O‘ZBEK VA RUS TILLARIDA ILMIY-PEDAGOGIK TUSHUNCHALARNING DISKURSIV REPREZENTATSIYASI (KORPUS TAHLILI MA’LUMOTLARI ASOSIDA)

Mualliflar

DOI:

https://doi.org/10.67227/eb5jqx87

Kalit so‘zlar:

pedagogik diskurs, ilmiy-pedagogik terminologiya, korpus lingvistikasi, o‘zbek tili, rus tili, qiyosiy tahlil, kollokatsiya, tillararo ekvivalentlik, tushunchaviy asimmetriya.

Abstrak

Maqolada pedagogik diskursga oid matnlarning qiyoslanadigan korpuslari materiallari asosida o‘zbek va rus tillarida ilmiy-pedagogik tushunchalarning diskursiv reprezentatsiyasi ko‘rib chiqiladi. Tadqiqotning maqsadi pedagogika va ta’lim sohasidagi asosiy tushunchalarning tilda ifodalanish usullaridagi o‘xshashlik va farqlarni aniqlashdan iborat bo‘lib, ular tillarning tipologik xususiyatlari, terminologik tizimlarning shakllanish tarixi hamda diskursiv amaliyotlarning o‘ziga xos jihatlari bilan belgilanadi. Tadqiqot materiali sifatida Rus tili milliy korpusi va O‘zbek tili milliy korpusining quyi korpuslari, shuningdek, 2015–2025-yillarga oid pedagogik matnlar asosida maxsus tuzilgan, umumiy hajmi qariyb 4,1 million so‘z qo‘llanishidan iborat qiyoslanadigan korpusdan foydalanilgan. Tadqiqotda chastotaviy, kollokatsion va konkordans tahlili, shuningdek, qiyosiy-tipologik va diskurs-tahlil metodlari qo‘llanilgan. 32 juft termin tavsiflanib, tillararo muvofiqlik turlari (to‘liq ekvivalentlik, qisman ekvivalentlik, tushunchaviy asimmetriya) aniqlangan, terminlarning kollokatsion profillari va diskursiv ixtisoslashuvidagi farqlar ochib berilgan. O‘zbek pedagogik terminologik tizimi asosiy birliklarning (ta’lim, bilim, malaka) yuqori darajadagi ko‘p ma’noliligi hamda rus tili orqali xalqaro leksikaning faol o‘zlashtirilishi bilan tavsiflanishi, rus tilida esa tushunchalarning yanada batafsil differensiatsiyalanishi kuzatilishi ko‘rsatilgan. Tadqiqot natijalaridan terminografiya, tarjima, maxsus maqsadlar uchun til o‘qitish hamda ikki tilli ta’lim resurslarini ishlab chiqishda foydalanish mumkin.

Yuklashlar

Yuklab olish maʼlumotlari hali mavjud emas.

Havolalar

1. Малахова В. Л. Специфика дискурса в перспективе лингвистических исследований // Вопросы журналистики, педагогики, языкознания. – 2022. – Т. 41, № 1. – С. 134–142. – DOI: 10.52575/2712-7451-2022-41-1-134-142. – URL: https://doi.org/10.52575/2712-7451-2022-41-1-134-142.

2. Захаров В. П., Богданова С. Ю. Корпусная лингвистика: учебник. – 3-е изд., перераб. – Санкт-Петербург: Издательство Санкт-Петербургского университета, 2020. – 234 с. – ISBN: 978-5-288-05997-1. – URL: https://sziu-lib.ranepa.ru/new_book/Html_04.26/zakharov/zakharov.html.

3. McEnery T., Brezina V. Fundamental Principles of Corpus Linguistics. – Cambridge: Cambridge University Press, 2022. – 326 p. – DOI: 10.1017/9781107110625. – URL: https://doi.org/10.1017/9781107110625.

4. Baker P. Using Corpora in Discourse Analysis. – 2nd ed. – London: Bloomsbury Academic, 2023. – 280 p. – ISBN: 978-1-350-08377-6 (e-book). – URL: https://www.bloomsbury.com/us/using-corpora-in-discourse-analysis-9781350083776/.

5. Tursunov M. Software of the National Corpus of the Uzbek Language // International Journal of Advance Scientific Research. – 2023. – Vol. 3, № 10. – P. 190–199. – URL: https://api.scienceweb.uz/storage/publication_files/4848/13856/6538d5e9a4677___%D0%A1%D0%B1.%D0%9A%D0%BE%D0%BD%D1%84.%D0%A7-1_compressed.pdf.

6. Khamroeva Sh., Mengliyev B., Kholova M., Gulyamova Sh. The 80/20 Principle in Morphemics-Morphology in the Educational Corpus of the Uzbek Language // 2024 International Conference on Computer Science and Engineering (UBMK). – 2024. – URL: https://www.tsuull.uz/sites/default/files/ubmk2024_the_80_20_principle_in_morphemics_0.pdf.

7. Agostini A., Usmanov T., Khamdamov U., Abdurakhmonova N., Mamasaidov M. UZWORDNET: A Lexical-Semantic Database for the Uzbek Language // Proceedings of the 11th Global Wordnet Conference. – 2021. – P. 8–19. – DOI: 10.18653/v1/2021.gwc-1.2. – URL: https://aclanthology.org/2021.gwc-1.2/.

8. Salaev U., Kuriyozov E., Gómez-Rodríguez C. SimRelUz: Similarity and Relatedness Scores as a Semantic Evaluation Dataset for Uzbek Language // Proceedings of the 1st Annual Meeting of the ELRA/ISCA Special Interest Group on Under-Resourced Languages (SIGUL 2022). – 2022. – P. 199–206. – URL: https://aclanthology.org/2022.sigul-1.26/.

9. Sharipov M., Kuriyozov E., Yuldashev O., Sobirov O. UzbekTagger: The Rule-Based POS Tagger for Uzbek Language // arXiv preprint. – 2023. – arXiv:2301.12711. – URL: https://arxiv.org/abs/2301.12711.

10. Veitsman Y., Hartmann M. Recent Advancements and Challenges of Turkic Central Asian Language Processing // arXiv preprint. – 2024. – arXiv:2407.05006. – URL: https://arxiv.org/abs/2407.05006. Shuningdek, konferensiya nashri: https://aclanthology.org/2025.loreslm-1.25/.

11. Mirkhanova G. et al. Uzbek Terminology and Linguistic Engineering Integration: Principles of Semantic Tagging of Terms in Uzbek Scientific Discourse for Language Corpora. – 2025.

12. Савчук С. О., Архангельский Т. А., Бонч-Осмоловская А. А., Донина О. В., Кузнецова Ю. Н., Ляшевская О. Н., Орехов Б. В., Подрядчикова М. В. Национальный корпус русского языка 2.0: новые возможности и перспективы развития // Вопросы языкознания. – 2024. – № 2. – С. 7–34. – DOI: 10.31857/0373-658X.2024.2.7-34. – URL: https://vja.ruslang.ru/ru/archive/2024-2/7-34.

13. Egbert J., Larsson T., Biber D. Doing Linguistics with a Corpus: Methodological Considerations for the Everyday User. – Cambridge: Cambridge University Press, 2020. – 88 p. – DOI: 10.1017/9781108888790. – URL: https://doi.org/10.1017/9781108888790.

14. Biber D., Egbert J., Keller D. Reconceptualizing Register in a Continuous Situational Space // Corpus Linguistics and Linguistic Theory. – 2020. – Vol. 16, № 3. – P. 581–616. – DOI: 10.1515/cllt-2018-0086. – URL: https://doi.org/10.1515/cllt-2018-0086.

15. Madatov K., Matlatipov S., Aripov M. Uzbek Text’s Correspondence with the Educational Potential of Pupils: A Case Study of the School Corpus // arXiv preprint. – 2023. – arXiv:2303.00465. – URL: https://arxiv.org/abs/2303.00465.

16. Kuriyozov E., Doval Y., Gómez-Rodríguez C. Cross-Lingual Word Embeddings for Turkic Languages // Proceedings of the Twelfth Language Resources and Evaluation Conference (LREC 2020). – Marseille: European Language Resources Association, 2020. – P. 4054–4062. – URL: https://aclanthology.org/2020.lrec-1.499/.

17. Шунейко А. А. Корпусная лингвистика: учебник для вузов. – Москва: Юрайт, 2022. – 222 с. – ISBN: 978-5-534-13603-6. – URL: https://urait.ru/bcode/497535.

18. The Need of Uzbek Learners to Use Language Corpus While Learning Languages // International Journal of Education, Social Science & Humanities. – 2023. – Vol. 11, № 1. – P. 61–63. – DOI: 10.5281/zenodo.7512722. – URL: https://doi.org/10.5281/zenodo.7512722.

19. Rabbimov I. M., Kobilov S. S. Multi-Class Text Classification of Uzbek News Articles Using Machine Learning // Journal of Physics: Conference Series. – 2020. – Vol. 1546, № 1. – Art. 012097. – DOI: 10.1088/1742-6596/1546/1/012097. – URL: https://doi.org/10.1088/1742-6596/1546/1/012097.

20. Kuriyozov E., Salaev U., Matlatipov S., Matlatipov G. Text Classification Dataset and Analysis for Uzbek Language // arXiv preprint. – 2023. – arXiv:2302.14494. – URL: https://arxiv.org/abs/2302.14494.

21. Закон Республики Узбекистан «Об образовании» от 23 сентября 2020 года № ЗРУ-637 // Национальная база данных законодательства Республики Узбекистан. – 24.09.2020. – № 03/20/637/1313. – URL: https://lex.uz/ru/docs/5013009.

22. Musaev M., Mussakhojayeva S., Khujayorov I., Khassanov Y., Ochilov M., Varol H. A. USC: An Open-Source Uzbek Speech Corpus and Initial Speech Recognition Experiments // Speech and Computer (SPECOM 2021). Lecture Notes in Computer Science. – Cham: Springer, 2021. – Vol. 12997. – P. 437–447. – DOI: 10.1007/978-3-030-87802-3_40. – URL: https://doi.org/10.1007/978-3-030-87802-3_40.

Yuklab olishlar

Nashr qilingan

2026-10-05

Qanday havola qilish kerak

O‘ZBEK VA RUS TILLARIDA ILMIY-PEDAGOGIK TUSHUNCHALARNING DISKURSIV REPREZENTATSIYASI (KORPUS TAHLILI MA’LUMOTLARI ASOSIDA). (2026). Ijtimoiy-Gumanitar Sohada Ilmiy-Innovatsion Tadqiqotlar, 3(10), 215-222. https://doi.org/10.67227/eb5jqx87