The Impact of ChatGPT’s Turkish Language Proficiency on Development: An Examination of Teachers’ Opinions

Öz

This study aimed to determine the impact of ChatGPT on the four fundamental language competencies for Turkish Language and Turkish Language and Literature teachers. Data was collected through a five-point likert scale survey from teachers who had experienced ChatGPT. Literature in the field was utilized in the development of the survey Additionally, the opinions of psychologists and academics in the public sector were considered to ensure the internal and external reliability of the survey. As teachers’ experience with ChatGPT was considered a criterion, purposive sampling was employed in the research. Descriptive analysis was used in the study, and SPSS 27.0 was the preferred data analysis program. The Cronbach’s Alpha value was taken into account to ensure the validity and reliability of the survey. Through descriptive analysis, the frequency, arithmetic mean, and standard deviation of each survey item were calculated and interpreted. The findings indicated positive effects of ChatGPT on the subcategories of reading, speaking, writing, and listening, leading to the conclusion that ChatGPT positively influences each subcategory and may enhance language proficiency in the future.

Anahtar Kelimeler

• ChatGPT
• language proficiency
• artificial intelligence
• language development

Yapay Zekânın Türkçe Dil Yeterliliğinin Gelişimi Üzerindeki Etkileri: Türkçe ve Türk Dili Öğretmenleri Üzerine Bir Araştırma

Öz

Bu çalışma, Türkçe ve Türk Dili ve Edebiyatı öğretmenlerinin yapay zekânın dilin dört temel yeterliğine etkisini belirlemeyi amaçlamıştır. Veriler yapay zekâyı deneyimlemiş öğretmenlerden beşli Likert tipinde bir anket formu aracılığıyla toplanmıştır. Anketin geliştirme sürecinde alan yazınından elde edilen verilerden yararlanılmıştır. Ayrıca anketin iç ve dış güvenirliğini sağlamak için kamuda görevli psikolog ve akademisyenlerin görüşleri dikkate alınmıştır. Öğretmenlerin dil öğretiminde yapay zekâyı deneyimlemiş olmaları bir ölçüt olarak kabul edildiğinden araştırmada amaçlı örnekleme yönteme başvurulmuştur. Araştırmada betimsel analiz yöntemi kullanılmış olup veri analizi için SPSS 27.0 veri analiz programı tercih edilmiştir. Anketin geçerlik ve güvenirliğini sağlamak için Cronbach’s alpha değeri göz önünde bulundurulmuştur. Betimsel analiz yöntemiyle her anket maddesinin frekansı, aritmetik ortalaması ve standart sapması hesaplanarak yorumlanmıştır. Elde edilen veriler öğretmenlerin yapay zekânın dilin okuma, konuşma, yazma ve dinleme ile bunları oluşturan alt kategorileri üzerinde olumlu görüşlere sahip olduğu sonucunu ortaya koymuştur. Bu bulgulardan hareketle yapay zekânın her bir dil becerisini olumlu yönde etkileyebileceği ve dil yeterliğinin geliştirdiği ifade edilebilir.

Anahtar Kelimeler

• ChatGPT
• dil yeterliği
• yapay zekâ
• dil gelişimi

Destekleyen Kurum

Destekleyen kurum bulunmamaktadır.

Etik Beyan

Bu araştırma Ağrı İbrahim Çeçen Üniversitesi Etik Komisyonunun 07.05.2024 tarihli ve E-95531838-050.102859 sayılı onayı ile yürütülmüştür.

Teşekkür

Tüm dergi çalışanlarına teşekkür eder, çalışmalarında başarılar dilerim.

Kaynakça

1. Adair, A. (2023). Teaching and learning with ai: how artificial intelligence is transforming the future of education. XRDS: Crossroads. The ACM Magazine for Students, 29(3), 7-9. https://doi.org/10.1145/3589252
2. Aina, M., & Joshua, W. (2024). Impact of ChatGPT in Higher Education Learning. JILTECH: Journal International of Lingua & Technology, 3(1). https://doi.org/10.55849/hiltech.v3i1.505
3. Al Mahmud, F. (2023). Investigating EFL students' writing skills through artificial intelligence: wordtune application as a tool. Journal of Language Teaching and Research, 14(5), 1395-1404. https://doi.10.17507/jiltr.1405.28
4. Anderson, S. A. (1990). Core indicators of nutritional state for difficult-to-sample populations. The Journal of Nutrition, 120, 155-1598. https://doi.org/10.1093/jn/120.suppl_11.1555
5. Arabiourrutia, M., Lopez, G., Artetxe, M., Alvarez, J., Bilbao, J., & Olazar, M. (2020). Waste tyre valorization by catalytic pyrolysis–A review. Renewable and Sustainable Energy Reviews, 129, 109932. https://doi.org/10.1016/j.rser.2020.109932
6. Aydoğan, H., & Akbarov, A. A. (2014). The four basic language skills, whole language & integrated skill approach in mainstream university classrooms in Turkey. Mediterranean Journal of Social Sciences, 5(9), 672-680. https://doi.org/10.5901/mjss.2014.v5n9p672
7. Babbie, E. R. (2020). The practice of social research. Cengage Learning.
8. Babu, C. S., & Akshara, P. M. (2024). Advanced applications of generative AI and natural language processing models. In P.A. Hesley (ED.), Revolutionizing conversational AI: Unleashing the power of ChatGPT-Based applications in generative AI and natural language processing (pp.. 228-248). IGI Global. https://doi.org/10.4018/979-8-3693-0502-7.ch011

9. Barakazi, E. (2023). The Role of Technological Innovations in Diversification of Recreational Activities: Interview with ChatGPT. Journal of Gastronomy, Hospitality and Travel 6(4), 1639-1649. https://doi.org/10.33083/joghat.2023.359
10. Bates, M. J. (1989). The design of browsing and berry-picking techniques for the online search interface. Online review, 13(5), 407-424.
11. Berardino, L., Gregory, D., & Gregory, J. (2023). Building the speaking skills required in today's workplace. Business Education Innovation Journal, 15(1).
12. Bonner, E., Lege, R., & Frazier, E. (2023). Large Language Model-Based Artificial Intelligence in the Language Classroom: Practical Ideas for Teaching. Teaching English with Technology, 23(1), 23-41.
13. Çetinkaya, G., & Kögce, D. (2014). An evaluation of secondary school Turkish and mathematics teachers’ verbal feedback to students. Turkish Journal of Social Work Research, 18(2), 113-136.
14. Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264-75278.
15. Choi, H., Hamanaka, T., & Matsui, K. (2017). Design and implementation of interactive product manual system using chatbot and sensed data. 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE) (s. 1-5).
16. Coniam, D. (2014). The linguistic accuracy of chatbots: Usability from an ESL perspective. Text & Talk, 34(5), 545-567.
17. Crawford, J. R., & Howell, D. C. (1998). Regression equations in clinical neuropsychology: An evaluation of statistical methods for comparing predicted and obtained scores. Journal of Clinical and Experimental Neuropsychology, 20(5), 755-762.
18. Creswell, J. W. (2017). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.) Sage. Dean, D. (2010). What works in writing instruction. National Council of Teachers of English.
19. Dempere, J., Modugu, K., Hesham, A., & Ramasamy, L. K. (2023). The impact of ChatGPT on higher education. In Frontiers in Education. Frontiers in Education, 8, Article 1206936. https://doi.org/10.3389/feduc.2023.1206936
20. Dong, Y., Jiang, X., Jin, Z., & Li, G. (2023). Self-collaboration code generation via chatbot. arXiv preprint arXiv:2304.07590. https://doi.org/10.48550/arXiv.2304.07590
21. Dong, Y., Wu, S. X. Y., Dong, W. Y., & Tang, Y. (2020). The effects of home literacy environment on children’s reading comprehension development: A meta-analysis. Educational Sciences: Theory & Practise, 20(2), 63-82. https://doi.org/10.12738/jestp.2020.2.001
22. Galvis, N. M. D. (2010). Peer editing: A strategic source in EFL students' writing process. Colombian Applied Linguistics Journal, 12(1), 85-98. https://doi.org/10.14483/22487085.85 Ghermandi, A., Camacho-Valdez, V., & Trejo-Espinosa, H. (2020). Social media-based analysis of cultural ecosystem services and heritage tourism in a coastal region of Mexico. Tourism Management, 77, Article 104002. https://doi.org/10.1016/j.tourman.2019.104002
23. Graham, F. (2022). Daily briefing: Will ChatGPT kill the essay assignment?. Nature. https://doi.org/10.1038/d41586-022-03833-7
24. Huang, J., & Li, S. (2023). Opportunities and challenges in the application of ChatGPT in foreign language teaching. International Journal of Education and Social Science Research, 6(04), 75-89.
25. Hung, J., & Chen, J. (2023). The benefits, risks and regulation of using ChatGPT in Chinese academia: a content analysis. Social Sciences, 12(7), 380. https://doi.org/10.3390/socsci1207380
26. Hunt, A. W., Turner, G. R., Palotojko, H., Bottari, C., & Dawson, D. R. (2013). Executive function, self-regulation and attribution in acquired brain injury: A scoping review. Neuropsychological rehabilitation, 23(6), 914-932. https://doi.org/10.1080/09602011.2013.835739
27. Javaid, M., Haleem, A., & Singh, R. P. (2023). ChatGPT for healthcare services: An emerging stage for an innovative perspective. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 3(1), 100105. https://doi.org/10.1016/j.tbench.2023.100105
28. Jo, H., & Park, D. H. (2024). Effects of ChatGPT’s AI capabilities and human-like traits on spreading information in work environments. Scientific Reports, 14(1), 7806. https://doi.org/10.1038/s41598-024-57977-0
29. Kaliyadan, F., & Kulkarni, V. (2019). Types of variables, descriptive statistics, and sample size. Indian Dermatology Online Journal, 10(1), 82-86. https://doi.org/10.4103/idoj.IDOJ_468_18
30. Klassen, R. (2002). A question of calibration: A review of the self-efficacy beliefs of students with learning disabilities. Learning disability quarterly, 25(2), 88-102. https://doi.org/10.2307/1511276
31. 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. https://doi.org/10.xxx/let.2023.3.1.55
32. Lee, S., Jones-Jang, S. M., Chung, M., Kim, N., & Choi, J. (2024). Who is óing chatgpt and why? extending the unified theory of acceptance and use of technology (UTAUT) model. Information Research an international electronic journal, 29(1), 54-72. https://doi.org/10.47989/ir291647
33. Lee, U. J. (2023). Few-shot is enough: exploring ChatGPT prompt engineering method for automatic question generation in English education. Education and Information Technologies, 1-33. https://doi.org/10.1007/s10639-023-12249-8
34. Lee, Y. C., Yamashita, N., Huang, Y., & Fu, W. (2020, April). “I hear you, I fell you”: encouraging deep self-disclosure through a chatbot. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-12).
35. Lin, C. C., Huang, A. Y., & Yang, S. J. (2023). A review of ai-driven conversational chatbots implementation methodologies and challenges (1999-2022). Sustainability, 15(5), 4012. https://doi.org/10.3390/su15054012
36. MacArthur, C. A. (2016). A multicomponent measure of writing motivation with basic college writers. Learning Disability Quarterly, 39(1), 31-43. https://doi.org/10.1177/0731948715583115
37. Marbun, T. O. (2023). The Implementation of Artificial Intelligence, Chatgpt, And Critical Thinking Method for Academic Endeavors at Theological Higher Education. Journal Didaskalia, 6(2), 84-100. https://doi.org/10.33856/didaskalia.v6i2.309
38. Martinez, J. R. (2016). School-based interventions targeting challenging behaviors exhibited by young children with autism spectrum disorder: A systematic literature review. Education and Training in Autism and Developmental Disabilities, 265-280.
39. Miller, D. (2023). Exploring the impact of artificial intelligence language model ChatGPT on the user experience. International Journal of Technology, Innovation and Management (IJTIM), 3(1), 1-8. https://doi.org/10.54489/ijtim.v3i1.195
40. Minh, A. N. (2024). Leveraging chatgpt for enhancing english writing skills and critical thinking in university freshmen. Journal of Knowledge Learning and Science Technology, 3(2), 51-62.
41. Mnguni, L. (2023). A critical reflection on the affordances of web 3.0 and artificial intelligence in life sciences education. Journal of Pedagogical Sociology and Psychology, 5(2), 1-9.
42. Muñoz, S. A. S., Gayoso, G. G., Huambo, A. C., Tapia, R. D. C., Incaluque, J. L., Aguila, O. E. P., …& Arias-Gonzáles, J. L. (2023). Examining the impacts of ChatGPT on student motivation and engagement. Social Space, 23(1), 1-27.
43. Murgia, E., Abbasiantaeb, Z., Aliannejadi, M., Huibers, T., Landoni, M., & Pera, M. S. (2023). Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization. UMAP 2023, 22-27. https://doi.org/10.1145/3563359.3597399
44. Petrović, J., & Jovanović (2021). The role of chatbots in foreign language learning: The present situation and the future outlook. In Artificial intelligence: Theory and applications (pp. 313-330). https://doi.org/10.1007/978-3-030-72711-6_17
45. Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & Education, 147, 103778. https://doi.org/10.1016/j.compedu.2019.103778
46. Robertson, L., Taczak, K., & Yancey, K. B. (2015). 3 Notes Toward A Theory of Prior Knowledge and Its Role In College Composers’ Transfer of Knowledge and Practice. Composition Forum, 26.
47. Rose, D. (2009). Introduction: writing in the Anthropocene. Australian Humanities Review, (47), 87. https://doi.org/10.22459/AHR.47.2009.08
48. Roumeliotis, K. I., & Tselikas, N. D. (2023). Chatgpt and Open-Ai Models: A preliminary review. Future Internet, 15(6), 192. https://doi.org/10.3390/fi15060192
49. Rudolph, J. T. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching, 6(1), 342-363. https://doi.org/10.37074/jalt.2023.6.1.9
50. Salam, M. Y., Tamam, M., Mudinillah, A. (2023). Using artificial intelligence for education in the education 5.0 era to improve reading skills. Arabiyat: Journal of Arabic Education & Arabic Studies/Jurnal Pendidikan Bahasa Arab dan Kebahasaaraban, 10(2). https://doi.org/10.15408/a.v10i2.35487
51. Schumacher, C., & Ifenthaler, D. (2018). Features students really expect from learning analytics. Computers in Human Behavior, 78, 397-407. https://doi.org/10.1016/j.chb.2017.06.030
52. Shafeeg, A., Shazhaev, I., Mihaylov, D., Tularov, A., & Shazhaev, I. (2023). Voice assistant integrated with chatgpt—Indonesian Journal of Computer Science, 12(1), 22. https://doi.org/10.33022/ijcs.v12i1.3146 Sharma, S., & Yadav, R. (2022). Chat GPT–A technological remedy or challenge for education system. Global Journal of Enterprise Information System, 14(4), 46-51.
53. Shi, X. (2024). Advantages, Challenges and Prospects of ChatGPT in Oral English Teaching. Transactions on Social Science, Education and Humanities Research, 4, 99-109. https://doi.org/10.62051/c49b2t84
54. Shihab, S. R., Sultana, N., Samad, A., & Hamza, M. (2023). Educational technology in teaching community: reviewing the dimension of integrating ed-tech tools and ideas in classrooms. Eduvest-Journal of Universal Studies, 3(6), 1028-1039. https://doi.org/10.59188/eduvest.v3i6.835
55. Sivo, S. A., Saunders, C., Chang, Q., & Jiang, J. J. (2006). How low should you go? Low response rates and the validity of inference in IS questionnaire research. Journal of the association for information systems, 7(1), 17. https://doi.org/10.17705/1jais.00093
56. Sorby, S., Veurink, N., & Streiner, S. (2018). Does spatial skills instruction improve STEM outcomes? The answer is ‘yes’. Learning and Individual Differences, 67, 209-222. https://doi.org/10.1016/j.lindif.2018.09.001
57. Steiss, J., Tate, T., Graham, S., Cruz, J., Hebert, M., Wang, J., & Olson, C. B. (2024). Comparing the quality of human and ChatGPT feedback of students’ writing. Learning and Instruction, 91, 101894. https://doi.org/10.1016/j.learninstruc.2024.101894
58. Suryana, I., Asrianto, A., & Murwantono, D. (2020). Artificial intelligence to master English listening skills for non-English major students. Journal of Languages and Language Teaching, 8(1), 48-59. https://doi.org/10.33394/jollt.v8i1.2221
59. Tokac, U., Novak, E., & Thompson, C. G. (2019). Effects of game‐based learning on students' mathematics achievement: A meta‐analysis. Journal of Computer Assisted Learning, 35(3), 407-420. https://doi.org/10.1111/jcal.12347
60. Usó-Juan, E., & Martinez-Flor, A. (2006). Approaches to language learning and teaching: Towards acquiring communicative competence through the four skills. In A. Martinez-Flor & E. Usó-Juan (Eds). Current trends in the development and teaching of the four language skills (pp.. 3-26). De Gruyter Mouton.
61. Wang, Z. (2014). Developing Accuracy and Fluency in Spoken English of Chinese EFL Learners. English language teaching, 7(2), 110-118. https://doi.org/10.5539/elt.v7n2p110
62. Wu, H., Wang, W., Wan, Y., Jiao, W., & Lyu, M. (2023). Chatgpt or grammarly? Evaluating chatbot on grammatical error correction benchmark. arXiv preprint arXiv:2303.13648. https://doi.org/10.48550/arXiv.2303.13648
63. Xing, R. (2023). Advancements in English listening education: ChatGPT and convolutional neural network integration. In Advancements in English listening education: ChatGPT and convolutional neural network integration, (pp. 280-290). https://doi.org/10.33902/JPR.202323980
64. Yildiz, M. (2023). Exploring the potential the chatbots and chatgpt in enhancing vocabulary knowledge. In M. J. Smith (Ed.), Transforming the Language Teaching Experience in the Age of AI (pp. 160-188). https://doi.org/10.3126/jong.v7.1-2.70236
65. Yu, H., & Guo, Y. (2023, September). Harnessing the Potential of Chat GPT in Education: Unveiling its value, navigating challenges, and crafting mitigation pathways. In 2023 5th International Workshop on Artificial Intelligence and Education (WAIE) (s. 48-52). https://doi.org/10.1109/WAIE60568.2023.00016
66. Zebua, J. A. Z., & Katemba, C. V. (2024). Students' perceptions of using the OpenAI Chatgpt application in improving writing skills. Journal of Language and Literature Studies, 4(1), 110-123. https://doi.org/10.36312/jolls.v4i1.1805