LINGVISTIK KORPUS YARATISHDA ESSE MATERIALLARINI TAYYORLASH BOSQICHLARI
This article explores the formation of a written learner corpus based on essays produced by non-philology students. The study applies linguistic and statistical analysis to identify lexical features, semantic fields, and typical errors in students’ written speech. The findings reveal the dominance of vocabulary related to education, professional activity, and competence. The results are significant for developing educational corpora and learner-oriented dictionaries.
1. Abdurakhmonova N, Urdishev K. Corpus based teaching Uzbek as a foreign language. Journal of Foreign Language Teaching and Applied Linguistics (J-FLTAL). 2019;6(12019):131-7.
2. Abdurakhmonova N. Dependency parsing based on Uzbek Corpus. InProceedings of the International Conference on Language Technologies for All (LT4All) 2019.
3. Abdullah Alfaifi, Eric Atw, Hedeya Ibrahim. Arabic Learner Corpus (ALC) v2. A New Written and Spoken Corpus of Arabic Learner2014 Saudia Arabia
4. D. Stewart, S. Bernardini, G. Aston Introduction: Ten years of TaLC / Corpora and language learners, Vol 17, John Benjamins Publishing Company Amsterdam/Philadelphia, 2004, - P. 3
5. Larisa Goulart Da Silva Academic vocabulary: a corpus linguistics study on how Brazilian students write academic English. 2016-a. Brazilia
6. Abdurakhmonova, N., & Urdishev, K. (2019). Corpus based teaching Uzbek as a foreign language. Journal of Foreign Language Teaching and Applied Linguistics (J-FLTAL), 6(12019), 131-7.
7. Абдурахмонова, Н., & Абдувахобов, Г. (2021). O ‘quv lug ‘atini tuzishning nazariy metodologik asoslari. Международный журнал искусство слова, 4(6).
8. Abdurakhmonova, N. (2021). Formal-Functional Models of The Uzbek Electron Corpus. ANGLISTICUM. Journal of the Association-Institute for English Language and American Studies, 10(8), 59-66.
9. Abdurakhmonova, N., Alisher, I., & Toirova, G. (2022, September). Applying Web Crawler Technologies for Compiling Parallel Corpora as one Stage of Natural Language
10. Processing. In 2022 7th International Conference on Computer Science and Engineering (UBMK) (pp. 73-75). IEEE.
11. Abdurakhmonova, N., Shakirovich, I. A., & O‘G‘Li, K. N. S. (2022). Morphological analyzer (morfoAnalyse) Python package for Turkic language. Science and Education, 3(9), 146-156.
12. Granger, S. (2003a). Error-tagged learner corpora and CALL: A promising synergy. CALICO Journal, 20(3): 465-480.
13. Granger, S. (2003b). The international corpus of learner English: A new resource for foreign language learning and teaching and second language acquisition research. TESOL Quarterly, 37(3): 538-546.
Copyright (c) 2026 «ACTA NUUz»
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
.jpg)
1.png)
