Yabancı Öğrencilerin Yapay Zekâ ile Türkçe Dil Becerisi Öğrenimi ve Algılarının İncelenmesi

Yıl 2025, Cilt: 16 Sayı: 1, 775 - 797

Kılıç Köçeri , Abdulhak Halim Ulaş

https://doi.org/10.51460/baebd.1614932

Öz

Yabancı dil öğreniminde teknolojik yeniliklerin artan etkisi, özellikle yapay zekânın sağladığı olanaklarla birlikte son yıllarda dikkat çekici şekilde artmıştır. Bu bağlamda araştırma, yapay zekânın Türkçenin dört temel becerisini geliştirmeye yönelik etkisini katılımcıların deneyim ve algıları üzerinden değerlendirmeyi amaçlamaktadır. Araştırmanın odak noktası yabancı dil olarak Türkçe öğreniminde yapay zekâ kullanımının okuma, yazma, konuşma ve dinleme becerilerine etkisini analiz etmektedir. Araştırmada nitel araştırma yöntemi benimsenmiş ve veri toplama sürecinde yarı yapılandırılmış görüşme formu kullanılmıştır. Araştırmaya 2024-2025 eğitim öğretim yılında Ağrı İbrahim Çeçen Üniversitesi’nde öğrenim gören 12 yabancı uyruklu öğrenci katılmıştır. Elde edilen veriler içerik analizi ile değerlendirilmiş ve yapay zekânın Türkçenin dört temel dil becerisini olumlu yönde etkilediği saptanmıştır.

Anahtar Kelimeler

Yapay Zekâ, Dil Öğrenimi, Okuma, Yazma, Konuşma, Dinleme

Etik Beyan

var.

Destekleyen Kurum

yok

Teşekkür

Tüm dergi çalışanı hocalarıma teşekkür ederim.

Examination of Foreign Students’ Acquisition of Turkish Language Skills through Artificial Intelligence and Their Perceptions

Öz

In recent years, the role of artificial intelligence in foreign language learning has garnered significant interest. Research has demonstrated the positive effects of artificial intelligence on language acquisition. This study aims to evaluate the impact of artificial intelligence on the development of the four fundamental skills of Turkish from the perspectives of the participants’ experiences and perceptions. The primary focus of the research is to analyze the effects of artificial intelligence usage on reading, writing, speaking, and listening skills in the context of learning Turkish as a foreign language. A qualitative research methodology was adopted, and a semi-structured interview form was utilized for data collection. The study involved 12 foreign students enrolled at Ağrı İbrahim Çeçen University during the 2024-2025 academic year. The data obtained were analyzed through content analysis, revealing that artificial intelligence positively influences the four essential language skills of Turkish.

Anahtar Kelimeler

Artificial Intelligence, Language Learning, Reading, Writing, Speaking, Listening

Kaynakça

• Athanassopoulos, S. M., & Komis, V. (2023). The use of ChatGPT as a learning tool to improve foreign language writing in a multilingual and multicultural classroom. Advances in Mobile Learning Educational Research, 3(2), 818-824. https://doi.org/10.25082/AMLER.2023.02.009
• Akkaya, N., & Şengül, L. (2023). Sohbet Robotları (Chatbots) ve Yabancı Dil Eğitimi. Dokuz Eylül Üniversitesi Buca Eğitim Fakültesi (58), 2988-2999. https://doi.org/10.534444/deubefd.1340781 Baidoo-Anu, D., & Ansah, L. O. (2023). Educational in the era of generative artificial intelligence (AI): Understanding potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500
• Baskara, R. (2023). Exploring the implication of ChatGPT for language learning in higher education. Indonesian Journal of English Language Teaching and Applied Linguistics, 7(2), 348-358. https://doi.org/10.21093/ijeltal.v7i2.1387
• Campbell, J. L. (2013). Coding in-depth semistructured interviews: Problems of unitization and intercoder reliability and agreement. Sociological Methods & Research, 42(3), 294-320. https://doi.org/10.1177/0049124113500475
• Cansız, M. K., & Yavan, N. (2018). Girişimcilik ekosisteminde Türkiye için yeni bir araç: Yenilik Merkezleri/Ağları. Verimlilik Dergisi, (4), 7-49.
• Creswell, J. W. (2013). Steps in conducting a scholarly mixed methods study.
• Eichstaedt, J. C. (2021). Closed-and open-vocabulary approaches to text analysis: A review, quantitative comparisonn, and recommendations. Psychological Methods, 26(4), 398. https://doi.org/10.1037/met0000349
• Estrada, M. A. (2023). Artificial intelligence (AI) can change the way of doing policy modelling. Journal of Policy Modelling, 45(6), 1099-1112. https://doi.org/10.1016/j.jpolmod.2023.11.005
• İltar, L. (2020). Kültürlerarası iletişimsel dil yeterliliği bağlamında göçmenlere Türkçe öğretimi. Göçmenlere Türkçe Öğretimi.
• Fitria, T. N. (2023). Artificial intelligence (AI) technology in OpenAI ChatGPT application: A reviwe of ChatGPT in writing English essay. Journal of English Language Teaching, 12(1), 44-58. https://doi.org/doi.org/10.15294/elt.v12i1.64069
• Franzosi, R. D., & Vicari, S. (2013). Quantitative narrative analysis software options compared: PC-ACE and CAQDAS (ATLAS. ti, MAXqda, and NVivo). Quality & Quantity, 47, 3219-3247. https://doi.org/10.1007/s11135-012-9714-3
• Giorgi, A. (2009). The descriptive phenomenological method in psychology: A modified Husserlian approach. Duquesne university press.
• Gugushvili, T., & Salukvadze, G. (2021). Using MAXQDA for analyzing documents: An example of prioritization research design in urban development. In M. Müller & S. Radiker (Eds.), The practice of qualitative data anaysis: Research examples using MAXQDA (pp. 107-120).
• Haleem, A. J., & Singh, R. P. (2022). An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges. BenchCouncil transactions on benchmarks, standarts and evaluations, 2(4), 100089. https://doi.org/10.1016/j.tbench.2023.100089
• Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022). Artificial intelligence for assessment and feedback to enhance student success in higher education. Mathematical Problems in Engineering, 2022(1), 5215722
• Ivanov, V., & Killian, L. (2005). A practitioner’s guide to lag order selection for VAR impulse response analysis. Studies in Nonlinear Dynamics & Econometrics, 9(1). https://doi.org/10.2202/1558-3708.1219
• Kallou, S., & Kikilia, A. (2021). A transformative educational fremework in tourism higher education through digital Technologies during the COVID-19 pandemic. Advances in Mobile Learning Educational Research, 1(1). https://doi.org/10.25082/AMLER.2021.01.005
• Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability, 15(16), 12451
• Katı, T. N., & Can, U. (2024). Yapay zekâ ile üretilen metinlerin yabancı dil olarak Türkçe öğretiminde okuma becerisine yönelik kullanılabilirliği: ChatGPT-3.5 örneği. İnönü Üniversitesi Eğitim Fakültesi Dergisi, 25(2), 538-569. https://doi.org/10.17679/inuefd.1415303
• Köçeri, K., & Kırkkılıç, H. A. (2024). Yapay Zekânın Türkçe Dil Yeterliliğinin Gelişimi Üzerindeki Etkileri: Türkçe ve Türk Dili Öğretmenleri Üzerinde Bir Araştırma. Mersin Üniversitesi Eğitim Fakültesi Dergisi, 20(3), 475-489. https://doi.org/10.17860/mersinefd.1504250
• Kohnke, H. D., & Davidson, J. M. (1940). A survey and discussion of lysimeters and a bibliography on their construction and performance. US Department of Agriculture.
• Koraishi, O. (2023). Teaching English in the age of AI: Embracing ChatGPT to optimize EFL materials and assessment. Language Education and Technology, 3(1), 55-72.
• Kostka, I., & Toncelli, R. (2023). Exploring applications of ChatGPT to English language teaching: Opportunities, challenges, and recommendations. TESL-EJ, 27(3), 3. https://doi.org/10.55593/ej.27107int
• Kuckartz, U., & Radiker, S. (2021). Using MAXQDA for mixed methods research. The Routledge reviewer’s guide to mixed methods analysis, 305-318.
• Mart, M., & Kaya, G. (2024). Okul öncesi öğretmen adaylarının yapay zekâya yönelik tutumları ve yapay zekâ okuryazarlığı arasındaki ilişkinin incelenmesi. Edutech Research, 2(1), 91-109.
• Meniado, J. C. (2023). The Impact of ChatGPT on English Language Teaching, Learning and Assesment: A Rapid Review of Literature. Arab World English Journal, 14(4).
• Miles, M. B. (1994). Qualitative Data Analysis: An Expanded Sourcebook. Thousand Oaks.
• Moser, A., & Korstjens, I. (2018). Series: Practical guidance to qualitative research: Part 3: Sampling, data collection and analysis: European Journal of Generative Practive, 24(1), 9-18. https://doi.org/10.1080/13814788.2017.1375091
• Montenegro-Rueda, M., Fernández-Cerero, J., Fernández-Batanero, J. M., & López-Meneses, E. (2023). Impact of the implementation of ChatGPT in education: A systematic review. Computers, 12(8), 153. https://doi.org/10.3390/computers12080153
• Müller, A. (2021). Using MAXQDA’s visiul tools. an axample with historical legal documents. In M. C. Gizzi & S. Radiker (Eds.), The practice of qualitative data analysis: Research examples using MAXQDA (pp. 55-70). https://doi.org/10.36192/978-3-948768058
• Negrila, A. M. C. (2023). The new revolution in language learning: The power of artificial intelligence and education 4.0. Bulletin of “Carol I” National Defence University (EN), 12(02), 16-27.
• Patty, J. (2024). The use of IA in language learning: what you need to know. Journal Review Pendidikan dan Pengajaran (JRPP), 7(1), 642-654.
• Pokrivcakova, S. (2019). Preparing teachers for the application of AI-powered technologies in foreign language education. Journal of Language and Cultural Education, 7(3), 135-153. https://doi.org/10.2478/jolace-2019-0025
• Rahman, M. M. (2023). Chatgpt for education and research: Opportunities, threats, and strategies. Applied Sciences, 13(9), 5783. https://doi.org/10.3390/app13095783
• Shishido, J. C. (2021). Promoting Briliance: Unlocking ChatGPT’s potential to Revolutionize EFL dialogu pratices. Language Processing Society 30th Annual Conference Proceedings (March 2024) (p. 3155-3159) Tokyo: Tokyo Denki University.
• Sovrano, F. A., & Bacchelli, A. (2023). Toward eliminating hallucinations: GPT-based explanatory AI for intelligence textbooks and documentation. In CEUR Workshop Proceedings (Vol. 5465). CEUR-WS
• Stebbins, R. A. (2001). Exploratory research in the social sciences (Vol. 48). Sage.
• Swedberg, R. (2020). Exploratory research. Enhancing progress in social science, 17-41.
• Tavşanlı, Ö. F., & Kaldırım, A. (2020). Türkiye’de süreç temelli yazma yaklaşımı: Bir tematik analiz çalışması. Cumhuriyet International Journal of Education, 9(1), 108-138.
• Xiao, Y., & Zhi, Y. (2003). An exploratory study of EFL learners’ use of ChatGPT for language learning tasks: Experience and perceptions. Languages, 8(3), 212. https://doi.org/10.3390/languages8030212
• White, M. D., & Marsh, E. E. (2006). Content analysis: A flexible methodology. Library Trends, 55(1), 22-45. https://doi.org/10.1353/lib.2006.0053
• Whitebread, D., & Pino-Pasternak, D. (2013). Video analysis of self-regulated learning in social and naturalistic context. Interpersonal regulation of leanring and motivation, 14-44.
• Yıldız, M. (2023). Exploring The Potential Of Chatbots And Chatgpt in Enhancing Vocabulary Knowledge. In Transforming The Language Teaching Experience İn The Age Of AI (pp. 160-188) IGI Global. https://doi.org/10.4018/978-1-6684-9893-4.ch010
• Young, J. C., & Shishido, M. (2023). Investigating OpenAI’s potentials in generating Chatbot’s dialogue for English as a foreign language learning. International Journal of Advanced Computer Science and Applications, 89(6).
• Zileli, E. N. (2023). Yabancı dil olarak Türkçe öğretiminde ChatGPT örneği. Uluslararası Karamanoğlu Mehmetbey Eğitim Araştırmaları Dergisi, 5(1), 42-51. https://doi.org/10.47770/ukmead.1296013
• Zhou, Y. (2023). Basic theory of fractional differential equations. World scientific. https://doi.org/10.11.1142/13289