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Abstract
The rapid advancement of artificial intelligence has significantly transformed the field of language education. Among recent innovations, ChatGPT, a large language model developed by OpenAI, has emerged as a powerful tool capable of generating human-like language and supporting various aspects of language learning. This study investigates the role of ChatGPT in language learning through a qualitative case study approach, focusing on its linguistic capabilities, pedagogical potential, and inherent limitations. The research analyzes ChatGPT-generated responses to EFL-oriented tasks targeting writing, grammar explanation, vocabulary development, and conversational interaction. The findings indicate that ChatGPT provides coherent, grammatically accurate, and contextually relevant language output, making it particularly effective in enhancing writing skills and lexical competence. Additionally, its capacity to offer immediate feedback and simplified explanations supports learner autonomy and personalized learning.
However, the study also reveals limitations related to pragmatic accuracy, cultural sensitivity, and ethical concerns, including the risk of learner over-reliance and academic integrity issues. While ChatGPT demonstrates strong alignment with communicative and input-based language learning theories, it lacks genuine understanding and affective interaction characteristic of human instructors. The study concludes that ChatGPT should be viewed as a complementary educational tool rather than a replacement for teachers. Its effective integration into language education requires pedagogical guidance and critical awareness. The findings contribute to the growing body of research on AI-assisted language learning and provide implications for educators and future research.
References
1. Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021).
On the dangers of stochastic parrots: Can language models be too big?
Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623.
2. Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P. Amodei, D. (2020). Language models are few-shot learners.
Advances in Neural Information Processing Systems, 33, 1877–1901.
3. Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.).
SAGE Publications.
4. Hymes, D. (1972). On communicative competence.
In J. B. Pride & J. Holmes (Eds.), Sociolinguistics (pp. 269–293). Penguin.
5. Исломов, Уткиржон. "UNDERSTANDING FOREIGN LANGUAGE ANXIETY AND ITS IMPACT ON LEARNING." Свет науки 8 (43) (2025).
6. Исломов, Уткиржон. "OVERCOMING FOREIGN LANGUAGE ANXIETY IN UNIVERSITY STUDENTS." Interpretation and researches 6 (52) (2025).
7. Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., … Sailer, M. (2023). ChatGPT for good? On opportunities and challenges of large language models for education.
Learning and Individual Differences, 103, 102274.
8. Kohnke, L., & Moorhouse, B. L. (2023). Facilitating language learning with ChatGPT: Opportunities and challenges.
TESL-EJ, 27(2), 1–14.
9. Krashen, S. D. (1985). The input hypothesis: Issues and implications.
Longman.
10. Long, M. H. (1996). The role of the linguistic environment in second language acquisition.
In W. C. Ritchie & T. K. Bhatia (Eds.), Handbook of second language acquisition (pp. 413–468). Academic Press.
11. Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit or the end of traditional assessments in higher education?
Journal of Applied Learning & Teaching, 6(1), 1–22.
12. Zhai, X. (2022). ChatGPT user experience: Implications for education.
Education and Information Technologies, 27, 1–20.
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