Araştırma Makalesi
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Uygulamalı Dilbilimde Yapay Zeka: Uygulamalar, Sınırlıklar ve Sorunlar

Yıl 2025, Cilt: 11 Sayı: 2, 957 - 969, 29.10.2025
https://doi.org/10.31464/jlere.1671085
https://izlik.org/JA97UH99GN

Öz

Yapay zekanın (YZ) kuramdan uygulamaya hızlı geçişi birçok alanda devrim yaratmıştır ve bilimsel araştırmalar da bundan etkilenmiştir. Dilbilimde YZ, dil incelemesi, derlem geliştirme ve dil öğrenimini değiştirerek son derece etkili olmuştur. Bu kısa makalede, alanyazın taraması yapılarak YZ'nin derlem dilbilimi ve uygulamalı dilbilimdeki uygulamaları aracılığıyla dilbilimsel araştırmalarda ki potansiyelini incelenmiştir. Ayrıca, YZ'nin kullanımındaki sınırlamaları ve etik sorunları ortaya konmuştur. Bu kapsamda makalede ilk olarak temel olan YZ kavramları açıklanmış, ardından YZ'nin derlem dilbilimindeki uygulamaları ve YZ'nin dil öğrenimi ve özellikle kişiselleştirilmiş öğrenme teknolojileri oluşturma ve dil edinimine yardımcı olma konusundaki rolü ile uygulamalı dilbilim üzerindeki etkisi ortaya konulmuştur. Son olarak, YZ'nin sınırlılıkları ve etik zorlukları içeren tartışmalı konuları ele alınmıştır.

Kaynakça

  • Ahmad, K., Iqbal, W., El-Hassan, A., Quadir, J., Benhaddou, D., & Ayyash, M. (2024). Data-driven artificial intelligence in education: A comprehensive review. IEEE Transactions on Learning Technologies, 17, 12-31. https://doi.org/10.1109/TLT.2023.3314610
  • Ahmadi, L. (2022). Rhetorical structure of applied linguistics research article discussions: A comparative cross-cultural analysis. Journal of Language & Education, 8(3), 11-22. https://doi.org/10.17323/jle.2022.12750
  • Alaqlobi, O., Alduais, A., Qasem, F., & Alasmari, M. (2024). Artificial intelligence in applied (linguistics): A content analysis and future prospects. Cogent Arts & Humanities, 11(1). https://doi.org/10.1080/23311983.2024.2382422
  • Backus, A., Cohen, M., Cohn, N., Faber, M., Krahmer, E., Laparle, S., Maier, E., Van Miltenburg, E., Roeflofsen, F., Sciubba, E., Scholman, M., Shterionov, D., Sie, M., Tomas, F., Vanmassenhove, E., Venhuizen, N., & de Vos, C. (2023). Big questions for linguistics in the age of AI. Linguistics in the Netherlands, 40, 301-308. https://doi.org/10.1075/avt.00094.bac
  • Baidoo-anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500
  • Baker, M., & Pérez-González, L. (2011). Translation and interpreting. In J. Simpson (Ed.), The Routledge handbook of applied linguistics (pp. 39-52). Taylor & Francis.
  • Bannister, P. (2024). English medium instruction educator language assessment literacy and the test of generative AI in online higher education. Journal of Research in Applied Linguistics, 15(2), 55-72. https://doi.org/10.22055/rals.2024.45862.3214
  • Corchado, J. M., López F, S., Núñez V, J. M., Garcia S, R., & Chamoso, P. (2023). Generative artificial intelligence: Fundamentals. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 12(1). DOI: https://doi.org/10.14201/adcaij.31704
  • Crosthwaite, P., & Baisa, V. (2023). Generative AI and the end of corpus-assisted data-driven learning? Not so fast! Applied Corpus Linguistics, 3, 1-4. https://doi.org/10.1016/j.acorp.2023.100066
  • Curry, N., Baker, P., & Brooks, G. (2024). Generative AI for corpus approaches to discourse studies: A critical evaluation of ChatGPT. Applied Corpus Linguistics, 4, 1-9. https://doi.org/10.1016/j.acorp.2023.100082
  • Dupre, G. (2021). (What) can deep learning contribute to theoretical linguistics? Minds and Machines, 31, 617-635. https://doi.org/10.1007/s11023-021-09571-w
  • Flowers, J. C. (2019). Strong and weak AI: Deweyan considerations. AAAI Spring Symposium: Towards Conscious AI Systems. AAAI Spring Symposium: Towards Conscious AI Systems. https://ceur-ws.org/Vol-2287/paper34.pdf
  • Hadi, M. U., Al-Tashi, Q., Qureshi, R., Shah, A., Muneer, A., Irfan, M., Zafar, A., Shaikh, M. B., Akhtar, N., Al-Garadi, M. A., Wu, J., & Mirjalili, S. (2023). Large language models: A comprehensive survey of applications, challenges, limitations, and future prospects. https://doi.org/10.36227/techrxiv.23589741.v1
  • Hagos, D. H., Battle, R., & Rawat, D. B. (2024). Recent advances in generative AI and large language models: Current status, challenges, and perspectives. IEEE Transactions on Artificial Intelligence, 5(12), 5873-5893. https://doi.org/10.1109/TAI.2024.3444742
  • Hockly, N. (2023). Artificial intelligence in English language teaching: The good, the bad and the ugly. RELC Journal, 54(2), 445-451. https://doi.org/10.1177/00336882231168504
  • Kaddour, J., Harris, J., Mozes, M., Bradley, H., Raileanu, R., & McHardy, R. (2023). Challenges and applications of large language models. ArXiv, abs/2307. https://doi.org/10.48550/arXiv.2307.10169
  • Kartal, G., & Yeşilyurt, Y. E. (2024). A bibliometric analysis of artificial intelligence in L2 teaching and applied linguistics between 1995 and 2022. ReCALL, 36(3), 359–375. https://doi.org/10.1017/S0958344024000077
  • Kostka, I., & Toncelli, R. (2023). Exploring applications of ChatGPT to English language teaching: Opportunities, challenges, and recommendations. The Electronic Journal for English as a Second Language, 27(3). https://doi.org/10.55593/ej.27107int
  • Kwok, H. L., Shi, Y., Xu, H., Li, D., & Liu, K. (2025). GenAI as a translation assistant? A corpus-based study on lexical and syntactic complexity of GPT-post-edited learner translation. System, 130. https://doi.org/10.1016/j.system.2025.103618
  • Laborda, J. G., Madarova, S., & Royo, T. M. (2024). Issues in the design and implementation of chatbots for oral language assessment. Journal of Research in Applied Linguistics, 15(2), 43-54. https://doi.org/10.22055/rals.2024.45822.3211
  • Łukaisk, M. (2023). Corpus linguistics and generative AI tools in term extraction: A case of Kashubian – a low-resource language. Applied Linguistics Papers, 27(4), 34-45. https://doi.org/10.32612/uw.25449354.2023.4.pp.34-45
  • McShane, M., & Nirenburg, S. (2021). Linguistics for the Age of AI. MIT Press.
  • Mohammadi, M. (2024). Language teachers’ assessment literacy in AI-aided adaptive learning environments. Journal of Research in Applied Linguistics, 15(2), 73-88. https://doi.org/10.22055/rals.2024.46120.3235
  • Prodan, A., Occhipinti, J.-A., Ahlip, R. A., Ujdur, G., Eyre, H. A., Goosen, K., Penza, L., & Heffernan, M. (2024). Cutting through the confusion and hype: Understanding the true potential of generative AI. SSRN. https://dx.doi.org/10.2139/ssrn.4995089
  • Roe, J. (2024). Exploring the impacts of GenAI on English and applied linguistics: Implications for a future-ready journal. Journal of English and Applied Linguistics, 3(1). http://dx.doi.org/10.59588/2961-3094.1092
  • Sharadgah, T. A., & Sa'di, R. A. (2022). A systematic review of research on the use of artificial intelligence in English language teaching and learning (2015-2021): What are the current effects? Journal of Information Technology Education: Research, 21, 337-377. https://doi.org/10.28945/4999
  • Sindhu, B., Prathamesh, R. P., Sameera, M. B., & KumaraSwamy, S. (2024). The evolution of a large language model: Models, applications and challenges. International Conference on Current Trends in Advanced Computing (ICCTAC), 1-8. https://doi.org/10.1109/ICCTAC61556.2024.10581180
  • Soy, S., Arsyad, S., & Syafryadin, S. (2023). The rhetorical structure of review article abstracts in applied linguistics published in high-impact international journals. Journal of Language and Literature, 23(2), 344-357. https://doi.org/10.24071/joll.v23i2.6128
  • Uchida, S. (2024). Using early LLMs for corpus linguistics: Examining ChatGPT's potential and limitations. Applied Corpus Linguistics, 4(1). https://doi.org/10.1016/j.acorp.2024.100089
  • Wang, F., Zhou, X., Li, K., Cheung, A. C. K., & Tian, M. (2025). The effects of artificial intelligence-based interactive scaffolding on secondary students’ speaking performance, goal setting, self-evaluation, and motivation in informal digital learning of English. Interactive Learning Environments, 1-20. https://doi.org/10.1080/10494820.2025.2470319
  • Zappavigna, M. (2023). Hack your corpus analysis: How AI can assist corpus linguists deal with messy social media data. Applied Corpus Linguistics, 3(2), 1-5. https://doi.org/10.1016/j.acorp.2023.100067
  • Zayda, M. (2024). Large language models and generative AI, oh my! Computer, 57(3), 127-132. https://doi.org/10.1109/MC.2024.3350290

AI in Applied Linguistics: Implications, Limitations, and Issues

Yıl 2025, Cilt: 11 Sayı: 2, 957 - 969, 29.10.2025
https://doi.org/10.31464/jlere.1671085
https://izlik.org/JA97UH99GN

Öz

AI's transition from theory to practice has revolutionized many fields, and scientific research is no different. AI is immensely influential in linguistics, changing language analysis, corpus development, and language learning. This paper reviews the literature and examines the potential of AI in linguistic research through its applications in corpus linguistics and applied linguistics. Also, the limitations and ethical issues inherent in AI's use are explained. This paper starts with describing traditional AI notions followed by the practical applications of AI in corpus linguistics and the impact of AI on language learning and applied linguistics, specifically its role in creating personalized learning technologies and assisting in language acquisition. Finally, this paper will cover the controversial topics of AI, including its inherent limitations and the ethical challenges it poses, concluding that while AI has potential, its responsible and knowledgeable implementation is key to advancing linguistic research and education.

Etik Beyan

This study complies with Research and Publication Ethics and the current study does not require ethics committee approval.

Kaynakça

  • Ahmad, K., Iqbal, W., El-Hassan, A., Quadir, J., Benhaddou, D., & Ayyash, M. (2024). Data-driven artificial intelligence in education: A comprehensive review. IEEE Transactions on Learning Technologies, 17, 12-31. https://doi.org/10.1109/TLT.2023.3314610
  • Ahmadi, L. (2022). Rhetorical structure of applied linguistics research article discussions: A comparative cross-cultural analysis. Journal of Language & Education, 8(3), 11-22. https://doi.org/10.17323/jle.2022.12750
  • Alaqlobi, O., Alduais, A., Qasem, F., & Alasmari, M. (2024). Artificial intelligence in applied (linguistics): A content analysis and future prospects. Cogent Arts & Humanities, 11(1). https://doi.org/10.1080/23311983.2024.2382422
  • Backus, A., Cohen, M., Cohn, N., Faber, M., Krahmer, E., Laparle, S., Maier, E., Van Miltenburg, E., Roeflofsen, F., Sciubba, E., Scholman, M., Shterionov, D., Sie, M., Tomas, F., Vanmassenhove, E., Venhuizen, N., & de Vos, C. (2023). Big questions for linguistics in the age of AI. Linguistics in the Netherlands, 40, 301-308. https://doi.org/10.1075/avt.00094.bac
  • Baidoo-anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500
  • Baker, M., & Pérez-González, L. (2011). Translation and interpreting. In J. Simpson (Ed.), The Routledge handbook of applied linguistics (pp. 39-52). Taylor & Francis.
  • Bannister, P. (2024). English medium instruction educator language assessment literacy and the test of generative AI in online higher education. Journal of Research in Applied Linguistics, 15(2), 55-72. https://doi.org/10.22055/rals.2024.45862.3214
  • Corchado, J. M., López F, S., Núñez V, J. M., Garcia S, R., & Chamoso, P. (2023). Generative artificial intelligence: Fundamentals. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 12(1). DOI: https://doi.org/10.14201/adcaij.31704
  • Crosthwaite, P., & Baisa, V. (2023). Generative AI and the end of corpus-assisted data-driven learning? Not so fast! Applied Corpus Linguistics, 3, 1-4. https://doi.org/10.1016/j.acorp.2023.100066
  • Curry, N., Baker, P., & Brooks, G. (2024). Generative AI for corpus approaches to discourse studies: A critical evaluation of ChatGPT. Applied Corpus Linguistics, 4, 1-9. https://doi.org/10.1016/j.acorp.2023.100082
  • Dupre, G. (2021). (What) can deep learning contribute to theoretical linguistics? Minds and Machines, 31, 617-635. https://doi.org/10.1007/s11023-021-09571-w
  • Flowers, J. C. (2019). Strong and weak AI: Deweyan considerations. AAAI Spring Symposium: Towards Conscious AI Systems. AAAI Spring Symposium: Towards Conscious AI Systems. https://ceur-ws.org/Vol-2287/paper34.pdf
  • Hadi, M. U., Al-Tashi, Q., Qureshi, R., Shah, A., Muneer, A., Irfan, M., Zafar, A., Shaikh, M. B., Akhtar, N., Al-Garadi, M. A., Wu, J., & Mirjalili, S. (2023). Large language models: A comprehensive survey of applications, challenges, limitations, and future prospects. https://doi.org/10.36227/techrxiv.23589741.v1
  • Hagos, D. H., Battle, R., & Rawat, D. B. (2024). Recent advances in generative AI and large language models: Current status, challenges, and perspectives. IEEE Transactions on Artificial Intelligence, 5(12), 5873-5893. https://doi.org/10.1109/TAI.2024.3444742
  • Hockly, N. (2023). Artificial intelligence in English language teaching: The good, the bad and the ugly. RELC Journal, 54(2), 445-451. https://doi.org/10.1177/00336882231168504
  • Kaddour, J., Harris, J., Mozes, M., Bradley, H., Raileanu, R., & McHardy, R. (2023). Challenges and applications of large language models. ArXiv, abs/2307. https://doi.org/10.48550/arXiv.2307.10169
  • Kartal, G., & Yeşilyurt, Y. E. (2024). A bibliometric analysis of artificial intelligence in L2 teaching and applied linguistics between 1995 and 2022. ReCALL, 36(3), 359–375. https://doi.org/10.1017/S0958344024000077
  • Kostka, I., & Toncelli, R. (2023). Exploring applications of ChatGPT to English language teaching: Opportunities, challenges, and recommendations. The Electronic Journal for English as a Second Language, 27(3). https://doi.org/10.55593/ej.27107int
  • Kwok, H. L., Shi, Y., Xu, H., Li, D., & Liu, K. (2025). GenAI as a translation assistant? A corpus-based study on lexical and syntactic complexity of GPT-post-edited learner translation. System, 130. https://doi.org/10.1016/j.system.2025.103618
  • Laborda, J. G., Madarova, S., & Royo, T. M. (2024). Issues in the design and implementation of chatbots for oral language assessment. Journal of Research in Applied Linguistics, 15(2), 43-54. https://doi.org/10.22055/rals.2024.45822.3211
  • Łukaisk, M. (2023). Corpus linguistics and generative AI tools in term extraction: A case of Kashubian – a low-resource language. Applied Linguistics Papers, 27(4), 34-45. https://doi.org/10.32612/uw.25449354.2023.4.pp.34-45
  • McShane, M., & Nirenburg, S. (2021). Linguistics for the Age of AI. MIT Press.
  • Mohammadi, M. (2024). Language teachers’ assessment literacy in AI-aided adaptive learning environments. Journal of Research in Applied Linguistics, 15(2), 73-88. https://doi.org/10.22055/rals.2024.46120.3235
  • Prodan, A., Occhipinti, J.-A., Ahlip, R. A., Ujdur, G., Eyre, H. A., Goosen, K., Penza, L., & Heffernan, M. (2024). Cutting through the confusion and hype: Understanding the true potential of generative AI. SSRN. https://dx.doi.org/10.2139/ssrn.4995089
  • Roe, J. (2024). Exploring the impacts of GenAI on English and applied linguistics: Implications for a future-ready journal. Journal of English and Applied Linguistics, 3(1). http://dx.doi.org/10.59588/2961-3094.1092
  • Sharadgah, T. A., & Sa'di, R. A. (2022). A systematic review of research on the use of artificial intelligence in English language teaching and learning (2015-2021): What are the current effects? Journal of Information Technology Education: Research, 21, 337-377. https://doi.org/10.28945/4999
  • Sindhu, B., Prathamesh, R. P., Sameera, M. B., & KumaraSwamy, S. (2024). The evolution of a large language model: Models, applications and challenges. International Conference on Current Trends in Advanced Computing (ICCTAC), 1-8. https://doi.org/10.1109/ICCTAC61556.2024.10581180
  • Soy, S., Arsyad, S., & Syafryadin, S. (2023). The rhetorical structure of review article abstracts in applied linguistics published in high-impact international journals. Journal of Language and Literature, 23(2), 344-357. https://doi.org/10.24071/joll.v23i2.6128
  • Uchida, S. (2024). Using early LLMs for corpus linguistics: Examining ChatGPT's potential and limitations. Applied Corpus Linguistics, 4(1). https://doi.org/10.1016/j.acorp.2024.100089
  • Wang, F., Zhou, X., Li, K., Cheung, A. C. K., & Tian, M. (2025). The effects of artificial intelligence-based interactive scaffolding on secondary students’ speaking performance, goal setting, self-evaluation, and motivation in informal digital learning of English. Interactive Learning Environments, 1-20. https://doi.org/10.1080/10494820.2025.2470319
  • Zappavigna, M. (2023). Hack your corpus analysis: How AI can assist corpus linguists deal with messy social media data. Applied Corpus Linguistics, 3(2), 1-5. https://doi.org/10.1016/j.acorp.2023.100067
  • Zayda, M. (2024). Large language models and generative AI, oh my! Computer, 57(3), 127-132. https://doi.org/10.1109/MC.2024.3350290
Toplam 32 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Uygulamalı Dilbilim ve Eğitim Dilbilimi
Bölüm Araştırma Makalesi
Yazarlar

Engin Evrim Önem 0000-0002-2711-7511

Gönderilme Tarihi 7 Nisan 2025
Kabul Tarihi 8 Ekim 2025
Erken Görünüm Tarihi 29 Ekim 2025
Yayımlanma Tarihi 29 Ekim 2025
DOI https://doi.org/10.31464/jlere.1671085
IZ https://izlik.org/JA97UH99GN
Yayımlandığı Sayı Yıl 2025 Cilt: 11 Sayı: 2

Kaynak Göster

APA Önem, E. E. (2025). AI in Applied Linguistics: Implications, Limitations, and Issues. Dil Eğitimi ve Araştırmaları Dergisi, 11(2), 957-969. https://doi.org/10.31464/jlere.1671085

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Journal of Language Education and Research (JLERE)
Dil Eğitimi ve Araştırmaları Dergisi

https://dergipark.org.tr/en/pub/jlere

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