Sınıf Öğretmeni Adaylarının Kaynaştırma Eğitiminde Yapay Zeka Kullanımına Yönelik Görüşleri

Abstract

Bu çalışma, sınıf öğretmeni adaylarının yapay zeka (YZ) teknolojilerinin kaynaştırma eğitimi kapsamında kullanımına ilişkin görüşlerini incelemektedir. Nitel araştırma desenine uygun olarak, 15 öğretmen adayıyla yarı yapılandırılmış görüşme formu aracılığıyla derinlemesine görüşmeler gerçekleştirilmiştir. Tematik analiz sonucunda katılımcıların YZ’yi; bireyselleştirilmiş öğrenmeyi destekleyen, anlık geri bildirim sağlayan ve öğrenci motivasyonunu artıran bir araç olarak gördükleri belirlenmiştir. Bununla birlikte; veri gizliliği, içerik güvenilirliği, erişim eşitsizliği ve etik yansımalar konusunda önemli kaygılar da dile getirilmiştir. Ayrıca katılımcılar, YZ’nin sınıf içi uygulamalarda etkili biçimde kullanılabilmesi için gerekli pedagojik ve teknik eğitimin yetersiz olduğunu vurgulamıştır. Bulgular, kaynaştırma eğitiminde YZ’nin sorumlu, adil ve etkili kullanımını destekleyecek şekilde öğretmen yetiştirme programlarının gözden geçirilmesi gerektiğini göstermektedir. Sonuç olarak çalışma, eğitimde YZ entegrasyonuna yönelik kapsamlı ve etik temelli bir yaklaşımın önemine işaret etmektedir.

Keywords

• Biryselleştirilmiş Eğitim
• Dijital Etik
• Kaynaştırma Eğitimi
• Sınıf Öğretmeni Adayları
• Yapay Zeka

Supporting Institution

Bu çalışma, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK) tarafından 2209-A – Lisans Öğrencileri Araştırma Projeleri Destek Programı (Proje No: 1919B012428349) kapsamında desteklenmiştir.

Project Number

Project No: 1919B012428349

Ethical Statement

Bu çalışmada, Yükseköğretim Kurumları Bilimsel Araştırma ve Yayın Etiği Yönergesi’nde belirtilen tüm kurallara uyulmuştur. Yönergede Bilimsel Araştırma ve Yayın Etiğine Aykırı Eylemler başlığı altında açıklanan eylemlerden hiçbiri gerçekleştirilmemiştir.

Perspectives of Primary School Teacher Candidates on the Use of Artificial Intelligence in Inclusive Education

Abstract

This study investigates how primary school teacher candidates perceive the integration of artificial intelligence (AI) technologies in inclusive education. Using a qualitative research design, in-depth interviews were conducted with 15 teacher candidates through a semi-structured interview form. Thematic analysis revealed that the participants viewed AI as a tool to support personalised learning, provide immediate feedback, and enhance student motivation. However, they also expressed significant concerns regarding data privacy, content reliability, unequal access, and ethical implications. In addition, the participants emphasised the lack of pedagogical and technical training necessary for the effective implementation of AI in classroom settings. The findings highlight the need to revise teacher education programmes in order to support the responsible, equitable, and effective use of AI in inclusive educational environments. Overall, the study points to the importance of a comprehensive and ethically grounded approach to the integration of AI in education.

Keywords

• Artificial intelligence
• Digital ethics
• Inclusive education
• Personalised education
• Teacher candidates

Supporting Institution

This study was supported by the Scientific and Technological Research Council of Türkiye (TÜBİTAK) within the scope of the 2209-A – Research Project Support Programme for Undergraduate Students (Project No: 1919B012428349).

Project Number

Project No: 1919B012428349

Ethical Statement

This study fully complies with all the ethical principles outlined in the Directive for Scientific Research and Publication Ethics of the Council of Higher Education (YÖK). None of the violations defined under the section titled “Acts Contrary to Scientific Research and Publication Ethics” in the directive were committed during the course of this research.

References

1. Adeleye, N. O. O., Eden, N. C. A., & Adeniyi, N. I. S. (2024). Innovative teaching methodologies in the era of artificial intelligence: A review of inclusive educational practices. World Journal of Advanced Engineering Technology and Sciences, 11(2), 069–079. https://doi.org/10.30574/wjaets.2024.11.2.0091
2. Adigun, O. T., Tijani, F. A., Haihambo, C. K., & Enock, S. L. (2025). Understanding pre-service teachers’ intention to adopt and use artificial intelligence in Nigerian inclusive classrooms. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1519472
3. Ainscow, M. (2020). Inclusion and equity in education: Making sense of global challenges. Prospects, 49(3), 123-134. https://doi.org/10.1007/s11125-020-09506-w
4. Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI And Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
5. Aksakal, Ş., Emre, İ., & Özbek, M. (2024). Sınıf öğretmenlerinin yapay zekaya ilişkin tutumlarının belirlenmesi. Eğitimde Yeni Yaklaşımlar Dergisi, 7(1), 1-13.
6. Bobrytska, V. I., Krasylnykova, H. V., Beseda, N. А., Krasylnykov, S. R., & Skyrda, T. S. (2024). Artificial intelligence (AI) in Ukrainian higher education: A comprehensive study of stakeholder attitudes, expectations and concerns. International Journal of Learning Teaching and Educational Research, 23(1), 400–426. https://doi.org/10.26803/ijlter.23.1.20
7. Borgonovi, F., Bastagli, F., Ochojska, M., & Piumatti, G. (2025). AI adoption in the education system: International insights and policy considerations for Italy (OECD Artificial Intelligence Papers No. 52). OECD Publishing. https://doi.org/10.1787/69bd0a4a-en
8. Braun, V., & Clarke, V. (2012). Thematic analysis. In American Psychological Association eBooks (pp. 57–71). https://doi.org/10.1037/13620-004

9. 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). https://doi.org/10.1186/s40594-023-00418-7
10. Coşkun, B. (2024). Aday öğretmenlerin yapay zekâ algıları ve eğitimde yapay zekâ kullanımına ilişkin düşünceleri. Kapadokya Eğitim Dergisi, 5(2), 439-456. https://doi.org/10.69643/kaped.1566047
11. Courduff, J., Szapkiw, A., & Wendt, J. L. (2016). Grounded in what works: Exemplary practice in special education teachers’ technology integration. Journal of Special Education Technology, 31(1), 26–38. https://doi.org/10.1177/0162643416633333
12. Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE.
13. De Boer, A., Pijl, S. J., & Minnaert, A. (2011). Regular primary schoolteachers’ attitudes towards inclusive education: a review of the literature. International Journal of Inclusive Education, 15(3), 331–353. https://doi.org/10.1080/13603110903030089
14. Doğan, M. E., Doğan, T. G., & Bozkurt, A. (2023). The use of artificial intelligence (ai) in online learning and distance education processes: a systematic review of empirical studies. Applied Sciences, 13(5), 3056. https://doi.org/10.3390/app13053056
15. Eden, C. A., Chisom, O. N., & Adeniyi, I. S. (2024). Integrating ai in education: opportunities, challenges, and ethical considerations. Magna Scientia Advanced Research and Reviews, 10(2), 006-013. https://doi.org/10.30574/msarr.2024.10.2.0039
16. Gabsi, A. E. H. (2024). Integrating artificial intelligence in industry 4.0: insights, challenges, and future prospects–a literature review. Annals of Operations Research, 1-28. https://doi.org/10.1007/s10479-024-06012-6
17. Gatlin, M. (2023). Assessing pre-service teachers’ attitudes and perceptions of using artificial intelligence in the classroom. Texas Educator Preparation, 7(2), 1–8. https://doi.org/10.59719/txep.v7i2.35
18. Guan, L., Zhang, Y., & Gu, M. M. (2025). Pre-service teachers preparedness for AI-integrated education: An investigation from perceptions, capabilities, and teachers’ identity changes. Computers and Education Artificial Intelligence, 8, 100341. https://doi.org/10.1016/j.caeai.2024.100341
19. Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field methods, 18(1), 59-82. https://doi.org/10.1177/1525822X05279903
20. Hnatiuk, O., Perepeliuk, T., Pavlyk, N., Dekarchuk, M., Dudnyk, O., & Polishchuk, T. (2022). Professional development of participants in the educational process for working with students of an inclusive group on an integrative basis. Journal of Higher Education Theory and Practice, 22(6), 63-73. https://doi.org/10.33423/jhetp.v22i6.5229
21. Holman, K., Marino, M., Vasquez, E., Taub, M., Hunt, J., & Tazi, Y. (2024). Navigating AI-Powered personalized learning in special education: A guide for preservice teacher faculty. Journal of Special Education Preparation, 4(2), 90–95. https://doi.org/10.33043/5b2xqcb3
22. Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12533
23. Ifenthaler, D., Majumdar, R., Gorissen, P., Judge, M., Mishra, S., Raffaghelli, J., & Shimada, A. (2024). Artificial intelligence in education: Implications for policymakers, researchers, and practitioners. Tech Know Learn 29, 1693–1710 (2024). https://doi.org/10.1007/s10758-024-09747-0
24. Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
25. König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608–622. https://doi.org/10.1080/02619768.2020.1809650
26. Koster, M., Nakken, H., Pijl, S. J., & Van Houten, E. (2009). Being part of the peer group: A literature study focusing on the social dimension of inclusion in education. International journal of inclusive education, 13(2), 117-140. https://doi.org/10.1080/13603110701284680
27. Küçükkara, M. F., Ünal, M., & Sezer, T. (2024). Okul öncesi eğitimi öğretmenlerinin yapay zekâya i̇lişkin görüşleri. Temel Eğitim Araştırmaları Dergisi, 4(1), 17–28. https://doi.org/10.55008/te-ad.1431142
28. Kumar, R., & Sharma, M. V. (2024). A brief idea of AI and its application to various fields. International Journal of Progressive Research in Engineering Management and Science (IJPREMS), 4(6), 1271-1279.
29. Kurtdede Fidan, N., & Kayar, İ. (2025). Sınıf öğretmenlerinin yapay zekâya bakışı: Uygulamaları, gelecek planları ve endişeleri. Batı Anadolu Eğitim Bilimleri Dergisi, 16(1), 1745-1773. https://doi.org/10.51460/baebd.1583635
30. Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3313831.3376727
31. Lincoln, Y.S., & Guba, E.G. (1985). Naturalistic inquiry. SAGE.
32. Massouti, A. (2021). Pre-service teachers’ perspectives on their preparation for inclusive teaching: Implications for an organizational change in teacher education. The Canadian Journal for the Scholarship of Teaching and Learning, 12(1). https://doi.org/10.5206/cjsotlrcacea.2021.1.10611
33. Merriam, S. B. (2009). Qualitative research: A guide to design and implementation. Jossey-Bass.
34. Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://doi.org/10.54675/EWZM9535
35. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Newbury Park, CA: Sage.
36. Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
37. Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023-10203-6
38. Ng, W., Nicholas, H., & Williams, A. (2010). School experience influences on pre-service teachers’ evolving beliefs about effective teaching. Teaching and Teacher Education, 26(2), 278–289. https://doi.org/10.1016/j.tate.2009.03.010
39. Özel Eğitim ve Rehberlik Hizmetleri Genel Müdürlüğü. (2022). Kaynaştırma/bütünleştirme yoluyla eğitim uygulamaları ulusal eylem planı (2022–2026) [National action plan for education through inclusion/integration practices (2022–2026)]. https://orgm.meb.gov.tr/meb_iys_dosyalar/2023_05/12081236_Ulusal_Eylem_PlanY_MayYs_2023.pdf
40. Pagliara, S. M., Bonavolonta, G., Pia, M., Falchi, S., Zurru, A. L., Fenu, G., & Mura, A. (2024). The integration of artificial intelligence in inclusive education: A Scoping Review. Information, 15(12), 774. https://doi.org/10.3390/info15120774
41. Palinkas, L. A. (2014). Qualitative and mixed methods in mental health services and implementation research. Journal of Clinical Child & Adolescent Psychology, 43(6), 851–861. https://doi.org/10.1080/15374416.2014.910791
42. Patton, M. Q. (2002). Qualitative research and evaluation methods Third Edition. Sage.
43. Patton, M. Q. (2014). Nitel araştırma ve değerlendirme yöntemleri (M. Bütün & S. B. Demir, Trans.). Pegem Akademi Yayıncılık.
44. Renkema, M., Van den Boom-Muilenburg, E., Friso-van den Bos, I., Theelen, H., Wopereis, I., & Schildkamp, K. (2025). AI-GO! Een raamwerk voor AI-geletterdheid in het onderwijs (AI-GO raamwerk) [AI-GO! A framework for AI literacy in education (AI-GO framework)]. Npuls AI- en Data Geletterdheid.
45. Roshanaei, M., Olivares, H., & Lopez, R. R. (2023). Harnessing AI to foster equity in education: Opportunities, challenges, and emerging strategies. Journal of Intelligent Learning Systems and Applications, 15(04), 123–143. https://doi.org/10.4236/jilsa.2023.154009
46. Sánchez-Cruzado, C., Campión, R. S., & Sánchez-Compaña, M. T. (2021). Teacher digital literacy: The indisputable challenge after COVID-19. Sustainability, 13(4), 1858. https://doi.org/10.3390/su13041858
47. Seyhan, A. (2024). Sosyal bilgiler öğretmenlerinin eğitimde yapay zeka kullanımına i̇lişkin görüşleri. The Journal of International Educational Sciences, 11(41), 100-125. https://doi.org/10.29228/inesjournal.78798
48. Tisdell, E. J., Merriam, S. B., & Stuckey-Peyrot, H. L. (2025). Qualitative research: A guide to design and implementation. John Wiley & Sons.
49. UNICEF. (2021). Policy guidance on AI for children (Version 2.0: Recommendations for building AI policies and systems that uphold child rights). https://www.unicef.org/innocenti/media/1341/file/UNICEF-Global-Insight-policy-guidance-AI-children-2.0-2021.pdf
50. Yazıcıoğlu, T. (2020). Destek eğitim odalarında görev yapan öğretmenlerin gözüyle destek eğitim odaları. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Özel Eğitim Dergisi, 21(2), 273–297. https://doi.org/10.21565/ozelegitimdergisi.584392
51. Yıldırım, A., Şimşek, H. (2021), Sosyal Bilimlerde Nitel Araştırma Yöntemleri. Seçkin Yayıncılık.
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(1). https://doi.org/10.1186/s41239-019-0171-0
53. Zhang, J., & Zhang, Z. (2024). AI in teacher education: Unlocking new dimensions in teaching support, inclusive learning, and digital literacy. Journal of Computer Assisted Learning, 40(4), 1871–1885. https://doi.org/10.1111/jcal.12988
54. Zhao, L., Wu, X., & Luo, H. (2022). Developing AI literacy for primary and middle school teachers in China: Based on a structural equation modelling analysis. Sustainability, 14(21), 14549. https://doi.org/10.3390/su142114549