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Journals / Medya ve Kültürel Çalışmalar Dergisi / 2026 / Cilt: 8 Sayı: 1

Artificial Intelligence Anxiety in the Context of the Technology Acceptance Model: A Study on Communicatıon Faculty Students

Teknoloji Kabul Modeli Bağlamında Yapay Zekâ Kaygısı: İletişim Fakültesi Öğrencileri Üzerine Bir Araştırma

Deniz Yaman(Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü İletişim Bilimleri (DR))0000-0002-3916-8244
Seyhan Aksoy(SÜLEYMAN DEMİREL ÜNİVERSİTESİ, İLETİŞİM FAKÜLTESİ, RADYO, TELEVİZYON VE SİNEMA BÖLÜMÜ)0000-0001-5167-5866
Pages
59–95
Publication Date
2026-04-30
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AI Summary & Key Takeaways

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

The findings reveal that the analyzed demographic variables create statistically significant differences (p< .05) in anxiety levels.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study aims to examine the artificial intelligence (AI) anxiety levels among communication faculty students, the future professionals of the media industry, within the context of the Technology Acceptance Model (TAM).
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Key Findings & Data:The findings reveal that the analyzed demographic variables create statistically significant differences (p< .05) in anxiety levels.
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Conclusion & Impact:These paradoxical findings indicate that as communication students' practical experience with generative AI deepens and they realize the transformation of their professions, their perception of technological threat rationally increases.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Teknoloji Kabul Modeli · Yapay Zekâ Kaygısı · Teknolojik Determinizm

Abstract

This study aims to examine the artificial intelligence (AI) anxiety levels among communication faculty students, the future professionals of the media industry, within the context of the Technology Acceptance Model (TAM). Employing a quantitative research design, data were collected via a questionnaire, and the effects of demographic variables (gender, age, department, income level, AI usage time) on AI anxiety sub-dimensions (Learning, Job Replacement, Sociotechnical Blindness, AI Configuration) were analyzed using independent samples t-test, ANOVA, and Tukey tests. The findings reveal that the analyzed demographic variables create statistically significant differences (p< .05) in anxiety levels. According to the analysis results, female participants exhibited higher anxiety levels within the context of the gender variable; while it was determined that as students' age increases, employment anxiety is replaced by ontological and configurational AI anxiety. Among communication disciplines, Public Relations and Publicity students were found to be the most anxious group regarding professional substitution. Furthermore, contrary to traditional assumptions in the literature, the professional anxiety of participants in the lower-income group was significantly lower than those in higher-income groups. Paradoxically, heavy users of AI tools (5-7 hours daily) exhibited significantly higher levels of unemployment and learning anxiety compared to light users. These paradoxical findings indicate that as communication students' practical experience with generative AI deepens and they realize the transformation of their professions, their perception of technological threat rationally increases.

Özet

Bu çalışmanın amacı, geleceğin medya profesyonelleri olan iletişim fakültesi öğrencilerinin yapay zekâ (YZ) kaygı düzeylerini Teknoloji Kabul Modeli (TKM) bağlamında incelemektir. Nicel araştırma tasarımının kullanıldığı çalışmada, veriler anket tekniği ile toplanmış; demografik değişkenlerin (cinsiyet, yaş, bölüm, gelir düzeyi, YZ kullanım süresi) YZ kaygı alt boyutları (Öğrenme, İş Değiştirme, Sosyoteknik Körlük, YZ Yapılandırması) üzerindeki etkisi bağımsız örneklem t-testi, tek yönlü varyans analizi (ANOVA) ve Tukey testleri ile ölçülmüştür. Bulgular; analiz edilen demografik değişkenlerin kaygı üzerinde istatistiksel olarak anlamlı farklılıklar (p< .05) olduğunu göstermektedir. Analiz sonuçlarına göre, cinsiyet değişkeni bağlamında kadın katılımcıların kaygı düzeyleri daha yüksek bulunurken; öğrencilerin yaşı ilerledikçe istihdam kaygısının yerini ontolojik ve biçimsel YZ kaygısına bıraktığı saptanmıştır. İletişim disiplinleri arasında özellikle Halkla İlişkiler ve Tanıtım Bölümü öğrencilerinin mesleki ikame konusunda fakülte genelindeki en kaygılı grup olduğu belirlenmiştir. Ayrıca literatürdeki geleneksel teknoloji kabullerinin aksine, alt gelir grubundaki katılımcıların mesleki kaygılarının üst gelir gruplarına kıyasla daha düşük olduğu ve YZ araçlarını günlük 5-7 saat gibi yoğun bir seviyede kullanan öğrencilerin, az kullananlara oranla işsizlik ve öğrenme kaygılarını anlamlı düzeyde daha yüksek hissettikleri tespit edilmiştir. Bu paradoksal bulgular, iletişim öğrencilerinin üretken YZ pratikleri derinleştikçe ve mesleklerinin dönüşümünü fark ettikçe, teknolojik tehdit algılarının da rasyonel bir temelde yükseldiğini ortaya koymaktadır.

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Cite This Article

Yaman, D., Aksoy, S. (2026). Artificial Intelligence Anxiety in the Context of the Technology Acceptance Model: A Study on Communicatıon Faculty Students. Medya ve Kültürel Çalışmalar Dergisi, Cilt: 8 Sayı: 1, 59–95. https://doi.org/10.55055/mekcad.1913633

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References (34)

  1. Amichai-Hamburger, Y. (2009). Technology and psychological well-being. Cambridge University Press. https://doi.org/10.1017/CBO9780511581446
  2. Akkaya, B., Özkan, A. & Özkan, H. (2021). Yapay Zekâ Kaygı (YZK) Ölçeği: Türkçeye uyarlama, geçerlik ve güvenirlik çalışması. Alanya Akademik Bakış, 5 (2), 1125-1146 DOI: 10.29023/alanyaakademik.833668
  3. Brosnan, M. J. (1998). Technophobia: The psychological impact of information technology. Routledge.
  4. Büyüköztürk, Ş. (2006). Veri analizi el kitabı. Ankara: Pagem Akademi Yayıncılık.
  5. Byrne, B. M. (2010). Structural equation modeling with amos: Basic concepts, applications, and programming. New York: Routledge.
  6. Creemers, R. (2018). China's social credit system: An evolving practice of control. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3175792
  7. 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
  8. Davis, F. D., Bagozzi, R. P. & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35 (8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
  9. DeVellis, R. F. (2017). Scale Development: Theory and Applications (4th ed.). Thousand Oaks, CA: Sage.
  10. Feng, Q. (2022). Analysis of technological determinism and social constructionism. Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022) (1391-1394). Atlantis Press. https://doi.org/10.2991/assehr.k.220504.252
  11. Fırat, M. (2023). What ChatGPT means for universities: Perceptions of scholars and students. Journal of Applied Learning and Teaching, 6 (1), 57-63. https://doi.org/10.37074/jalt.2023.6.1.22
  12. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, ıntention and behaviour: An ıntroduction to theory and research. Reading. MA: Addison-Wesley.
  13. George, D. & Mallery, P. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 update. Boston: Allyn & Bacon.
  14. Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13 (7), 692. https://doi.org/10.3390/educsci13070692
  15. Ha, J. G., Page, T. & Thorsteinsson, G. (2011). A study on technophobia and mobile device design. International Journal of Contents, 7 (2), 17-25. https://doi.org/10.5392/IJoC.2011.7.2.017
  16. Hair, J. F. & J. W. Black & B. J. Babin & E. R. Anderson (2010). Multivariate data analysis (7th. Edition). Edinburgh: Pearson Education Limited.
  17. Héder, M. (2021). AI and the resurrection of technological determinism. Információs Társadalom, 21 (2), 119-130. https://doi.org/10.22503/inftars.XXI.2021.2.8
  18. Johnson, D. G. ve Verdicchio, M. (2017). AI anxiety. Journal of the Association for Information Science and Technology, 68 (9), 2267-2270. https://doi.org/10.1002/asi.23867
  19. Kaya, A. Y., Ata, F. & Bursa, A. (2022). İletişim fakülteleri müfredatında dijitalleşme: Gazetecilik ile radyo, sinema ve televizyon bölümü eğitimindeki dijital derslerin analizi. Akdeniz Üniversitesi İletişim Fakültesi Dergisi, (39), 1-23. https://doi.org/10.31123/akil.1144098
  20. Khasawneh, O. Y., & Bellamy, A. (2014). Technophobia: An exploratory study. Computers in Human Behavior, 30, 11-12.
  21. Kline, R. B. (2011). Principles and practice of structural equation modeling (5th Edition). New York: The Guilford Press.
  22. Kruger, J. & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77 (6), 1121–1134. https://doi.org/10.1037/0022-3514.77.6.1121
  23. Kuyucu, M. (2016). Kullanımlar ve doyumlar perspektifinden radyo dinleme alışkanlıkları ve doyumları. Proceedings of SOCIOINT 2016 3rd International Conference on Education, Social Sciences and Humanities, 296- 325.
  24. McLuhan, M. (1995). Understanding media: The extensions of man. Cambridge: MIT Press.
  25. McLuhan, M., & Fiore, Q. (1967). The medium is the massage. London: Penguin Books.
  26. Nomura, T., Suzuki, T., Kanda, T. & Kato, K. (2006). Measurement of anxiety toward robots. 15th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN06) (372-377). IEEE. https://doi.org/10.1109/ROMAN.2006.314462
  27. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
  28. Oksanen, A., Savolainen, I., Savela, N. & Oksanen-Särelä, K. (2020). Artificial intelligence in the workplace: Does AI anxiety exist? Robotics, 9 (4), 108. https://doi.org/10.3390/robotics9040108
  29. Özdamar, K. (2002). Paket Programlar ile İstatistiksel Veri Analizi. Eskişehir: Kaan Kitabevi.
  30. Tavakol, M., & Dennick, R. (2011). Making Sense of Cronbach’s Alpha. International Journal of Medical Education, 2, 53-55. http://dx.doi.org/10.5116/ijme.4dfb.8dfd
  31. Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46 (2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  32. 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
  33. Wang, Y. Y. & Wang, Y. S. (2019). Development and validation of an artificial intelligence anxiety scale: an initial application in predicting motivated learning behavior. Interactive Learning Environments, 1–16. https://doi.org/10.1080/10494820.2019.167488
  34. Williams, M. D., Rana, N. P. & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): A literature review. Journal of Enterprise Information Management, 28 (3), 443-488. https://doi.org/10.1108/JEIM-09-2014-0088