Formation of lexical and grammatical skills of technical university students based on phrasal verbs of the English language through practice with a chatbot
https://doi.org/10.20310/1810-0201-2025-30-3-591-609
Abstract
Importance. The current stage of digital transformation of education, supported by global initiatives from UNESCO and the national development strategies of the Russian Federation until 2030, is characterized by the integration of innovative technologies such as artificial intelligence (AI) technologies into the higher education system. This area is particularly relevant in technical universities, where the formation of professional foreign language communicative competence is the main goal of foreign language education. Phrasal verbs, widely used in professional communication and technical documentation, remain one of the most difficult lexical and grammatical categories of the English language for students of future engineers. However, in practice, their study is complicated by the lack of a systematic approach in textbooks, a shortage of classroom hours, and the low effectiveness of traditional methods of teaching vocabulary and grammar. To achieve the main purpose of the study, chatbots are used as a tool for extracurricular speech practice aimed at automating the skills of using phrasal verbs. The purpose of this study is to determine the effectiveness of the methodology for the formation of lexical and grammatical skills of technical university students based on phrasal verbs of the English language through practice with a chatbot.
Research Methods. To conduct this study, the following groups of methods were used: a) theoretical: study and analysis of domestic and foreign pedagogical, methodological, and psychological scientific literature on the research problem; analysis and generalization of experience on the problem under study, modeling; b) empirical: observation, questioning, interview, testing; c) statistical: quantitative and qualitative analysis results obtained, mathematical data processing; d) formative: experimental work was carried out under controlled conditions to verify the author's teaching methodology; the data obtained were used to analyze and identify cause-and-effect relationships between variables. The effectiveness of the methodology for the formation of lexical and grammatical skills of technical university students based on phrasal verbs through practice with a chatbot was carried out by comparing the test results at the ascertaining and control stages. IBM SPSS Statistics 21 software was used to analyze the data, and the averages were compared according to the parametric statistical method, the Student’s t-test. The object of control was 15 lexical and grammatical skills (9 receptive and 6 productive skills).
Literature Review. During the analysis of scientific and educational literature on the research topic, the results of scientific papers on the use of chatbots for the formation of foreign language communicative competence were summarized, and the main research directions were identified.
Results and Discussion. The developed methodology for the formation of lexical and grammatical skills of technical university students based on phrasal verbs of the English language through practice with a chatbot was tested during experimental study and proved its effectiveness in comparison with traditional teaching methods in all controlled parameters. The conducted experimental study revealed that at the initial stage of training, both groups of control group (CG) (N = 24) and experimental group (EG) (N = 24) have an equal level of language training, since there was no statistical significance between the groups (p > 0.05 for most of the controlled parameters). The indicators in the EG have a high statistical significance (p < 0.001), which indicates the pronounced effectiveness of the applied teaching methodology. In CG, most indicators are also significant, but the significance level varies between p < 0.001 (parameters 2–8, 10–11, 13–15) and p < 0.05 (parameters 1, 9, 12). The least pronounced and having weak statistical significance in CG is the controlled parameter No. 1 “to correlate the sound form of a word with its meaning” (*p = 0.037), while in EG, despite the fact that it was better formed, it nevertheless has a low t = 4.87 (p < 0.001) compared to with other skills. The difference in effectiveness between СG and EG is obvious due to the fact that the Student’s t-test scores in EG are significantly higher than in СG, for example, for parameter No. 6 “to differentiate phrasal verbs and similar monolex verbs” t = 4.67 (СG) versus t = 7.89 (EG). The largest gap in the Student’s t-criterion is observed in productive skills, for example, for parameter No. 9 “to predict grammatical constructions with phrasal verbs” t = 4.12 (CG) versus t = 8.12 (EG).
Conclusion. Experimental study has revealed that chatbots ChatGPT and DeepSeek do not have the technical capability to develop listening skills. At the same time, some chatbots (for example, Replika AI) provide more natural communication, TalkPal chatbots and Praktika.ai are more effective for correcting errors. Speech practice with a chatbot aroused the interest of students, which helped to increase their motivation to learn English. The interactive learning format and the ability to receive instant feedback have made the process more fun and accessible. Using several different chatbots at the same time allowed students to familiarize themselves with the possibilities provided by chatbots and choose the one that best suited the needs of a particular student. The results of the research can be used in further study to identify the linguistic and didactic potential of AI technologies and its application in the framework of foreign language training for students of nonlinguistic universities, the formation of lexical and grammatical skills of students through other AI technologies, as well as in the methodology of teaching a foreign language.
Keywords
About the Authors
M. N. EvstigneevRussian Federation
Maxim N. Evstigneev, Cand. Sci. (Education), Associate Professor of Linguistics and Linguodidactics Department
Scopus ID: 57206855992
ResearcherID: AAE-8965-2022
33 Internatsionalnaya St., Tambov, 392000
P. I. Lobeeva
Russian Federation
Polina I. Lobeeva, English Lecturer of “English for Mechanical Engineering” Department
Bld. 1, 5, 2-nd Baumanskaya St., Moscow, 105005
N. V. Hausmann-Ushkova
Russian Federation
Nadezhda V. Hausmann-Ushkova, Dr. Sci. (Philology), Professor, Professor of Linguistics and Linguodidactics Department
33 Internatsionalnaya St., Tambov, 392000
References
1. Сысоев П.В. Технологии искусственного интеллекта в обучении иностранному языку // Иностранные языки в школе. 2023. № 3. С. 6-16. https://elibrary.ru/qfmzhw
2. Авраменко А.П., Ахмедова А.С., Буланова Е.Р. Технология чат-ботов как средства формирования иноязычной грамматической компетенции при самостоятельном обучении // Вестник Тамбовского университета. Серия: Гуманитарные науки. 2023. Т. 28. № 2. С. 386-394. https://doi.org/10.20310/1810-0201-2023-28-2-386-394, https://elibrary.ru/abfjqp
3. Черкасова Е.А. Дидактические и методические функции чат-ботов в обучении студентов нелингвистических направлений подготовке иноязычной грамматике // Вестник Тамбовского университета. Серия: Гуманитарные науки. 2023. Т. 28. № 6. С. 1443-1451. https://doi.org/10.20310/1810-0201-2023-28-6-1443-1451, https://elibrary.ru/cvexfj
4. Харламенко И.В. Искусственный интеллект в помощь учителю иностранного языка при работе над лексическими навыками // Иностранные языки в школе. 2024. № 3. С. 55-60. https://elibrary.ru/pxxouk
5. Ивченко М.И., Поляков О.Г. Использование инструмента искусственного интеллекта ELSA speak в обучении произношению // Иностранные языки в школе. 2025. № 2. С. 54-58. https://elibrary.ru/zrvafq
6. Сысоев П.В., Ивченко М.И. Формирование иноязычных фонетических навыков речи обучающихся на основе инструментов искусственного интеллекта // Перспективы науки и образования. 2025. № 2 (74). С. 600-614. https://doi.org/10.32744/pse.2025.2.38, https://elibrary.ru/jrddjj
7. Евстигнеев М.Н. Планирование учебного занятия по иностранному языку с помощью технологий генеративного искусственного интеллекта // Вестник Тамбовского университета. Серия: Гуманитар ные науки. 2024. Т. 29. № 3. С. 617-634. https://doi.org/10.20310/1810-0201-2024-29-3-617-634, https://elibrary.ru/ahylwe
8. Евстигнеев М.Н. Тематический контроль и критериальное оценивание иноязычных письменных умений с помощью технологий искусственного интеллекта // Вестник Тамбовского университета. Серия: Гуманитарные науки. 2024. Т. 29. № 4. С. 913-926. https://doi.org/10.20310/1810-0201-2024-29-4-913-926, https://elibrary.ru/jaajxe
9. Сысоев П.В., Филатов Е.М. Методика развития иноязычных речевых умений студентов на основе практики с чат-ботом // Перспективы науки и образования. 2023. № 3 (63). С. 201-218. https://doi.org/10.32744/pse.2023.3.13, https://elibrary.ru/fjyhew
10. Canale M., Swain M. Theoretical bases of communicative approaches to second language teaching and testing // Applied Linguistics. 1980. № 1. Р. 47-54. https://elibrary.ru/ilaqrh
11. Крылов Э.Г., Халяпина Л.П., Архипова Е.И. Обучение студентов инженерных специальностей английскому языку как языку профессии: интегративный подход // Язык и культура. 2021. № 54. С. 203-223. https://doi.org/10.17223/19996195/54/12, https://elibrary.ru/aitvkz
12. Сысоев П.В., Беляев А.А., Евстигнеев М.Н. Разработка методики обучения ординаторов иноязычному профессиональному общению на основе интегрированного подхода // Перспективы науки и образования. 2024. № 3 (69). С. 284-300. https://doi.org/10.32744/pse.2024.3.17, https://elibrary.ru/jmemvf
13. Сысоев П.В., Завьялов В.В. Методические принципы предметно-языкового интегрированного обучения // Иностранные языки в школе. 2021. № 5. С. 30-39. https://elibrary.ru/cfuofx
14. Гальскова Н.Д., Гез Н.И. Теория обучения иностранным языкам. Лингводидактика и методика. Москва: Академия, 2009. 336 с.
15. Щукин А.Н., Фролова Г.М. Методика преподавания иностранных языков. Москва: Академия, 2015. 287 с.
16. Fryer L., Carpenter R. Bots as language learning tools // Language Learning & Technology. 2006. Vol. 10. № 3. P. 8-14. https://doi.org/10.64152/10125/44068
17. Labadze L., Grigolia M., Machaidze L. Role of AI chatbots in education: systematic literature review // International journal of Educational Technology in Higher education. 2023. Vol. 20. № 1. Art. 56. https://doi.org/10.1186/s41239-023-00426-1, https://elibrary.ru/wklbvu
18. Yoon S.Y. Student readiness for AI instruction: perspectives on AI in university EFL classrooms // Multimedia-Assisted Language Learning. 2019. № 22 (4). P. 134-160.
19. Fryer L.K., Nakao K., Thompson A. Chatbot learning partners: Connecting learning experiences, interest and competence // Computers in Human Behaviour. 2019. № 93. Р. 279-289.
20. Çakmak F. Chatbot-human interaction and its effects on EFL students’ L2 speaking performance and speaking anxiety // Novitas-ROYAL (Research on Youth and Language). 2022. № 16 (2). P. 113-131.
21. Huang W., Hew T., Fryer L.K. Chatbots for language learning – are they really useful? A systematic review of chatbot-supported language learning // Journal of Computer Assisted Learning. 2022. № 38 (1). Р. 237- 257. https://doi.org/10.1111/jcal.12610, https://elibrary.ru/bdwitp
22. Тихонова Н.В., Ильдуганова Г.М. «Меня пугает то, с какой скоростью развивается искусственный интеллект»: восприятие студентами искусственного интеллекта в обучении иностранным языкам // Высшее образование в России. 2024. Т. 33. № 4. С. 63-83. https://doi.org/10.31992/0869-3617-2024-33-4-63-83, https://elibrary.ru/fnuavr
23. Сорокин Д.О. Отношение учеников школ и студентов вузов к применению чат-ботов с искусственным интеллектом в образовании // Державинский форум. 2023. Т. 7. № 1 (25). С. 21-30. https://elibrary.ru/revite
24. Dewi D.F., Nur’Aini S., Suwarti T.S. Students’ perception on the use of chatbot from Memrise site and their willingness to communicate in English // Linguistics and Education Journal. 2023. № 2 (1). Р. 11-21.
25. Khatri B.B., Karki P.D. Artificial Intelligence (AI) in Higher Education: Growing Academic Integrity and Ethical Concerns // Nepalese Journal of Development and Rural Studies. 2023. № 20 (01). Р. 1-7. https://doi.org/10.3126/njdrs.v19i01.51910, https://elibrary.ru/aiobxf
26. Сысоев П.В. Этика и ИИ-плагиат в академической среде: понимание студентами вопросов соблюдения авторской этики и проблемы плагиата в процессе взаимодействия с генеративным искусственным интеллектом // Высшее образование в России. 2024. Т. 33, № 2. С. 31-53. https://doi.org/10.31992/0869-3617-2024-33-2-31-53, https://elibrary.ru/vtaiuo
27. Титова С.В. Технологические решения на базе искусственного интеллекта в обучении иностранным языкам // Вестник Московского университета. Серия 19: Лингвистика и межкультурная коммуникация. 2024. № 2. С. 18-37. https://doi.org/10.55959/MSU-2074-1588-19-27-2-2, https://elibrary.ru/owsqvg
28. Сысоев П.В., Евстигнеев М.Н. Интеграция технологий искусственного интеллекта в лингвометодическую подготовку будущих учителей иностранного языка // Язык и культура. 2025. № 69. С. 204-219. https://doi.org/10.17223/19996195/69/10, https://elibrary.ru/guzvbi
29. Лобеева П.И. Дидактический потенциал использования чат-ботов при изучении фразовых глаголов английского языка // Вестник Тамбовского университета. Серия: Гуманитарные науки. 2023. Т. 28. № 6. С. 1467-1476. https://doi.org/10.20310/1810-0201-2023-28-6-1467-1476, https://elibrary.ru/fmyeoc
30. Kim N. A study on the use of artificial intelligence chatbots for improving English grammar skills // Journal of Digital Convergence. 2019. № 17. Р. 37-46.
31. Сорокин Д.О. Использование веб-приложения Character.ai для развития умений иноязычного речевого взаимодействия обучающихся // Иностранные языки в школе. 2025. № 2. С. 59-65. https://elibrary.ru/kpckof
Review
For citations:
Evstigneev M.N., Lobeeva P.I., Hausmann-Ushkova N.V. Formation of lexical and grammatical skills of technical university students based on phrasal verbs of the English language through practice with a chatbot. Tambov University Review. Series: Humanities. 2025;30(3):591-609. (In Russ.) https://doi.org/10.20310/1810-0201-2025-30-3-591-609