SavedAdd your journal

Journals / Asya Studies / 2026 / Sayı: 35

Are Turkish and Social Studies Teacher Candidates Ready to Use Artificial Intelligence in Education? A Mixed-Methods Research Study

Türkçe ve Sosyal Bilgiler Öğretmeni Adayları Eğitimde Yapay Zekâ Kullanmaya Hazır mı? Karma Yöntem Araştırması

Hatice Güneş(AYDIN ADNAN MENDERES ÜNİVERSİTESİ EĞİTİM FAKÜLTESİ TÜRKÇE VE SOSYAL BİLİMLER EĞİTİMİ BÖLÜMÜ TÜRKÇE EĞİTİMİ ANA BİLİM DALI)0000-0003-4498-194X
Pages
1–19
Publication Date
2026-03-31
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

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

Based on the findings of the study, it is recommended that courses on artificial intelligence be added to the teacher training curriculum.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The purpose of this study is to examine pre-service teachers' readiness levels in the context of accessing and using artificial intelligence technology.
📊
Key Findings & Data:The quantitative data of the study were obtained using the “Artificial Intelligence Readiness Scale for Teacher Candidates” and analyzed using the SPSS 22 software package.
💡
Conclusion & Impact:Based on the findings of the study, it is recommended that courses on artificial intelligence be added to the teacher training curriculum.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Hazırbulunuşluk · Öğretmen Adayı · Sosyal Bilgiler

Abstract

The purpose of this study is to examine pre-service teachers' readiness levels in the context of accessing and using artificial intelligence technology. The study investigated whether prospective teachers' readiness levels for artificial intelligence varied according to the department in which they were educated, their grade level, and their gender. The study used a mixed-method approach combining quantitative and qualitative research; the study group consisted of students studying Turkish and Social Sciences Education at a state university's faculty of education. The quantitative data of the study were obtained using the “Artificial Intelligence Readiness Scale for Teacher Candidates” and analyzed using the SPSS 22 software package. In the qualitative part of the research, data on teacher candidates' readiness for artificial intelligence was obtained using a semi-structured interview form, and these were subjected to content analysis. The results of the research determined that students generally had a medium-high level of readiness for the use of artificial intelligence. In the qualitative dimension of the research, data was obtained indicating that teacher candidates did not receive any direct training on the use of artificial intelligence in education, that they had knowledge in different courses, and that they made efforts to explore the field of artificial intelligence and benefit from it as much as possible, especially through their individual efforts. Based on the findings of the study, it is recommended that courses on artificial intelligence be added to the teacher training curriculum.

Özet

Bu araştırmanın amacı, yapay zekâ teknolojisine erişim ve kullanma bağlamında öğretmen adaylarının hazırbulunuşluk düzeylerini ele almaktır. Çalışmada, öğretmen adaylarının eğitim-öğretim gördükleri bölüm, sınıf düzeyi ve cinsiyete göre yapay zekâ hazırbulunuşluk düzeylerinin değişip değişmediği incelenmiştir. Araştırmada, karma yöntemden yararlanılmış; nicel ve nitel bulgular birleştirilmiştir. Çalışma grubunda bir devlet üniversitesinin eğitim fakültesinde öğrenim gören Türkçe ve Sosyal Bilgiler Eğitimi Bölümü öğrencileri yer almıştır. Çalışmanın nicel verileri, “Öğretmen Adaylarına Yönelik Yapay Zekâ Hazırbulunuşluk Ölçeği” ile elde edilmiş ve veriler SPSS 22 paket programı ile analiz edilmiştir. Araştırmanın nitel kısmında yarı yapılandırılmış görüşme formu ile öğretmen adaylarının yapay zekâya yönelik hazırbulunuşluklarına dair veriler elde edilmiş ve bunlar içerik analizine tabi tutulmuştur. Çalışma sonucunda, öğrencilerin genel olarak yapay zekâ kullanımına yönelik orta-üst seviyede bir hazırbulunuşluk düzeyine sahip oldukları belirlenmiştir. Araştırmanın nitel boyutunda öğretmen adaylarının eğitimde yapay zekâ kullanımına dair doğrudan herhangi bir eğitim almadıkları, farklı derslerde bilgi sahibi oldukları ve özellikle bireysel çabaları ile yapay zekâ alanını keşfetme ve bu alandan ellerinden geldiğince faydalanma gayretlerinin bulunduğuna dair bir kısım veriler elde edilmiştir. Çalışmada ortaya çıkan sonuçlar doğrultusunda öğretmen eğitimi müfredatına yapay zekâya yönelik derslerin açılması önerilmektedir.

🔖

Cite This Article

Güneş, H. (2026). Are Turkish and Social Studies Teacher Candidates Ready to Use Artificial Intelligence in Education? A Mixed-Methods Research Study. Asya Studies, Sayı: 35, 1–19. https://doi.org/10.31455/asya.1824710

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (29)

  1. Arslan, K., Köşger, N. & Görgülü Arı, A. (2025). Yapay zekâ uygulamalarına yönelik öğretmen görüşleri: SWOT analizi. Kuram ve Uygulamada Sosyal Bilimler Dergisi, 9(2), 364-384. https://doi.org/10.48066/kusob.1817791
  2. Baimukhambetova, K., Ybyraimzhanov, K., Moldabek, K., Akhatayeva, U. B., Zhetkizgenova, A. & Uaidullakyzy, E. (2026). Evaluating the relationship between pre-service teachers’ artificial intelligence readiness and professional self-efficacy. Education Sciences, 16(1), Article 43. https://doi.org/10.3390/educsci16010043
  3. Bautista, A., Estrada, C., Jaravata, A.M., Mangaser, L.M., Narag, F., Soquila, R. & Asuncion, R.J. (2024). Preservice teachers’ readiness towards integrating AI-based tools in education: A TPACK approach. Educational Process: International Journal, 13(3), 40-68. https://doi.org/10.22521/edupij.2024.133.3
  4. Belda-Medina, J. & Calvo-Ferrer, J. (2022). Using chatbots as AI conversational partners in language learning. Applied Sciences, 12(17), 1-16. https://doi.org/10.3390/app12178427
  5. Bui, P., Korhonen, T., Kontkanen, S., Karme, S., Piispa-Hakala, S. & Veermans, M. (2025). Exploring pre-service teachers’ generative AI readiness and behavioral intentions: A pilot study. LUMAT: International Journal on Math, Science and Technology Education, 13(1), 1-32. https://doi.org/10.31129/LUMAT.13.1.2755
  6. Creswell, J. W. (2003). Research design: Qualitative, quantitative, and mixed methods approaches (2nd ed.). Sage.
  7. Creswell, J. W. & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE publications.
  8. Ding, A. C. E., Ottenbreit-Leftwich, A., Lu, Y. H. & Glazewski, K. (2019). EFL teachers’ pedagogical beliefs and practices with regard to using technology. Journal of Digital Learning in Teacher Education, 35(1), 20–39. https://doi.org/10.1080/21532974.2018.1537816
  9. Garg, R. K., Urs, V. L., Agrawal, A. A., Chaudhary, S. K., Paliwal, V. & Kar, S. K. (2023). Exploring the role of ChatGPT in patient care (diagnosis and treatment) and medical research: A systematic review. Health Promotion Perspectives, 13(3), 183–191. https://doi.org/10.34172/hpp.2023.22
  10. George, D. & Mallery, M. (2010). SPSS for Windows step by step: A simple guide and reference (10th ed.). Pearson.
  11. Farrokhnia, M., Banihashem, S. K., Noroozi, O. & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846
  12. Felix, C. V. (2020). The role of the teacher and AI in education. E. Sengupta, P. Blessinger, & M. S. Makhanya (Eds.). In International perspectives on the role of technology in humanizing higher education (pp. 22–48). Emerald Publishing.
  13. Forbes. Com. https://www.forbes.com/advisor/education/it-and-tech/artificial-intelligence-in-school/ (Erişim Tarihi: 15.10.2025).
  14. Fundi, M., Sanusi, İ. T., Oyelere, S. S. & Ayere, M. (2024). Advancing AI education: Assessing Kenyan in-service teachers' preparedness for integrating artificial intelligence in competence-based curriculum. Computers in Human Behavior Reports, 0(14), 1-10. https://doi.org/10.1016/j.chbr.2024.100412
  15. Karagöl, E. & Yıldırım, D. (2025). Türkçe eğitiminde yapay zekâ kullanımı: Türkçe eğitimcileri yapay zekâ hakkında ne düşünüyor? Ana Dili Eğitimi Dergisi, 13(2), 356-374. https://doi.org/10.16916/aded.1611540
  16. Kaur, D. J. & Gill, N. S. (2019). Artificial intelligence and deep learning for decision makers: A growth hacker’s guide to cutting edge technologies. BPB Publications.
  17. Leech, N. L. & Onwuegbuzie, A. J. (2009). A typology of mixed methods research designs. Qual Quant, 0(43), 265–275. https://link.springer.com/article/10.1007/s11135-007-9105-3
  18. Lucas, M., Bem-Haja, P., Zhang, Y., Llorente-Cejudo, C. & Palacios- Rodríguez, C. (2025). A comparative analysis of pre-service teachers’ readiness for AI integration. Computers and Education: Artificial Intelligence, 8, 100396, 1-9. https://doi.org/10.1016/j.caeai.2025.100396
  19. Nabiyev, V. & Erümit, A. K. (2020). Foundations of AI. I.V. Nabiyev & A. K. Erümit (Eds). In Education from Theory to Practice (pp. 2-37). Pegem Akademi Yayınları.
  20. Owoc, M. L., Sawicka, A. & Weichbroth, P. (2021). Artificial intelligence technologies in education: benefits, challenges and strategies of ımplementation. Owoc, M. L., Pondel, M. (Eds). In Artificial intelligence for knowledge management. AI4KM 2019. IFIP Advances in Information and Communication Technology, 599. Springer, Cham. https://doi.org/10.1007/978-3-030-85001-2_4
  21. Özüdoğru, G. & Yıldız Durak, H. (2024, July 11–13). Turkish adaptation of the AI readiness scale for preservice teachers. 10th International New York Conference on Social, Human, Administrative and Educational Sciences.
  22. Ramazanoglu, M. & Akın, T. (2025). AI readiness scale for teachers: Development and validation. Educ Inf Technol 0(30), 6869–6897. https://doi.org/10.1007/s10639-024-13087-y
  23. Sarıkaya, B. & Kavan, N. (2024). Türkçe Öğretmeni adaylarının yapay zekâya yönelik tutumlarının incelenmesi. Elektronik Eğitim Bilimleri Dergisi, 13(26), 191-203. https://doi.org/10.55605/ejedus.1550010
  24. Sarıkaya, B. & Yıldız Şakiroğlu, H. (2025). Türkçe Öğretmeni adaylarının yapay zekâ kaygıları üzerine bir inceleme. Asya Studies, 9(33), 23-38.https://doi.org/10.31455/asya.1752686 Sumakul, D. T., Hamied, F. & Sukyadi, D. (2022). Artificial intelligence in EFL classrooms: Friend or foe? LEARN Journal: Language Education and Acquisition Research Network, 15(1), 232-256. https://files.eric.ed.gov/fulltext/EJ1336138.pdf
  25. Sun, F., Tian, P., Sun, D., Fan, Y. & Yang, Y. (2024). Pre-service teachers' inclination to integrate AI into STEM education: Analysis of influencing factors. British Journal of Educational Technology, 0(55), 2574–2596. https://doi.org/10.1111/bjet.13469
  26. Tabachnick, B. G. & Fidell, L. S. (2013). Using multivariate statistics (sixth ed.). Pearson.
  27. Uymaz, M. (2024). Present and future of artificial intelligence: A case study on prospective teachers. Sakarya University Journal of Education, 14(Special Issue-AI in Education), 194-212. https://doi.org/10.19126/suje.1466052
  28. Unal, A. & Hobe, J. (2025). Preservice teachers’ readiness for integrating AI in elementary classrooms. Journal of Education and Training Studies 13(4), 34-47. https://doi.org/10.11114/jets.v13i4.7785
  29. Yeşiltaş, E. (2024). Öğretmen mesleki yeterlikleri açısından bir değerlendirme: Yapay zekâ öğretmenin yerini alabilir mi? T. Çalık ve S. Eryılmaz (Editör). Türk Asrı Eşiğinde Eğitim Bilimleri ve Sosyal Bilimler Üzerine Değerlendirmeler İçinde (s. 120-132). Türk Eğitim-Sen Genel Merkezi Yayınları.