Yapay Zekanın Eğitimde Kullanımına İlişkin Çalışmaların İncelenmesi: Bir Meta Sentez Çalışması

Öz

Bu meta-sentez çalışması, son yıllarda hızla genişleyen bir alan olan eğitimde yapay zekâ (YZ) kullanımına ilişkin güncel araştırmaları sistematik biçimde incelemektedir. Çalışmanın temel amacı, YZ destekli uygulamaların etkilerini değerlendirmek, paydaşların algı ve kabul düzeylerini ortaya koymak ve geleceğe yönelik eğilimleri incelemektir. 2018–2023 yılları arasında yayımlanan yüksek lisans ve doktora tezleri, Yükseköğretim Kurulu Ulusal Tez Merkezi (YÖKTEZ) ve ProQuest veri tabanları aracılığıyla belirlenmiştir. PRISMA kılavuzları doğrultusunda dâhil etme ve hariç tutma ölçütleri uygulanmış; yalnızca İngilizce veya Türkçe, tam metin erişimi bulunan, K-12 ya da yükseköğretim düzeyinde yürütülmüş nitel veya karma yöntem tezleri analize alınmıştır. Nicel yöntem kullanan, eğitim dışı alanlara odaklanan veya tam metin erişimi olmayan çalışmalar kapsam dışı bırakılmıştır. Sonuçta 27 tez seçilmiş ve Polat ve Ay’ın (2016) tanımladığı meta-sentez süreci doğrultusunda tematik olarak incelenmiştir. Bulgular, YZ’nin akademik başarıya katkı sağladığını, öğrenme süreçlerini kişiselleştirdiğini ve öğretim yöntemlerini zenginleştirdiğini göstermektedir. Öğretmenler ve öğrenciler YZ’ye genel olarak olumlu yaklaşmakta; ancak veri gizliliği, güvenlik ve etik konularında kaygılar da taşımaktadır. Ayrıca teknolojik altyapı yetersizlikleri, sınırlı kurumsal destek ve yüksek bütçe gereklilikleri önemli engeller olarak belirlenmiştir. Çalışma, YZ destekli eğitim sistemlerine geçişte ulusal düzeyde stratejik politikaların geliştirilmesi gerektiği sonucuna ulaşmıştır.

Anahtar Kelimeler

• Eğitimde yapay zeka
• yapay zekada eğitim teknolojisi
• yapay zeka tabanlı eğitim araçları.

Exploring Studies on the Use of Artificial Intelligence in Education: A Meta-Synthesis Study

Öz

This meta-synthesis study systematically examines recent research on the use of artificial intelligence (AI) in education, a field that has rapidly expanded in recent years. The primary aim is to evaluate the effects of AI, explore stakeholders’ perceptions and acceptance levels, and assess future trends. Master’s and doctoral theses published between 2018 and 2023 were identified through the Higher Education Council National Thesis Center (YÖKTEZ) and ProQuest databases. Following PRISMA guidelines, inclusion and exclusion criteria were applied, allowing only English or Turkish full-text theses or dissertations that used qualitative or mixed methods at the K-12 or higher education levels. Studies employing quantitative methods, focusing on non-educational domains, or lacking full-text access were excluded. Ultimately, 27 studies were selected. These were analyzed using the meta-synthesis process described by Polat and Ay (2016), and thematic findings were synthesized. Results indicate that AI enhances academic achievement, personalizes learning, and enriches instructional practices. Teachers and students generally express positive attitudes toward AI, though concerns remain about data privacy, security, and ethical issues. The findings also highlight challenges, such as insufficient technological infrastructure, limited institutional support, and the need for substantial budgets. The study concludes that strategic national policies are essential for effectively transitioning to AI-supported educational systems.

Anahtar Kelimeler

• Artificial intelligence in education
• educational technology in AI
• AI-based educational tools.

Kaynakça

1. Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), ep429. https://doi.org/10.30935/cedtech/13152
2. Akdeniz, M., & Özdinç, F. (2021). Eğitimde yapay zeka konusunda Türkiye adresli çalışmaların incelenmesi [Examining Turkey-based studies on artificial intelligence in education]. YYÜ Eğitim Fakültesi Dergisi (YYU Journal of Education Faculty), 18, 912–932.
3. Almasri, F. (2024). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education, 54(5), 977–997. https://doi.org/10.1007/s11165-024-10176-3
4. Arik, G., & Seferoglu, S. S. (2022). Eğitimde yapay zeka çalışmaları: Araştırma eğilimleri, karşılaşılan zorluklar ve çözüm önerileri [Artificial intelligence studies in education: Research trends, challenges, and solutions]. In V. Nabiyev & A. K. Erümit (Eds.), Eğitimde yapay zeka kuramdan uygulamaya (pp. 260–280). Pegem Akademi. https://doi.org/10.14527/9786257052986.10
5. Arslan, K. (2020). Eğitimde yapay zeka ve uygulamaları [Artificial intelligence in education and its applications]. Batı Anadolu Eğitim Bilimleri Dergisi, 11(1).
6. Bai, J. Y. H., Müskens, W., Zawacki-Richter, O., & Loglo, F. S. (2023). Future prospects of artificial intelligence in education: Developing strategic scenarios to engage educators. 22–29. https://doi.org/10.14742/apubs.2023.534
7. Baker, T., Smith, L., & Anissa, N. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Nesta.
8. Batista, J., Mesquita, A., & Carnaz, G. (2024). Generative AI and Higher Education: Trends, Challenges, and Future Directions from a Systematic Literature Review. Information, 15(11). https://doi.org/10.3390/info15110676

9. Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21(1), 4. https://doi.org/10.1186/s41239-023-00436-z
10. Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century. Sustainability, 13(2). https://doi.org/10.3390/su13020800
11. Çetin, M., & Aktaş, A. (2021). Yapay zeka ve eğitimde gelecek senaryoları [Artificial intelligence and future scenarios in education]. OPUS International Journal of Society Research, 18. https://doi.org/10.26466/opus.911444
12. Charow, R., Jeyakumar, T., Younus, S., Dolatabadi, E., Salhia, M., Al-Mouaswas, D., Anderson, M., Balakumar, S., Clare, M., Dhalla, A., Gillan, C., Haghzare, S., Jackson, E., Lalani, N., Mattson, J., Peteanu, W., Tripp, T., Waldorf, J., Williams, S., & Wiljer, D. (2021). Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review. JMIR Medical Education, 7(4), e31043. https://doi.org/10.2196/31043
13. Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
14. Coşkun, F., & Gülleroğlu, H. D. (2021). Yapay zekanın tarih içindeki gelişimi ve eğitimde kullanılması [The historical development of artificial intelligence and its use in education]. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Dergisi, 54, 947–966.
15. Dağ, F. (2022). Eğitimde yapay zeka uygulamalarına ilişkin yaklaşımlar ve modeller [Approaches and models for artificial intelligence applications in education]. In V. Nabiyev & A. K. Erümit (Eds.), Eğitimde yapay zeka (pp. 114–144). Pegem Akademi.
16. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
17. Dönmez, M. (2024). AI-based feedback tools in education: A comprehensive bibliometric analysis study. International Journal of Assessment Tools in Education, 11(4), https://doi.org/10.21449/ijate.1467476
18. Doug, B. (2019). Artificial intelligence, authentic impact: How educational AI is making the grade. Edtechmagazine. https://edtechmagazine.com/k12/article/2019/08/artificial-intelligence-authentic-impact-how-educational-ai-making-grade-perfcon
19. Fahimirad, M., & Kotamjani, S. S. (2018). A review on application of artificial intelligence in teaching and learning in educational contexts. International Journal of Learning and Development, 8(4), https://doi.org/10.5296/ijld.v8i4.14057
20. Felix, C. V. (2020). The role of the teacher and AI in education. In E. Sengupta, P. Blessinger, & M. S. Makhanya (Eds.), Innovations in higher education teaching and learning (pp. 33–48). Emerald Publishing Limited. https://doi.org/10.1108/S2055-364120200000033003
21. Ferhataj, A., Memaj, F., Sahatçija, R., Ora, A., & Koka, E. (2025). Ethical concerns in AI development: Analyzing students’ perspectives on robotics and society. Journal of Information, Communication and Ethics in Society. https://doi.org/10.1108/JICES-08-2024-0111
22. Fu, Y., Weng, Z., & Wang, J. (2024). Examining AI use in educational contexts: A scoping meta-review and bibliometric analysis. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00442-w
23. Ghimire, A., & Edwards, J. (2024). Generative AI adoption in classroom in context of technology acceptance model (TAM) and the innovation diffusion theory (IDT). arXiv. https://doi.org/10.48550/arXiv.2406.15360
24. Güneş, D., & Erdem, R. (2022). Nitel araştırmaların analizi: Meta-sentez [Analysis of qualitative research: Meta-synthesis]. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 22(2), 81-98. https://doi.org/10.18037/ausbd.1227313
25. İşler, B., & Kılıç, M. Y. (2021). Eğitimde yapay zekâ kullanımı ve gelişimi [The use and development of artificial intelligence in education]. E-Journal of New Media / Yeni Medya Elektronik Dergi, 5, 1–11.
26. Karakose, T., Ozdogru, M., & Malkoc, N. (2024). Leading sustainable school improvement: A meta-synthesis of qualitative research on problems and challenges faced by school leaders. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1449174
27. Karakose, T., & Tülübaş, T. (2023). How can ChatGPT facilitate teaching and learning: Implications for contemporary education. Educational Process International Journal, 12(4), 7-16. https://doi.org/10.22521/edupij.2023.124.1
28. Kayabaş, İ. (2010). Yapay zeka sohbet ajanlarının uzaktan eğitimde öğrenci destek sistemi olarak kullanılabilirliği [The usability of artificial intelligence chatbots as student support systems in distance education]. Anadolu Üniversitesi.
29. Knox, J. (2020). Artificial intelligence and education in China. Learning, Media and Technology, 45(3), 298–311. https://doi.org/10.1080/17439884.2020.1754236
30. Korucu, A. T., & Biçer, H. (2022). Eğitimde yapay zekanın rolleri ve eğitsel yapay zeka uygulamaları [The roles of artificial intelligence in education and educational AI applications]. In V. Nabiyev & A. K. Erümit (Eds.), Eğitimde yapay zeka (pp. 38–56). Pegem Akademi.
31. Martin, F., Zhuang, M., & Schaefer, D. (2024). Systematic review of research on artificial intelligence in K-12 education (2017–2022). Computers and Education: Artificial Intelligence, 6, 100195. https://doi.org/10.1016/j.caeai.2023.100195
32. Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2010). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. International Journal of Surgery, 8(5), 336–341. https://doi.org/10.1016/j.ijsu.2010.02.007
33. Nabiyev, V. (2021). Yapay zekâ derin öğrenme stratejili oyunlar örüntü tanıma doğal dil işleme [Artificial intelligence deep learning strategy games pattern recognition natural language processing]. Seçkin.
34. Nabiyev, V., & Erümit, A. K. (2022). Yapay zekanın temelleri [The foundations of artificial intelligence]. In V. Nabiyev & A. K. Erümit (Eds.), Eğitimde yapay zeka (pp. 2–34). Pegem Akademi.
35. Niet, I., Hagemeijer, M., Gardenier, A. M., & Est, R. van. (2024). Framing the (un)sustainability of AI: Environmental, social, and democratic aspects. In Digital technologies for sustainable futures. Routledge.
36. Osetskyi, V., Vitrenko, A., Tatomyr, I., Bilan, S., & Hirnyk, Y. (2020). Artificial intelligence application in education: Financial implications and prospects. Financial and Credit Activity Problems of Theory and Practice, 2(33), 574–584. https://doi.org/10.18371/fcaptp.v2i33.207230
37. Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020
38. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
39. Polat, S., & Ay, O. (2016). Meta-sentez: Kavramsal bir çözümleme [Meta-synthesis: A conceptual analysis]. Eğitimde Nitel Araştırmalar Dergisi, 4(2), 52–64.
40. Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 22. https://doi.org/10.1186/s41039-017-0062-8
41. Rong, Q., Xiao, Y., Kong, W., & Gao, X. (2023). Empowering Higher Education: A Comprehensive Review of Artificial Intelligence Integration. In C. Anutariya, D. Liu, Kinshuk, A. Tlili, J. Yang, & M. Chang (Eds.), Smart Learning for A Sustainable Society (pp. 179–184). Springer Nature. https://doi.org/10.1007/978-981-99-5961-7_21
42. Sayari, K. T. (2025). Infrastructure and investment needs for AI implementation in education. In Teachers’ roles and perspectives on AI integration in schools (pp. 141–162). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3373-1017-6.ch005
43. Sharma, R. K. (2025). Ethics in AI: Balancing innovation and responsibility. International Journal of Science and Research Archive, 14(1), 544–551. https://doi.org/10.30574/ijsra.2025.14.1.0122
44. Sheikh, H., Prins, C., & Schrijvers, E. (2023). Policy for AI as a System Technology. In Mission AI: The New System Technology (pp. 333–375). Springer International Publishing. https://doi.org/10.1007/978-3-031-21448-6_10
45. Shete, S. G., Koshti, P., & Pujari, V. I. (2024). The impact of AI-powered personalization on academic performance in students. 2024 5th International Conference on Recent Trends in Computer Science and Technology (ICRTCST), 295–301. https://doi.org/10.1109/ICRTCST61793.2024.10578480
46. Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology, 8(1), 45. https://doi.org/10.1186/1471-2288-8-45
47. Tlili, A., Saqer, K., Salha, S., & Huang, R. (2025). Investigating the effect of artificial intelligence in education (AIEd) on learning achievement: A meta-analysis and research synthesis. Information Development. https://doi.org/10.1177/02666669241304407
48. Tunç, Z., & Baş, Ö. (2024). Analysis of Studies Based on Türkiye Examining the Relationship between Artificial Intelligence and Education: A Meta Synthesis Study. İçtimaiyat, 8, 38–56. https://doi.org/10.33709/ictimaiyat.1532815
49. Türkmen, G. (2025). The Review of Studies on Explainable Artificial Intelligence in Educational Research. Journal of Educational Computing Research, 63(2), 277–310. https://doi.org/10.1177/07356331241310915
50. Verdecchia, R., Sallou, J., & Cruz, L. (2023). A systematic review of Green AI. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 13(4), e1507. https://doi.org/10.1002/widm.1507
51. Wang, N., Wang, X., & Su, Y.-S. (2024). Critical analysis of the technological affordances, challenges and future directions of Generative AI in education: A systematic review. Asia Pacific Journal of Education, 44(1), 139–155. https://doi.org/10.1080/02188791.2024.2305156
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), 39. https://doi.org/10.1186/s41239-019-0171-0