CORPUS-BASED APPROACHES TO ACADEMIC WRITING INSTRUCTION: A DATA-DRIVEN LEARNING PERSPECTIVE FOR FUTURE ENGLISH TEACHERS
Authors
Asilbek R. Karimov, Yaroslav Vladimirovich Golovko ()Files
Abstract
Academic writing represents one of the most demanding competencies for EFL learners, requiring simultaneous control over lexical accuracy, grammatical complexity, cohesion, and register. This study investigates the effectiveness of corpus-based analysis, specifically data-driven learning through the Corpus of Contemporary American English (COCA), in developing academic writing skills among future English teachers at Chirchiq State Pedagogical University. Using a mixed-methods experimental design, the research evaluates a corpus-integrated worksheet targeting six key writing subskills: cohesive phrase use, avoidance of repetition, phrase-level complexity, collocational competence, register awareness, and lexical precision. Reflective questionnaire data from 32 B2-level EFL students and evaluative data from six experienced EFL academic writing teachers reveal that corpus-based instruction significantly enhances collocational competence and cohesive phrase use, while also improving register awareness and lexical precision. The findings confirm that data-driven learning constitutes a powerful and innovative complement to traditional academic writing instruction, with important implications for teacher education programs in Uzbekistan and similar educational contexts.
References
Details
License
Copyright (c) 2026 Omega Journal of Linguistics and Language Studies
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
