Artificial Intelligence and Foreign Language Learning in Higher Education: Analysis of Research Methods
https://doi.org/10.24833/2687-0126-2025-7-3-54-68
Abstract
The paper presents a systematic review of research methods devoted to the use of artificial intelligence in foreign language learning in universities. The relevance of the paper is related to the growing role of artificial intelligence technology, such as large language models in higher education and foreign language learning. The aim of the study is to obtain a methodological picture of the research field in this area. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, the authors selected and analysed scientific publications that apply qual- itative and quantitative methods to the study of artificial intelligence for foreign language learning in higher education. From a corpus of almost 3000 sources, 32 studies in English that describe the methodology and are in the public domain were selected. The results of the review showed that the majority of the works were devoted to English as a foreign language, published between 2023 and 2024, and used quantitative and mixed empirical methods, primarily questionnaires. While noting the undoubted advantages of such methods (such as standardisation, anonymity, and the possibility of automated processing of results), the authors draw attention to the insufficiency of using only quantitative and mixed research methods to understand the peculiarities of applying artificial intelligence in universities for learning foreign languages. The paper proposes to draw attention to both theoretical and empirical qualitative methods from different scientific fields in order to gain a better understanding of the field of study, which will allow taking into account the context, ethical, and non-numerical behavioural characteristics of people interacting with artificial intelligence in education. The paper contributes to the understanding of the current state of the field of research on artificial intelligence for foreign language learning in higher education by offering recommendations for the methodology of future research.
Keywords
neural network,
foreign language education,
university,
large language model,
LLM,
PRISMA,
AIEd,
AIHEd
Supporting agencies: The paper was prepared as part of a study by a research team within the MGIMO University project “Challenges and opportunities for integrating artificial intelligence (henceforth AI) tools into the educational process in language and academic discipline departments”.
About the Authors
A. E. Ulanova
MGIMO University
Russian Federation
Russian Federation
Alexandra E. Ulanova, Cand. Sci. (Philosophy), is a Senior Lecturer in the Department of Philosophy named after A. F. Shishkin
Moscow
A. V. Buniakova
MGIMO University
Russian Federation
Russian Federation
Anastasia V. Buniakova, Cand. Sci. (Economics), is a Senior Lecturer in the English Language Department No. 2
Moscow
A. Y. Lazko
MGIMO University
Russian Federation
Russian Federation
Andrei Y. Lazko is a Senior Lecturer in the English Language Department No. 2
Moscow
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For citations:
Ulanova A.E., Buniakova A.V., Lazko A.Y. Artificial Intelligence and Foreign Language Learning in Higher Education: Analysis of Research Methods. Professional Discourse & Communication. 2025;7(3):54-68. https://doi.org/10.24833/2687-0126-2025-7-3-54-68
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