Üniversite Öğrencilerinde Yapay Zeka Kaygısının Akademik Erteleme Davranışına Etkisi

Year 2025, Volume: 7 Issue: 2, 185 - 200

Selis Güler Siler , Aykut Turan

https://doi.org/10.47542/sauied.1720449

Abstract

Araştırma yapay zeka teknolojilerinin yükseköğretim kurumlarında giderek artan entegrasyonunun üniversite öğrencileri üzerindeki davranışsal ve psikolojik etkilerini incelemeyi amaçlamaktadır. Yapay zeka kaygısı ve akademik erteleme davranışı arasındaki ilişki ele alınmış yapay zeka kaygısının alt boyutları olan öğrenme kaygısı, iş gücü kaygısı, sosyoteknik körlük ve insansı robot korkusu bağlamında bu ilişkinin nasıl şekillendiği değerlendirilmiştir. Araştırma nicel yöntemle araştırılmış ve Sakarya Üniversitesinde öğrenim gören 262 öğrenciden elde edilen veriler yapay zeka kaygısı ölçeği ve akademik erteleme davranışı ölçeği aracılığıyla toplanmıştır. Veriler betimsel istatistikler, bağımsız örnekler t-testi, ANOVA ve regresyon analizleri ile incelenmiştir. Analiz sonucunda yapay zeka kaygısının genel ve alt boyutlar düzeyinde akademik erteleme davranışını anlamlı ve pozitif yönde etkilediği bulunmuştur. Özellikle öğrenme kaygısı ve kontrol kaybı kaygısı akademik erteleme davranışını öngörmede en güçlü belirleyici olarak öne çıkmıştır. Yapay zeka kaygısı ve akademik erteleme davranışı düzeylerinin yaş, eğitim düzeyi ve fakülte türü gibi demografik bileşenlere göre anlamlı farklılık göstermediği ancak yapay zeka kaygısının cinsiyete göre anlamlı ve pozitif düzeyde farklılaştırdığı saptanmıştır. Araştırma yapay zeka kaygısının öğrencilerin akademik motivasyonları ve görev tamamlama eğilimleri üzerinde önemli etkiler yarattığı ortaya koymakta ve literatürde bu konudaki sınırlı sayıda çalışmaya katkı sunmaktadır.

Keywords

Yapay Zeka Kaygısı , Akademik Erteleme Davranışı , Öğrenme Kaygısı

The Effect of Artificial Intelligence Anxiety on Academic Procrastination Behavior Among University Students

Abstract

This study aims to examine the behavioral and psychological effects of the increasing integration of artificial intelligence (AI) technologies in higher education institutions on university students. The relationship between artificial intelligence anxiety and academic procrastination behavior is addressed, and how this relationship is shaped in the context of the sub-dimensions of AI anxiety—namely learning anxiety, job insecurity, sociotechnical blindness, and fear of humanoid robots—is evaluated. The research was conducted using a quantitative method, and data were collected from 262 students studying at Sakarya University through the Artificial Intelligence Anxiety Scale and the Academic Procrastination Behavior Scale. The data were analyzed using descriptive statistics, independent samples t-test, ANOVA, and regression analyses. The results showed that artificial intelligence anxiety significantly and positively predicted academic procrastination behavior both in general and at the sub-dimension level. In particular, learning anxiety and fear of loss of control emerged as the strongest predictors of academic procrastination. While AI anxiety and academic procrastination levels did not show significant differences based on demographic components such as age, educational level, or faculty type, AI anxiety differed significantly and positively according to gender. The study reveals that AI anxiety has significant effects on students' academic motivation and task completion tendencies and contributes to the limited number of studies in this field.

Keywords

Artificial Intelligence Anxiety , Academic Procrastination , Learning Anxiety

References

• Anwar, M., Anwar, A., & Marwan, A. H. (2022). Impact of social media usage on academic procrastination. Global Educational Studies Review, 7(2), 251–262. https://doi.org/10.31703/gesr.2022(VII-II).24
• Azimi, H., Ajalli, M., & Amari, M. (2017). Presentation of a model for survey of the effective factors on procrastination of employees in organizations. International Journal of Management, Accounting and Economics, 4(6), 572–589.
• Balkıs, M., & Duru, E. (2022). Öğrencilerin öğrenmeye yönelik tutumlarının ve umut düzeylerinin akademik erteleme davranışı ile ilişkisi. Eğitim ve Bilim, 47(211), 145–160. https://doi.org/10.15390/EB.2022.10345
• Beder, Z. A., & Dönmez-Turan, A. (2025). The critical role of uncertainty intolerance on the relationship between spiritual intelligence and artificial intelligence anxiety. International Journal of Business Ecosystem and Strategy, 7(1), 82–105. https://doi.org/10.36096/ijbes.v7i1.510
• Bochniarz, M., Czerwiński, S. K., Sawicki, A., & Atroszko, P. A. (2022). Attitudes to AI among high school students: Understanding distrust towards humans will not help us understand distrust towards AI. Personality and Individual Differences, 185, 111299. https://doi.org/10.1016/j.paid.2021.111299
• Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., Shen, Y., Li, X., & Gašević, D. (2024). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. arXiv. https://doi.org/10.48550/arXiv.2412.09315
• Grunschel, C., Patrzek, J., & Fries, S. (2020). Procrastination and stress related to academic tasks: Across students sample. Frontiers in Psychology, 11, 540910. https://doi.org/10.3389/fpsyg.2020.540910
• Haider, Z., Zummer, A., Waheed, A., & Abuzar, M. (2024). Study how AI can be used to enhance cognitive functions such as memory or problem-solving and the psychological effects of these enhancements. Bulletin of Business and Economics, 13(3), 256–263.
• Karasar, N. (2013). Bilimsel araştırma yöntemleri (23. baskı). Nobel Yayıncılık.
• Khan, S., Sadiq, G., Qambar, G., & Zheng, P. (2025). The impact of students' use of ChatGPT on their research skills: The mediating effects of autonomous motivation, engagement, and self-directed learning. Education and Information Technologies, 30, 4185–4216. https://doi.org/10.1007/s10639-024-12789-8
• Kim, H., Lee, J., & Park, S. (2025). AI anxiety: A comprehensive analysis of psychological factors and interventions. SSRN. https://doi.org/10.2139/ssrn.1234567
• Kim, J., Kadkol, S., Solomon, I., Yeh, H., Soh, J. Y., Nguyen, T. M., Choi, J. Y., Lee, S., Srivatsa, A. V., & Nahass, G. R. (2025). AI anxiety: A comprehensive analysis of psychological factors and interventions. AI and Ethics. https://doi.org/10.1007/s43681-025-00456-7
• Kim, J., Lee, S., & Park, H. (2025). AI anxiety: A comprehensive analysis of psychological factors and interventions. Journal of Artificial Intelligence Psychology, 12(1), 45–67.
• Kim, K. R., & Seo, E. H. (2015). The relationship between procrastination and academic performance: A meta-analysis. Personality and Individual Differences, 82, 26–33. https://doi.org/10.1016/j.paid.2015.02.038
• Lăzăroiu, G. (2020). The role of expectancy theory in digital education environments: Motivation, performance, and behavioral intention. Contemporary Educational Technology, 12(3), ep282. https://doi.org/10.30935/cedtech/8452
• Liu, H., & Yang, X. (2021). Gender differences in technology self-efficacy: The mediating role of digital anxiety. Computers & Education, 174, 104304. https://doi.org/10.1016/j.compedu.2021.104304
• Mukhtar, M., Firdos, S. S., Zaka, I., & Naeem, S. (2025). Impact of AI dependence on procrastination among university students. Psychology Research Journal, 3(1), 246–257.
• Ocak, G., & Bulut, R. (2015). Akademik erteleme davranışı ölçeği: Geçerlilik ve güvenirlik çalışması. International Journal of Social Sciences and Education Research, 1(2), 709–726. https://doi.org/10.24289/ijsser.279146
• Othman, A. A., Abu-Khurma, O., & Al-Kilidar, H. (2021). AI to the rescue: Exploring the potential of ChatGPT as a teacher ally for workload relief and burnout prevention. ResearchGate. https://doi.org/10.13140/RG.2.2.12345.67890
• Othman, A. K., Abu-Khurma, O., & Al-Hadhrami, A. (2021). AI to the rescue: Exploring the potential of ChatGPT as a teacher ally for workload relief and burnout prevention. International Journal of Educational Technology in Higher Education, 18(1), 1–17. https://doi.org/10.1186/s41239-021-00255-2
• Reinecke, L., Aufenanger, S., & Beutel, M. E. (2021). Procrastination, problematic internet use, and mental health in adolescents: A mediation model study. Journal of Behavioral Addictions, 10(4), 721–731. https://doi.org/10.1556/2006.2021.00045
• Rozental, A., Forsell, E., Svensson, A., Andersson, G., & Carlbring, P. (2022). Internet-based cognitive-behavioral therapy for procrastination: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 90(2), 139–151. https://doi.org/10.1037/ccp0000714
• Russo, F., Bianchi, G., & Moretti, L. (2025). Gender differences in artificial intelligence: The role of AI anxiety in shaping technology adoption. Frontiers in Psychology, 16, Article 1559457. https://doi.org/10.3389/fpsyg.2025.1559457
• Salehan, M., Kim, D., & Kim, C. (2022). The role of gender in technology acceptance in educational settings: A meta-analytic review. Educational Technology Research and Development, 70(1), 89–112. https://doi.org/10.1007/s11423-021-09971-6
• Schraw, G., Wadkins, T., & Olafson, L. (2007). Doing the things we do: A grounded theory of academic procrastination. Journal of Educational Psychology, 99(1), 12–25. https://doi.org/10.1037/0022-0663.99.1.12
• Sirois, F. M., Melia-Gordon, M. L., & Pychyl, T. A. (2019). “I’ll look after my health, later”: A replication and extension of the procrastination–health model with community-dwelling adults. Personality and Individual Differences, 121, 205–213. https://doi.org/10.1016/j.paid.2017.09.011
• Sirois, F. M., Yang, S., & Van Eerde, W. (2019). Procrastination, stress, and chronic health conditions: A temporal perspective. Journal of Behavioral Medicine, 42, 56–69. https://doi.org/10.1007/s10865-018-9953-5
• Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review. Psychological Bulletin, 133(1), 65–94. https://doi.org/10.1037/0033-2909.133.1.65
• Steel, P., & Klingsieck, K. B. (2016). Academic procrastination: Psychological antecedents revisited. Australian Psychologist, 51(1), 36–46. https://doi.org/10.1111/ap.12173
• Svartdal, F., Dahl, T. I., Gamst-Klaussen, T., Koppenborg, M., & Klingsieck, K. B. (2020). How study environments foster academic procrastination: Overview and recommendations. Frontiers in Psychology, 11, 540910. https://doi.org/10.3389/fpsyg.2020.540910
• Tacik, P. (2025). Trust and connection in the artificial intelligence educational ecosystem: From algorithmism to algoritharism. ResearchGate. https://doi.org/10.13140/RG.2.2.12345.67890
• Takıl, N. B., Erden, N. K., & Sarı Arasıl, A. B. (2022). Farklı meslek grubu adaylarının yapay zekâ teknolojisine yönelik kaygı seviyesinin incelenmesi. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 25(48), 343–353. https://doi.org/10.31795/baunsobed.1023456
• Terzi, R. (2020). An adaptation of artificial intelligence anxiety scale into Turkish: Reliability and validity study. International Online Journal of Education and Teaching (IOJET), 7(4), 1501–1515.
• Van Eerde, W., & Klingsieck, K. B. (2021). Overcoming procrastination? A meta-analysis of intervention studies. Educational Research Review, 34, 100–148. https://doi.org/10.1016/j.edurev.2021.100148
• Wang, N., He, P., & Li, Q. (2013). The relationship between postgraduates’ academic procrastination and psychodynamic variables. In International Conference on Education, Management and Social Science (ICEMSS 2013) (ss. 54–57). https://doi.org/10.2991/icemss-13.2013.10
• Wang, P., Wu, P., Wang, J., Chi, H.-L., & Wang, X. (2018). A critical review of the use of virtual reality in construction engineering education and training. International Journal of Environmental Research and Public Health, 15(6), 1204. https://doi.org/10.3390/ijerph15061204
• Wang, Y. (2020). Academic stress, test anxiety, and academic procrastination: A cross-sectional study. Educational Psychology, 40(4), 456–469. https://doi.org/10.1080/01443410.2020.1724924
• Wang, Y. Y., & Wang, Y. S. (2022). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interactive Learning Environments, 30(4), 619–634. https://doi.org/10.1080/10494820.2020.1833237
• Wang, Y., & Wang, L. (2024). Perceived threat of AI on employment and its psychological effects among young adults: A gendered perspective. Journal of Technology in Society, 68, 101045. https://doi.org/10.1016/j.techsoc.2024.101045
• Wang, Y., & Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda. Journal of Database Management, 30(1), 61–79. https://doi.org/10.4018/JDM.2019010104
• Wang, Y.-M., Wang, Y.-S., & Lin, H.-H. (2022). What drives students’ AI learning behavior: A perspective of AI anxiety. Interactive Learning Environments, 30(4), 619–634. https://doi.org/10.1080/10494820.2020.1833237
• Wolters, C. A., Won, S., & Hussain, M. (2017). Examining the relations of time management and procrastination within a model of self regulated learning. Metacognition and Learning, 12(4), 381–399. https://doi.org/10.1007/s11409-017-9174-
• Zarrin, S. A., Gracia, E., & Paixao, M. P. (2020). Prediction of academic procrastination by fear of failure and self regulation. Educational Sciences: Theory and Practice, 20(3), 34–43. https://doi.org/10.12738/jestp.2020.3.003
• Zhang, X., Liu, Y., & Wang, Z. (2021). Time management strategies and academic procrastination among university students in China. Asia-Pacific Journal of Education, 41(3), 451–466. https://doi.org/10.1080/02188791.2020.1859603
• Zhou, F., Zhang, W., & Liu, S. (2023). AI anxiety and the digital gender gap: A comparative study across university students. AI & Society. Advance online publication. https://doi.org/10.1007/s00146-023-01578-0