IMPLEMENTATION OF PROGRAMS FOR AUTOMATIC DETECTION AND CORRECTION OF GRAMMATICAL ERRORS IN ENGLISH WRITING
DOI:
https://doi.org/10.47390/SPR1342V6I3Y2026N55Ключевые слова:
English writing, grammatical errors, automated error detection, artificial intelligence, grammatical error correction (GEC), digital education, writing skills, pedagogical experiment.Аннотация
This article examines the methodological foundations and effectiveness of implementing automated grammar error detection and correction programs in English academic writing within higher education. The study employs a mixed-method research design, combining quantitative and qualitative analysis through a pedagogical experiment involving control and experimental groups. AI-based platforms such as Grammarly, ProWritingAid, and ChatGPT were used to provide automated feedback and grammatical analysis. The findings indicate a significant reduction in grammatical errors, improved self-editing skills, and enhanced writing accuracy among students. Statistical analysis confirms the pedagogical effectiveness of automated feedback systems and supports their systematic integration into the educational process.
Библиографические ссылки
1. Bryant, C., Yuan, Z., Qorib, M. R., Cao, H., Ng, H. T., & Briscoe, T. (2023). Grammatical error correction: A survey of the state of the art. Computational Linguistics, 643-701.
2. Damerau, F. J. (1964). A technique for computer detection and correction of spelling errors. Communications of the ACM, 7(3), 171-176.
3. Elov, B., & Ahmedova, M. (2025). Til korpusi matnlarida imlo tuzatish. Computer linguistics: problems, solutions, prospects, 1(1).
4. Ilfiah, I., Hudzaifah, I., Syarifah, S., & Islam, S. (2024). Ability to Evaluate Students' Written Essay Errors Using Quillbot Grammar Checker. Teaching English to Young Learners in Indonesia (TEYLIN), 5(1), 31-39.
5. Khabutdinov, I. A., Chashchin, A. V., Grabovoy, A. V., Kildyakov, A. S., & Chekhovich, U. V. (2024). RuGECToR: Rule-based neural network model for Russian language grammatical error correction. Programming and Computer Software, 50(4), 315-321.
6. Omelianchuk, K., Liubonko, A., Skurzhanskyi, O., Chernodub, A., Korniienko, O., & Samokhin, I. (2024, June). Pillars of grammatical error correction: Comprehensive inspection of contemporary approaches in the era of large language models. In Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024) (pp. 17-33).
7. Raheem, B. R., Anjum, F., & Ghafar, Z. N. (2023). Exploring the profound impact of artificial intelligence applications (Quillbot, Grammarly and ChatGPT) on English academic writing: A systematic review. International Journal of Integrative Research (IJIR), 1(10), 599-622.
8. Track, L. L. M., & Track, U. CRAC 2025 Shared Task on Multilingual Coreference Resolution.
9. Wang, D., Su, J., & Yu, H. (2020). Feature extraction and analysis of natural language processing for deep learning English language. IEEE Access, 8, 46335-46345.
10. Zhu, J., Shi, X., & Zhang, S. (2021). Machine learning‐based grammar error detection method in English composition. Scientific programming, 2021(1), 4213791.
