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- Acet, İ., Şensiz, N., Bilir, S., Ciğerci, Ü., Çirişoğlu, M., & Yeşil, S. (2024). İlkokul öğretmenlerinin yapay zekâya ilişkin tutumlarının çeşitli değişkenler açısından incelenmesi: Kastamonu örneği. International Journal of Social and Humanities Sciences Research (JSHSR), 11(112), 2055-2062
- Açıkgül, K., & Sad, S. N. (2026). Educators' acceptance and use of AI software: UTAUT2 model. SAGE Open, 16(1), 1–19. https://doi.org/10.1177/21582440251413449
- Aksakal, Ş., Emre, İ., & Özbek, M. (2024). Sınıf öğretmenlerinin yapay zekâya ilişkin tutumlarının belirlenmesi. Eğitimde Yeni Yaklaşımlar Dergisi, 7(1), 1-13.
- Allehyani, S. H., & Algamdi, M. A. (2023). Digital competences: Early childhood teachers' beliefs and perceptions of ChatGPT application in teaching English as a second language (ESL). International Journal of Learning, Teaching and Educational Research, 22(11), 216–233.
- Ang, L., & Eisend, M. (2018). Single versus multiple measurement of attitudes: A meta-analysis of advertisingstudies validates the single-item measure approach. Journal of Advertising Research, 58(2), 218-227.
- Arıkanoğlu, M., & Yaman Lesinger, F. Y. (2024). Okul öncesi öğretmenlerinin yapay zekâya yönelik tutumlarının belirlenmesi (KKTC örneği). International Journal of Su-Ay Development Association (IJOSDA), 3(2), 80–91.
- Baker, T., & Smith, L. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Nesta. https://media.nesta.org.uk/documents/Future_of_AI_and_education_v5_WEB.pdf
- Banaz, E., & Maden, S. (2024). Türkçe öğretmen adaylarının yapay zekâ tutumlarının farklı değişkenler açısından incelenmesi. Trakya Eğitim Dergisi, 14(2), 1173-1180.
- Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
- Behera, C., & Acharya, A. K. (2025). Transforming early childhood education through digital innovation: A comprehensive review of evidence and key challenges. TPM – Testing, Psychometrics, Methodology in Applied Psychology, 32(S3), 2288–2297.
- Bergdahl, N., & Sjöberg, J. (2025). Attitudes, perceptions and AI self-efficacy in K-12 education. Computers and Education: Artificial Intelligence, 8, 100358.
- Berne, J., Doss, C. J., & Shapiro, A. (2025). Pre-K teachers are optimistic about educational technology, though current use varies widely: Findings from the American Public School Pre-K Teacher Survey (RR A4412-2). RAND Corporation. https://doi.org/10.7249/RRA4412-2
- Bozer Özsaraç, E. N., & Ergin, E. (2025). What drives teachers' use of AI in preschool education? A motivational perspective based on Expectancy-Value Theory. International Journal of Current Educational Studies (IJCES), 4(2), 1–29. https://doi.org/10.46328/ijces.191
- Bozkurt, A. (2023). ChatGPT, üretken yapay zeka ve algoritmik paradigma değişikliği. Alanyazın, 4(1), 63–72. https://doi.org/10.59320/alanyazin.1283282
- Büyüköztürk, Ş. (2017). Sosyal bilimler için veri analizi el kitabı. Pegem Akademi.
- 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), 89–92
- Chiu, T. K. F., Ahmad, Z., & Çoban, M. (2025). Development and validation of teacher artificial intelligence (AI) competence self-efficacy (TAICS) scale. Education and Information Technologies, 30(5), 6667–6685. https://doi.org/10.1007/s10639-024-13094-z
- Collie, R. J., Martin, A. J., & Gasevic, D. (2024). Teachers' generative AI self-efficacy, valuing, and integration at work: Examining job resources and demands. Computers and Education: Artificial Intelligence, 7 100333. https://doi.org/10.1016/j.caeai.2024.100333
- Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications.
- Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications.
- Çayak, S. (2024). Investigating the relationship between teachers' attitudes toward artificial intelligence and their artificial intelligence literacy. Journal of Educational Technology & Online Learning, 7(4), 367 383. https://doi.org/10.31681/jetol.1490307
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
- Demirdağ, S., Ünver, İ. K., & Gürez, I. (2025). Öğretmenlerin yapay zekâ tutum ölçeğinin geliştirilmesi: Bir geçerlilik ve güvenirlik çalışması. Asya Studies, 9(33), 1-22.
- Dringó-Horváth, I., Rajki, Z., & T. Nagy, J. (2025). University teachers' digital competence and AI literacy: Moderating role of gender, age, experience, and discipline. Education Sciences, 15(7), 868.
- Dwivedi, Y. K., Rana, N. P., Chen, H., & Williams, M. D. (2011, September). A meta-analysis of the unified theory of acceptance and use of technology (UTAUT). In IFIP international working conference on governance and sustainability in information systems-managing the transfer and diffusion of it (pp. 155-170). Berlin, Heidelberg: Springer Berlin Heidelberg.
- Erol, M., Canbeldek Erol, M., Erol, A., & Gök Çolak, F. (2025). Exploring the relationship between teachers' AI attitudes, AI self-efficacy, and AI technological pedagogical content knowledge. European Journal of Education, 60(4), e70332.
- Field, A. (2013). Discovering statistics using SPSS (4th ed.). Sage Publications
- Galindo-Domínguez, H., Delgado, N., Losada, D., & Etxabe, J. M. (2024). 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.
- George, D., & Mallery, P. (2024). IBM SPSS statistics 29 step by step: A simple guide and reference. Routledge. https://doi.org/10.4324/9781032622156
- Gürkan, S. N., Çiçek Taş, C., Dere, F., & Güven, G. (2025, 18–20 Eylül). Okul öncesi eğitimde yapay zekâ: Öğretmenlerin kabulü, okuryazarlığı ve görüşleri üzerine bir inceleme [Sözlü bildiri]. XI. Uluslararası TURKCESS Eğitim ve Sosyal Bilimler Kongresi, Hasan Kalyoncu Üniversitesi, Gaziantep, Türkiye.
- Herzallah, A. M., & Makaldy, R. (2025). Technological self-efficacy and sense of coherence: Key drivers in teachers' AI acceptance and adoption. Computers and Education: Artificial Intelligence, 8, 100377.
- Karasar, N. (2023). Bilimsel araştırma yöntemi. Nobel Yayıncılık.
- Kardeş, S., Uygun, N., & Terim Türkmen, T. (2025). Attitudes of preschool teachers towards artificial intelligence. Southeast Asia Early Childhood Journal, 14(1), 120–135. https://doi.org/10.37134/saecj.vol14.1.9.2025
- Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Demir Kaya, M. (2024). The roles of personality traits, AI anxiety, and demographic factors in attitudes toward artificial intelligence. International Journal of Human–Computer Interaction, 40(2), 497–514. https://doi.org/10.1080/10447318.2022.2151730
- Kewalramani, S., Palaiologou, I., Dardanou, M., Allen, K. A., & Phillipson, S. (2021). Using robotic toys in early childhood education to support children's social and emotional competencies. Australasian Journal of Early Childhood, 46(4), 355–369. https://doi.org/10.1177/18369391211056668
- Kırkıç, K., & Çetinkaya, F. (2020). The relationship between preschool teachers' self-efficacy beliefs and their teaching attitudes. International Journal of Evaluation and Research in Education (IJERE), 9(4), 807 815. https://doi.org/10.11591/ijere.v9i4.20670
- Kong, S. C., Wang, Y. Q., & Lai, M. (2024). Examining teachers' behavioural intention of using generative artificial intelligence tools for teaching and learning based on the extended technology acceptance model. Computers and Education: Artificial Intelligence, 7, 100328. https://doi.org/10.1016/j.caeai.2024.100328
- Kölemen, E. B., & Yıldırım, B. (2025). A new era in early childhood education (ECE): Teachers' opinions on the application of artificial intelligence. Education and Information Technologies, 30(12), 17405–17446. https://doi.org/10.1007/s10639-025-13478-9
- Küçükkara, M. F., Ünal, M., & Sezer, T. (2024). Okul öncesi eğitimi öğretmenlerinin yapay zekâya ilişkin görüşleri. Temel Eğitim Araştırmaları Dergisi, 4(1), 17–28. https://doi.org/10.55008/te-ad.1431142
- Mart, M., & Kaya, G. (2024). Okul öncesi öğretmen adaylarının yapay zekâya yönelik tutumları ve yapay zekâ okur yazarlığı arasındaki ilişkinin incelenmesi. Edutech Research, 2(1), 91–109.
- Pellas, N. (2023). The effects of generative AI platforms on undergraduates' narrative intelligence and writing self-efficacy. Education Sciences, 13(11), 1155.
- Polyportis, A. (2026). Exploring the Intention-Behaviour Gap in Artificial Intelligence adoption: the case study of students' ChatGPT usage in Dutch higher education. Computers in Human Behavior: Artificial Humans, 100266.
- Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
- Sáez-Velasco, S., Alaguero-Rodríguez, M., Rodríguez-Cano, S., & Delgado-Benito, V. (2025). Students' attitudes towards AI and how they perceive the effectiveness of AI in designing video games. Sustainability, 17(7), 3096.
- Sal, S., Çelik, İ., Tepeli, K., Kudubeş, A. A., & Bektaş, M. (2025). Çocuk gelişimi bölümü öğrencilerinin dijital okuryazarlık düzeylerinin yapay zekaya yönelik genel tutumlarına etkisinin incelenmesi. Sürekli Tıp Eğitimi Dergisi, 34(5), 366-375.
- Salaam, M. A. (2023). Examining the implementation of artificial intelligence in early childhood education settings in Ghana: Educators' attitudes and perceptions towards its long-term viability. American Journal of Education and Technology, 2(4), 36–49.
- Schepman, A., & Rodway, P. (2020). Initial validation of the general attitudes towards Artificial Intelligence Scale. Computers in Human Behavior Reports, 1, 100014. https://doi.org/10.1016/j.chbr.2020.100014
- Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
- Seyrek, M., Yıldız, S., Emeksiz, H., Şahin, A., & Türkmen, M. T. (2024). Öğretmenlerin eğitimde yapay zekâ kullanımına yönelik algıları. International Journal of Social and Humanities Sciences Research (JSHSR), 11(106), 845–856. https://doi.org/10.5281/zenodo.11113077
- Solamillo, K. A. (2025). Artificial Intelligence Anxiety and Attitudes among Pre-Service and In-Service Physical Education Teachers: Addressing an Underserved Field in AI Education. LatIA, (3), 245.
- Staddon, R. V. (2020). Bringing technology to the mature classroom: age differences in use and attitudes. International Journal of Educational Technology in Higher Education, 17(1), 11.
- Su, J., Ng, D. T. K., & Chu, S. K. W. (2023). Artificial intelligence (AI) literacy in early childhood education: The challenges and opportunities. Computers and Education: Artificial Intelligence, 4, 100124. https://doi.org/10.1016/j.caeai.2023.100124
- 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. https://doi.org/10.1016/j.caeai.2024.100355
- UNESCO. (2024). AI competency framework for teachers. United Nations Educational, Scientific and Cultural Organization
- Uzun, Y. (2025). Eğitimde dijital dönüşüm: Sınıf öğretmeni adaylarının yapay zekâya yönelik tutumları. International Journal of Education Technology and Scientific Researches (IJETSAR), 10(31), 246–261.
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
- Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
- Verster, J. C., Sandalova, E., Garssen, J., & Bruce, G. (2021). The use of single-item ratings versus traditional multiple-item questionnaires to assess mood and health. European Journal of Investigation in Health, Psychology and Education, 11(1), 183-198.
- Zhang, S., & Colvin, K. (2024). Comparison of different reliability estimation methods for single item assessment: a simulation study. Frontiers in Psychology, 15, 1482016.