Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale

Barzan Batuk; Nuri Türk; Mustafa Özmen

EN TR

Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale

Abstract

Artificial Intelligence (AI) tools are actively used by academics and students. ChatGPT stands out among the AI tools most used by undergraduate and graduate students. ChatGPT offers students idea development and academic writing support for their assignments and research. This study examined the validity and reliability of the ChatGPT Usage Scale in Turkish culture. The ChatGPT Usage Scale consists of three subscales: Academic Writing Aid, Academic Task Support, and Reliance and Trust. The study participants consisted of 332 undergraduate and graduate students. Reliability analyses conducted on the ChatGPT Usage Scale show that Cronbach's alpha and McDonald's omega values ranged from .87 to .96. According to the results of the study's Confirmatory Factor Analysis (CFA), the fit indices of the ChatGPT Usage Scale were determined to be good. The results of the scale's item discriminant analysis and item-total correlation values were found to be at acceptable levels. Furthermore, the scale's high item factor loadings and convergent validity demonstrate its construct validity. All research findings demonstrate that the Turkish version of the ChatGPT Usage Scale is reliable and valid. Therefore, this scale is expected to make significant contributions to future studies on the integration of AI and ChatGPT into the Turkish education system.

Keywords

ChatGPT Usage, Artificial Intelligence, Scale Adaptation

ChatGPT Kullanım Ölçeği'nin Türkçe Versiyonunun Psikometrik Özellikleri

Abstract

Yapay Zeka (YZ) araçları, akademisyenler ve öğrenciler tarafından aktif olarak kullanılmaktadır. Lisans ve lisansüstü öğrencilerinin en çok kullandığı AI araçları arasında ChatGPT ön plana çıkmaktadır. ChatGPT, öğrencilere ödevlerinde ve araştırmalarında fikir geliştirme ve akademik yazım desteği sunmaktadır. Bu çalışmada, ChatGPT Kullanım Ölçeği'nin Türk kültüründe geçerlilik ve güvenilirliği incelenmiştir. ChatGPT Kullanım Ölçeği, Akademik Yazım Yardımı, Akademik Ödev Desteği ile Bağlılık ve Güven olmak üzere üç alt boyuttan oluşmaktadır. Araştırmanın katılımcıları, 332 lisans ve lisansüstü öğreciden oluşmaktadır. ChatGPT Kullanım Ölçeği üzerinde yürütülen güvenirlik analizleri, sonuçları Cronbach alfa ve McDonald's omega değerlerinin .87-.96 arasında değiştiğini göstermektedir. Çalışmanın Doğrulayıcı Faktör Analizi (DFA) sonuçlarına göre, ChatGPT Kullanım Ölçeği'nin uyum indekslerinin iyi düzeyde olduğu saptanmıştır. Ölçeğin madde ayırt edicilik analizi sonuçları ve madde toplam korelasyon değerlerinin kabul edilebilir seviyede olduğu görülmüştür. Ayrıca ölçeğin madde faktör yüklerinin yüksek olması ve benzeşim geçerliliğini sağlaması, yapı geçerliliğini sağladığını göstermektedir. Araştırmanın tüm bulguları, ChatGPT Kullanım Ölçeği'nin Türkçe formunun güvenilir ve geçerli olduğunu göstermektedir. Dolayısla, bu ölçeğin Türk eğitim sistemine AI ve ChatGPT’nin entagrasyonu konusunda yapılacak çalışmalara önemli katkılarda bulunması beklenmektedir.

Keywords

ChatGPT Kullanımı, Yapay Zeka, Ölçek Uyarlama

References

Araujo, T., Helberger, N., Kruikemeier, S., and De Vreese, C. H. (2020). In AI we trust? Perceptions about automated decision-making by artificial intelligence. AI & Society. 35, 611–623. https://doi.org/10.1007/s00146-019-00931-w
Athanassopoulos, S., Manoli, P., Gouvi, M., Lavidas, K., & Komis, V. (2023). The use of ChatGPT as a learning tool to improve foreign language writing in a multilingual and multicultural classroom. Advances in Mobile Learning Educational Research, 3(2), 818-824.
Banh, L., & Strobel, G. (2023). Generative artificial intelligence. Electron Markets, 33, 63. https://doi.org/10.1007/s12525-023-00680-1
Batuk, B. Aktu, Y., & Türk, N. (2025). Yapay Zeka Kabul Ölçeği Kısa Formu’nun Psikometrik Özelliklerinin İncelenmesi. Çukurova Sosyal Bilimler Enstitüsü Dergisi, 34(Uygarlığın Dönüşümü-Sosyal Bilimlerin Bakışıyla Yapay Zekâ), 438-451. https://doi.org/10.35379/cusosbil.1695975
Bayram. N. (2013). Yapısal eşitlik modellemesine giriş (3.baskı). Ezgi Kitapevi.
Brislin, R. W., Lonner, W. J., & Thorndike, R. M. (1973). Cross-cultural research methods. JohnWiley & Sons
Büyüköztürk, Ş. (2018). Faktör analizi: Temel kavramlar ve ölçek geliştirmede kullanımı. Kuram ve Uygulamada Eğitim Yönetimi, 32(32), 470-483.
Büyüköztürk, Ş., Çakmak, E. K., Akgün, Ö. E., Karadeniz, Ş., Demirel, F. (2014). Bilimsel araştırma yöntemleri (18th ed.). Pegem Akademi Publications.
Can, A. (2020). Spss ile Bilimsel Araştırma Sürecinde Nicel Veri Analizi (9th Ed.). Ankara: Pegem Akademi.
Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023). MAILS-Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change-and meta-competencies. Computers in Human Behavior: Artificial Humans, 1(2), 100014. https://doi.org/10.1016/j.chbah.2023.100014

Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3),464–504. https://doi.org/10.1080/10705510701301834
Chen, L. (2017). International competitiveness and the fourth industrial revolution. Entrepreneurial Business and Economics Review, 5(4), 111-133. https://doi.org/10.15678/eber.2017.050405
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
Çobanoğulları, F., & Özbek, Ö. (2025). AI-powered language learning: Developing the chatGPT usage scale for foreign language learners. Education and Information Technologies, 1-18. https://doi.org/10.1007/s10639-025-13342-w
Denecke, K., Abd-Alrazaq, A., & Househ, M. (2021). Artificial Intelligence for Chatbots in Mental Health: Opportunities and Challenges. In: M. Househ, E. Borycki, & A. Kushniruk (Eds.), Multiple Perspectives on Arti ficial Intelligence in Healthcare: Opportunities and Challenges (pp. 115 128). Cham: Springer International Publishing.
F. S. (2023). Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT. Education Sciences, 13(9), 856. https://doi.org/10.3390/educsci13090856
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846
Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452–459. https://doi.org/10.1038/nature14541
Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2014). Exploratory factor analysis. Multivariate data analysis. Prentice Hall.
Hartley, K., Hayak, M., & Ko, U. H. (2024). Artificial intelligence supporting independent student learning: An evaluative case study of ChatGPT and learning to code. Education Sciences, 14(2), 120. https://doi.org/10.3390/educsci14020120
Huallpa, J. J. (2023). Exploring the ethical considerations of using Chat GPT in university education. Periodicals of Engineering and Natural Sciences, 11(4), 105-115. https://doi.org/10.21533/pen.v11.i4.200
Jackson, P. C. (2019). Introduction to artificial intelligence. Courier Dover Publications. https://doi.org/10.1007/s00146-016-0646-7
Janiesch, C., Zschech, P., & Heinrich, K. (2021). Machine learning and deep learning. Electronic Markets, 31(3), 685–695. https://doi.org/10.1007/s12525-021-00475-2
Karagöz, Y. (2021). Bilimsel araştırma yöntemleri ve yayın etiği (3.Baskı). Nobel.
Karasar, N. (2012). Bilimsel araştırma yöntemi. Nobel Yayınevi.
Kline, R. B. (2011). Principles and practice of structural equation modeling. NY: The Guilford Press.
Lester, J., Branting, K., & Mott, B. (2004). Conversational agents. The Practical Handbook of Internet Computing, 220–240.
Luger, G. F., & Chakrabarti, C. (2017). From Alan Turing to modern AI: practical solutions and an implicit epistemic stance. AI & Society, 32(3), 321-338.
Maral, S., Naycı, N., Bilmez, H., Erdemir, E. İ., & Satici, S. A. (2025). Problematic ChatGPT Use Scale: AI-Human Collaboration or Unraveling the Dark Side of ChatGPT. International Journal of Mental Health and Addiction, 1-27. https://doi.org/10.1007/s11469-025-01509-y
Mazı, A. (2025). Developing a primary school teacher attitude scale for the use of ChatGPT in mathematics education. Acta Psychologica, 261, 105729. https://doi.org/10.1016/j.actpsy.2025.105729
Mitchell, M. (2019). Artificial intelligence: A guide for thinking humans. Penguin UK
Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023). Challenges and opportunities of generative AI for higher education as explained by ChatGPT. Education sciences, 13(9), 856.
Nemt-Allah, M., Khalifa, W., Badawy, M., Elbably, Y., & Ibrahim, A. (2024). Validating the ChatGPT Usage Scale: psychometric properties and factor structures among postgraduate students. BMC psychology, 12(1), 497. https://doi.org/10.1186/s40359-024-01983-4
O’Shaughnessy, M. R., Schiff, D. S., Varshney, L. R., Rozell, C. J., & Davenport, M. A. (2023). What governs attitudes toward artificial intelligence adoption and governance? Science and Public Policy, 50(2), 161-176. https://doi.org/10.1093/scipol/scac056
Rahman, M. M., & Watanobe, Y. (2023). ChatGPT for Education and Research: Opportunities, Threats, and Strategies. Applied Sciences, 13(9), 5783. https://doi.org/10.3390/app13095783
Schwab, K. (2017). The Fourth Industrial Revolution. World Economic Forum.
Shrestha, N. (2021). Factor analysis as a tool for survey analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4-11
Su, J., & Yang, W. (2023). Unlocking the power of ChatGPT: A framework for applying generative AI in education. ECNU Review of Education, 6(3), 355-366. https://doi.org/10.1177/20965311231168423
Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics. Allyn and Bacon
Taktak, M. & Bafrali, G. (2025). ChatGPT usage scale in education: Validity and reliability study. International Journal of Technology in Education (IJTE), 8(1), 193-207. https://doi.org/10.46328/ijte.1024
TheTab. (202, November, 23). These are the Russell Group unis that have banned students from using ChatGPT. Retrieved Novemver 23, 2025, https://thetab.com/uk/2023/03/03/these-are-the-russell-group-unis-that-have-banned-students-from-using-chatgpt-297148
Türk, N., Batuk, B., Kaya, A., & Yıldırım, O. (2025). What Makes University Students Accept Generative Artificial Intelligence? A Moderated Mediation Model. BMC Psychology, 13, 1257. https://doi.org/10.1186/s40359-025-03559-2
UCL. (2025). Engaging with AI in your education and assessment. Retrieved Novemver 23, 2025, from https://www.ucl.ac.uk/students/exams-and-assessments/assessment-success-guide/engaging-ai-your-education-and-assessment
Velastegui, D., Pérez, M. L. R., & Garcés, L. F. S. (2023). Impact of Artificial Intelligence on learning behaviors and psychological well-being of college students. Salud, Ciencia y Tecnologia-Serie de Conferencias, 2, 343.
Wang, B., Rau, P.-L. P., & Yuan, T. (2022). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9), 1324–1337. https://doi.org/10.1080/0144929X.2022.2072768
Yilmaz, F. G. K., Yilmaz, R., & Ceylan, M. (2023). Generative artificial intelligence acceptance scale: A validity and reliability study. International Journal of Human–Computer Interaction, 1-13. https://doi.org/10.1080/10447318.2023.2288730
YOK. (2024). Üretken yapay zekânın bilimsel araştırma ve yayınlarda kullanımının etik boyut. Retrieved Novemver 23, 2025, from https://proje.yok.gov.tr/documentFiles/17539645334.Y%C3%BCksek%C3%B6%C4%9Fretimde%20%C3%BCretken%20yapay%20zeka%20kullan%C4%B1m%C4%B1-tr.pdf
Zhang, B. & Dafoe, A. (2019). Artificial intelligence: American attitudes and trends. Available at SSRN 3312874. https://doi.org/10.2139/ssrn.3312874

Details

Primary Language

English

Subjects

Psychological Foundations of Education

Journal Section

Research Article

Authors

Barzan Batuk ^*
0000-0002-1393-2814
Türkiye

Nuri Türk
0000-0002-7059-9528
Türkiye

Mustafa Özmen
0000-0001-9621-7498
Türkiye

Publication Date

December 31, 2025

Submission Date

November 28, 2025

Acceptance Date

December 29, 2025

Published in Issue

Year 2025 Volume: 4 Number: 2

IZ

https://izlik.org/JA82SD25ER

APA

Batuk, B., Türk, N., & Özmen, M. (2025). Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale. Siirt Sosyal Araştırmalar Dergisi, 4(2), 47-60. https://izlik.org/JA82SD25ER

AMA

1.Batuk B, Türk N, Özmen M. Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale. Siirt Sosyal Araştırmalar Dergisi. 2025;4(2):47-60. https://izlik.org/JA82SD25ER

Chicago

Batuk, Barzan, Nuri Türk, and Mustafa Özmen. 2025. “Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale”. Siirt Sosyal Araştırmalar Dergisi 4 (2): 47-60. https://izlik.org/JA82SD25ER.

EndNote

Batuk B, Türk N, Özmen M (December 1, 2025) Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale. Siirt Sosyal Araştırmalar Dergisi 4 2 47–60.

IEEE

[1]B. Batuk, N. Türk, and M. Özmen, “Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale”, Siirt Sosyal Araştırmalar Dergisi, vol. 4, no. 2, pp. 47–60, Dec. 2025, [Online]. Available: https://izlik.org/JA82SD25ER

ISNAD

Batuk, Barzan - Türk, Nuri - Özmen, Mustafa. “Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale”. Siirt Sosyal Araştırmalar Dergisi 4/2 (December 1, 2025): 47-60. https://izlik.org/JA82SD25ER.

JAMA

1.Batuk B, Türk N, Özmen M. Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale. Siirt Sosyal Araştırmalar Dergisi. 2025;4:47–60.

MLA

Batuk, Barzan, et al. “Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale”. Siirt Sosyal Araştırmalar Dergisi, vol. 4, no. 2, Dec. 2025, pp. 47-60, https://izlik.org/JA82SD25ER.

Vancouver

1.Barzan Batuk, Nuri Türk, Mustafa Özmen. Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale. Siirt Sosyal Araştırmalar Dergisi [Internet]. 2025 Dec. 1;4(2):47-60. Available from: https://izlik.org/JA82SD25ER

33994

This work is licensed under a Creative Commons Attribution-Non Commercial 4.0 International License.

Psychometric Properties of the Turkish Version of the ChatGPT Usage Scale

Abstract

Keywords

ChatGPT Kullanım Ölçeği'nin Türkçe Versiyonunun Psikometrik Özellikleri

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

IZ

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