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Abstract
The article examines the transformative influence of artificial intelligence on higher education with a particular focus on English philology and language learning. The relevance of the study lies in the rapid integration of AI-driven tools into linguistic education, which reshapes traditional teaching methods, learner autonomy, and academic skills development. The problem addressed in this research concerns the insufficient methodological readiness of universities and instructors to integrate AI-based technologies effectively into philological training. The study employs comparative analysis, thematic review, and pedagogical observation to identify the opportunities and boundaries of AI implementation in foreign language acquisition. Much attention is given to generative AI systems, automated feedback platforms, and adaptive learning models, as they directly influence students’ writing proficiency, vocabulary development, and critical thinking. The findings reveal that AI tools significantly enhance language learning outcomes when appropriately integrated with human-mediated instruction; however, challenges related to academic integrity, over-dependence on automation, and digital competence gaps remain substantial. It is concluded that AI can serve as a powerful catalyst for modernizing English philology programs, provided that universities develop clear methodological frameworks and equip students with ethical and technological literacy
References
1. Al-Saleem, B. & Karem, A. (2021) ‘Digital feedback and the development of university students’ academic writing‘, Journal of Applied Linguistics, 14(2), pp. 45-62.
2. British Council (2024) Language Education and Digital Transformation: Global Report 2024. London: British Council.
3. Chen, L. (2022) ‘Reading comprehension in digitally mediated environments: A systematic review’, Studies in Language and Education, 9(3), pp. 112-130.
4. EDUCAUSE (2023) Higher Education Digital Learning Index 2023. Colorado: EDUCAUSE Publications.
5. Fuchs, C. (2019) ‘Pronunciation learning and interactive phonetic tools in higher education’, System, 87, pp. 102-118.
6. Gilmore, A. (2020) ‘Authenticity in language learning and digital mediation’, Language Teaching Research, 24(6), pp. 754-770.
7. Golonka, E. (2021) ‘Technology-mediated language learning: Reassessing assumptions’, Annual Review of Applied Linguistics, 41, pp. 131-152.
8. Hockly, N. (2022) Digital Literacies in Language Education. Cambridge: Cambridge University Press.
9. Kessler, G. (2020) ‘Technology-supported language learning and learner autonomy reconsidered’, Language Learning & Technology, 24(3), pp. 5-25.
10. Li, X. & Martin, P. (2023) ‘University students’ use of digital writing assistants: Implications for academic integrity’, Journal of Academic Ethics, 21(4), pp. 337-355.
11. Liu, H. (2021) ‘Corpus-informed writing development in tertiary English programmes’, Journal of English for Academic Purposes, 52, pp. 1-10.
12. Stockwell, G. (2023) ‘Reconceptualising digital support tools in language learning‘, Computer Assisted Language Learning, 36(8), pp. 1523-1544.
13. Turnitin (2024) Academic Integrity Trends Report 2024. California: Turnitin Research Division.
14. UNESCO (2023) Technology in Higher Education: Global Monitoring Report 2023. Paris: UNESCO Publications.
15. Wang, Y. (2022) ‘Digital scaffolding and vocabulary expansion among university learners’, International Journal of Applied Linguistics, 32(1), pp. 87-104.
16. Zhang, M. (2020) ‘Cognitive engagement and digital reading tools in academic contexts’, Reading in a Foreign Language, 32(2), pp. 205-227.
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