Contemporary Research Analysis Journal

This study aims to explore teachers’ metaphors regarding artificial intelligence. Today, artificial intelligence technologies are becoming increasingly prevalent in educational settings, significantly altering teaching practices, teachers’ roles and the structure of learning environments. In this process of change, how teachers position artificial intelligence directly influences how this technology is used in education. Therefore, it is important to investigate what teachers liken artificial intelligence to and the underlying thoughts behind these analogies. As metaphors reveal how individuals make sense of complex and abstract concepts, they have been used as the primary data source in this study. A review of the literature reveals that artificial intelligence makes significant contributions to education, such as personalising learning, reducing teachers’ workload, and supporting decision-making processes. Conversely, significant concerns such as ethical issues, the risk of dependency, the weakening of students’ thinking and creative skills, and inequality of opportunity also attract attention. 

The research was conducted using the phenomenology design, one of the qualitative research methods; data obtained from 12 teachers with different subject specialisms and levels of experience were analysed using content analysis. The findings reveal that teachers’ views revolve around the themes of “access to information”, “supporting learning”, “the limited nature of interaction”, “encouraging complacency” and “controlled use”. The research found that teachers view artificial intelligence as a tool that provides rapid access to information, facilitates learning and supports the teaching process. However, participants stated that artificial intelligence has limitations when it comes to conveying emotions, taking individual differences into account and establishing value-based communication. Furthermore, views emerged suggesting that artificial intelligence could steer students towards ready-made information and potentially weaken critical thinking and creative processes. Nevertheless, teachers emphasised that, when used consciously and for pedagogical purposes, artificial intelligence could make significant contributions to the educational process. In this context, the research revealed that teachers perceive artificial intelligence as a multi-dimensional structure that encompasses both opportunities and risks. Consequently, it was concluded that pedagogical guidance, ethical awareness and conscious usage processes are crucial for the effective use of artificial intelligence in education.

Artificial intelligence, Metaphor, Teacher, Access to information

1. Ahmad, S. F., Rahmat, M. K., Mubarik, M. S., Alam, M. M., & Hyder, S. I. (2021). Artificial intelligence and its role in education. Sustainability, 13(22), 2-11. 
2. Akyel, Y., ve Tur, E. (2024). Eğitim bilimlerinde yapay zekânın potansiyeli ve beklentiler, zorluklar ve gelecek yönelimleri. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 25(1), 645–711. https://doi.org/10.29299/kefad.1322341 
3. Altun, E. (2024). Yapay zekâ ve pedagoji: Eğitimde fırsatlar ve zorluklar. Dijital Teknolojiler ve Eğitim Dergisi, 3(1), 80–95. 
4. Arslan, K. (2020). Eğitimde yapay zeka ve uygulamaları. Batı Anadolu Eğitim Bilimleri Dergisi, 11(1), 71–88.
5. Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In J. A. Larusson & B. White (Eds.), Learning analytics: From research to practice (pp. 61–75). Springer.
6. Boztepe, C. (2025). Eğitimde yapay zekâ uygulamaları: Fırsatlar, sınırlılıklar ve etik tartışmalar. Dumlupınar Üniversitesi Eğitim Bilimleri Enstitüsü Dergisi, 9(1), 98–121. https://doi.org/10.71272/debder.1706141 
7. Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial intelligence trends in education: A narrative overview. Procedia Computer Science, 136, 16–24. 
8. Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32, 444–452. 
9. Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE.
10. Çam, M. B., Çelik, N. C., Turan-Güntepe, E., & Durukan, Ü. G. (2021). Öğretmen adaylarının yapay zekâ teknolojileri ile ilgili farkındalıklarının belirlenmesi. Hatay Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18(48), 263–285.
11. Felix, C. V. (2020). The role of the teacher and AI in education. In International perspectives on the role of technology in humanizing higher education. Emerald Publishing. 
12. Gölbaşı, B., & Okul, Ö. (2024). Öğretmen adaylarının “yapay zekâ” kavramına ilişkin metaforik algıları. In XI. International Eurasian Educational Research Congress (pp. 49–58). Eurasian Educational Research Association.
13. Gül, F. Ö. (2024). Eğitimde yapay zekâ: eğitim fakültesi akademisyenleri için fırsatlar ve riskler. Medeniyet Eğitim Araştırmaları Dergisi, 8(2), 71-97.
14. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. 
15. Lakoff, G., & Johnson, M. (1980). Metaphors we live by. University of Chicago Press.
16. Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE.
17. Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. UCL IOE Press. 
18. Merriam, S. B. (2013). Qualitative research: A guide to design and implementation (3rd ed.). Jossey-Bass.
19. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). SAGE.
20. Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28, 4221–4241.
21. Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). SAGE.
22. Porayska-Pomsta, K., Holmes, W., & Nemorin, S. (2023/2024). The Ethics of Artificial Intelligence in Education. Routledge.
23. Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press. 
24. Seyrek, M. (2024). Öğretmenlerin eğitimde yapay zekâ kullanımına yönelik görüşleri. Journal of Social, Humanities and Administrative Sciences Studies, 10(2), 215–228.
25. Tack, A., & Piech, C. (2022). The AI teacher test: Measuring the pedagogical ability of Blender and GPT-3 in educational dialogues (pp. 1–16). arXiv.
26. UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO.