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Have Teachers Embraced Artificial Intelligence? A Synthesis of Teachers' Experiences from K-12 Education Systems

Year 2025, Volume: 12 Issue: 1, 70 - 100, 30.06.2025

İbrahim Can Güngör , Talip Öztürk

https://doi.org/10.34086/rteusbe.1660052

Abstract

Filling the gap between theory and practice in educational environments largely depends on teachers' nuanced approaches. However, while the integration of artificial intelligence (AI) into global K-12 education systems provides a strong alternative for restructuring educational environments, the direction of teachers' experiences regarding the embrace or resistance to AI remains uncertain. Understanding the experiences of teachers, who are the professional practitioners of teaching, regarding the presence of AI in education is crucial in bridging such a gap. This review study focuses on the Web of Science (WOS) and ERIC databases to synthesize global experiences of teachers' adoption of AI in educational settings, examining and discussing empirical evidence to understand the opportunities and challenges this process presents from the teachers' perspectives. According to the procedure, the findings from the synthesis of 42 studies highlight four clusters of patterns related to teachers' experiences with AI integration: personal and behavioral factors, policies, curricula and uncertainties, dilemmas and differences in understanding, and persuasive pedagogical conditions. In this context, various recommendations are made for teachers and other practitioners.

Keywords

K-12 education systems teacher experiences technology acceptance artificial intelligence integration

References

  • Al Darayseh, A. (2023). Acceptance of artificial intelligence in teaching science: Science teachers’ perspective. Computers and Education: Artificial Intelligence, 4(100132), 100132. https://doi.org/10.1016/j.caeai.2023.100132
  • Al-Amri, N. A., & Al-Abdullatif, A. M. (2024). Drivers of chatbot adoption among K–12 teachers in Saudi Arabia. Education Sciences, 14(9), 1034. https://doi.org/10.3390/educsci14091034
  • Alam, A. (2021). Should robots replace teachers? Mobilisation of AI and learning analytics in education. 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3), 1-12. https://doi.org/10.1109/ICAC353642.2021.9697300
  • Almaki, S. H., Mafarja, N., & Al Mansoori, H. M. S. (2025). Teacher well-being and use of artificial intelligence applications and tools: Moderation effects of leadership support in inclusive classroom. STEM Education, 5(1), 109–129. https://doi.org/10.3934/steme.2025006
  • An, X., Chai, C. S., Li, Y., Zhou, Y., Shen, X., Zheng, C., & Chen, M. (2023). Modeling English teachers’ behavioral intention to use artificial intelligence in middle schools. Education and Information Technologies, 28(5), 5187–5208. https://doi.org/10.1007/s10639-022-11286-z
  • Antonenko, P., & Abramowitz, B. (2023). In-service teachers’ (mis)conceptions of artificial intelligence in K-12 science education. Journal of Research on Technology in Education, 55(1), 64–78. https://doi.org/10.1080/15391523.2022.2119450
  • Bakhadirov, M., Alasgarova, R., & Rzayev, J. (2024). Factors influencing teachers' use of artificial intelligence for instructional purposes. IAFOR Journal of Education, 12(2), https://files.eric.ed.gov/fulltext/EJ1440077.pdf
  • Bal, R. & Gill, I. S. (2020). Policy approaches to artificial intelligence based technologies in China, European union and the United States. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3699640
  • Bateman, T. (2025). Teacher perspectives of ChatGPT as a pedagogical tool in the K-12 setting: a case study. Quality Assurance in Education, 33(2), 203–217. https://doi.org/10.1108/qae-02-2024-0042
  • Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Computers and Education: Artificial Intelligence, 3(100068), 100068. https://doi.org/10.1016/j.caeai.2022.100068
  • Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends: For Leaders in Education & Training, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
  • Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: A narrative overview. Procedia Computer Science, 136, 16–24. https://doi.org/10.1016/j.procs.2018.08.233
  • Chavez, H., Chavez-Arias, B., Contreras-Rosas, S., Alvarez-Rodríguez, J. M., & Raymundo, C. (2023). Artificial neural network to predict student performance using nonpersonal information. Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1106679
  • Cheah, Y. H., Lu, J., & Kim, J. (2025). Integrating generative artificial intelligence in K-12 education: Examining teachers’ preparedness, practices, and barriers. Computers and Education: Artificial Intelligence, 8(100363), 100363. https://doi.org/10.1016/j.caeai.2025.100363
  • Chen, J. J & Lin, J. C. (2024). Artificial intelligence as a double-edged sword: Wielding the POWER principles to maximize its positive effects and minimize its negative effects. Contemporary Issues in Early Childhood 25(1): 146–153.
  • Chen, R., Lee, V. R., & G Lee, M. (2025). A cross-sectional look at teacher reactions, worries, and professional development needs related to generative AI in an urban school district. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13350-w
  • Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1(100002), 100002. https://doi.org/10.1016/j.caeai.2020.100002
  • Chocarro, R., Cortiñas, M., & Marcos-Matás, G. (2021). Teachers’ attitudes towards chatbots in education: a technology acceptance model approach considering the effect of social language, bot proactiveness, and users’ characteristics. Educational Studies, 1–19. https://doi.org/10.1080/03055698.2020.1850426
  • Choi, S., Jang, Y., & Kim, H. (2023). Influence of pedagogical beliefs and perceived trust on teachers’ acceptance of educational artificial intelligence tools. International Journal of Human-Computer Interaction, 39(4), 910–922. https://doi.org/10.1080/10447318.2022.2049145
  • Crompton, H., Jones, M. V., & Burke, D. (2024). Affordances and challenges of artificial intelligence in K-12 education: a systematic review. Journal of Research on Technology in Education, 56(3), 248–268. https://doi.org/10.1080/15391523.2022.2121344
  • Cukurova, M., Miao, X., & Brooker, R. (2023). Adoption of artificial intelligence in schools: Unveiling factors influencing teachers’ engagement. In Lecture Notes in Computer Science (pp. 151–163). Springer Nature Switzerland.
  • Delello, J. A., Sung, W., Mokhtari, K., Hebert, J., Bronson, A., & De Giuseppe, T. (2025). AI in the classroom: Insights from educators on usage, challenges, and mental health. Education Sciences, 15(2), 113. https://doi.org/10.3390/educsci15020113
  • Delello, J., Sung, W., Mokhtari, K., & De Giuseppe, T. (2024). Are K-16 educators prepared to address the educational and ethical ramifications of artificial intelligence software? In K. Arai (Ed.), Advances in information and communication: FICC 2024 (pp. 406–432). Lecture Notes in Networks and Systems; Springer.
  • Erol, M., & Erol, A. (2024). Use of artificial intelligence (AI) technologies in education according to primary school teachers: Opportunities and challenges. Sakarya University Journal of Education, 14(3), 426–446. https://doi.org/10.19126/suje.1446227
  • Fahreni, R., Ali, H. S., & Daud, A. (2024). Teachers’ perspective on the use of artificial intelligence in teaching and learning process: A systematic literature review. SCOPE: Journal of English Language Teaching, 9(1), 417-423.
  • Farahani, M. S., & Ghasmi, G. (2024). Artificial Intelligence in education: A comprehensive study. Forum for Education Studies, 2(3), 1379. https://doi.org/10.59400/fes.v2i3.1379
  • Fassbender, W. J. (2024). “I can almost recognize its voice”: AI and its impact on ethical teacher-centaur labor. English Teaching Practice & Critique, 23(1), 104–117. https://doi.org/10.1108/etpc-08-2023-0101
  • Forero-Corba, W., & Negre Bennasar, F. (2023). Técnicas y aplicaciones del Machine Learning e Inteligencia Artificial en educación: una revisión sistemática. RIED Revista Iberoamericana de Educación a Distancia, 27(1), 209–253. https://doi.org/10.5944/ried.27.1.37491
  • Fu, L. (2025). The role of STEM teachers’ emotional intelligence and psychological well-being in predicting their artificial intelligence literacy. Acta Psychologica, 253(104708), 104708. https://doi.org/10.1016/j.actpsy.2025.104708
  • Funa, A. A., & Gabay, R. A. E. (2025). Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study. Social Sciences & Humanities Open, 11(101221), 101221. https://doi.org/10.1016/j.ssaho.2024.101221
  • Galindo-Domínguez, H., Delgado, N., Campo, L., & Losada, D. (2024b). Relationship between teachers’ digital competence and attitudes towards artificial intelligence in education. International Journal of Educational Research, 126(102381), 102381. https://doi.org/10.1016/j.ijer.2024.102381
  • Galindo-Domínguez, H., Delgado, N., Losada, D., & Etxabe, J.-M. (2024a). An analysis of the use of artificial intelligence in education in Spain: The in-service teacher’s perspective. Journal of Digital Learning in Teacher Education, 40(1), 41–56. https://doi.org/10.1080/21532974.2023.2284726
  • Gârdan, I. P., Manu, M. B., Gârdan, D. A., Negoiță, L. D. L., Paștiu, C. A., Ghiță, E., & Zaharia, A. (2025). Adopting AI in education: optimizing human resource management considering teacher perceptions. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1488147
  • Gkintoni, E., Antonopoulou, H., Sortwell, A., & Halkiopoulos, C. (2025). Challenging cognitive load theory: the role of educational neuroscience and artificial intelligence in redefining learning efficacy. Brain Sciences, 15(2), 203. https://doi.org/10.3390/brainsci15020203
  • Gursoy, F., & Kakadiaris, I. A. (2023). Artificial intelligence research strategy of the United States: critical assessment and policy recommendations. Frontiers in Big Data, 6, 1206139. https://doi.org/10.3389/fdata.2023.1206139
  • Güngör, İ. C., Zayimoğlu Öztürk, F., & Can, İ. (2024). Sosyal bilgiler eğitiminde yapay zekâ. Farklı bakış açılarıyla eğitimde yapay zekâ içinde (ss. 115-137). Eğitim Yayınevi.
  • Hajkowicz, S., Sanderson, C., Karimi, S., Bratanova, A., & Naughtin, C. (2023). Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021. Technology in Society, 74(102260), 102260. https://doi.org/10.1016/j.techsoc.2023.102260
  • Hammoud, R. (2025). Exploring chemistry teachers’ knowledge and perceptions of AI: Opportunities and challenges. International Journal of Research in Education and Science, 11(1), 49–60. https://doi.org/10.46328/ijres.3584
  • Han, A., Zhou, X., Cai, Z., Han, S., Ko, R., Corrigan, S., & Peppler, K. A. (2024). Teachers, parents, and students’ perspectives on integrating generative AI into elementary literacy education. Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–17.
  • Hart, C. (2001). Doing a literature search: A comprehensive guide for the social sciences. SAGE.
  • Hays, L., Jurkowski, O., & Sims, S. K. (2024). ChatGPT in K-12 education. TechTrends : For Leaders in Education & Training, 68(2), 281–294. https://doi.org/10.1007/s11528-023-00924-z
  • Hu, Y., Xu, Y., & Wu, B. (2025). A dual-pathway model of teacher-AI collaboration based on the job demands-resources theory. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13421-y
  • Jang, Y., Choi, S., Jung, H., & Kim, H. (2022). Practical early prediction of students’ performance using machine learning and eXplainable AI. Education and Information Technologies, 27(9), 12855–12889. https://doi.org/10.1007/s10639-022-11120-6
  • Jatileni, C. N., Sanusi, I. T., Olaleye, S. A., Ayanwale, M. A., Agbo, F. J., & Oyelere, P. B. (2024). Artificial intelligence in compulsory level of education: perspectives from Namibian in-service teachers. Education and Information Technologies, 29(10), 12569–12596. https://doi.org/10.1007/s10639-023-12341-z
  • Karan, B., & Angadi, G. R. (2023). Potential risks of artificial intelligence integration into school education: A systematic review. Bulletin of Science, Technology & Society, 43(3–4), 67–85. https://doi.org/10.1177/02704676231224705
  • Kasepalu, R., Prieto, L. P., Ley, T., & Chejara, P. (2022). Teacher artificial intelligence-supported pedagogical actions in collaborative learning coregulation: A Wizard-of-Oz study. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.736194
  • Kasinidou, M., Kleanthoys, S., & Otterbacher, J. (2025). Cypriot teachers’ digital skills and attitudes towards AI. Discover Education, 4(1). https://doi.org/10.1007/s44217-024-00390-6
  • Kim, J. (2024). Types of teacher-AI collaboration in K-12 classroom instruction: Chinese teachers’ perspective. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12523-3
  • Kurata, L., Ayanwale, M. A., Molefi, R. R., & Sanni, T. (2025). Teaching religious studies with artificial intelligence: A qualitative analysis of Lesotho secondary schools teachers’ perceptions. International Journal of Educational Research Open, 8(100417), 100417. https://doi.org/10.1016/j.ijedro.2024.100417
  • Laak, K.-J., & Aru, J. (2024). Generative AI in K-12: Opportunities for learning and utility for teachers. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky (pp. 502–509). Springer Nature Switzerland.
  • Lee, I., & Perret, B. (2022). Preparing high school teachers to integrate AI methods into STEM classrooms. Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence / Thirty-Fourth Conference on Innovative Applications of Artificial Intelligence / Twelfth Symposium on Educational Advances in Artificial Intelligence (pp. 12783-12791). Association for the Advancement of Artificial Intelligence.
  • Lee, S. J., & Kwon, K. (2024). A systematic review of AI education in K-12 classrooms from 2018 to 2023: Topics, strategies, and learning outcomes. Computers and Education: Artificial Intelligence, 6(100211), 100211. https://doi.org/10.1016/j.caeai.2024.100211
  • Li, M. (2024). Integrating Artificial Intelligence in primary mathematics education: Investigating internal and external influences on teacher adoption. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-024-10515-w
  • Lim, W. M. (2024). What is qualitative research? An overview and guidelines. Australasian Marketing Journal (AMJ). https://doi.org/10.1177/14413582241264619
  • Lin, X.-F., Shen, W., Huang, S., Wang, Y., Zhou, W., Ling, X., & Li, W. (2025). Exploring Chinese teachers’ concerns about teaching artificial intelligence: the role of knowledge and perceived social good. Asia Pacific Education Review. https://doi.org/10.1007/s12564-024-10034-x
  • Mah, C., Walker, H., Phalen, L., Levine, S., Beck, S. W., & Pittman, J. (2024). Beyond CheatBots: Examining tensions in teachers’ and students’ perceptions of cheating and learning with ChatGPT. Education Sciences, 14(5), 500. https://doi.org/10.3390/educsci14050500
  • Mansfield, K. L., Ghai, S., Hakman, T., Ballou, N., Vuorre, M., & Przybylski, A. K. (2025). From social media to artificial intelligence: improving research on digital harms in youth. The Lancet. Child & Adolescent Health, 9(3), 194–204. https://doi.org/10.1016/s2352-4642(24)00332-8
  • 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), 100195. https://doi.org/10.1016/j.caeai.2023.100195
  • McGehee, N. (2024). Breaking barriers: A Meta-Analysis of educator acceptance of AI technology in education. Michigan Virtual. https://michiganvirtual.org/research/publications/breaking-barriers-a-meta-analysis-of-educator-acceptance-of-ai-technology-in-education/
  • Meylani, R. (2024). Artificial Intelligence in the education of teachers: A qualitative synthesis of the cutting-edge research literature. Journal of Computer and Education Research, 12(24), 600–637. https://doi.org/10.18009/jcer.1477709
  • Miao, F; Holmes, W. (2021). Artificial intelligence and education. Guidance for policy-makers. United Nations Educational, Scientific and Cultural Organization (UNESCO): Paris, France.
  • Mintz, J., Holmes, W., Liu, L., & Perez-Ortiz, M. (2023). Artificial intelligence and K-12 education: Possibilities, pedagogies and risks. Computers in the Schools: Interdisciplinary Journal of Practice, Theory, and Applied Research, 40(4), 325–333. https://doi.org/10.1080/07380569.2023.2279870
  • Molefi, R. R., Ayanwale, M. A., Kurata, L., & Chere-Masopha, J. (2024). Do in-service teachers accept artificial intelligence-driven technology? The mediating role of school support and resources. Computers and Education Open, 6 (100191), 100191. https://doi.org/10.1016/j.caeo.2024.100191
  • Nabizadeh, A. H., Leal, J. P., Rafsanjani, H. N., & Shah, R. R. (2020). Learning path personalization and recommendation methods: A survey of the state-of-the-art. Expert Systems with Applications, 159(113596), 113596. https://doi.org/10.1016/j.eswa.2020.113596
  • Nja, C. O., Idiege, K. J., Uwe, U. E., Meremikwu, A. N., Ekon, E. E., Erim, C. M., Ukah, J. U., Eyo, E. O., Anari, M. I., & Cornelius-Ukpepi, B. U. (2023). Adoption of artificial intelligence in science teaching: From the vantage point of the African science teachers. Smart Learning Environments, 10(1). https://doi.org/10.1186/s40561-023-00261-x
  • Nur S. Z. & Melor M. Y. (2023). Teachers’ perceptions and continuance usage intention of Artificial Intelligence technology in TESL. International Journal of Multidisciplinary Research And Analysis, 06(05). https://doi.org/10.47191/ijmra/v6-i5-34
  • Oh, S.-Y., & Ahn, Y. (2024). Exploring teachers’ perception of artificial intelligence: The Socio-emotional deficiency as opportunities and challenges in human-AI complementarity in K-12 education. In Lecture Notes in Computer Science (pp. 439–447). Springer Nature Switzerland.
  • Örtegren, A., & Velander, J. (2023). Artificial intelligence in Nordic K-12 education : implications of materials and resources for digital citizenship formation. NERA Conference 2023, Oslo, Norway, March 15-17, 2023. https://umu.diva-portal.org/smash/record.jsf?pid=diva2%3A1745127&dswid=9115
  • Patac, L. P., & Patac, A. V., Jr. (2025). Using ChatGPT for academic support: Managing cognitive load and enhancing learning efficiency – A phenomenological approach. Social Sciences & Humanities Open, 11(101301), 101301. https://doi.org/10.1016/j.ssaho.2025.101301
  • Pedro, F., Subosa, M., Rivas, A. and Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000366994
  • Pham, S. T. H., & Sampson, P. M. (2022). The development of artificial intelligence in education: A review in context. Journal of Computer Assisted Learning, 38(5), 1408–1421. https://doi.org/10.1111/jcal.12687
  • Pitrella, V. et al. (2024). Artificial intelligence for personalized learning in K-12 education. A scoping review. In: Casalino, G., et al. Higher Education Learning Methodologies and Technologies Online. HELMeTO 2023. Communications in Computer and Information Science, vol 2076. Springer, Cham. https://doi.org/10.1007/978-3-031-67351-1_25
  • Rakap, S., & Balikci, S. (2024). Enhancing IEP goal development for preschoolers with autism: A preliminary study on ChatGPT integration. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-024-06343-0
  • Ray Pörn, Mats Braskén, Mattias Wingren, & Sören Andersson. (2024). Attitudes towards and Expectations on the Role of Artificial Intelligence in the Classroom among Digitally Skilled Finnish K-12 Mathematics Teachers. LUMAT: International Journal on Math, Science and Technology Education, 12(3), 53–77. https://doi.org/10.31129/LUMAT.12.3.2102
  • Republic of Turkey Ministry of National Education (2024). Policy brief for artificial intelligence in education: Lessons from international forum of artificial intelligence in education. Republic of Turkey Ministry of National Education Directorate General for Innovation and Educational Technologies. Ankara.
  • Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599. https://doi.org/10.1007/s40593-016-0110-3
  • Ruiz Viruel, S., Sánchez Rivas, E., & Ruiz Palmero, J. (2025). The role of artificial intelligence in project-based learning: Teacher perceptions and pedagogical implications. Education Sciences, 15(2), 150. https://doi.org/10.3390/educsci15020150
  • Salha, S., Mousa, A., & Khayat, S. (2024). Artificial intelligence in education (AIED) policies in school context: A mixed approach research. Leadership and Policy in Schools, 1–19. https://doi.org/10.1080/15700763.2024.2443675
  • Savolainen, R. (2016). Information seeking and searching strategies as plans and patterns of action: A conceptual analysis. The Journal of Documentation72(6), 1154–1180. https://doi.org/10.1108/jd-03-2016-0033
  • Seo, K., Yoo, M., Dodson, S., & Jin, S.-H. (2024). Augmented teachers: K–12 teachers’ needs for artificial intelligence’s complementary role in personalized learning. Journal of Research on Technology in Education, 1–18. https://doi.org/10.1080/15391523.2024.2330525
  • Skolverket [the Swedish National Agency for Education] (2022). Läroplan för grundskolan, förskoleklassen och fritidshemmet. [Curriculum for elementary school, preschool and out of school care] https://www.skolverket.se/undervisning/grundskolan/laroplan-och-kursplaner-for-grundskolan/laroplan-lgr22-for-grundskolan-samt-for-forskoleklassen-och-fritidshemmet
  • Small, G. W., Lee, J., Kaufman, A., Jalil, J., Siddarth, P., Gaddipati, H., Moody, T. D., & Bookheimer, S. Y. (2020). Brain health consequences of digital technology use. Dialogues in Clinical Neuroscience, 22(2), 179–187. https://doi.org/10.31887/dcns.2020.22.2/gsmall
  • Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
  • Sperling, K., McGrath, C., Stenliden, L., Åkerfeldt, A., & Heintz, F. (2023). Mapping AI literacy in teacher education. International Symposium on Digital Transformation . https://open.lnu.se/index.php/isdt/article/view/3744
  • Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Sage.
  • Su, J., Zhong, Y., & Ng, D. T. K. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence, 3(100065), 100065. https://doi.org/10.1016/j.caeai.2022.100065
  • Taheri, A., RahimiZadeh, K., & Rao, R. V. (2021). An efficient balanced teaching-learning-based optimization algorithm with individual restarting strategy for solving global optimization problems. Information Sciences, 576, 68–104. https://doi.org/10.1016/j.ins.2021.06.064
  • Tan, X., Cheng, G., & Ling, M. H. (2025). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education: Artificial Intelligence, 8(100355), 100355. https://doi.org/10.1016/j.caeai.2024.100355
  • Tekin, Ö. G. (2024). Factors affecting teachers' acceptance of artificial intelligence technologies: Analyzing teacher perspectives with structural equation modeling. Instructional Technology and Lifelong Learning, 5(2), 399 - 420. https://doi.org/10.52911/itall.1532218
  • 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
  • Tran, T. T. T. (2025). Enhancing EFL writing revision practices: The impact of AI- and teacher-generated feedback and their sequences. Education Sciences, 15(2), 232. https://doi.org/10.3390/educsci15020232
  • Uygun, D. (2024). Teachers’ perspectives on artificial intelligence in education. Advances in Mobile Learning Educational Research, 4(1), 931–939. https://doi.org/10.25082/amler.2024.01.005
  • Van Roy, V., Rossetti, F., Perset, K. and Galindo-Romero, L., AI Watch (2021). National strategies on Artificial Intelligence: A European perspective. Publications Office of the European Union, https://dx.doi.org/10.2760/069178
  • Velander, J., Taiye, M. A., Otero, N., & Milrad, M. (2024). Artificial Intelligence in K-12 Education: eliciting and reflecting on Swedish teachers’ understanding of AI and its implications for teaching & learning. Education and Information Technologies, 29(4), 4085–4105. https://doi.org/10.1007/s10639-023-11990-4
  • Viberg, O., Cukurova, M., Feldman-Maggor, Y., Alexandron, G., Shirai, S., Kanemune, S., Wasson, B., Tømte, C., Spikol, D., Milrad, M., Coelho, R., & Kizilcec, R. F. (2024). What explains teachers’ trust in AI in education across six countries? International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00433-x
  • Wang, K., Chai, C.-S., Liang, J.-C., & Sang, G. (2024). Exploring teachers’ behavioural intentions to design artificial intelligence-assisted learning in Chinese K–12 education. Technology Pedagogy and Education, 33(5), 629–645. https://doi.org/10.1080/1475939x.2024.2369241
  • Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252(124167), 124167. https://doi.org/10.1016/j.eswa.2024.124167
  • Whalen, J., Grube, W., Xu, C., & Torrey Trust. (2025). K-12 educators’ reactions and responses to ChatGPT and GenAI during the 2022–2023 school year. TechTrends : For Leaders in Education & Training, 69(1), 125–137. https://doi.org/10.1007/s11528-024-01028-y
  • World Economic Forum. (2024). Shaping the future of learning: The role of AI in education 4.0. Available online: https://www.weforum.org/publications/shaping-the-future-of-learning-the-role-of-ai-in-education-4-0/
  • Xie, B., Sarin, P., Wolf, J., Garcia, R. C. C., Delaney, V., Sieh, I., Fuloria, A., Dennison, D. V., Bywater, C., & Lee, V. R. (2024). Co-designing AI education curriculum with cross-disciplinary high school teachers. Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 38(21), 23146–23154.
  • Yau, K. W., Chai, C. S., Chiu, T. K. F., Meng, H., King, I., & Yam, Y. (2023). A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools. Education and Information Technologies, 28(1), 1041–1064. https://doi.org/10.1007/s10639-022-11161-x
  • Yim, I. H. Y., & Wegerif, R. (2024). Teachers’ perceptions, attitudes, and acceptance of artificial intelligence (AI) educational learning tools: An exploratory study on AI literacy for young students. Future in Educational Research, 2(4), 318–345. https://doi.org/10.1002/fer3.65
  • Yuan, S., He, T., Huang, H., Hou, R., & Wang, M. (2020). Automated Chinese essay scoring based on deep learning. CMC-Computers Materials & Continua, 65(1), 817–833.
  • Yue, M., Jong, M. S.-Y., & Ng, D. T. K. (2024). Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, 29(15), 19505–19536. https://doi.org/10.1007/s10639-024-12621-2

Öğretmenler Yapay Zekâyı Benimsedi Mi? K-12 Eğitim Sistemlerinden Öğretmen Deneyimlerinin Bir Sentezi

Year 2025, Volume: 12 Issue: 1, 70 - 100, 30.06.2025

İbrahim Can Güngör , Talip Öztürk

https://doi.org/10.34086/rteusbe.1660052

Abstract

Eğitim ortamlarında teori ve uygulama arasındaki boşluğun doldurulması büyük ölçüde öğretmenlerin incelikli yaklaşımlarından geçmektedir. Ancak, küresel K-12 eğitim sistemlerinde yapay zekânın eğitime entegrasyonu eğitim ortamlarının yeniden yapılandırılması için güçlü bir alternatif olmasına karşın, yapay zekâyı kucaklama ya da buna direnç gösterme nedenlerine yönelik öğretmen deneyimlerinin hangi yönde ilerlediği belirsizdir. Öğretimin profesyonel uygulayıcıları olan öğretmenlerin yapay zekânın eğitimdeki varlığına yönelik deneyimleri anlamak bu tür bir boşluğun doldurulmasında son derece önemlidir. Bu derleme çalışması, Web of Science (WOS) ve ERIC veri tabanlarındaki çalışmalara odaklanarak, öğretmenlerin eğitim ortamlarında yapay zekânın benimsemeleri ile ilgili küresel deneyimleri sentezlemekte, bu sürecin sunduğu fırsatları ve zorlukları öğretmenlerin perspektifinden anlamak için ampirik kanıtları incelemekte ve tartışmaktadır. Prosedüre göre, 42 çalışmanın sentezine ilişkin bulgular, öğretmenlerin yapay zekâ entegrasyonu konusundaki deneyimleri ile ilgili kişisel ve davranışsal faktörler, politikalar, müfredatlar ve belirsizlikler, ikilemler ve anlayış farklılıkları ile ikna edici pedagojik koşullara dair dört örüntü kümesine dikkat çekmektedir. Bu çerçevede öğretmenlere ve diğer uygulayıcılara çeşitli önerilerde bulunulmaktadır.

Keywords

K-12 eğitim sistemleri öğretmen deneyimleri teknoloji kabulü yapay zekâ entegrasyonu

References

  • Al Darayseh, A. (2023). Acceptance of artificial intelligence in teaching science: Science teachers’ perspective. Computers and Education: Artificial Intelligence, 4(100132), 100132. https://doi.org/10.1016/j.caeai.2023.100132
  • Al-Amri, N. A., & Al-Abdullatif, A. M. (2024). Drivers of chatbot adoption among K–12 teachers in Saudi Arabia. Education Sciences, 14(9), 1034. https://doi.org/10.3390/educsci14091034
  • Alam, A. (2021). Should robots replace teachers? Mobilisation of AI and learning analytics in education. 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3), 1-12. https://doi.org/10.1109/ICAC353642.2021.9697300
  • Almaki, S. H., Mafarja, N., & Al Mansoori, H. M. S. (2025). Teacher well-being and use of artificial intelligence applications and tools: Moderation effects of leadership support in inclusive classroom. STEM Education, 5(1), 109–129. https://doi.org/10.3934/steme.2025006
  • An, X., Chai, C. S., Li, Y., Zhou, Y., Shen, X., Zheng, C., & Chen, M. (2023). Modeling English teachers’ behavioral intention to use artificial intelligence in middle schools. Education and Information Technologies, 28(5), 5187–5208. https://doi.org/10.1007/s10639-022-11286-z
  • Antonenko, P., & Abramowitz, B. (2023). In-service teachers’ (mis)conceptions of artificial intelligence in K-12 science education. Journal of Research on Technology in Education, 55(1), 64–78. https://doi.org/10.1080/15391523.2022.2119450
  • Bakhadirov, M., Alasgarova, R., & Rzayev, J. (2024). Factors influencing teachers' use of artificial intelligence for instructional purposes. IAFOR Journal of Education, 12(2), https://files.eric.ed.gov/fulltext/EJ1440077.pdf
  • Bal, R. & Gill, I. S. (2020). Policy approaches to artificial intelligence based technologies in China, European union and the United States. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3699640
  • Bateman, T. (2025). Teacher perspectives of ChatGPT as a pedagogical tool in the K-12 setting: a case study. Quality Assurance in Education, 33(2), 203–217. https://doi.org/10.1108/qae-02-2024-0042
  • Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Computers and Education: Artificial Intelligence, 3(100068), 100068. https://doi.org/10.1016/j.caeai.2022.100068
  • Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends: For Leaders in Education & Training, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
  • Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: A narrative overview. Procedia Computer Science, 136, 16–24. https://doi.org/10.1016/j.procs.2018.08.233
  • Chavez, H., Chavez-Arias, B., Contreras-Rosas, S., Alvarez-Rodríguez, J. M., & Raymundo, C. (2023). Artificial neural network to predict student performance using nonpersonal information. Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1106679
  • Cheah, Y. H., Lu, J., & Kim, J. (2025). Integrating generative artificial intelligence in K-12 education: Examining teachers’ preparedness, practices, and barriers. Computers and Education: Artificial Intelligence, 8(100363), 100363. https://doi.org/10.1016/j.caeai.2025.100363
  • Chen, J. J & Lin, J. C. (2024). Artificial intelligence as a double-edged sword: Wielding the POWER principles to maximize its positive effects and minimize its negative effects. Contemporary Issues in Early Childhood 25(1): 146–153.
  • Chen, R., Lee, V. R., & G Lee, M. (2025). A cross-sectional look at teacher reactions, worries, and professional development needs related to generative AI in an urban school district. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13350-w
  • Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1(100002), 100002. https://doi.org/10.1016/j.caeai.2020.100002
  • Chocarro, R., Cortiñas, M., & Marcos-Matás, G. (2021). Teachers’ attitudes towards chatbots in education: a technology acceptance model approach considering the effect of social language, bot proactiveness, and users’ characteristics. Educational Studies, 1–19. https://doi.org/10.1080/03055698.2020.1850426
  • Choi, S., Jang, Y., & Kim, H. (2023). Influence of pedagogical beliefs and perceived trust on teachers’ acceptance of educational artificial intelligence tools. International Journal of Human-Computer Interaction, 39(4), 910–922. https://doi.org/10.1080/10447318.2022.2049145
  • Crompton, H., Jones, M. V., & Burke, D. (2024). Affordances and challenges of artificial intelligence in K-12 education: a systematic review. Journal of Research on Technology in Education, 56(3), 248–268. https://doi.org/10.1080/15391523.2022.2121344
  • Cukurova, M., Miao, X., & Brooker, R. (2023). Adoption of artificial intelligence in schools: Unveiling factors influencing teachers’ engagement. In Lecture Notes in Computer Science (pp. 151–163). Springer Nature Switzerland.
  • Delello, J. A., Sung, W., Mokhtari, K., Hebert, J., Bronson, A., & De Giuseppe, T. (2025). AI in the classroom: Insights from educators on usage, challenges, and mental health. Education Sciences, 15(2), 113. https://doi.org/10.3390/educsci15020113
  • Delello, J., Sung, W., Mokhtari, K., & De Giuseppe, T. (2024). Are K-16 educators prepared to address the educational and ethical ramifications of artificial intelligence software? In K. Arai (Ed.), Advances in information and communication: FICC 2024 (pp. 406–432). Lecture Notes in Networks and Systems; Springer.
  • Erol, M., & Erol, A. (2024). Use of artificial intelligence (AI) technologies in education according to primary school teachers: Opportunities and challenges. Sakarya University Journal of Education, 14(3), 426–446. https://doi.org/10.19126/suje.1446227
  • Fahreni, R., Ali, H. S., & Daud, A. (2024). Teachers’ perspective on the use of artificial intelligence in teaching and learning process: A systematic literature review. SCOPE: Journal of English Language Teaching, 9(1), 417-423.
  • Farahani, M. S., & Ghasmi, G. (2024). Artificial Intelligence in education: A comprehensive study. Forum for Education Studies, 2(3), 1379. https://doi.org/10.59400/fes.v2i3.1379
  • Fassbender, W. J. (2024). “I can almost recognize its voice”: AI and its impact on ethical teacher-centaur labor. English Teaching Practice & Critique, 23(1), 104–117. https://doi.org/10.1108/etpc-08-2023-0101
  • Forero-Corba, W., & Negre Bennasar, F. (2023). Técnicas y aplicaciones del Machine Learning e Inteligencia Artificial en educación: una revisión sistemática. RIED Revista Iberoamericana de Educación a Distancia, 27(1), 209–253. https://doi.org/10.5944/ried.27.1.37491
  • Fu, L. (2025). The role of STEM teachers’ emotional intelligence and psychological well-being in predicting their artificial intelligence literacy. Acta Psychologica, 253(104708), 104708. https://doi.org/10.1016/j.actpsy.2025.104708
  • Funa, A. A., & Gabay, R. A. E. (2025). Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study. Social Sciences & Humanities Open, 11(101221), 101221. https://doi.org/10.1016/j.ssaho.2024.101221
  • Galindo-Domínguez, H., Delgado, N., Campo, L., & Losada, D. (2024b). Relationship between teachers’ digital competence and attitudes towards artificial intelligence in education. International Journal of Educational Research, 126(102381), 102381. https://doi.org/10.1016/j.ijer.2024.102381
  • Galindo-Domínguez, H., Delgado, N., Losada, D., & Etxabe, J.-M. (2024a). An analysis of the use of artificial intelligence in education in Spain: The in-service teacher’s perspective. Journal of Digital Learning in Teacher Education, 40(1), 41–56. https://doi.org/10.1080/21532974.2023.2284726
  • Gârdan, I. P., Manu, M. B., Gârdan, D. A., Negoiță, L. D. L., Paștiu, C. A., Ghiță, E., & Zaharia, A. (2025). Adopting AI in education: optimizing human resource management considering teacher perceptions. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1488147
  • Gkintoni, E., Antonopoulou, H., Sortwell, A., & Halkiopoulos, C. (2025). Challenging cognitive load theory: the role of educational neuroscience and artificial intelligence in redefining learning efficacy. Brain Sciences, 15(2), 203. https://doi.org/10.3390/brainsci15020203
  • Gursoy, F., & Kakadiaris, I. A. (2023). Artificial intelligence research strategy of the United States: critical assessment and policy recommendations. Frontiers in Big Data, 6, 1206139. https://doi.org/10.3389/fdata.2023.1206139
  • Güngör, İ. C., Zayimoğlu Öztürk, F., & Can, İ. (2024). Sosyal bilgiler eğitiminde yapay zekâ. Farklı bakış açılarıyla eğitimde yapay zekâ içinde (ss. 115-137). Eğitim Yayınevi.
  • Hajkowicz, S., Sanderson, C., Karimi, S., Bratanova, A., & Naughtin, C. (2023). Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021. Technology in Society, 74(102260), 102260. https://doi.org/10.1016/j.techsoc.2023.102260
  • Hammoud, R. (2025). Exploring chemistry teachers’ knowledge and perceptions of AI: Opportunities and challenges. International Journal of Research in Education and Science, 11(1), 49–60. https://doi.org/10.46328/ijres.3584
  • Han, A., Zhou, X., Cai, Z., Han, S., Ko, R., Corrigan, S., & Peppler, K. A. (2024). Teachers, parents, and students’ perspectives on integrating generative AI into elementary literacy education. Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–17.
  • Hart, C. (2001). Doing a literature search: A comprehensive guide for the social sciences. SAGE.
  • Hays, L., Jurkowski, O., & Sims, S. K. (2024). ChatGPT in K-12 education. TechTrends : For Leaders in Education & Training, 68(2), 281–294. https://doi.org/10.1007/s11528-023-00924-z
  • Hu, Y., Xu, Y., & Wu, B. (2025). A dual-pathway model of teacher-AI collaboration based on the job demands-resources theory. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13421-y
  • Jang, Y., Choi, S., Jung, H., & Kim, H. (2022). Practical early prediction of students’ performance using machine learning and eXplainable AI. Education and Information Technologies, 27(9), 12855–12889. https://doi.org/10.1007/s10639-022-11120-6
  • Jatileni, C. N., Sanusi, I. T., Olaleye, S. A., Ayanwale, M. A., Agbo, F. J., & Oyelere, P. B. (2024). Artificial intelligence in compulsory level of education: perspectives from Namibian in-service teachers. Education and Information Technologies, 29(10), 12569–12596. https://doi.org/10.1007/s10639-023-12341-z
  • Karan, B., & Angadi, G. R. (2023). Potential risks of artificial intelligence integration into school education: A systematic review. Bulletin of Science, Technology & Society, 43(3–4), 67–85. https://doi.org/10.1177/02704676231224705
  • Kasepalu, R., Prieto, L. P., Ley, T., & Chejara, P. (2022). Teacher artificial intelligence-supported pedagogical actions in collaborative learning coregulation: A Wizard-of-Oz study. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.736194
  • Kasinidou, M., Kleanthoys, S., & Otterbacher, J. (2025). Cypriot teachers’ digital skills and attitudes towards AI. Discover Education, 4(1). https://doi.org/10.1007/s44217-024-00390-6
  • Kim, J. (2024). Types of teacher-AI collaboration in K-12 classroom instruction: Chinese teachers’ perspective. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12523-3
  • Kurata, L., Ayanwale, M. A., Molefi, R. R., & Sanni, T. (2025). Teaching religious studies with artificial intelligence: A qualitative analysis of Lesotho secondary schools teachers’ perceptions. International Journal of Educational Research Open, 8(100417), 100417. https://doi.org/10.1016/j.ijedro.2024.100417
  • Laak, K.-J., & Aru, J. (2024). Generative AI in K-12: Opportunities for learning and utility for teachers. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky (pp. 502–509). Springer Nature Switzerland.
  • Lee, I., & Perret, B. (2022). Preparing high school teachers to integrate AI methods into STEM classrooms. Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence / Thirty-Fourth Conference on Innovative Applications of Artificial Intelligence / Twelfth Symposium on Educational Advances in Artificial Intelligence (pp. 12783-12791). Association for the Advancement of Artificial Intelligence.
  • Lee, S. J., & Kwon, K. (2024). A systematic review of AI education in K-12 classrooms from 2018 to 2023: Topics, strategies, and learning outcomes. Computers and Education: Artificial Intelligence, 6(100211), 100211. https://doi.org/10.1016/j.caeai.2024.100211
  • Li, M. (2024). Integrating Artificial Intelligence in primary mathematics education: Investigating internal and external influences on teacher adoption. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-024-10515-w
  • Lim, W. M. (2024). What is qualitative research? An overview and guidelines. Australasian Marketing Journal (AMJ). https://doi.org/10.1177/14413582241264619
  • Lin, X.-F., Shen, W., Huang, S., Wang, Y., Zhou, W., Ling, X., & Li, W. (2025). Exploring Chinese teachers’ concerns about teaching artificial intelligence: the role of knowledge and perceived social good. Asia Pacific Education Review. https://doi.org/10.1007/s12564-024-10034-x
  • Mah, C., Walker, H., Phalen, L., Levine, S., Beck, S. W., & Pittman, J. (2024). Beyond CheatBots: Examining tensions in teachers’ and students’ perceptions of cheating and learning with ChatGPT. Education Sciences, 14(5), 500. https://doi.org/10.3390/educsci14050500
  • Mansfield, K. L., Ghai, S., Hakman, T., Ballou, N., Vuorre, M., & Przybylski, A. K. (2025). From social media to artificial intelligence: improving research on digital harms in youth. The Lancet. Child & Adolescent Health, 9(3), 194–204. https://doi.org/10.1016/s2352-4642(24)00332-8
  • 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), 100195. https://doi.org/10.1016/j.caeai.2023.100195
  • McGehee, N. (2024). Breaking barriers: A Meta-Analysis of educator acceptance of AI technology in education. Michigan Virtual. https://michiganvirtual.org/research/publications/breaking-barriers-a-meta-analysis-of-educator-acceptance-of-ai-technology-in-education/
  • Meylani, R. (2024). Artificial Intelligence in the education of teachers: A qualitative synthesis of the cutting-edge research literature. Journal of Computer and Education Research, 12(24), 600–637. https://doi.org/10.18009/jcer.1477709
  • Miao, F; Holmes, W. (2021). Artificial intelligence and education. Guidance for policy-makers. United Nations Educational, Scientific and Cultural Organization (UNESCO): Paris, France.
  • Mintz, J., Holmes, W., Liu, L., & Perez-Ortiz, M. (2023). Artificial intelligence and K-12 education: Possibilities, pedagogies and risks. Computers in the Schools: Interdisciplinary Journal of Practice, Theory, and Applied Research, 40(4), 325–333. https://doi.org/10.1080/07380569.2023.2279870
  • Molefi, R. R., Ayanwale, M. A., Kurata, L., & Chere-Masopha, J. (2024). Do in-service teachers accept artificial intelligence-driven technology? The mediating role of school support and resources. Computers and Education Open, 6 (100191), 100191. https://doi.org/10.1016/j.caeo.2024.100191
  • Nabizadeh, A. H., Leal, J. P., Rafsanjani, H. N., & Shah, R. R. (2020). Learning path personalization and recommendation methods: A survey of the state-of-the-art. Expert Systems with Applications, 159(113596), 113596. https://doi.org/10.1016/j.eswa.2020.113596
  • Nja, C. O., Idiege, K. J., Uwe, U. E., Meremikwu, A. N., Ekon, E. E., Erim, C. M., Ukah, J. U., Eyo, E. O., Anari, M. I., & Cornelius-Ukpepi, B. U. (2023). Adoption of artificial intelligence in science teaching: From the vantage point of the African science teachers. Smart Learning Environments, 10(1). https://doi.org/10.1186/s40561-023-00261-x
  • Nur S. Z. & Melor M. Y. (2023). Teachers’ perceptions and continuance usage intention of Artificial Intelligence technology in TESL. International Journal of Multidisciplinary Research And Analysis, 06(05). https://doi.org/10.47191/ijmra/v6-i5-34
  • Oh, S.-Y., & Ahn, Y. (2024). Exploring teachers’ perception of artificial intelligence: The Socio-emotional deficiency as opportunities and challenges in human-AI complementarity in K-12 education. In Lecture Notes in Computer Science (pp. 439–447). Springer Nature Switzerland.
  • Örtegren, A., & Velander, J. (2023). Artificial intelligence in Nordic K-12 education : implications of materials and resources for digital citizenship formation. NERA Conference 2023, Oslo, Norway, March 15-17, 2023. https://umu.diva-portal.org/smash/record.jsf?pid=diva2%3A1745127&dswid=9115
  • Patac, L. P., & Patac, A. V., Jr. (2025). Using ChatGPT for academic support: Managing cognitive load and enhancing learning efficiency – A phenomenological approach. Social Sciences & Humanities Open, 11(101301), 101301. https://doi.org/10.1016/j.ssaho.2025.101301
  • Pedro, F., Subosa, M., Rivas, A. and Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000366994
  • Pham, S. T. H., & Sampson, P. M. (2022). The development of artificial intelligence in education: A review in context. Journal of Computer Assisted Learning, 38(5), 1408–1421. https://doi.org/10.1111/jcal.12687
  • Pitrella, V. et al. (2024). Artificial intelligence for personalized learning in K-12 education. A scoping review. In: Casalino, G., et al. Higher Education Learning Methodologies and Technologies Online. HELMeTO 2023. Communications in Computer and Information Science, vol 2076. Springer, Cham. https://doi.org/10.1007/978-3-031-67351-1_25
  • Rakap, S., & Balikci, S. (2024). Enhancing IEP goal development for preschoolers with autism: A preliminary study on ChatGPT integration. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-024-06343-0
  • Ray Pörn, Mats Braskén, Mattias Wingren, & Sören Andersson. (2024). Attitudes towards and Expectations on the Role of Artificial Intelligence in the Classroom among Digitally Skilled Finnish K-12 Mathematics Teachers. LUMAT: International Journal on Math, Science and Technology Education, 12(3), 53–77. https://doi.org/10.31129/LUMAT.12.3.2102
  • Republic of Turkey Ministry of National Education (2024). Policy brief for artificial intelligence in education: Lessons from international forum of artificial intelligence in education. Republic of Turkey Ministry of National Education Directorate General for Innovation and Educational Technologies. Ankara.
  • Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599. https://doi.org/10.1007/s40593-016-0110-3
  • Ruiz Viruel, S., Sánchez Rivas, E., & Ruiz Palmero, J. (2025). The role of artificial intelligence in project-based learning: Teacher perceptions and pedagogical implications. Education Sciences, 15(2), 150. https://doi.org/10.3390/educsci15020150
  • Salha, S., Mousa, A., & Khayat, S. (2024). Artificial intelligence in education (AIED) policies in school context: A mixed approach research. Leadership and Policy in Schools, 1–19. https://doi.org/10.1080/15700763.2024.2443675
  • Savolainen, R. (2016). Information seeking and searching strategies as plans and patterns of action: A conceptual analysis. The Journal of Documentation72(6), 1154–1180. https://doi.org/10.1108/jd-03-2016-0033
  • Seo, K., Yoo, M., Dodson, S., & Jin, S.-H. (2024). Augmented teachers: K–12 teachers’ needs for artificial intelligence’s complementary role in personalized learning. Journal of Research on Technology in Education, 1–18. https://doi.org/10.1080/15391523.2024.2330525
  • Skolverket [the Swedish National Agency for Education] (2022). Läroplan för grundskolan, förskoleklassen och fritidshemmet. [Curriculum for elementary school, preschool and out of school care] https://www.skolverket.se/undervisning/grundskolan/laroplan-och-kursplaner-for-grundskolan/laroplan-lgr22-for-grundskolan-samt-for-forskoleklassen-och-fritidshemmet
  • Small, G. W., Lee, J., Kaufman, A., Jalil, J., Siddarth, P., Gaddipati, H., Moody, T. D., & Bookheimer, S. Y. (2020). Brain health consequences of digital technology use. Dialogues in Clinical Neuroscience, 22(2), 179–187. https://doi.org/10.31887/dcns.2020.22.2/gsmall
  • Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
  • Sperling, K., McGrath, C., Stenliden, L., Åkerfeldt, A., & Heintz, F. (2023). Mapping AI literacy in teacher education. International Symposium on Digital Transformation . https://open.lnu.se/index.php/isdt/article/view/3744
  • Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Sage.
  • Su, J., Zhong, Y., & Ng, D. T. K. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence, 3(100065), 100065. https://doi.org/10.1016/j.caeai.2022.100065
  • Taheri, A., RahimiZadeh, K., & Rao, R. V. (2021). An efficient balanced teaching-learning-based optimization algorithm with individual restarting strategy for solving global optimization problems. Information Sciences, 576, 68–104. https://doi.org/10.1016/j.ins.2021.06.064
  • Tan, X., Cheng, G., & Ling, M. H. (2025). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education: Artificial Intelligence, 8(100355), 100355. https://doi.org/10.1016/j.caeai.2024.100355
  • Tekin, Ö. G. (2024). Factors affecting teachers' acceptance of artificial intelligence technologies: Analyzing teacher perspectives with structural equation modeling. Instructional Technology and Lifelong Learning, 5(2), 399 - 420. https://doi.org/10.52911/itall.1532218
  • 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
  • Tran, T. T. T. (2025). Enhancing EFL writing revision practices: The impact of AI- and teacher-generated feedback and their sequences. Education Sciences, 15(2), 232. https://doi.org/10.3390/educsci15020232
  • Uygun, D. (2024). Teachers’ perspectives on artificial intelligence in education. Advances in Mobile Learning Educational Research, 4(1), 931–939. https://doi.org/10.25082/amler.2024.01.005
  • Van Roy, V., Rossetti, F., Perset, K. and Galindo-Romero, L., AI Watch (2021). National strategies on Artificial Intelligence: A European perspective. Publications Office of the European Union, https://dx.doi.org/10.2760/069178
  • Velander, J., Taiye, M. A., Otero, N., & Milrad, M. (2024). Artificial Intelligence in K-12 Education: eliciting and reflecting on Swedish teachers’ understanding of AI and its implications for teaching & learning. Education and Information Technologies, 29(4), 4085–4105. https://doi.org/10.1007/s10639-023-11990-4
  • Viberg, O., Cukurova, M., Feldman-Maggor, Y., Alexandron, G., Shirai, S., Kanemune, S., Wasson, B., Tømte, C., Spikol, D., Milrad, M., Coelho, R., & Kizilcec, R. F. (2024). What explains teachers’ trust in AI in education across six countries? International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00433-x
  • Wang, K., Chai, C.-S., Liang, J.-C., & Sang, G. (2024). Exploring teachers’ behavioural intentions to design artificial intelligence-assisted learning in Chinese K–12 education. Technology Pedagogy and Education, 33(5), 629–645. https://doi.org/10.1080/1475939x.2024.2369241
  • Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252(124167), 124167. https://doi.org/10.1016/j.eswa.2024.124167
  • Whalen, J., Grube, W., Xu, C., & Torrey Trust. (2025). K-12 educators’ reactions and responses to ChatGPT and GenAI during the 2022–2023 school year. TechTrends : For Leaders in Education & Training, 69(1), 125–137. https://doi.org/10.1007/s11528-024-01028-y
  • World Economic Forum. (2024). Shaping the future of learning: The role of AI in education 4.0. Available online: https://www.weforum.org/publications/shaping-the-future-of-learning-the-role-of-ai-in-education-4-0/
  • Xie, B., Sarin, P., Wolf, J., Garcia, R. C. C., Delaney, V., Sieh, I., Fuloria, A., Dennison, D. V., Bywater, C., & Lee, V. R. (2024). Co-designing AI education curriculum with cross-disciplinary high school teachers. Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 38(21), 23146–23154.
  • Yau, K. W., Chai, C. S., Chiu, T. K. F., Meng, H., King, I., & Yam, Y. (2023). A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools. Education and Information Technologies, 28(1), 1041–1064. https://doi.org/10.1007/s10639-022-11161-x
  • Yim, I. H. Y., & Wegerif, R. (2024). Teachers’ perceptions, attitudes, and acceptance of artificial intelligence (AI) educational learning tools: An exploratory study on AI literacy for young students. Future in Educational Research, 2(4), 318–345. https://doi.org/10.1002/fer3.65
  • Yuan, S., He, T., Huang, H., Hou, R., & Wang, M. (2020). Automated Chinese essay scoring based on deep learning. CMC-Computers Materials & Continua, 65(1), 817–833.
  • Yue, M., Jong, M. S.-Y., & Ng, D. T. K. (2024). Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, 29(15), 19505–19536. https://doi.org/10.1007/s10639-024-12621-2
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Details

Primary Language Turkish
Subjects Educational Sociology
Journal Section Research Article
Authors

İbrahim Can Güngör 0000-0002-4267-5669

Talip Öztürk 0000-0003-3543-0468

Publication Date June 30, 2025
Submission Date March 18, 2025
Acceptance Date May 19, 2025
Published in Issue Year 2025 Volume: 12 Issue: 1

Cite

ISNAD Güngör, İbrahim Can - Öztürk, Talip. “Öğretmenler Yapay Zekâyı Benimsedi Mi? K-12 Eğitim Sistemlerinden Öğretmen Deneyimlerinin Bir Sentezi”. Recep Tayyip Erdoğan Üniversitesi Sosyal Bilimler Dergisi 12/1 (June 2025), 70-100. https://doi.org/10.34086/rteusbe.1660052.
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