Methodological foundations of the meta-digital competence system: a case study in language education

Introduction. The rapid advancement of generative artificial intelligence necessitates a methodological foundation for new theoretical constructs in pedagogy. The contemporary educational system requires an updated theoretical and methodological framework that extends beyond digital literacy to integrate the metacognitive, ethical, and sociocultural aspects of human-machine collaboration. Aim. The aim of this research is to elucidate the methodological foundations and system architecture of meta-digital competence as a theoretical framework for developing teachers’ professional competencies in the context of the proliferation of artificial intelligence. Methodology and research methods. The study is based on a systematic analysis of the theoretical foundations of meta-digital competence, integrating the principles of cognitive psychology, the theory of distributed cognition, and the competence approach. The methods employed include conceptual analysis, structural-functional modelling, and theoretical synthesis within the context of AI proliferation. Results. The epistemological foundations of meta-digital competence are elucidated, encompassing the transition from classical cognition to metacognition. Four methodological principles are established that underpin the structure and functioning of meta-digital competence: distributed cognitive activity, metacognitive reflection, ethical responsibility, and adaptive development. A six-component architecture of meta-digital competence is delineated, accompanied by a description of the mechanisms for integrating its elements. Scientific novelty. For the first time, the methodological foundations of the meta-digital competence system, regarded as a qualitatively new phenomenon in pedagogy, have been developed. A new type of human-machine interaction, conceptualised as an extended cognitive system, has been proposed. The principles governing the structural organisation and functioning of the meta-digital competence system within the educational context are substantiated. Practical significance. A theoretical framework has been established for the design of educational programmes in the era of artificial intelligence, alongside a conceptual foundation for the transformation of pedagogical practices across various subject areas in this new reality.

1. Guechairi S. Artificial intelligence in education: a comprehensive bibliometric study on Scopus (2010–2024). ATRAS Journal. 2025;5:445–463. doi:10.70091/atras/AI.28

2. Holmes W., Bialik M., Fadel C. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign; 2019. Accessed June 10, 2025. https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf

3. Xu W., Ouyang F. Artificial intelligence in education: a systematic literature review. Expert Systems with Applications. 2024;254:124383. doi:10.1016/j.eswa.2024.124167

4. Chen X., Xie H., Zou D., Hwang G.J. Two decades of artificial intelligence in education: contributors, collaborations, research topics, challenges, and future directions. Educational Technology & Society. 2022;25(1):28–47. doi:10.30191/ETS.202201_25(1).0003

5. Bin-Hady W., Al-Kadi A., Hazaea A., Ali J. Exploring the dimensions of ChatGPT in English language learning: a global perspective. Library Hi Tech. 2023. doi:10.1108/LHT-05-2023-0200

6. Chen L., Chen P., Lin Z. Artificial intelligence in education: a review. IEEE Access. 2020;8:75264–75278. doi:10.1109/ACCESS.2020.2988510

7. Ouyang F., Zheng L., Jiao P. Integration of artificial intelligence performance prediction and learning analytics to improve student learning in online engineering course. International Journal of Educational Technology in Higher Education. 2023;20(1):1–23. doi:10.1186/s41239-022-00372-4

8. Semyonkina I.A., Prusakova P.V. Application of artificial intelligence tools in foreign language teaching: a theoretical review. Filologicheskie nauki. Voprosy teorii i praktiki = Philology. Theory & Practice. 2025;18(1):115–125. (In Russ.) Accessed June 10, 2025. Available from: https://cyberlen-inka.ru/article/n/primenenie-instrumentov-iskusstvennogo-intellekta-v-prepodavanii-inostran-nogo-yazyka-teoreticheskiy-obzor/viewer

9. Kovalchuk S.V., Taranenko I.A., Ustinova M.B. Using AI technologies for foreign language teaching at university. Sovremennye problemy nauki i obrazovaniya = Modern Problems of Science and Education. 2023;6:1. (In Russ.) doi:10.17513/spno.33000

10. Gruzdev A.V. The use of generative artificial intelligence in the study and teaching of foreign languages: the results of a systematic analysis. Pedagogika i prosveshchenie = Pedagogy and Education. 2025;1:105–115. (In Russ.) doi:10.7256/2454-0676.2025.1.73607

11. Selezneva V.V., Bunakova T.A. The use of artificial intelligence in teaching English as a foreign language amid digital transformation. Mir nauki, kul’tury, obrazovaniya = The World of Science, Culture and Education. 2025;1(110):242–246. (In Russ.) doi:10.24412/1991-5497-2025-1110-242-246

12. Konkol M.M. Metacyfer competence as a new paradigm for education in the age of artificial intelligence. Uchenye zapiski Rossiiskogo gosudarstvennogo sotsial’nogo universiteta = Scientific Notes of the Russian State Social University. 2025;24(2):112–119. (In Russ.) doi:10.17922/2071-5323-2025-24-2-112-119

13. Flavell J.H. Metacognition and cognitive monitoring: a new area of cognitive-developmental inquiry. American Psychologist. 1979;34(10):906–911. Accessed June 10, 2025. https://psycnet.apa.org/record/1980-09388-001

14. Celik I. Towards intelligent-TPACK: an empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior. 2023;138:107468. doi:10.1016/j.chb.2022.107468

15. Chaib M., Ounissi A. Teachers’ sense of competence in terms of ICT use: the case of secondary school teachers. Research in Learning Technology. 2023;31. doi:10.25304/rlt.v31.2874

16. Tondeur J., Scherer R., Baran E., Siddiq F. Teacher educators as gatekeepers: preparing the next generation of teachers for technology integration in education. British Journal of Educational Technology. 2019;50(3):1–21. doi:10.1111/bjet.12748

17. Raitskaya L., Tikhonova E. ChatGPT: where is a silver lining? Exploring the realm of GPT and large language models. Journal of Language and Education. 2023;9(3):5–11. doi:10.17323/jle.2023.18119

18. Ironsi C. Exploring the potential of generative AI in English language teaching. In: Laila U., Yu P., Mulli J., Syed Z.A.S., eds. Facilitating Global Collaboration and Knowledge Sharing in Higher Education with Generative AI. IGI Global; 2024:162–185. doi:10.4018/979-8-3693-0487-7.ch007

19. Garrett N., Beard N., Fiesler C. AI ethics education: a systematic literature review. Computers and Education: Artificial Intelligence. 2025;7:100257. doi:10.1016/j.caeai.2025.100405

20. Shanmugasundaram M., Tamilarasu A. The impact of digital technology, social media, and artificial intelligence on cognitive functions: a review. Frontiers in Cognition. 2023;2:1203077. doi:10.3389/fcogn.2023.1203077

21. Konkol M.M., Chigasheva M.A. A sociological portrait of a MGIMO foreign language teacher in the context of integrating artificial intelligence tools into the educational paradigm. Mir nauki, kul’tury, obrazovaniya = The World of Science, Culture and Education. 2024;4(107):85–90. (In Russ.) doi:10.24412/1991-5497-2024-4107-85-90

22. Gilster P. Digital Literacy. New York: Wiley; 1997. Accessed June 10, 2025. https://archive.org/de-tails/digitalliteracy0000gils/mode/1up

23. Hutchins E. Cognition in the Wild. Cambridge: MIT Press; 1995. Accessed June 10, 2025. https://books.google.ru/books?hl=ru&lr=&id=CGIaNc3F1MgC&oi=fnd&pg=PP11&dq=%22Ed-win+Hutchins%22&ots=9Hq-5dru1W&sig=-nKrqlZiiiPAm-fNqJxkc7VyX0xo&redir_esc=y#v=one-page&q=%22Edwin%20Hutchins%22&f=false

24. Petko D., Mishra P., Koehler M.J. TPACK in context: an updated model. Computers and Education Open. 2025;8:100244. doi:10.1016/j.caeo.2025.100244

25. Long D., Magerko B. What is AI literacy? Competencies and design considerations. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: Association for Computing Machinery; 2020:1–16. doi:10.1145/3313831.3376727

26. Tikhonova N.V., Sabirova D.R. Teacher AI literacy: a theoretical conceptualisation. Obrazovanie i nauka = The Education and Science Journal. 2025;27(6):180–206. (In Russ.) doi:10.17853/1994-5639-2024-10-180-206

27. Smagulova G.Zh., Sarzhanova G.B., Tleuzhanova G.K., Stanchu N. The development of future foreign language teachers’ digital competences in creating multimedia tutorials. Obrazovanie i nauka = The Education and Science Journal. 2021;23(6):216–245. (In Russ.) doi:10.17853/1994-5639-2021-6-216-245

28. Zhao L., Wang Y. Teachers’ practices in the use of digital technology to promote students’ self-regulated learning and metacognition: a systematic review. Teaching and Teacher Education. 2025;148:104715. doi:10.1016/j.tate.2025.104715

29. Schraw G. Promoting general metacognitive awareness. Instructional Science. 1998;26(1-2):113–125. doi:10.1023/A:1003044231033

30. Moshman D. Metacognitive theories revisited. Educational Psychology Review. 2018;30(2):599–606. doi:10.1007/s10648-017-9413-7

31. Efklides A. Metacognition and affect: what can metacognitive experiences tell us about the learning process? Educational Research Review. 2006;1(1):3–14. doi:10.1016/j.edurev.2005.11.001

32. Trace A. Jr. What Ivan Knows that Johnny Doesn’t. New York: Random House; 1961. Accessed June 10, 2025. https://books.google.ru/books/about/What_Ivan_Knows_that_Johnny_Doesn_t.htm-l?id=A7z2-7plCiwC&redir_esc=y

33. Равен Дж. Педагогическое тестирование: Проблемы, заблуждения, перспективы. М.: Когито– Центр; 2001. Режим доступа: https://www.livelib.ru/book/131087/readpart-pedagogicheskoe-te-stirovanie-problemy-zabluzhdeniya-perspektivy-dzhon-raven (дата обращения: 10.06.2025).

34. Recommendations of the European Parliament and of the Council of 18 December 2006 on Key Competences for Lifelong Learning. Official Journal of the European Union. 30.12.2006. Accessed June 10, 2025. https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:394:0010:0018:en:PDF

35. Zimnyaya I.A. Klyuchevye kompetentnosti kak rezul’tativno-tselevaya osnova kompetentnostnogo podkhoda v obrazovanii = Key Competence of How to Effectively Target the Basis of Competence Approach in Education. Moscow: Research Centre for Issues in the Quality of Specialist Training; 2004. (In Russ.) Accessed June 10, 2025. https://www.studmed.ru/view/zimnyaya-ia-klyuchevye-kompetentnosti-kak-rezulta-tivno-celevaya-osnova-kompetentnostnogo-podhoda-v-obrazovanii_75b32e46499.html

36. Robert I.V. Teoriya i metodika informatizatsii obrazovaniya: psikhologo-pedagogicheskii i tekhnologicheskii aspekty = Theory and Methodology of Informatisation of Education: Psychological, Pedagogical and Technological Aspects. Moscow: Institute of Informatisation of Education of the Russian Academy of Education; 2008. 356 p. (In Russ.)

37. Vorobyeva K.I., Belous S., Savchenko N.V., Nikitina S.A., Zhdanov S.P. Personalized learning through AI: pedagogical approaches and critical insights. Contemporary Educational Technology. 2025;17(2):ep574. doi:10.30935/cedtech/16108