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Journals / Journal for the Education of Gifted Young Scientists / 2026 / Volume: 14 Issue: 3

Examining the social validity of a Cybersecurity Awareness Training Program in AI-Supported Education (CATP-AIsE) for gifted students

Halil Senturk(T.C. MİLLİ EĞİTİM BAKANLIĞI)0000-0002-8672-8048
Pages
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Publication Date
2026-09-30
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AI Summary & Key Takeaways

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

Paired-samples t-test results indicated statistically significant improvements across all five dimensions of cybersecurity awareness (p < .001), with a large overall effect size (Cohen’s d = 1.85).

📌 3 Key Takeaways

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Objective & Hypothesis:Despite the rapid integration of AI-supported tools into special education settings, empirical evidence regarding cybersecurity awareness among gifted students remains extremely limited.
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Key Findings & Data:This mixed-methods study examined whether AI-supported, scenario-based educational interventions could produce measurable improvements in the cybersecurity awareness of gifted students (N = 50, aged 11–14) enrolled in a Science and Art Center program in Türkiye.
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Conclusion & Impact:Paired-samples t-test results indicated statistically significant improvements across all five dimensions of cybersecurity awareness (p < .001), with a large overall effect size (Cohen’s d = 1.85).
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Artificial Intelligence (AI) · Cybersecurity awareness · Cybersecurity Awareness Training Program

Abstract

Despite the rapid integration of AI-supported tools into special education settings, empirical evidence regarding cybersecurity awareness among gifted students remains extremely limited. This mixed-methods study examined whether AI-supported, scenario-based educational interventions could produce measurable improvements in the cybersecurity awareness of gifted students (N = 50, aged 11–14) enrolled in a Science and Art Center program in Türkiye. Quantitative data were collected using the Cybersecurity Awareness Scale administered before and after a four-week intervention, while qualitative data were obtained through scenario-based, AI-supported activities focusing on password security and phishing recognition. Paired-samples t-test results indicated statistically significant improvements across all five dimensions of cybersecurity awareness (p < .001), with a large overall effect size (Cohen’s d = 1.85). Qualitative thematic analysis revealed three key cognitive transformations: Learning Through Immediate Feedback, Systems Thinking, and Digital Skepticism. These findings suggest that AI-supported, scenario-based instruction may offer a promising mechanism for bridging the knowledge–behavior gap in gifted education and provide preliminary evidence for integrating cybersecurity awareness into specialized educational programs. Important methodological limitations, including the absence of a control group and issues related to multiple comparisons, are discussed.

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Cite This Article

Senturk, H., *, H. S. (2026). Examining the social validity of a Cybersecurity Awareness Training Program in AI-Supported Education (CATP-AIsE) for gifted students. Journal for the Education of Gifted Young Scientists, Volume: 14 Issue: 3. https://doi.org/10.17478/jegys.1989405

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References (26)

  1. Al-Azawei, A., Al-Bahrani, A., & Al-Bahrani, M. (2024). Examining digital security behaviors and ethics among gifted and high-achieving students: A cross-sectional analysis of technical competence versus security awareness. Computers & Education, 210, 104952. https://doi.org/10.1016/j.compedu.2023.104952
  2. Andress, J. (2014). The basics of information security: Understanding the fundamentals of InfoSec in theory and practice. Syngress.
  3. Ansari, M. F., Sharma, P. K., & Dash, B. (2022). Prevention of phishing attacks using AI-based cybersecurity awareness training. International Journal of Smart Sensor and Adhoc Network, 3(3), 61–72. https://doi.org/10.47893/ijssan.2022.1221
  4. Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278.
  5. Creswell, J. W., & Miller, D. L. (2000). Determining validity in qualitative inquiry. Theory Into Practice, 39(3), 124– 130. https://doi.org/10.1207/s15430421tip3903_2
  6. Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). Sage Publications.
  7. Dede, M., Yılmaz, O., & Şahin, E. (2026). Özel yetenekliler eğitimi merkezlerinde (BİLSEM) dijital güvenlik ve yapay zekâ entegrasyonu: Yönetici ve öğretmen perspektifleri (Digital security and AI integration in gifted education centers [BİLSEM]: Administrator and teacher perspectives). Journal of Gifted Education and Creativity, 14(1), 45– 68.
  8. ENISA (European Union Agency for Cybersecurity). (2022). Cybersecurity guide for SMEs: 12 steps to securing your business. Publications Office of the European Union. https://www.enisa.europa.eu/publications/cybersecurity-guide-for-smes
  9. Erkoç, M. F., Karataş, S., & Can, T. (2025). Simülasyon ve senaryo tabanlı siber güvenlik eğitiminin ortaokul öğrencilerinin tehdit algısına etkisi (The effect of simulation- and scenario-based cybersecurity education on secondary school students’ threat perception). Eğitim Teknolojisi Kuram ve Uygulama, 15(2), 112–135. https://doi.org/10.17860/mersinefd.123456
  10. Guo, H., & Tınmaz, H. (2023). A survey on college students’ cybersecurity awareness and education from the perspective of China. Journal for the Education of Gifted Young Scientists, 11(3), 351–367. https://dergipark.org.tr/en/pub/jegys/article/1323423
  11. Hj. Mohamed, A., Ismail, R., & Yusof, N. M. (2025). Dark side of AI in smart classrooms: Privacy risks, over-reliance, and security vulnerabilities in adaptive learning platforms. Interactive Learning Environments, 33(3), 1845–1862. https://doi.org/10.1080/10494820.2024.2312011
  12. Kim, S., & Lee, J. (2025). Cognitive over-reliance on generative AI: How adaptive feedback loops alter risk perception in cybersecurity scenarios. Journal of Educational Computing Research, 63(1), 88–114. https://doi.org/10.1177/07356331241256789
  13. Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage Publications.
  14. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
  15. Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). Sage Publications.
  16. Mukhamadiyeva, S., & Hernández-Torrano, D. (2024). Adaptive learning to maximize gifted education: Teacher perceptions, practices, and experiences. Journal for the Education of the Gifted, 47(2), 180–205. https://doi.org/10.1177/1932202X241253166
  17. Orakcı, Ş. (2025). Autonomous learning and creative cognition: The mediating effect of gifted students’ self- efficacy. Frontiers in Psychology, 15, 1301528. https://doi.org/10.3389/fpsyg.2024.1301528
  18. Özbek, G., & Dağyar, M. (2022). Examining gifted students’ evaluations of their education programs in terms of their project production and management. Frontiers in Psychology, 12, 833395. https://doi.org/10.3389/fpsyg.2022.833395
  19. Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 1–13. https://doi.org/10.1186/s41039-017-0062-8
  20. Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599.
  21. Schmitt, M., & Flechais, I. (2023). Digital deception: Generative artificial intelligence in social engineering and phishing. arXiv. https://doi.org/10.48550/arXiv.2310.13715
  22. Schmitt, M., Flechais, I., & CyberSecurity Group. (2024). Countering AI-driven social engineering: Evaluating scenario-based phishing simulations in secondary education. Computers & Security, 138, 103650. https://doi.org/10.1016/j.cose.2023.103650
  23. Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. John Wiley & Sons.
  24. Subotnik, R. F., Olszewski-Kubilius, P., & Worrell, F. C. (2011). Rethinking giftedness and gifted education: A proposed direction forward based on psychological science. Psychological Science in the Public Interest, 12(1), 3–54.
  25. Tortop, H. S., & Ilgaz, G. (2026). Development of the Personalized Learning Self-Efficacy Scale and the Personalized Instruction Self-Efficacy Scale. Journal of Gifted Education and Creativity, 13(1), 49–59. https://doi.org/10.5281/zenodo.21035409
  26. Yurtsever, M., & Yurtsever, G. G. (2025). Eğitimde yapay zekâ çalışmalarında öğretmenlerin rolü ve bakış açıları (Teachers’ roles and perspectives in AI studies in education). Cumhuriyet Uluslararası Eğitim Dergisi, 14(2), 344–357.