Articles | Open Access | https://doi.org/10.37547/ijp/Volume05Issue11-96

The Role Of Artificial Intelligence In Developing Students’ Writing Skills In Efl Classrooms

Buranova Madina Uktamovna , PhD, Associate professor of the Department of English Language, Faculty of English Language, Samarkand State Institute of Foreign Languages, Uzbekistan

Abstract

The rapid integration of artificial intelligence (AI) into educational environments has transformed the teaching and learning of English as a Foreign Language (EFL). Writing, a cognitively demanding skill requiring mastery of grammar, vocabulary, organization, and discourse conventions, particularly benefits from AI-driven tools. This article explores how AI contributes to the development of EFL learners’ writing skills, focusing on intelligent tutoring systems, automated writing evaluation (AWE), machine translation, natural language processing (NLP), and generative AI systems such as large language models. Drawing from recent empirical studies, the paper analyzes the advantages of AI—personalized feedback, error correction, scaffolding, increased engagement—while also addressing concerns related to overreliance, academic integrity, teacher preparedness, and ethical considerations. The findings suggest that when purposefully integrated into pedagogy, AI enhances writing proficiency by supporting metacognitive awareness, fostering autonomous learning, and enabling data-driven assessment practices. Effective implementation, however, requires pedagogical planning, digital literacy training, and a balance between AI support and independent student production.  

Keywords

Artificial intelligence, EFL writing, automated writing evaluation

References

D’Mello, S., & Graesser, A. (2015). Feeling, thinking, and computing with affect-aware learning technologies. Learning and Instruction, 40, 152–170.

Hyland, K. (2007). Genre pedagogy: Language, literacy, and L2 writing instruction. Journal of Second Language Writing, 16(3), 148–164.

Hyland, K. (2016). Teaching and researching writing (3rd ed.). Routledge.

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, 5.

F., Gasser, U., Groh, G., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Instruction, 101, 1–12.

Li, J., Dewaele, J.-M., & Hu, Y. (2022). The predictive effects of artificial intelligence-assisted feedback on L2 writing performance. System, 106, 102740.

Nesselhauf, N. (2005). Collocations in a learner corpus. John Benjamins.

Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4.

Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153–189.

Swain, M. (2005). The output hypothesis: Theory and research. In E. Hinkel (Ed.), Handbook of research in second language teaching and learning (pp. 471–483). Routledge.

Wang, Y., Han, X., & Yang, J. (2020). Revisiting automated writing evaluation (AWE) feedback: Effects on revision and writing quality. Computer Assisted Language Learning, 33(4), 1–26.

Zou, D., & Xie, H. (2018). Personalized vocabulary learning with AI-based recommendations. Educational Technology & Society, 21(2), 233–244.

Buranova M.U., Buranova L.U. (2020) New modern trends in teaching foreign language, International Journal of Research, Vol.7/4

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Buranova Madina Uktamovna. (2025). The Role Of Artificial Intelligence In Developing Students’ Writing Skills In Efl Classrooms. International Journal of Pedagogics, 5(11), 404–406. https://doi.org/10.37547/ijp/Volume05Issue11-96