Exploring the Relationship Between Teachers' Artificial Intelligence Awareness and Computational Thinking Skills: Differences Across Sociodemographic and Professional Variables

Yıl 2025, Sayı: 66, 4394 - 4431, 29.12.2025

Muhammet Remzi Karaman" , İdris Göksu

https://doi.org/10.53444/deubefd.1779666

Öz

This study aimed to determine teachers' level of artificial intelligence (AI) awareness and computational thinking (CT) skills. We also examined whether AI awareness and CT skills were related and how these variables differed across various sociodemographic and professional variables. This study, conducted in Turkey during the 2024-2025 academic year using a descriptive correlational survey design, involved 981 teachers (female = 514, male = 467) who volunteered to participate. Data were analysed using descriptive statistics, independent samples t-test, one-way analysis of variance (ANOVA), and Pearson correlation. The analysis indicated that teachers' AI awareness and CT skills were above average. Furthermore, significant differences in teachers' AI awareness and CT skills were revealed based on sociodemographic and professional variables. A positive statistically significant correlation was found between AI awareness and CT skills. Based on the results, we made recommendations for researchers and practitioners.

Anahtar Kelimeler

Computational thinking , artificial intelligence awareness , AI , 21st century skills

Etik Beyan

The Scientific Research and Publication Ethics Committee of Mardin Artuklu University approved this study (Number=133090, 2024/2). All stages of the study were conducted according to the principles of scientific research and publication ethics. Participants' participation was voluntary, and the data obtained were kept confidential. Furthermore, the thesis was uploaded to the scientific plagiarism detection program used by Mardin Artuklu University and declared plagiarism-free.

Teşekkür

This study is based on the master's thesis "An examination of teachers’ artificial intelligence awareness and computational thinking skills in terms of various variables," which was carried out under the supervision of the second author at Mardin Artuklu University and was approved and accepted in June 2025. The authors thank the teachers who participated in this study and are grateful to the academic staff who served on the master’s thesis committee for their valuable contributions.

Öğretmenlerin Yapay Zeka Farkındalığı ile Bilgisayarca Düşünme Becerileri Arasındaki İlişkinin incelenmesi: Sosyodemografik ve Mesleki Değişkenlere Göre Farklılıklar

Öz

Bu çalışmanın amacı öğretmenlerin yapay zekâ (YZ) farkındalığı ve bilgisayarca düşünme (BD) beceri düzeylerini tespit etmektir. Ayrıca, YZ farkındalığı ve BD becerilerinin ilişkili olup olmadığını ve bu değişkenlerin çeşitli sosyodemografik ve mesleki değişkenlere göre farklılaşıp farklılaşmadığını ortaya koymaktır. İlişkisel tarama modeliyle Türkiye’de yürütülen bu araştırmaya, 2024-2025 akademik yılında gönüllü katılım esasına dayalı olarak 981 öğretmen (kadın = 514, erkek = 467) katılım sağlamıştır. Verilerin analizinde betimsel istatistikler, bağımsız örneklem t-testi, tek yönlü varyans analizi (ANOVA) ve Pearson Korelasyon analizi yapılmıştır. Analiz sonuçları, öğretmenlerin YZ farkındalık düzeylerinin ve BD becerilerinin orta düzeyde olduğunu göstermiştir. Ayrıca, sosyo-demografik değişkenlere göre öğretmenlerin AI farkındalığı ve BD becerilerinde anlamlı farklılıklar bulunmuştur. YZ farkındalığı ile BD becerileri arasında pozitif yönde istatistiki olarak anlamlı ilişki tespit edilmiştir. Sonuçlara dayanarak, araştırmacılar ve uygulayıcılar için önerilerde bulunduk.

Anahtar Kelimeler

Bilgisayarca düşünme , yapay zeka farkındalığı , YZ , 21. yüzyıl becerileri

Kaynakça

• Abbak, Y. (2018). Öğretmenlerin yaşam boyu öğrenme yeterlikleri ile yenilikçilik düzeylerinin incelenmesi [Investigation of levels innovations and lifelong learning competencies of teachers] (Thesis no. 524388) [Master's thesis, Erciyes University]. https://tez.yok.gov.tr/
• Ağırtaş, A., & Çavuş, H. (2022). Üniversitelerde görev yapan öğretim elemanlarının acil uzaktan eğitim dönemindeki dijitalleşme durumlarının incelenmesi [Examining the digitization status of faculty members in universities in emergency remote education]. Çağ University Journal of Social Sciences, 19(1), 36–52.
• Ahmad, M., Subih, M., Fawaz, M., Alnuqaidan, H., Abuejheisheh, A., Naqshbandi, V., & Alhalaiqa, F. (2024). Awareness, benefits, threats, attitudes, and satisfaction with AI tools among Asian and African higher education staff and students. Journal of Applied Learning and Teaching, 7(1). https://doi.org/10.37074/jalt.2024.7.1.10
• Akdeniz, M., & Özdinç, F. (2021). Eğitimde yapay zekâ konusunda Türkiye adresli çalışmaların incelenmesi [Examination of Turkey addressing studies regarding artificial intelligence in education]. YYU Journal of Education Faculty, 18(1), 912–932. https://doi.org/10.33711/yyuefd.938734
• Akkol, S., & Balkan, Z. E. (2024). Yapay zekânın ilkokul öğretmenleri tarafından kullanımı: 50 öğretmen üzerinde uygulama [The use of artificial intelligence by primary school teachers: A study on 50 teachers]. Social Sciences Studies Journal, 10(10), 1754–1770.
• Albarracín-Vivo, D., Encabo-Fernández, E., Jerez-Martínez, I., & Hernández-Delgado, L. (2024). Gender differences and critical thinking: A study on the written compositions of primary education students. Societies, 14(7), Article 118. https://doi.org/10.3390/soc14070118
• Aldawsari, R. (2024). Role of artificial intelligence in education from the perspectives of teachers. Library Progress International, 44(3), 17740–17753.
• Alkhatlan, A., & Kalita, J. (2019). Intelligent tutoring systems: A comprehensive historical survey with recent developments. International Journal of Computer Applications, 18, 43.
• Ansen Gürkan, C., Atmaca, K., Atmaca, A., Yalçın, D., & Canıbek, M. (2025). Yapay zeka destekli kişiselleştirilmiş öğrenmenin ilkokul öğrencileri üzerine etkileri [The effects of artificial intelligence supported personalized learning on primary school students]. International QMX Journal, 4(3), 448-460. https://doi.org/10.5281/zenodo.15071255
• Bagheri, F., & Ghanizadeh, A. (2016). Critical thinking and gender differences in academic self-regulation in higher education. Journal of Applied Linguistics and Language Research, 3(3), 133–145.
• Banaz, E., & Demirel, O. (2024). Türkçe öğretmen adaylarının yapay zekâ okuryazarlıklarının farklı değişkenlere göre incelenmesi [Investigation of artificial intelligence literacy of prospective Turkish teachers according to different variables]. The Journal of Buca Faculty of Education, 60, 1516–1529.
• Banaz, E., & Maden, S. (2024). Türkçe öğretmen adaylarının yapay zekâ tutumlarının farklı değişkenler açısından incelenmesi [An investigation of Turkish pre-service teachers' attitudes towards artificial intelligence in terms of different variables]. Trakya Journal of Education, 14(2), 1173–1180. https://doi.org/10.24315/tred.1430419
• Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning & Leading with Technology, 38(6), 20–23.
• Breslyn, W., & McGinnis, J. R. (2019). Investigating preservice elementary science teachers’ understanding of climate change from a computational thinking systems perspective. Eurasia Journal of Mathematics, Science and Technology Education, 15(6), Article em1696. https://doi.org/10.29333/ejmste/103566
• Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., Henke, N., & Trench, M. (2017, June). Artificial intelligence: The next digital frontier? McKinsey Global Institute.
• Bundy, A. (2007). Computational thinking is pervasive. Journal of Scientific and Practical Computing, 1(2), 67–69.
• Büyüköztürk, Ş., Kılıç Çakmak, E., Akgün, Ö. E., Karadeniz, Ş., & Demirel, F. (2024). Eğitimde bilimsel araştırma yöntemleri (36th ed.). Pegem Akademi.
• Celik, I. (2023). Exploring the determinants of artificial intelligence (AI) literacy: Digital divide, computational thinking, cognitive absorption. Telematics and Informatics, 83, Article 102026. https://doi.org/10.1016/j.tele.2023.102026
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences, second edition (2nd ed.). Lawrence Erlbaum Associates.
• Cojean, S., Brun, L., Amadieu, F., & Dessus, P. (2023). Teachers’ attitudes towards AI: what is the difference with non-AI technologies? Proceedings of the Annual Meeting of the Cognitive Science Society, 45(45), 2069–2076.
• Coşkun, F., & Gülleroğlu, H. D. (2021). Yapay zekânın tarih içindeki gelişimi ve eğitimde kullanılması [Development of artificial intelligence in history and its usage in education]. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Dergisi, 54(3), 947–966. https://doi.org/10.30964/auebfd.916220
• Crompton, H., & Burke, D. (2024). The nexus of ISTE standards and academic progress: A mapping analysis of empirical studies. TechTrends, 68, 711–722. https://doi.org/10.1007/s11528-024-00973-y
• Csizmadia, A., Curzon, P., Humphreys, S., Ng, T., Selby, C., & Woollard, J. (2015). Computational thinking - a guide for teachers. https://www.computingatschool.org.uk/media/kscbloob/computationalthinking.pdf
• Çam, M. B., Çelik, N., Turan Güntepe, E., & Durukan, Ü. G. (2021). Öğretmen adaylarının yapay zekâ teknolojileri ile ilgili farkındalıklarının belirlenmesi [Determining teacher candidates’ awareness of artificial intelligence technologies]. Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18(48), 263–285.
• Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2025). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları (8th ed.). Pegem Akademi.
• Dagienė, V., Jevsikova, T., Stupurienė, G., & Juškevičienė, A. (2022). Teaching computational thinking in primary schools: Worldwide trends and teachers’ attitudes. Computer Science and Information Systems, 19(1), 1–24. https://doi.org/10.2298/CSIS201215033D
• Dai, Y., Chai, C. S., Lin, P. Y., Jong, M. S. Y., Guo, Y., & Qin, J. (2020). Promoting students’well-being by developing their readiness for the artificial intelligence age. Sustainability, 12(16), Article 6597. https://doi.org/10.3390/su12166597
• Demir, B., & Beyazhançer, R. (2024). İlköğretim matematik öğretmeni adaylarının yapay zekâ öz-yeterliklerinin bazı değişkenler açısından incelenmesi [Investigation of artificial intelligence self-efficacy of prospective elementary mathematics teachers in terms of some variables]. International Journal of Social and Humanities Sciences Research, 11(113), 2393–2398. https://doi.org/10.5281/zenodo.14279357
• Demirtaş, H., & Dönmez, B. (2008). Secondary school teachers’ perceptions about their problem solving abilities. İnönü University Journal of the Faculty of Education, 9(16), 177–198.
• Du, H., Sun, Y., Jiang, H., Islam, A. Y. M. A., & Gu, X. (2024). Exploring the effects of AI literacy in teacher learning: an empirical study. Humanities and Social Sciences Communications, 11(1), Article 559. https://doi.org/10.1057/s41599-024-03101-6
• Eker, C., & Halıcı Gürbüz, S. (2024). Matematik öğretmenlerinin matematik dersinde yapay zekâ kullanımına yönelik yeterlilik algıları [Mathematics teachers' perceptions of competence regarding the use of artificial intelligence in mathematics lessons]. Journal of Social, Humanities and Administrative Sciences, 7(7), 513– 528. https://doi.org/10.26677/TR1010.2024.1425
• Erdoğdu, F., & Çakır, O. (2024). Öğretmen adaylarının yapay zekâ okuryazarlıklarının ve yapay zekâya ilişkin algılarının belirlenmesi [Determining teacher candidates' artificial intelligence literacy and their perceptions of artificial intelligence]. Uluslararası Türk Kültür Coğrafyasında Sosyal Bilimler Dergisi, 9(2), 63–95. https://doi.org/10.55107/turksosbilder.1594635
• Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284. https://doi.org/10.1080/15391523.2010.10782551
• Fagerlund, J., Leino, K., Kiuru, N., & Niilo-Rämä, M. (2022). Finnish teachers’ and students’ programming motivation and their role in teaching and learning computational thinking. Frontiers in Education, 7, Article 948783. https://doi.org/10.3389/feduc.2022.948783
• Falloon, G. (2024). Advancing young students’ computational thinking: An investigation of structured curriculum in early years primary schooling. Computers and Education, 216, Article 105045. https://doi.org/10.1016/j.compedu.2024.105045
• Ferikoğlu, D., & Akgün, E. (2022). An investigation of teachers’ artificial intelligence awareness: A scale development study. Malaysian Online Journal of Educational Technology, 10(3), 215–231. https://doi.org/10.52380/mojet.2022.10.3.407
• Fodouop Kouam, A. W. (2024). The effectiveness of intelligent tutoring systems in supporting students with varying levels of programming experience. Discover Education, 3, Article 278. https://doi.org/10.1007/s44217-024-00385-3
• Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill.
• Fraillon, J., Ainley, J., Schulz, W., Friedman, T., & Duckworth, D. (2020). Preparing for life in a digital world: IEA international computer and information literacy study 2018 international report. Springer. https://doi.org/10.1007/978-3-030-38781-5
• Gaber, S. A., Shahat, H. A., Alkhateeb, I. A., Al Hasan, S. A., Alqatam, M. A., Almughyirah, S. M., & Kamel, M. K. (2023). Faculty members’ awareness of artificial ıntelligence and ıts relationship to technology acceptance and digital competencies at King Faisal University. International Journal of Learning, Teaching and Educational Research, 22(7), 473–496. https://doi.org/10.26803/ijlter.22.7.25
• Gasaymeh, A. M., & AlMohtadi, R. (2024). College of education students’ perceptions of their computational thinking proficiency. Frontiers in Education, 9, Article 1478666. https://doi.org/10.3389/feduc.2024.1478666
• Gignac, G. E., & Szodorai, E. T. (2024). Defining intelligence: Bridging the gap between human and artificial perspectives. Intelligence, 104, Article 101832. https://doi.org/10.1016/j.intell.2024.101832
• Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), Article 692. https://doi.org/10.3390/educsci13070692
• Guggemos, J. (2024). On the predictors of computational thinking and its relationship with artificial intelligence. In P. Isaias, D.G. Sampson, & D.Ifenthaler, D. (Eds), Artificial intelligence for supporting human cognition and exploratory learning in the digital age. Cognition and exploratory learning in the digital age (pp. 179–201). Springer, Cham. https://doi.org/10.1007/978-3-031-66462-5_10
• Güleç, S. (2020). Problem solving skills in social studies education and problem solving skills of social studies teachers. Journal of Education and Training Studies, 8(3), 48-55. https://doi.org/10.11114/jets.v8i3.4686
• Gülel, S., Sargın, A., & Çetin, H. İ. (2023). Yapay zekâ eğitici eğitimi. Eurasian Education & Literature Journal, 17, 64–73. https://doi.org/10.17740/eas.edu.2023-v17-05
• Güneyli, A., Burgul, N. S., Dericioğlu, S., Cenkova, N., Becan, S., Şimşek, Ş. E., & Güneralp, H. (2024). Exploring teacher awareness of artificial ıntelligence in education: A case study from Northern Cyprus. European Journal of Investigation in Health, Psychology and Education, 14(8), 2358–2376. https://doi.org/10.3390/ejihpe14080156
• Hamerski, P. C., McPadden, D., Caballero, M. D., & Irving, P. W. (2022). Students’ perspectives on computational challenges in physics class. Physical Review Physics Education Research, 18(2), Article 020109. https://doi.org/10.1103/PhysRevPhysEducRes.18.020109
• Iqbal Malik, S., Mathew, R., Moufaq Tawafak, R., & Khan, I. (2019). Gender difference in perceiving algorithmic thinking in an introductory programmıng course. EDULEARN19 Proceedings, 1, 8246–8254. https://doi.org/10.21125/edulearn.2019.2042
• ISTE. (2011). Operational definition of computational thinking for K-12 education. https://cdn.iste.org/www-root/Computational_Thinking_Operational_Definition_ISTE.pdf
• ISTE. (2024). ISTE computational thinking competencies. https://iste.org/standards/computational-thinking-competencies
• İçöz, S., & İçöz, E. (2024). Türkçe öğretmen adaylarının yapay zekâ uygulamalarına yönelik farkındalık düzeylerinin incelenmesi [Investigation of Turkish pre-service teachers' awareness levels towards artificial intelligence applications]. Ulusal Eğitim Dergisi, 4(3), 987–1001. https://doi.org/10.5281/zenodo.10909458
• Karaçaltı, C., Korkmaz, Ö., & Çakır, R. (2018). Examination of the students’ computational-critical thinking and problem-solving skills on their success of programming course. Amasya Education Journal, 7(2), 343–370.
• Karaman, M. R., & Goksu, İ. (2024). Are lesson plans created by ChatGPT more effective? An experimental study. International Journal of Technology in Education, 7(1), 107–127. https://doi.org/10.46328/ijte.607
• Kasinidou, M., Kleanthoys, S., & Otterbacher, J. (2025). Cypriot teachers’ digital skills and attitudes towards AI. Discover Education, 4, Article 1. https://doi.org/10.1007/s44217-024-00390-6
• Kaya, M., & Köseoğlu, Z. (2024). Geleceğin eğitimini şekillendirmek: Öğretmen yardımcısı yapay zekâ [Shaping future education: Teacher assistant artificial intelligence]. Pearson Journal of Social Sciences & Humanities, 8(29), 1555-1578. https://doi.org/10.5281/zenodo.13384238
• Koehler, M. J., Mishra, P., Akcaoglu, M., & Rosenberg, J. (2013). The technological pedagogical content knowledge framework for teachers and teacher educators. In ICT Integrated Teacher Education: A Resource Book (pp. 1–8). CEMCA (Commonwealth Educational Media Centre for Asia).
• Korkmaz, Ö. (2009). Öğretmenlerin eleştirel düşünme eğilim ve düzeyleri. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 10(1), 1–13.
• Korkmaz, Ö., Çakır, R., Özden, M. Y., Oluk, A., & Sarıoğlu, S. (2015). Bireylerin bilgisayarca düşünme becerilerinin farklı değişkenler açısından incelenmesi. Ondokuz Mayıs Üniversitesi Eğitim Fakültesi Dergisi, 34(2), 68–87. https://doi.org/10.7822/omuefd.34.2.5
• Korkmaz, Ö., Çakir, R., & Özden, M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in Human Behavior, 72, 558–569. https://doi.org/10.1016/j.chb.2017.01.005
• Köse, B., Radıf, H., Uyar, B., Baysal, İ., & Demirci, N. (2023). Öğretmen görüşlerine göre eğitimde yapay zekânın önemi [The importance of artificial intelligence in education according to teachers' views]. Journal of Social, Humanities and Administrative Sciences, 9(71), 4203–4209. http://dx.doi.org/10.29228/JOSHAS.74125
• Kutluca, A. Y. (2018). Öğretmen adaylarının problem çözme becerilerini yordayan değişkenlerin incelenmesi [The investigation of variables predicting prospective teachers' problem solving skills]. Asian Journal of Instruction, 6(1), 1–20.
• Lee, C., & Xiong, J. (2024). From keyboard to chatbot: An aı-powered integration platform with large-language models for teaching computational thinking for young children. ArXiv, 1, 1–26. http://arxiv.org/abs/2405.00750
• Liao, J., Zhong, L., Zhe, L., Xu, H., Liu, M., & Xie, T. (2024). Scaffolding computational thinking with ChatGPT. IEEE Transactions on Learning Technologies, 17, 1668–1682. https://doi.org/10.1109/TLT.2024.3392896
• Lin, S., & Wong, G. K. W. (2024). Gender differences in computational thinking skills among primary and secondary school students: A systematic review. Education Sciences, 14(7), Article 790. https://doi.org/10.3390/educsci14070790
• Liu, Y., Zhang, K., Li, Y., Yan, Z., Gao, C., Chen, R., Yuan, Z., Huang, Y., Sun, H., Gao, J., He, L., & Sun, L. (2024). Sora: A review on background, technology, limitations, and opportunities of large vision models. http://arxiv.org/abs/2402.17177
• Lockwood, J., & Mooney, A. (2017). Computational thinking in education: Where does it fit? A systematic literary review. International Journal of Computer Science Education in Schools, 2(1), 41–60. https://doi.org/10.21585/ijcses.v2i1.26
• Madoń, K. (2024). The relationship between artificial intelligence (AI) exposure and returns to education. Central European Economic Journal, 11(58), 461–474. https://doi.org/10.2478/ceej-2024-0029
• Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. https://doi.org/https://doi.org/10.1016/j.futures.2017.03.006
• Mariam Mathews, P., Konda Reddy, N., Vaza, R. N., Parmar, A. B., Velu, C. M., Sahni, N., & Professor, A. (2024). Measuring impact-evaluating the effectiveness of IoT and AI integration in educational administration. Educational Administration: Theory and Practice, 30(4), 8428–8435.
• Mart, M., & Kaya, G. (2024). Okul öncesi öğretmen adaylarının yapay zekâya yönelik tutumları ve yapay zekâ okur yazarlığı arasındaki ilişkinin incelenmesi [The examination of preschool teacher candidates’ attitudes towards artificial intelligence and their artificial intelligence literacy relationship]. Edutech Research, 2(1), 91–109.
• Mertler, C. A., & Vannatta, R. A. (2016). Advanced and multivariate statistical methods: Practical application and interpretation. Routledge. https://doi.org/10.4324/9781315266978
• Mills, K. A., Cope, J., Scholes, L., & Rowe, L. (2025). Coding and computational thinking across the curriculum: a review of educational outcomes. Review of Educational Research, 95(3), 581–618. https://doi.org/10.3102/00346543241241327
• Nerse, S. (2020). Dijital eğitimde eşitsizlikler: Kırsal-kentsel ayrımlar ve sosyoekonomik farklılaşmalar. İnsan ve Toplum Dergisi, 10(4), 413–444. https://doi.org/10.12658/M0548
• Ofosu-Ampong, K., Acheampong, B., Kevor, M.O., & Amankwah-Sarfo, F. (2023). Acceptance of artificial intelligence (ChatGPT) in education: Trust, innovativeness and psychological need of students. Information and Knowledge Management, 13(4), 37–47. https://doi.org/10.7176/ikm/13-4-03
• Orim, R. E., & Egwo, P. M. (2020). Marital status and mathematics teachers’ instructional delivery in secondary schools in Obubra L.G.A., C.R.S. Nter-Disciplinary Journal of Science Education (IJ-SED), 2(1), 14–20.
• Ökten, M. S. (2024). Türkiye’de dijital dönüşümün eğitimdeki fırsat eşit(siz)liği üzerindeki etkileri. Sosyolojik Bağlam Dergisi, 5(3), 531–556. https://doi.org/10.52108/2757-5942.5.3.7
• Palop, B., Díaz, I., Rodríguez-Muñiz, L. J. & Santaengracia, J. J. (2025). Redefining computational thinking: A holistic framework and its implications for K-12 education. Education and Information Technologies, 30, 13385–13410. https://doi.org/10.1007/s10639-024-13297-4
• Pokrivcakova, S. (2023). Pre-service teachers’ attitudes towards artificial intelligence and its integration into EFL teaching and learning. Journal of Language and Cultural Education, 11(3), 100–114. https://doi.org/10.2478/jolace-2023-0031
• Pusmaz, A. (2023). Algoritmik düşünme. In A. Gökhan & F. Erdoğan (Eds.), Matematik ve fen bilimleri eğitiminde yeni yaklaşımlar. Efe Akademi Yayınları.
• Qualtrics. (2025, August 8). Sample size calculator. https://www.qualtrics.com/blog/calculating-sample-size/
• Rapti, C., & Panagiotidis, P. (2024). Teachers’ attitudes towards AI integration in foreign language learning: Supporting differentiated ınstruction and flipped classroom. European Journal of Education, 7(2), 88–104.
• Razia, B., Awwad, B., & Taqi, N. (2023). The relationship between artificial intelligence (AI) and its aspects in higher education. Development and Learning in Organizations, 37(3), 21–23. https://doi.org/10.1108/DLO-04- 2022-0074
• Renz, A., & Hilbig, R. (2020). Prerequisites for artificial intelligence in further education: identification of drivers, barriers, and business models of educational technology companies. International Journal of Educational Technology in Higher Education, 17(14), 1–21. https://doi.org/10.1186/s41239-020-00193-3
• Rodrigues, R. N., Costa, C., Brito-Costa, S., Abbasi, M., & Martins, F. (2025). Impact of a training program on developing computational thinking in pre-service primary school teachers: From theory to practice. Educational Process: International Journal, 17, Article 14. https://doi.org/10.22521/edupij.2025.14.37
• Rodríguez-García, J. D., Moreno-León, J., Román-González, M., & Robles, G. (2020). LearningML: A tool to foster computational thinking skills through practical artificial intelligence projects. Revista de Educación a Distancia, 20(63), Artículo 07. https://doi.org/10.6018/red.410121
• Romero, M., Lepage, A., & Lille, B. (2017). Computational thinking development through creative programming in higher education. International Journal of Educational Technology in Higher Education, 14(1), Article 42. https://doi.org/10.1186/s41239-017-0080-z
• Rossi, P. G., & Fedeli, L. (2012). Intelligent tutoring system: A short history and new challenges. In P. Gigliola, P. G.
• Rossi, & D. Zarka (Eds.), Intelligent Tutoring Systems: An Overview (pp. 13–58). Pensa MultiMedia Editore. https://u-pad.unimc.it/retrieve/0f3b0262-82ac-4c26-94a2-60f3d2ccff0c/Intelligent_Tutoring_Systems_overview.pdf
• Salahshoor, N., & Rafiee, M. (2016). The relationship between critical thinking and gender: A case of Iranian EFL learners. Journal of Applied Linguistics and Language Research, 3(2), 117–123.
• Schreglmann, S., & Doğruluk, S. (2012). Bilişim teknolojileri öğretmen adaylarının problem çözme becerilerinin çeşitli değişkenler açısından incelenmesi [Investigation of problem solving skills of prospective information technologies teachers in terms of different variables]. Amasya Üniversitesi Eğitim Fakültesi Dergisi, 1(2), 143–150.
• Serin, O. (2006). The examination of primary school teachers’ problem-solving skills in terms of various variables. Education and Science, 31(142), 80–88.
• Seyrek, M., Şahin, A., Yıldız, S., Türkmen, M. T., & Emeksiz, H. (2024). Öğretmenlerin eğitimde yapay zekâ kullanımına yönelik algıları [Teachers' perceptions on the use of artificial intelligence in education]. International Journal of Social and Humanities Sciences Research (JSHSR), 11(106), 845–856. https://doi.org/10.5281/zenodo.11113077
• Shubina, I., & Kulakli, A. (2019). Critical thinking, creativity and gender differences for knowledge generation in education. Literacy Information and Computer Education Journal (LICEJ), 10(1), 3086–3093.
• Simmonds, J., Gutierrez, F. J., Casanova, C., Sotomayor, C., & Hitschfeld, N. (2019). A teacher workshop for introducing computational thinking in rural and vulnerable environments. 50th ACM Technical Symposium on Computer Science Education (SIGCSE ’19), 1143–1149. https://doi.org/10.1145/3287324.3287456
• So, H. J., Jong, M. S. Y., & Liu, C. C. (2020). Computational thinking education in the asian pacific region. Asia-Pacific Education Researcher, 29(1), 1–8. https://doi.org/10.1007/s40299-019-00494-w
• Sok, S., & Heng, K. (2023). ChatGPT for education and research: A review of benefits and risks. Cambodian Journal of Educational Research, 3(1), 110–121. https://doi.org/10.62037/cjer.2023.03.01.06
• Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning and Teaching, 6(1), 31–40. https://doi.org/10.37074/jalt.2023.6.1.17
• Şimşek, Ö., Demir, S., Bağçeci, B., & Kinay, İ. (2013). Öğretim elemanlarının teknopedagojik eğitim yeterliliklerinin çeşitli değişkenler açısından incelenmesi [Examining technopedagogical knowledge competencies of teacher trainers in terms of some variables]. Ege Journal of Education, 14(1), 1–23.
• Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
• Tagare, D. (2024). Factors that predict K-12 teachers’ ability to apply computational thinking skills. ACM Transactions on Computing Education, 24(1), Article 3. https://doi.org/10.1145/3633205
• 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
• Topal, M., Topal, N., Görgel, A., Kama, H., & Yağız, N. (2025). Probleme dayalı öğrenme ve kuramsal dayanakları: Öğrenme sürecine yeni bir yaklaşım [Problem based learning and its theoretical foundations: a new approach to the learning process]. Socrates Journal of Interdisciplinary Social Researches, 11(49), 46–64. https://doi.org/10.5281/zenodo.14632143
• Triantafyllou, S. A., Sapounidis, T., & Farhaoui, Y. (2024). Gamification and computational thinking in education: A systematic literature review. Salud, Ciencia y Tecnología - Serie de Conferencias, 3(659), 1–25. https://doi.org/10.56294/sctconf2024659
• Tripon, C. (2022). Supporting future teachers to promote computational thinking skills in teaching STEM—a case study. Sustainability, 14(19), 1–17. https://doi.org/10.3390/su141912663
• Uyak, S., Güngör Uyak, S., Ürey, D., Keskin, Ö., Aymaz, A., & Aydın, İ. (2023). Okul öncesi eğitim kurumlarında yapay zekâ uygulamaları: Yönetici ve öğretmen görüşleri [Artificial intelligence applications in preschool education institutions: administrators and teachers' opinions]. International Social Mentality and Researcher Thinkers Journal, 9(75), 4625–4636. http://dx.doi.org/10.29228/smryj.72414
• Uygun, D., Aktaş, I., Duygulu, İ., & Köseer, N. (2024). Exploring teachers’ artificial intelligence awareness. Advances in Mobile Learning Educational Research, 4(2), 1093–1104. https://doi.org/10.25082/amler.2024.02.004
• Van den Berg, G., & du Plessis, E. (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. Education Sciences, 13(10), 1–12. https://doi.org/10.3390/educsci13100998
• Walsh, T. (2020). 2062 Yapay zekâ dünyası (Z. Dirihan, Çev.; 1. bs.). Say Yayınları.
• Wang, Y., Wei, Z., Wijaya, T. T., Cao, Y., & Ning, Y. (2025). Awareness, acceptance, and adoption of Gen-AI by K-12 mathematics teachers: an empirical study integrating TAM and TPB. BMC Psychology, 13(1), Article 478. https://doi.org/10.1186/s40359-025-02781-2
• Wardat, Y., Tashtoush, M. A., AlAli, R., & Jarrah, A. M. (2023). ChatGPT: A revolutionary tool for teaching and learning mathematics. Eurasia Journal of Mathematics, Science and Technology Education, 19(7), Article em2286. https://doi.org/10.29333/ejmste/13272
• Weng, X., Ye, H., Dai, Y., & Ng, O. L. (2024). Integrating artificial intelligence and computational thinking in educational contexts: A systematic review of instructional design and student learning outcomes. Journal of Educational Computing Research, 62(6), 1640–1670. https://doi.org/10.1177/07356331241248686
• Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
• Wu, S. P. W., Peel, A., Bain, C., Anton, G., Horn, M., & Wilensky, U. (2020). Workshops and co-design can help teachers integrate computational thinking into their K-12 STEM classes. Proceedings of International Conference on Computational Thinking Education 2020, 63, 63–68.
• Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. TechTrends, 60(6), 565–568. https://doi.org/10.1007/s11528-016-0087-7
• Yaman, S., & Yalçın, N. (2005). Fen bilgisi öğretiminde probleme dayalı öğrenme yaklaşımının yaratıcı düşünme becerisine etkisi [Effectiveness on creative thinking skills of problem based learning approach in science teaching]. İlköğretim Online, 4(1), 42–52.
• Yünkül, E., Durak, G., Çankaya, S., & Misirli, Z. A. (2017). The effects of Scratch software on students computational thinking skills. Necatibey Faculty of Education Electronic Journal of Science and Mathematics Education, 11(2), 502–517.
• Zafrullah, Ramadhani, A. M., Retnawati, H., & Nabilah. (2024). Computational thinking and its application in school: A bibliometric analysis (2008-2023). Proceedings of the International Conference on Current Issues in Education (ICCIE 2023), 329–338. https://doi.org/10.2991/978-2-38476-245-3_35
• Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2(2), Article 100025. https://doi.org/10.1016/j.caeai.2021.100025