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Journals / Anadolu Journal of Educational Sciences International / 2026 / Cilt: 16 Sayı: 3

Investigating the Relationship Between High School Students’ Artificial Intelligence Literacy and Computational Thinking Skills

Lise Öğrencilerinin Yapay Zeka Okuryazarlığı ve Bilgi İşlemsel Düşünme Becerileri Arasındaki İlişkinin İncelenmesi

Ayşegül Ugış(MİLLİ EĞİTİM BAKANLIĞI KASTAMONU)0009-0007-0241-3166
Zeynep Piri(KASTAMONU ÜNİVERSİTESİ)0000-0002-1849-1878
Pages
1268–1295
Publication Date
2026-09-20
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

These findings indicate that artificial intelligence literacy programs at high school level can be differentiated according to school type and student needs and developed in parallel with computational thinking skills.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Abstract In the digital age, young people's ability to understand and purposefully use artificial intelligence technologies stands out as a critical competency area in education.
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Key Findings & Data:The research, conducted with 106 high school students using a correlational survey model, employed the Artificial Intelligence Literacy Scale and the Computational Thinking Self-Efficacy Scale.
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Conclusion & Impact:These findings indicate that artificial intelligence literacy programs at high school level can be differentiated according to school type and student needs and developed in parallel with computational thinking skills.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Yapay Zeka · Yapay Zeka Okuryazarlığı · Bilgi İşlemsel Düşünme Becerileri

Abstract

Abstract In the digital age, young people's ability to understand and purposefully use artificial intelligence technologies stands out as a critical competency area in education. Artificial intelligence literacy and computational thinking skills have overlapping technical and critical dimensions. This study examines the relationship between high school students' artificial intelligence literacy and computational thinking skills. The research, conducted with 106 high school students using a correlational survey model, employed the Artificial Intelligence Literacy Scale and the Computational Thinking Self-Efficacy Scale. The findings showed that students' artificial intelligence literacy was at a moderate level. While no significant differences were found based on gender and grade level variables, it was observed that Anatolian High School students had a higher level of artificial intelligence literacy than Vocational High School students. An analysis of the sub-dimensions revealed that the significant difference was driven by practical application and critical evaluation; however, no significant discrepancy was found between the two groups regarding technical understanding. A strong positive correlation was found between artificial intelligence literacy and computational thinking skills (rs = .775, p < .001). These findings indicate that artificial intelligence literacy programs at high school level can be differentiated according to school type and student needs and developed in parallel with computational thinking skills.

Özet

Dijital çağda gençlerin yapay zeka teknolojilerini anlama ve bilinçli kullanma becerileri, eğitimde kritik bir yetkinlik alanı olarak öne çıkmaktadır. Yapay zeka okuryazarlığı ve bilgi işlemsel düşünme becerileri teknik ve eleştirel boyutlarıyla birbiri ile örtüşebilecek yapıda olan iki önemli beceri türüdür. Bu çalışma, lise öğrencilerinin yapay zeka okuryazarlığı ile bilgi işlemsel düşünme becerileri arasındaki ilişkiyi incelemektedir. 106 lise öğrencisi ile yapılan ve ilişkisel tarama modeli kullanılarak yürütülen araştırmada, Yapay Zeka Okuryazarlığı Ölçeği ve Bilgi İşlemsel Düşünme Öz-Yeterlik Ölçeği kullanılmıştır. Bulgular, öğrencilerin yapay zeka okuryazarlığının orta düzeyde olduğunu göstermiştir. Yapay zeka okuryazarlığı düzeylerinde cinsiyet ve sınıf düzeyi değişkenlerine göre anlamlı fark bulunmazken, Anadolu Lisesi öğrencilerinin yapay zeka okuryazarlık düzeyinin Meslek Lisesi öğrencilerine göre daha yüksek olduğu görülmüştür. Alt boyutlar incelendiğinde bu farkın pratik uygulama ve eleştirel değerlendirme boyutlarından kaynaklandığı, teknik anlama boyutunda ise iki grubun benzer düzeyde olduğu görülmüştür. Yapay zeka okuryazarlığı ile bilgi işlemsel düşünme becerileri arasında güçlü ve pozitif bir korelasyon bulunmuştur (rs = .775, p < .001). Bulgular, lise düzeyinde yapay zeka okuryazarlığı programlarının okul türüne ve öğrenci ihtiyaçlarına göre farklılaştırılmasının faydalı olabileceğini göstermektedir.

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Cite This Article

Ugış, A., Piri, Z. (2026). Investigating the Relationship Between High School Students’ Artificial Intelligence Literacy and Computational Thinking Skills. Anadolu Journal of Educational Sciences International, Cilt: 16 Sayı: 3, 1268–1295. https://doi.org/10.18039/ajesi.1935640

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References (59)

  1. Bozkurt, A., & Sharma, R. C. (2023). Generative AI and prompt engineering: The art of whispering to let the genie out of the algorithmic world. Asian Journal of Distance Education, 18(2), i-vii.
  2. Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. In Proceedings of the 2012 annual meeting of the American Educational Research Association (1, p. 25).
  3. Büyüköztürk, Ş., Çakmak Kılıç, E., Akgün, Ö. E., Karadeniz, Ş., & Demirel, F. (2021). Sosyal bilimler için veri analizi el kitabı: İstatistik, araştırma deseni, SPSS uygulamaları ve yorum (28. baskı). Pegem Akademi.
  4. Cheng, C. C., Wang, J. S., Zhai, X., & Yang, Y. T. C. (2025). AI literacy and gender equity in elementary education: A quasi-experimental study of a STEAM–PBL–AIoT course with questionnaire validation. International Journal of STEM Education, 12(1), 50. https://doi.org/10.1186/s40594-025-00574-y
  5. Chiu, T. K., Ahmad, Z., Ismailov, M., & Sanusi, I. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6, 100171. https://doi.org/10.1016/j.caeo.2024.100171
  6. Choi, W. C., Chang, C. I., Choi, I. C., Lam, L. C., Leong, K. I., & Ng, S. I. (2025). Artificial Intelligence (AI) Literacy in Education: Definition, Competencies, Opportunities and Challenges. Preprints.
  7. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
  8. Çelebi, C., Demir, U., & Karakuş, F. (2023). Yapay zeka okuryazarlığı konulu çalışmaların sistematik derleme yöntemiyle incelenmesi. Necmettin Erbakan Üniversitesi Ereğli Eğitim Fakültesi Dergisi, 5(2), 535-560. https://doi.org/ 10.51119/ereegf.2023.67
  9. Celik, I. (2023). Exploring the determinants of artificial intelligence (Ai) literacy: Digital divide, computational thinking, cognitive absorption. Telematics and Informatics, 83, 102026. https://doi.org/10.1016/j.tele.2023.102026
  10. Elçiçek, M. (2024). Öğrencilerin yapay zeka okuryazarlığı üzerine bir inceleme. Bilgi ve İletişim Teknolojileri Dergisi, 6(1), 24-35. https://doi.org/10.53694/bited.1460106
  11. Er, E. E. (2025). Yapay zeka okuryazarlığı: Ortaokul öğrencileri için öğretim programı geliştirme ve ölçek uyarlama [Yayımlanmamış yüksek lisans tezi]. Süleyman Demirel Üniversitesi.
  12. Estevez, J., Garate, G., & Graña, M. (2019). Gentle introduction to artificial intelligence for high-school students using scratch. IEEE Access, 7, 179027–179036. doi: 10.1109/ACCESS.2019.2956136
  13. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2022). How to design and evaluate research in education. 11th ed, Singapore, McGraw Hill.
  14. García‐Pérez, L., Roldán‐Álvarez, D., & Cañas, J. M. (2025). Does Gender Influence the Learning Process of Computational Thinking in Secondary Education?. Computer Applications in Engineering Education, 33(3), e70050. https://doi.org/10.1002/cae.70050
  15. George, D. & Mallery, M. (2019). SPSS for windows step by step: A simple guide and reference 17.0 update (15. ed.). Routledge.
  16. Gong, X., Tang, Y., Liu, X., Jing, S., Cui, W., Liang, J., & Wang, F. Y. (2020). K-9 artificial intelligence education in Qingdao: Issues, challenges and suggestions. In 2020 IEEE international Conference on networking, Sensing and control (ICNSC) (pp. 1-6). IEEE.
  17. Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38-43. Doi: 10.3102/0013189X12463051
  18. Guan, Y., Zhang, C., He, H., Zhang, W., Hu, Z., Bi, T., & Jin, X. (2025). AI literacy predicts computational thinking through multidimensional interactions among Chinese high school students. Scientific Reports, 15(1), 33092. https://doi.org/10.1038/s41598-025-16712-z
  19. Güler, A., & Polatgil, M. (2025). Bilişim alanında öğrenim gören öğrencilerin yapay zeka okuryazarlığı düzeylerinin ölçülmesi. Journal of Computer and Education Research, 13(25), 30-53. 10.18009/jcer.1549267
  20. Heintz (2022) The computational thinking and artificial intelligence duality in Kong, S. C., & Abelson, H. (Eds.). Computational thinking education in K-12: Artificial intelligence literacy and physical computing. MIT Press.
  21. Hu, Z., He, H., Zhang, C., & Guan, Y. (2025). Development and influencing factors of artificial intelligence literacy and computational thinking in Chinese university students. Scientific Reports, 15(1), 42708. https://doi.org/10.1038/s41598-025-26888-z
  22. Hsu, TC., Hsu, TP. Teaching AI with games: the impact of generative AI drawing on computational thinking skills. Educ Inf Technol 30, 21499–21518 (2025). https://doi.org/10.1007/s10639-025-13624-3
  23. Huang, X., & Qiao, C. (2024). Enhancing computational thinking skills through artificial intelligence education at a STEAM high school. Science & Education, 33(2), 383-403. https://doi.org/10.1007/s11191-022-00392-6
  24. International Society for Technology in Education. (2024). ISTE standards (v4.02). https://cms-live-media.iste.org/ISTE_STANDARDS_2024_v02.pdf
  25. Kalelioğlu, F., Gülbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4(3), 583-596.
  26. Karaoğlan Yılmaz, F. G. & Yılmaz, R. (2023). Yapay zeka okuryazarlığı ölçeğinin Türkçeye uyarlanması. Bilgi ve İletişim Teknolojileri Dergisi, 5(2), 172-190. https://doi.org/10.53694/bited.1376831
  27. Kim, K., & Kwon, K. (2024). Designing an inclusive artificial intelligence (AI) curriculum for elementary students to address gender differences with collaborative and tangible approaches. Journal of Educational Computing Research, 62(7), 1617-1644. https://doi.org/10.1177/07356331241271059
  28. Kong, S. C., Cheung, W. M. Y., & Zhang, G. (2023). Evaluating an artificial intelligence literacy programme for developing university students’ conceptual understanding, literacy, empowerment and ethical awareness. Educational Technology & Society, 26(1), 16-30. https://doi.org/10.30191/ETS.202301_26(1).0002
  29. Kong, S. C., Korte, S. M., Burton, S., Keskitalo, P., Turunen, T., Smith, D.,. & Beaton, M. C. (2025). Artificial Intelligence (AI) literacy–an argument for AI literacy in education. Innovations in Education and Teaching International, 62(2), 477-483. https://doi.org/10.1080/14703297.2024.2332744
  30. Kovačević, A., & Demić, E. (2024). The impact of gender, seniority, knowledge, and interest on attitudes to artificial intelligence. IEEE Access, 12, 129765-129775. Doi: 10.1109/ACCESS.2024.3454801
  31. Laupichler, M. C., Aster, A., Haverkamp, N., & Raupach, T. (2023). Development of the “scale for the assessment of non-experts’ AI literacy”–An exploratory factor analysis. Computers in Human Behavior Reports, 12, 100338. https://doi.org/10.1016/j.chbr.2023.100338
  32. Li Q, Huang T, Huang L, Wu X (2026) The impact of university students’ computational thinking on AI literacy: A longitudinal study based on SEM-PLS. PLoS One 21(5): e0350124. https://doi.org/10.1371/ journal.pone.0350124
  33. Lin, X. F., Zhou, Y., Shen, W., Luo, G., Xian, X., & Pang, B. (2024). Modeling the structural relationships among Chinese secondary school students’ computational thinking efficacy in learning AI, AI literacy, and approaches to learning AI. Education and Information Technologies, 29(5), 6189-6215. https://doi.org/10.1007/s10639-023-12029-4
  34. Lin, Y., Yang, Y., & Zhang, Y. (2025). Scaffolding third graders’ computational thinking in an artificial intelligence course. Educational Technology & Society, 28(4), 338-367. https://doi.org/10.22318/icls2025.375771
  35. Long, D., & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16). https://doi.org/10.1145/3313831.3376727
  36. Ma, M., Ng, D. T. K., Liu, Z., & Wong, G. K. (2025). Fostering responsible AI literacy: A systematic review of K-12 AI ethics education. Computers and Education: Artificial Intelligence, 8, 100422. https://doi.org/10.1016/j.caeai.2025.100422
  37. Milli Eğitim Bakanlığı. (2025). Eğitimde yapay zekâ politika belgesi ve eylem planı (2025-2029). Yenilik ve Eğitim Teknolojileri Genel Müdürlüğü. https://yegitek.meb.gov.tr/meb_iys_dosyalar/2025_06/17092340_egitimdeyapayzekapolitikabelgesiveeylemplani202520291.pdf
  38. Ng, D. T. K., Su, J., Leung, J. K. L., & Chu, S. K. W. (2024). Artificial intelligence (AI) literacy education in secondary schools: a review. Interactive Learning Environments, 32(10), 6204-6224. https://doi.org/10.1080/10494820.2023.2255228
  39. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. McGraw-Hill.
  40. OECD (2025). Empowering learners for the age of AI: An AI literacy framework for primary and secondary education. OECD. Paris. https://ailiteracyframework.org
  41. Seker, O., Kwon, K., & Kocak, O. (2025). Exploring researchers’ artificial intelligence (AI) literacy: The mediating role of digital literacy and data literacy between 21st century skills and AI literacy. Information Development, 0(0). https://doi.org/10.1177/02666669251336368
  42. Shamir, G., & Levin, I. (2022). Teaching machine learning in elementary school. International Journal of Child-Computer Interaction, 31, 100415. https://doi.org/10.1016/j.ijcci.2021.100415
  43. Sok, S., Heng, K., & Pum, M. (2025). Investigating high school students’ attitudes toward the use of AI in education: Evidence from Cambodia. Sage Open, 15(3), 21582440251353575. DOI: 10.1177/21582440251353575
  44. Stolpe, K., & Hallström, J. (2024). Artificial intelligence literacy for technology education. Computers and Education Open, 6, Article 100159. https://doi.org/10.1016/j.caeo.2024.100159
  45. Tzirides, A. O. O., Zapata, G., Kastania, N. P., Saini, A. K., Castro, V., Ismael, S. A.,. & Kalantzis, M. (2024). Combining human and artificial intelligence for enhanced AI literacy in higher education. Computers and Education Open, 6, 100184. https://doi.org/10.1016/j.caeo.2024.100184
  46. Türel, E., Küçükvardar, M., Myatiyev, O., & Avcı, Y. (2024). Eğitim ve iletişim sürecinde yapay zeka okuryazarlığına ilişkin bir araştırma. International European Journal of Managerial Research (EUJMR), 8(15),198-212. https://doi.org/10.62666/eujmr.1588636
  47. Veldhuis, A., Lo, P. Y., Kenny, S., & Antle, A. N. (2025). Critical Artificial Intelligence literacy: A scoping review and framework synthesis. International Journal of Child-Computer Interaction, 43, 100708. https://doi.org/10.1016/j.ijcci.2024.100708
  48. Wang, T., & Cheng, E. C. K. (2021). An investigation of barriers to Hong Kong K-12 schools incorporating Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 2, 100031. https://doi.org/10.1016/j.caeai.2021.100031
  49. Weng, X., Ye, H., Dai, Y., & Ng, O. (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), 1420-1450. https://doi.org/10.1177/07356331241248686
  50. Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.
  51. Wing, J. (2011). Research notebook: Computational thinking—What and why? The Link Magazine, Spring. Carnegie Mellon University, Pittsburgh. Retrieved from http://link.cs.cmu.edu/article.php?a=600
  52. Wu, D., & Zhang, J. (2025). Generative artificial intelligence in secondary education: Applications and effects on students’ innovation skills and digital literacy. PLoS One, 20(5), e0323349. https://doi.org/10.1371/journal.pone.0323349
  53. Yağcı, M. (2018). A Study on Computational Thinking and High School Students’ Computational Thinking Skill Levels, International Online Journal of Educational Sciences, 10(2), 81-96. doi: 10.15345/iojes.2018.02.006
  54. Yeter, I. H., Yang, W., & Sturgess, J. B. (2024). Global initiatives and challenges in integrating artificial intelligence literacy in elementary education: Mapping policies and empirical literature. Future in Educational Research, 2(4), 382-402. https://doi.org/10.1002/fer3.59
  55. Yim, I. H. Y., & Su, J. (2025). Artificial intelligence (AI) learning tools in K-12 education: A scoping review. Journal of Computers in Education, 12(1), 93-131. https://doi.org/10.1007/s40692-023-00304-9
  56. Zhang, D., Yang, H., He, Y., & Guo, W. (2025). Modeling the relationships between secondary school students’ AI learning attitude, AI literacy and AI career interest. Education and Information Technologies, 30(17), 25223-25250. https://doi.org/10.1007/s10639-025-13715-1
  57. Zhong, B., & Liu, X. (2025). Evaluating AI literacy of secondary students: Framework and scale development. Computers & Education, 227, 105230. https://doi.org/10.1016/j.compedu.2024.105230
  58. Kong, S. C., Korte, S. M., Burton, S., Keskitalo, P., Turunen, T., Smith, D.,. & Beaton, M. C. (2025). Artificial Intelligence (AI) literacy–an argument for AI literacy in education. Innovations in Education and Teaching International, 62(2), 477-483. https://doi.org/10.1080/14703297.2024.2332744
  59. Tzirides, A. O. O., Zapata, G., Kastania, N. P., Saini, A. K., Castro, V., Ismael, S. A.,. & Kalantzis, M. (2024). Combining human and artificial intelligence for enhanced AI literacy in higher education. Computers and Education Open, 6, 100184. https://doi.org/10.1016/j.caeo.2024.100184