.
Email: dzyuba_ev@spbstu.ru
ORCID iD: 0000-0002-3833-516X
SPIN-code: 6106-5500
Scopus Author ID: 56998786000
ResearcherId: AAJ-5882-2021

Doctor of Philology (Advanced Doctorate), Professor, Higher School of International Relations, Institute of Humanities

29 Polytechnicheskaya St, Saint Petersburg, 195251, Russian Federation

References

  1. Avraamenko, A.P. (2022). Psychological and pedagogical aspects of teaching foreign languages individualization by means of artificial intelligence. Bulletin of the Orenburg State University, 3(235), 60–65. (In Russ.). http://doi.org/10.25198/1814-6457-233-60
  2. Azimov, E.G., Kulibina, N.V., & Van, V. (2023). Linguistic and didactic potential of social networks in teaching Russian as a foreign language. Russian Language Studies, 21(2), 133–147. (In Russ.). http://doi.org/10.22363/2618-8163-2023-21-2-133-147
  3. Bartosh, D.K., Gal’skova, N.D., Koptelov, A.V., & Kharlamova, M.V. (2018). Technology of e-learning of foreign languages: Status and prospects. Moskva : MGPU. (In Russ.).
  4. Bogomaz, I.V., Budnikov, V.S., Anastasova, E.V., Pikov, N.O., & Vasil’eva, A.V. (2019). Learning a foreign language on the basis of VR-technology. Informatisation of Education and Science, 4(44), 176–192. (In Russ.).
  5. Bozhenkova, N.A., Rubleva, E.V., & Bakharlu, Kh. (2023). Dictionary of IT terms as a tool for Russian language studies and linguodidactics in the context of digitalization in education. Russian Language Studies, 21(4), 457–473. (In Russ.). http://doi.org/10.22363/2618-8163-2023-21-4-457-473
  6. Bubnova, I.A. (2021). Values and image of the future of generation Z. RUDN Journal of Language Studies, Semiotics and Semantics, 12(2), 269–278. (In Russ.). https:// doi.org/10.22363/2313-2299-2021-12-2-269-278
  7. Dunaeva, Yu. (2024). Artificial intelligence: Features of Russian digital education strategy. proceedings of topical issues in international political geography (TIPG 2022), Springer Geography, Springer. https://doi.org/10.1007/978-3-031-50407-5_27
  8. Dunaeva, Yu.G. (2023). Scientific intelligence in education: Peaceful trends, tasks and readiness of university science. Global and international challenges in a changing world, (pp. 91–111). Saint-Peterburg. (In Russ.).
  9. Dziuba, E.V., Eremina, S.A., & Mushenko, E.V. (2023). artificial intelligence in the methodology of teaching Russian as a foreign language. Pedagogical Education in Russia, (6), 178–189. (In Russ.).
  10. Guo, K., & Wang, D. (2024). To resist it or to embrace it? Examining ChatGPT’s potential to support teacher feedback in EFL writing. Education and Information Technologies, 29, 8435–8463. https://doi.org/10.1007/s10639-023-12146-0
  11. Holmes, W., Anastopoulou, S., Schaumburg, H., & Mavrikis, M. (2018). Technology-enhanced personalized learning: Untangling the evidence. Stuttgart, Robert Bosch Stiftung. URL: https://www.bosch-stiftung.de/sites/default/files/publications/pdf/2018-08/Study_ Technology-enhanced%20Personalised%20Learning.pdf (accessed: 1 December 2023)
  12. Ignatovich, T.V. (2021). Teaching Russian as a foreign language with the use of LearningApps service. Russian Language Studies, 19(1), 51–65. (In Russ.). http://doi.org/10.22363/2618-8163-2021-19-1-51-65
  13. Kharlamenko, I.V. (2023). Chat-bots in teaching English. Foreign Languages at School, (3), 55—59. (In Russ.).
  14. Kovaleva, A.G., Obvintseva, N.V., Platonova, S.V., & Murashkina, K.V. (2024). Step-by-step development of digital competence of a translator among students of linguistic educational programs of UrFU. Pedagogical Education in Russia, (1), 109–116. (In Russ.).
  15. Lavrinenko, I.Yu. (2023). The ChatGPT use in the English language teaching process in a non-language university: Theoretical aspect. Herald of Siberian Institute of Business and Information Technologies, 12(2), 18–25. (In Russ.). https://doi.org/10.24412/2225-8264-2023-2-18-25
  16. Mehring, J. (2017). Technology as a Teaching and Learning Tool in the Flipped classroom. In M. Carrier, R.M. Damerow & M. Kathleen (Eds.), Digital Language Learning and Teaching. Research, Theory, and Practice (1st ed., pp. 235–246). Routledge.
  17. Morozova, A.L., & Kostyukova, T.A. (2023). Virtual reality in teaching dialogic speech in English: MGIMO-Odintsovo experience. Language and Сulture, (63), 207–238. (In Russ.). http://doi.org/10.17223/19996195/63/11
  18. Rubleva, E.V. (2015). Intergenerational conflict in 21st century education: Will the strongest man win? Vestnik TsMO MGU. Filologiya. Kul’turologiya. Pedagogika. Metodika, (3), 113–122. (In Russ.).
  19. Strelchuk, E.N., Kozhevnikova, M.N., & Borchenko, V.S. (2023). Blended learning in Russian higher education: The evolution of the term in science and practice. Educational Process: International Journal, 12(1), 97–116. https://doi.org/10.22521/edupij.2023. 121.6
  20. Sysoev, P.V. (2023). Artificial intelligence in education: Awareness, readiness and practice of using artificial intelligence technologies in professional activities by university faculty. Higher Education in Russia, 32(10), 9–33. (In Russ.). https://doi.org/10.31992/0869-3617-2023-32-10-9-33
  21. Sysoev, P.V., & Filatov, E.M. (2024). Method of teaching students’ foreign language creative writing based on evaluative feedback from artificial intelligence. Perspectives on Science and Education, 1(67), 115–135. (In Russ.). https://doi.org/10.32744/pse.2024.1.6
  22. Sysoev, P.V., & Filatov, E.M. (2023). ChatGPT in students’ research work: to Prohibit or to educate? Bulletin of Tambov University. Series: Humanities, 28(2), 276–301. (In Russ.). https://doi.org/10.20310/1810-0201-2023-28-2-276-301
  23. Sysoev, P.V., Filatov, E.M., & Sorokin, D.O. (2023). Chat-bots and Voice assistants in the development of learners’ foreign language speech skills. Language and Culture, (63), 272–289. (In Russ.). https://doi.org/10.17223/19996195/63/14
  24. Vyazovskaya, V.V., Danilevskaya, T.A., & Trubchaninova, M.E. (2020). Online resources in teaching Russian as a foreign language: Expectations vs reality. Russian Language Studies, 18(1), 69–84. (In Russ.). http://doi.org/10.22363/2618-8163-2020-18-1-69-84
  25. Zhang, V., & Vesnina, L.E. (2020). Model of blended learning of Russian grammar in Chinese university. Philological Сlass, 27(2), 149–160. (In Russ.).
  26. 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), 16(2), 113–131.

Supplementary files

Supplementary Files
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1. Figure 1. Poster for May 1 (students’ work). Examples of slogans: Solidarity, equality, justice! Honest labor is the basis of life! Decent wages are our right! For peaceful labor! For a decent life! Labor unites!

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2. Figure 2. Postcard for May 1 (students’ work). Example of congratulation: Dear teacher, I congratulate you on May Day. I wish you good labor and joy in your work. Your student Wang Li (unedited text)

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Copyright (c) 2024 Dziuba E.V.

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