Non-Educational Use of Artificial Intelligence in English Language Education: Unity of Teaching and Learning Disruption
DOI:
https://doi.org/10.18662/rrem/17.4/1064Keywords:
artificial intelligence, language education, teaching languages, learning languages, text, workbookAbstract
Artificial intelligence (AI) is being introduced into various aspects of our daily activities, including education. The study of foreign languages, as part of the educational system, is also influenced by new developing technologies. Researchers believe that artificial intelligence contributes to the displacement of traditional teaching methods and changes in the role of the teacher. This phenomenon is sure to be an achievement and progress. However, practical experience in teaching a foreign language at a nonlinguistic university shows the opposite: the use of artificial intelligence technologies by students does not speed up the process of teaching and learning a foreign language, but, on the contrary, complicates and slows it down. The aim of the study is to analyze the use of AI in linguistic education in a non-linguistic university, to identify the reasons for the lack of its effective educational impact, and to propose solutions. To achieve the stated goal, the work uses a comprehensive research methodology combining theoretical approaches, including analysis of literature on the topic of the study, generalization and classification, as well as empirical methods, implying the study of local pedagogical experience, questionnaires, and statistical analysis. The study demonstrates that non-educational use of AI breaks the unity of educational process composed of teaching and learning. Artificial intelligence in teaching foreign languages helps the teacher make the educational process highly differentiated and individualized. It is a valuable tool that makes the educational process more efficient and energy-saving. However, in learning foreign languages from the student's position, devoid of a motivating component, the artificial intelligence used non-educationally have no learning effect and does not allow students to fully assimilate and process the educational material. The author suggests ways to overcome this situation.
References
Alpaydin, E. (2014). Introduction to machine learning. Cambridge, MA: The MIT Press.
Banerjee, D. (2020). Natural Language Processing (NLP) simplified: A step-by-step guide. Data Science Foundation. https://datascience.foundation/sciencewhitepaper/natural-language-processingnlp-simplified-a-step-by-step-guide
Berendt, B., Littlejohn, A. & Blakemore, M. (2020). AI in education: Learner choice and fundamental rights. Learning, Media and Technology, 45(3), 312-324. https://doi.org/10.1080/17439884.2020.1786399
Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. In Metcalfe, J. & Shimamura, A. P. (Eds.), Metacognition: Knowing about knowing. Cambridge, MA: The MIT Press (pp. 185-205). https://bjorklab.psych.ucla.edu/wp-content/uploads/sites/13/2016/07/RBjork_1994a.pdf
Celik, I., Dindar, M., Muukkonen, H. & Järvelä, S. (2022). The promises and challenges of Artificial Intelligence for teachers: a systematic review of research. TechTrends, 66, 616-630. https://doi.org/10.1007/s11528-022-00715-y
Chen, L., Chen, P. & Lin, Z. (2020). Artificial Intelligence in education: A review. IEEE Access, 8, 75264-75278. https://doi.org/10.1109/ACCESS.2020.2988510
Evstigneev, M. N. (2024). Principles of teaching foreign languages based on artificial intelligence technologies. Bulletin of Tambov University. Series: Humanities, 29(2), 309-323. https://doi.org/10.20310/1810-0201-2024-29-2-309-323
Flavell, J. H. (1976). Metacognitive aspects of problem solving. In Resnick, L. B. (Ed.), The nature of intelligence (pp. 231-235). Lawrence Erlbaum Associates. https://doi.org/10.4324/9781032646527
Haddad, S. (2021). The complex role of AI in exam marking. Digital Learning, 0723. https://www.thelpi.org/wp-content/uploads/2021/03/digital-learning-2021.pdf
Hattie, J. (2012). Visible learning for teachers: Maximizing impact on learning. Routledge. https://doi.org/10.4324/9780203181522
Healey, J. (2020). Artificial Intelligence. Thirroul: The Spinney Press.
Heymann, H. W. (2005). Was macht Üben intelligent? Pädagogik, 57(11), 6-11. https://www.fachportal-paedagogik.de/literatur/vollanzeige.html?FId=3028272
International Center for Academic Integrity (ICAI). (2021). The fundamental values of academic integrity. (3rd ed.). https://academicintegrity.org/aws/ICAI/asset_manager/get_file/911282?ver=1
Karatas, F., Abedi, F. Y., Gunyel, F., Karadeniz, D. & Kuzgun, Y. (2024). Incorporating AI in foreign language education: An investigation into ChatGPT’s effect on foreign language learners. Education and Information Technologies, 29, 19343-19366. https://doi.org/10.1007/s10639-024-12574-6
Kim, S., Park, J. & Lee, H. (2019). Automated essay scoring using a deep learning model. Journal of Educational Technology Development and Exchange, 2(1), 1-17. https://doi.org/10.4018/978-1-7998-3476-2.ch003
Luckin, R., Holmes, W., Griffiths, M. & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. London: Pearson.
Meurers, D. (2020). Natural language processing and language learning. In Chapelle, C. A. (Ed.), The Concise Encyclopedia of Applied Linguistics. Wiley-Blackwell. https://doi.org/10.1002/9781405198431.WBEAL0858
Novikov, D. (2004). Statistical methods in pedagogical research (typical cases). Moscow: MZ-Press. https://www.researchgate.net/publication/274390588_Novikov_DA_Statisticeskie_metody_v_pedagogiceskih_issledovaniah_tipovye_slucai_M_MZ-Press_2004_--_67_s
Popenici, S.A.D. & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(22). https://doi.org/10.1186/s41039-017-0062-8
Race, P. (2001). The lecturer's toolkit: A practical guide to learning, teaching & assessment. Kogan Page.
Rusmiyanto, R., Huriati, N., Fitriani, N., Tyas, N. K., Rofi’i, A., & Sari, M. N. (2023). The role of artificial intelligence (AI) in developing English language learner’s communication skills. Journal on Education, 6(1), 750- 757. https://doi.org/10.31004/joe.v6i1.2990
Schmidt, T., & Strasser, T. (2018). Media-assisted foreign language learning – concepts and functions. In: Surkamp, C., Viebrock, B. (eds) Teaching English as a Foreign Language (pp.211-231). J.B. Metzler, Stuttgart. https://doi.org/10.1007/978-3-476-04480-8_12
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
Strasser, T. (2021). AI in the EFL-classroom. Clarifications, potentials and limitations. In C. Lütge & T. Merse (Eds.) Digital Teaching and Learning: Perspectives for English Language Education. Tübingen: Narr Francke Attempto. https://www.narr.de/digital-teaching-and-learning-perspectives-for-english-language-educa-18244/
Sysoev, P. V. (2024). Didactic properties and methodological functions of neural networks. Perspectives of Science and Education, 6(72), 672-690. https://doi.org/10.32744/pse.2024.6.42
Sysoev, P. V., Filatov, E. M. & Sorokin. D. O. (2024). Feedback in foreign language teaching: from information technology to Artificial Intelligence. Language and Culture, 65, 242-261. https://doi.org/10.22363/2618-8163-2024-22-2-300-317
Sysoev, P. V., Filatov, E. M., Evstigneev, M. N., Polyakov, O. G., Evstigneeva, I. A. & Sorokin, D. O. (2024). Matrix of artificial intelligence tools in linguo-methodological training of future foreign language teachers. Bulletin of Tambov University. Series: Humanities, 29(3), 559-588. https://doi.org/10.20310/1810-0201-2025-30-2-336-351
Titova, S. V. & Timuryan, K. K. (2024). Intelligent agents in FL teaching: Typology, possibilities, challenges. Language and Culture, 65, 262-287. https://doi.org/10.17223/19996195/65/12
Titova, S. V. (2024). Artificial Intelligence-based technological solutions in foreign language teaching: an analytical review. Bulletin of Moscow University. Series 19. Linguistics and Intercultural Communication, 27(2), 18-37. http://linguistics-communication-msu.ru/upload/iblock/022/56mlpmy9uogw2tpemjk17jwrqaxbbtt8/Ser_19_2024_2_18_38_Titova.pdf
Tolstyh, O. M. (2023). The potential of Artificial Intelligence in language education: practical recommendations for teachers. Horizons of Education: Proceedings of the IV International Scientific and Practical Conference. Omsk: OGPU, 391-393. https://www.researchgate.net/publication/372743869_Potencial_iskusstvennogo_intellekta_v_azykovom_obrazovanii_prakticeskie_rekomendacii_dla_prepodavatelej
UNESCO. (2021). Rewired global declaration on connectivity for education. https://en.unesco.org/futuresofeducation/sites/default/files/2021-12/Rewired%20Global%20Declaration%20on%20Connectivity%20for%20Education.pdf
UNESCO. (2023). AI and Education: Guidance for Policy-makers. Especially sections on ethics and challenges. https://www.unesco.org/en/articles/ai-and-education-guidance-policy-makers
Watters, A. (2021).Teaching machines: The history of personalized learning. MIT Press.
Yang, A. (2024). Challenges and opportunities for foreign language teachers in the era of Artificial Intelligence. International Journal of Education and Humanities, 4(1), 39-50. https://doi.org/ 10.58557/(ijeh).v4i1.202
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64-70. https://doi.org/10.1207/s15430421tip4102_2
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 The Authors & InManifest Network

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant this journalright of first publication, with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work, with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g. post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g. in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as an earlier and greater citation of published work (See The Effect of Open Access).
Revista Romaneasca pentru Educatie Multidimensionala Journal has an Attribution-NonCommercial-NoDerivs
CC BY-NC-ND