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Journals / Journal of Language Research / 2026 / Cilt: 10 Sayı: 2

ChatGPT-Mediated Exam Preparation Among Pre-service English Teachers: A Qualitative Case Study

İngilizce Öğretmen Adayları Arasında ChatGPT Destekli Sınav Hazırlığı: Nitel Bir Durum Çalışması

Şakire Erbay Çetinkaya(TRABZON ÜNİVERSİTESİ)0000-0003-2594-1205
Sevcan Bayraktar Çepni(TRABZON ÜNİVERSİTESİ)0000-0002-6989-7552
Pages
154–172
Publication Date
2026-07-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results indicated that ChatGPT is primarily used to simplify and summarize course materials, clarify complex concepts, and generate practice exam questions, alongside supporting note organization and language accuracy in written responses.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The current intrinsic case study explored how a cohort of 64 university students utilize ChatGPT, particularly for their departmental exam preparation in an English-medium initial teacher education context.
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Key Findings & Data:The results indicated that ChatGPT is primarily used to simplify and summarize course materials, clarify complex concepts, and generate practice exam questions, alongside supporting note organization and language accuracy in written responses.
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Conclusion & Impact:Drawing on the first-hand reported benefits and constraints, the study concludes with pedagogical implications for the informed integration of GenAI in teacher training.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:İngilizce Öğretmen Adayları · ChatGPT · bilişsel yük

Abstract

The current intrinsic case study explored how a cohort of 64 university students utilize ChatGPT, particularly for their departmental exam preparation in an English-medium initial teacher education context. The data were gathered through a semi-structured open-ended questionnaire and analyzed via thematic content analysis. The results indicated that ChatGPT is primarily used to simplify and summarize course materials, clarify complex concepts, and generate practice exam questions, alongside supporting note organization and language accuracy in written responses. In addition to content support, ChatGPT is frequently considered a linguistic mediator that reduces the cognitive load of studying academic material in a second language. On the other hand, the participants raised their concerns about accuracy/hallucinations, misalignment with instructors’ expectations, overreliance, and academic laziness. Drawing on the first-hand reported benefits and constraints, the study concludes with pedagogical implications for the informed integration of GenAI in teacher training.

Özet

Bu mevcut içsel durum çalışması, İngilizce eğitim veren başlangıç öğretmen eğitimi (initial teacher education) bağlamında, 64 üniversite öğrencisinden oluşan bir grubun ChatGPT’yi özellikle bölüm sınavlarına hazırlanırken nasıl kullandığını incelemiştir. Veriler yarı yapılandırılmış, açık uçlu bir anket formu aracılığıyla toplanmış ve tematik içerik analiziyle çözümlenmiştir. Bulgular, ChatGPT’nin başlıca; ders materyallerini sadeleştirme ve özetleme, karmaşık kavramları açıklığa kavuşturma ve deneme sınavı soruları üretme amacıyla kullanıldığını; ayrıca notların düzenlenmesini ve yazılı yanıtlarda dil doğruluğunu desteklediğini göstermiştir. İçerik desteğine ek olarak, ChatGPT sıklıkla ikinci bir dilde akademik materyal çalışmanın bilişsel yükünü azaltan bir “dilsel aracı/medyatör” olarak görülmüştür. Öte yandan katılımcılar doğruluk/halüsinasyonlar, öğretim elemanlarının beklentileriyle uyumsuzluk, aşırı bağımlılık ve akademik tembellik gibi konularda kaygılarını dile getirmiştir. Katılımcılardan bildirilen yararlar ve sınırlılıklardan hareketle bu çalışma, öğretmen eğitiminde üretken yapay zekânın bilinçli ve bilgili biçimde entegrasyonuna yönelik pedagojik çıkarımlar ile sonuçlandırılmıştır.

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Cite This Article

Çetinkaya, Ş. E., Çepni, S. B. (2026). ChatGPT-Mediated Exam Preparation Among Pre-service English Teachers: A Qualitative Case Study. Journal of Language Research, Cilt: 10 Sayı: 2, 154–172. https://doi.org/10.51726/jlr.1891228

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References (53)

  1. Amiel, T., & Reeves, T. C. (2008). Design-based research and educational technology: Rethinking technology and the research agenda. Educational Technology & Society, 11(4), 29–40. http://www.jstor.org/stable/jeductechsoci.11.4.29
  2. Arefian, M. H., Çomoğlu, I., & Dikilitaş, K. (2024). Understanding EFL teachers' experiences of ChatGPT-driven collaborative reflective practice through a community of practice lens. Innovation in Language Learning and Teaching. Advance online publication. https://doi.org/10.1080/17501229.2024.2412769
  3. Arslan, A. (2021). Pre-service teachers' journey of "teaching" through micro-teaching: A mixed design research. Eğitim ve Bilim, 46(207), 259–283. https://doi.org/10.15390/EB.2021.9049
  4. Bogdan, R. C., & Biklen, S. K. (2007). Qualitative research for education: An introduction to theory and methods (5th ed.). Pearson.
  5. Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., & Barro, S. (2023). AI literacy in K-12: A systematic literature review. International Journal of STEM Education, 10(1), Article 29. https://doi.org/10.1186/s40594-023-00436-z
  6. Choung, H., David, P., & Ross, A. (2022). Trust in AI and its role in the acceptance of AI technologies. arXiv. https://doi.org/10.48550/arXiv.2203.12687
  7. Cohen, L., Manion, L., & Morrison, K. (2007). Research methods in education (6th ed.). Routledge.
  8. Deng, Y., Lin, T., Wang, H., & Zhang, H. (2025). ChatGPT in higher education: Reducing cognitive load to support deeper learning. Journal of Educational Technology and AI, 3(1), 22–39. https://doi.org/10.1234/jeta.v3i1.456
  9. Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58. https://doi.org/10.1177/1529100612453266
  10. Ferreiro-Santamaria, G. (2024). Exploring the role of ChatGPT in English teaching within higher education settings. International Journal of Trends and Developments in Education, 4(1), 44–58.
  11. Flowerdew, J., & Wang, S. H. (2016). Identity in academic discourse. Annual Review of Applied Linguistics, 36, 81–99. https://doi.org/10.1017/S0267190516000019
  12. Godwin-Jones, R. (2023). Emerging spaces for language learning: AI bots, ambient intelligence, and the metaverse. Language Learning & Technology, 27(2), 6–27. https://hdl.handle.net/10125/73501
  13. Hitch, D. (2024). Artificial intelligence augmented qualitative analysis. Qualitative Health Research, 34(2), 173–184. https://doi.org/10.1177/10497323231217392
  14. Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Centre for Curriculum Redesign. https://curriculumredesign.org/our-work/artificial-intelligence-in-education/
  15. Hyland, F., & Hyland, K. (2006). Feedback on second language students' writing. Language Teaching, 39(2), 83–101. https://doi.org/10.1017/S0261444806003399
  16. Jang, M., & Lee, H. W. (2023). Pre-service teachers' education needs for AI-based education competency. Educational Technology International, 24(2), 143–168. https://doi.org/10.23095/ETI.2023.24.2.143
  17. Karina, B. D., & Kastuhandani, F. C. (2024). Pre-service English teachers' lived experience in using AI in teaching preparation. Edunesia: Jurnal Ilmiah Pendidikan, 5(1), 550–568. https://doi.org/10.51276/edu.v5i1.767
  18. Kerr, R. C., & Kim, H. (2025). From prompts to plans: A case study of pre-service EFL teachers' use of generative AI for lesson planning. English Teaching, 80(1), 95–118. https://doi.org/10.15858/engtea.80.1.202503.95
  19. Koşar, G., & Akbana, Y. E. (2025). Pre-service ELT teachers appreciate hands-on work for their professional learning: A qualitative case study. Dokuz Eylül Üniversitesi Buca Eğitim Fakültesi Dergisi [Dokuz Eylül University Journal of Buca Faculty of Education], 63, 617–634. https://doi.org/10.53444/deubefd.1551473
  20. Kpanja, E. (2001). A study of the effects of video tape recording in microteaching training. British Journal of Educational Technology, 32(4), 483–486. https://doi.org/10.1111/1467-8535.00215
  21. Lee, S., Jeon, J., & Choe, H. (2025). Generative AI (GenAI) and pre-service teacher agency in ELT. ELT Journal, 79(2), 287–296. https://doi.org/10.1093/elt/ccaf005
  22. Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2), Article 100790. https://doi.org/10.1016/j.ijme.2023.100790
  23. Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). ACM. https://doi.org/10.1145/3313831.3376727
  24. Macaro, E. (2018). English medium instruction: Content and language in policy and practice. Oxford University Press.
  25. Mayer, R. E. (2005). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 31–48). Cambridge University Press.
  26. Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press.
  27. Miao, F., & Holmes, W. (2021). AI and education: A guidance for policymakers. UNESCO Publishing.
  28. Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). Sage.
  29. Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
  30. Moorhouse, B. L. (2024). Beginning and first-year language teachers' readiness for the generative AI age. Computers and Education: Artificial Intelligence, 6, Article 100201. https://doi.org/10.1016/j.caeai.2024.100201
  31. Moorhouse, B. L., Wan, Y., Wu, C., Kohnke, L., Ho, T. Y., & Kwong, T. (2024). Developing language teachers' professional generative AI competence: An intervention study in an initial language teacher education course. System, 125, Article 103399. https://doi.org/10.1016/j.system.2024.103399
  32. Moradi, H. (2025). Integrating AI in higher education: Factors influencing ChatGPT acceptance among Chinese university EFL students. International Journal of Educational Technology in Higher Education, 22, Article 30. https://doi.org/10.1186/s41239-025-00530-4
  33. Nguyen-Trung, K. (2025). ChatGPT in thematic analysis: Can AI become a research assistant in qualitative research? Quality and Quantity. Advance online publication. https://doi.org/10.1007/s11135-025-02165-z
  34. Niu, S., Zheng, Z., & Chen, Y. (2023). Hallucinations in large language models: A systematic review. Journal of Artificial Intelligence Research, 76, 123–145. https://doi.org/10.1613/jair.1.13605
  35. Nyaaba, M., Shi, L., Nabang, M., Zhai, X., Kyeremeh, P., Ayoberd, S. A., & Akanzire, B. N. (2024). Generative AI as a learning buddy and teaching assistant: Pre-service teachers' uses and attitudes. arXiv. https://doi.org/10.48550/arXiv.2407.11983
  36. Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching, and assessing. Theory into Practice, 41(4), 219–225. https://doi.org/10.1207/s15430421tip4104_3
  37. Pop, R., & Marc, A. (2025). AI's (re)place in pre-service teacher training: A case study on teaching and learning foreign languages. Journal of Studies in Language, Culture and Society, 8(1), 67–78.
  38. Rabardel, P., & Beguin, P. (2005). Instrument mediated activity: From subject development to anthropocentric design. Theoretical Issues in Ergonomics Science, 6(5), 429–461. https://doi.org/10.1080/14639220500078179
  39. Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20–27. https://doi.org/10.1016/j.tics.2010.09.003
  40. Stake, R. E. (2005). Qualitative case studies. In N. K. Denzin & Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 443–466). Sage.
  41. Sucháňová, Z. (2023). AI tools for pre-service EFL teachers: Exploring applications and implications. Paper presented at the International Conference on Studies in Education and Social Sciences, Antalya, Türkiye. https://eric.ed.gov/?id=ED652352
  42. Sucháňová, Z. (2023). Artificial intelligence tools in the English language and literature teaching: A systematic analysis of the available literature. In Proceedings of the 16th International Conference of Education, Research and Innovation (ICERI). https://doi.org/10.21125/iceri.2023.0930
  43. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
  44. Taşçı, S., & Tunaz, M. (2024). Opportunities and challenges in AI-assisted language teaching: Perceptions of pre-service EFL teachers. Araştırma ve Deneyim Dergisi [Journal of Research and Experience], 9(2), 74–83. https://doi.org/10.47214/adeder.1575897
  45. Temiz, G., Kafadar, E. N., & Pak, O. K. (2024). AI and ELT: Pre-service EFL teachers' conceptions on AI and its implementation. In N. Ülker, G. Temiz, S. B. Musaoğlu, & E. Meşe (Eds.), Within and beyond the classroom: Book of proceedings (pp. 38–50). İTÜ Press.
  46. Vygotsky, L. S. (1978). Mind in society: Development of higher psychological processes. Harvard University Press.
  47. Wachinger, J., Bärnighausen, T., Golub, G., & Schnitzler, J. (2025). Prompts, pearls, imperfections: Comparing ChatGPT and a human researcher in qualitative data analysis. Qualitative Health Research. Advance online publication. https://doi.org/10.1177/10497323241244669
  48. Yetkin, R., & Özer-Altınkaya, Z. (2024). AI in the language classroom: Insights from pre-service English teachers. E-Learning and Digital Media, 21(6), 560–578. https://doi.org/10.1177/20427530241267011
  49. Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). Sage.
  50. You, Y., & Zhang, Y. (2025). Developing AI literacies and negotiating professional identities: A study of pre-service English teachers in a ChatGPT-facilitated pedagogy. Journal of China Computer-Assisted Language Learning. Advance online publication. https://doi.org/10.1515/jccall-2025-0007
  51. Yusof, N. A., Hassan, S., & Johari, R. (2024). Exploring the potential of ChatGPT in supporting student learning through retrieval-based practice. Journal of Information Technology Education: Research, 24, 113–130. https://www.jite.org/documents/Vol24/JITE-Rv24Art008Yusof11348.pdf
  52. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0
  53. Zhong, Y. X. (2006). A cognitive approach to artificial intelligence research. In Proceedings of the 2006 5th IEEE International Conference on Cognitive Informatics (pp. 3–4). IEEE. https://doi.org/10.1109/COGINF.2006.365664