A matrix of artificial intelligence tools in pre-service foreign language teacher training
https://doi.org/10.20310/1810-0201-2024-29-3-559-588
Abstract
Importance. The modern stage of information and technological development of civilization is characterised by the dynamic emergence of artificial intelligence (AI) technologies and the development of tools based on them, which are being more and more introduced into various spheres of life. The education system in general, and foreign language education in particular, is no exception. Currently, there are several dozen AI tools that are actively used by students and teachers in the development of foreign language communicative skills and the development of language skills. There is a rather voluminous body of research in the academic literature devoted to the disclosure of the language teaching potential of modern AI tools. However, most of the studies are of a pilot nature. The focus of scholars’ attention is on particular methods for the development of students’ communicative skills or the development of certain language skills based on individual AI tools. The systematic consideration of the integration of AI technologies into the process of teaching foreign language majoring students – future foreign language teachers – linguistic and teaching methods training has not been the subject of a special study. The purpose of this study is to develop a matrix of AI tools used in the linguistic and teaching methods training of future foreign language teachers.
Materials and Methods. The study is conducted on the basis of the expert assessment method, which allows to: a) identify the language teaching potential, as well as the limitations of the most common AI tools; b) summarise and classify the available knowledge in the form of a matrix of AI tools used in the linguistic and teaching methods training of future foreign language teachers. The materials of the study were research articles, published in Russian and foreign academic journals, indexed in Web of Science and Scopus.
Results and Discussion. A matrix of AI tools in the linguistic and teaching methods training of future foreign language teachers has been developed. The matrix is presented according to six types of feedback from generative AI used in foreign language teaching and teaching methods. The following are the main and most accessible AI tools for teachers and students providing feedback of each type: a) Replika, LingvoBot, Multitran_bot, Slavaribot, WorldContextBot, ChatGPT, Google Assistant, EGEEnglish.ru (educational and social feedback); b) ChatGPT, YandexGPT and GigaChat (information and reference feedback); c) ChatGPT 4.0, YandexGPT, GigaChat, Twee (methodological feedback); d) ChatGPT, YandexGPT, GigaChat, Turnitin, software “Antiplagiat” (analytical feedback); e) Grammarly, PaperRater, Pigai, ChatGPT 4.0, YandexGPT, GigaChat, Criterion (assessment and evaluative feedback); f) ChatGPT, YandexGPT, GigaChat, AI Poem Generator, Midjourney, Suno, Sora, Runway (conditionally creative feedback).
Conclusion. The novelty of the research consists in the development of a matrix of AI tools in the linguistic and teaching methods training of future foreign language teachers. The prospects for further research lie in the development of teaching methods for aspects of language, types of speech activity, as well as specialised disciplines based on specific AI tools. In their entirety, these particular methods will enable the creation of an integrated system of linguistic and teaching methods training of future foreign language teachers based on AI tools.
Keywords
About the Authors
P. V. SysoyevRussian Federation
Pavel V. Sysoyev, Dr. habil. (Education), Professor, Director of Russian Academy of Education Research
Centre; Professor of Department of Language Education
ScopusID: 8419258800, ResearcherID: I-6136-2016
33 Internatsionalnaya St., Tambov, 392000; 1 bldg, 1 Malaya Pirogovskaya St., Moscow, 119991
E. M. Filatov
Russian Federation
Evgeniy M. Filatov, Research Scholar of Foreign
Language Multicultural Education Research Laboratory
Scopus ID: 58609035100, ResearcherID: HDO-3688-2022
33 Internatsionalnaya St., Tambov, 392000
M. N. Evstigneev
Russian Federation
Maxim N. Evstigneev, PhD (Education), Associate
Professor, Associate Professor of Linguistics and
Linguodidactics Department
Scopus ID: 57206855992, ResearcherID: AAE-8965-2022
33 Internatsionalnaya St., Tambov, 392000
O. G. Polyakov
Russian Federation
Oleg G. Polyakov, Dr. habil. (Education), Professor, Head of Linguistics and Linguodidactics Department
Scopus ID: 57191782124, ResearcherID: A-7660-2016
33 Internatsionalnaya St., Tambov, 392000
I. A. Evstigneeva
Russian Federation
Ilona A. Evstigneeva, PhD (Education), Associate
Professor, Associate Professor of Linguistics and
Linguodidactics Department
Scopus ID: 57206857675, ResearcherID: AAE-8847-2022
33 Internatsionalnaya St., Tambov, 392000
D. O. Sorokin
Russian Federation
Danila O. Sorokin, Research Scholar of Foreign
Language Multicultural Education Research Laboratory
Scopus ID: 58120432100, ResearcherID: AFF-7904-2022
33 Internatsionalnaya St., Tambov, 392000
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Review
For citations:
Sysoyev P.V., Filatov E.M., Evstigneev M.N., Polyakov O.G., Evstigneeva I.A., Sorokin D.O. A matrix of artificial intelligence tools in pre-service foreign language teacher training. Tambov University Review. Series: Humanities. 2024;29(3):559-588. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-3-559-588