Optimisation of business communication training in English using an artificial intelligence tool for text sentiment analysis
- Authors: Tupikova S.E.1, Pustovedova V.A.1
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Affiliations:
- Saratov State University
- Issue: Vol 30, No 4 (2025)
- Pages: 828-841
- Section: THEORY AND METHODS OF FOREIGN LANGUAGE TEACHING
- URL: https://journal-vniispk.ru/1810-0201/article/view/328009
- DOI: https://doi.org/10.20310/1810-0201-2025-30-4-828-841
- ID: 328009
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Abstract
Importance. Artificial Intelligence (AI) is rapidly permeating all areas of professional activity, leading to increased demands for digital skills among specialists. One of the ways to prepare competitive personnel should be the integration of AI tools into the educational process. The aim of this research is to analyse the advantages of implementing the AI Email Tone Analyzer tool for the development of professional communication competencies among students in the field of business communication in English. In the context of rapid digital progress and the growing volume of communication via electronic means, it is essential not only to be able to articulate thoughts but also to correctly interpret the tone and emotional nuance of messages.Materials and Methods. Analysis of scientific literature related to the topic, comparison and summarisation of empirical data, as well as conducting an experiment. The materials for the research included business letters published on the 101 Business Letter website, as well as letters written by master’s students from the language faculty. The participants in the experiment consisted of 50 first and second-year students enrolled in the full-time Master’s programme (field 44.04.01 “Pedagogical Education”, profile “Foreign Languages in the Context of Contemporary Culture”). The experiment is conducted as part of the course “Business Foreign Language” at the Pedagogical Institute of Saratov State University named after N.G. Chernyshevsky.Results and Discussion. It has been proven that the use of the AI tool AI Email Tone Analyzer significantly enhances students’ proficiency in professional communication skills. The average number of errors in business correspondence has decreased by 42 %, while the average time taken to prepare letters has reduced by 7 minutes. Qualitative analysis also revealed an increase in students’ confidence in their skills and competencies – 66 % of students reported a reduction in anxiety level when writing business emails in English due to automated feedback. Furthermore, there was a significant increase in students’ engagement in the learning process – 78 % of respondents emphasized that they began to participate more frequently and willingly in written assignments and discussions in English after the implementation of this AI tool. 82 % of students started to consult their teacher less often when writing business emails, preferring to analyze the text with the help of artificial intelligence first indicating a rise in autonomy. In terms of communication processes, 100 % of students noted a marked increase in satisfaction with communication and a reduction in misunderstandings between business partners or interlocutors thanks to the tone adjustments made by the AI Email Tone Analyzer.Conclusion. The conducted research has led to the following key conclusions: the AI Email Tone Analyzer assists students in better recognising and adapting the tone of their messages according to the audience and situation, which promotes more effective communication; the use of the tool enables students to receive immediate feedback on how their messages may be perceived, fostering the development of critical thinking and self-reflection. The prospects for further research appear to lie in a more detailed analysis of the capabilities of the AI tool, the expansion of its application scope, including its integration into the process of learning foreign languages, as well as the examination of the impact of new technologies on organizational processes and behaviour.
About the authors
S. E. Tupikova
Saratov State University
Email: tupikovase@mail.ru
ORCID iD: 0000-0002-1236-9206
SPIN-code: 9140-4100
Cand. Sci. (Philology), Associate Professor, Associate Professor of the Department of English Language and Teaching Methods
Russian Federation, 83 Astrakhanskaya St., Saratov, 410012, Russian FederationV. A. Pustovedova
Saratov State University
Author for correspondence.
Email: vikakiv2003@mail.ru
ORCID iD: 0009-0008-2799-3336
SPIN-code: 8915-2236
Research Scholar of English Language and Teaching Methods Department
Russian Federation, 83 Astrakhanskaya St., Saratov, 410012, Russian FederationReferences
- Abramova I.E. (2025). Application of generative AI technologies in adult foreign language learning: peer men-toring. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review. Series: Humanities, vol. 30, no. 1, pp. 35-49. (In Russ.) https://doi.org/10.20310/1810-0201-2025-30-1-35-49, https://elibrary.ru/vogutw
- Shamov A.N., Pankratov E.N., Golovanova L.N. (2025). Innovation in a foreign language education as an idea with new opportunities. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review. Series: Humanities, vol. 30, no. 1, pp. 118-131. (In Russ.) https://doi.org/10.20310/1810-0201-2025-30-1-118-131, https://elibrary.ru/orcekw
- Titova S.V. (2023). Teaching foreign language writing skills in the digital environment of the university. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review. Series: Humanities, vol. 28, no. 2, pp. 302-316. (In Russ.) https://doi.org/10.20310/10.20310/1810-0201-2023-28-2-302-316, https://elibrary.ru/vizjkh
- Bogdanova T.F. (2023). Means of the expressing sentiment in the conditions of modern business internet corres-pondence in Russian, English and Chinese languages. Vestnik Omskogo gosudarstvennogo pedagogicheskogo universiteta. Gumanitarnye issledovaniya = Review of Omsk State Pedagogical University. Humanitarian re-search, vol. 1, no. 38, pp. 57-62. (In Russ.) https://doi.org/10.36809/2309-9380-2023-38-57-62, https://elibrary.ru/dntacx
- Tupikova S.E. (2015). Cognitive modelling of the implementation of the emotional aspect through the modal category of tonality. Yazyk i mir izuchaemogo yazyka = Language and the World of the Studied Language, vol. 6, pp. 109-114. (In Russ.) https://elibrary.ru/vilngz
- Tupikova S.E. (2011). The category of tonality and its levels of representation in society column genre. Voprosy kognitivnoi lingvistiki = Issues of Cognitive Linguistics, vol. 4, no. 29, pp. 68-73. (In Russ.) https://elibrary.ru/nyahzz
- Boldyrev N.N. (2014). Interpretation of the world and world knowledge in language. Kognitivnye issledovaniya yazyka = Cognitive Studies of Language, vol. 19, pp. 20-28. (In Russ.) https://elibrary.ru/snhbjb
- Titova S.V. (2024). Technological solutions based on artificial intelligence in teaching foreign languages: an analytical review. Vestnik Moskovskogo universiteta. Seriya 19. Lingvistika i mezhkul’turnaya kommunikatsiya = Moscow State University Bulletin. Series 19. Linguistics and Intercultural Communication, vol. 27, no. 2, pp. 18-37. (In Russ.) https://doi.org/10.55959/MSU-2074-1588-19-27-2-2, https://elibrary.ru/owsqvg
- Sysoyev P.V. (2025). Teaching a foreign language in the age of artificial intelligence: controversial issues and prospects for methodological research. Inostrannye yazyki v shkole = Foreign Languages at School, no. 2, pp. 66-74. (In Russ.) https://elibrary.ru/pwhsis
- Crompton H., Burke D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, vol. 20, no. 1, pp. 1-22. https://doi.org/10.1186/s41239-023-00392-8, https://elibrary.ru/vyfmfk
- Surahman E., Wang T.H. (2022). Academic dishonesty and trustworthy assessment in online learning: A syste-matic literature review. Journal of Computer Assisted Learning, vol. 38, no. 6, pp. 1535-1553. https://doi.org/10.1111/jcal.12708, https://elibrary.ru/myyyzu
- Huang X., Zou D., Cheng G., Chen X., Xie H. (2023). Trends, research issues and applications of artificial intel-ligence in language education. Educational Technology and Society, vol. 26, no. 1, pp. 112-131. https://doi.org/10.30191/ETS.202301_26(1).0009
- Su J., Yang W. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence, vol. 3, pp. 1-13. https://doi.org/10.1016/j.caeai.2022.100049, https://elibrary.ru/dbvsoo
- Hwang S. (2022). Examining the effects of artificial intelligence on elementary students’ mathematics achieve-ment: A meta-analysis. Sustainability, vol. 14, no. 20, pp. 1-18. https://doi.org/10.3390/su142013185, https://elibrary.ru/manyxp
- Li S., Gu X. (2023). A risk framework for human-centered artificial intelligence in education. Educational Tech-nology and Society, vol. 26, no. 1, pp. 187-202. https://doi.org/10.30191/ETS.202301_26(1).0014
- Evstigneev M.N. (2024). Principles of foreign language teaching based on artificial intelligence technologies. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review. Series: Humani-ties, vol. 29, no. 2, pp. 309-323. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-2-309-323, https://elibrary.ru/ygipmo
- Sharples M. (2023). Towards social generative AI for education: theory, practices and ethics. Learning, vol. 9, no. 2, pp. 159-167. https://doi.org/10.1080/23735082.2023.2261131, https://elibrary.ru/cbhgrk
- Godwin-Jones R. (2022). Partnering with AI: Intelligent writing assistance and instructed language learning. Language Learning and Technology, vol. 26, no. 2, pp. 5-24. http://doi.org/10125/73474
- Wei L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 moti-vation, and self-regulated learning. Frontiers in Psychology, vol. 14. https://doi.org/10.3389/fpsyg.2023.1261955, https://elibrary.ru/josnly
- Pustovedova V.A., Tupikova S.E., Bykova N.O. (2025). Linguodidactic potential of artificial intelligence tech-nologies for teaching foreign languages (on the example of science specialization). Inostrannye yazyki v shkole = Foreign Languages at School, no. 5, pp. 70-75. (In Russ.) https://elibrary.ru/auwudb
- Bannikova L.V., Bezzubkina V.I. (2024). Schoolchildren’s socio-professional orientation in foreign language education: the role of a foreign language teacher. Inostrannye yazyki v shkole = Foreign Languages at School, no. 2, pp. 45-50. (In Russ.) https://elibrary.ru/ptrtoe
- Sysoyev P.V., Filatov E.M., Evstigneev M.N., et al. (2024). A matrix of artificial intelligence tools in pre-service foreign language teacher training. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review. Series: Humanities, vol. 29, no. 3, pp. 559-588. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-3-559-588, https://elibrary.ru/jazkme
- Anh L.T.Q. (2024). AI Chatbots in English language learning: a critical review. Journal of Knowledge Learning and Science Technology, vol. 3, no. 2, pp. 185-195. https://doi.org/10.60087/jklst.vol3.n2.p195
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