Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels

Ali Kaya; Yusuf Levent Şahin; Gülçin Elif Turan; Kadriye Kobak

doi:10.24106/kefdergi.1909844

EN TR

Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels

Abstract

The aim of this study is to examine the relationship between secondary school teachers’ perceptions of artificial intelligence literacy and their perceived levels of technostress. Technostress refers to the stress experienced by individuals, particularly educators, due to rapid technological developments, while artificial intelligence literacy involves teachers’ ability to understand, use, and apply artificial intelligence technologies. The study employed a quantitative research method and was conducted with a total of 311 secondary school teachers working in public schools in the central districts of Eskişehir during the 2023–2024 academic year. The research aimed to determine teachers’ levels of artificial intelligence literacy and technostress, as well as to explore the effects of technological developments on educators. Data analysis focused on identifying the relationship between teachers’ artificial intelligence literacy levels and their perceived technostress levels. The findings revealed that teachers experienced moderate levels of technostress and that technostress levels did not differ significantly according to demographic variables. Additionally, the results indicated that teachers’ low levels of artificial intelligence literacy were not significantly related to their technostress levels. It is believed that the findings of this study contribute valuable insights for shaping educational policies and designing professional development programs that support teachers in adapting to technological advancements.

Keywords

artificial intelligence, literacy, teachers, technostress

Öğretmenlerin Yapay Zekâ Okuryazarlığı ile Teknostres Düzeyleri Arasındaki İlişkinin İncelenmesi

Abstract

Bu araştırmanın amacı, ortaokul öğretmenlerinin yapay zekâ okuryazarlığı algıları ile algıladıkları teknostres düzeyleri arasındaki ilişkiyi incelemektir. Teknostres, özellikle eğitimcilerin hızlı teknolojik gelişmeler nedeniyle yaşadıkları stresi ifade ederken; yapay zekâ okuryazarlığı, öğretmenlerin yapay zekâ teknolojilerini anlama, kullanma ve uygulama becerilerini kapsamaktadır. Araştırma, nicel araştırma yöntemiyle yürütülmüş olup 2023–2024 eğitim-öğretim yılında Eskişehir ili merkez ilçelerinde bulunan devlet okullarında görev yapan toplam 311 ortaokul öğretmeni ile gerçekleştirilmiştir. Çalışmada öğretmenlerin yapay zekâ okuryazarlığı ve teknostres düzeyleri belirlenmiş, bu iki değişken arasındaki ilişki incelenmiştir. Bulgular, öğretmenlerin orta düzeyde teknostres yaşadıklarını ve teknostres düzeylerinin demografik değişkenlere göre anlamlı farklılık göstermediğini ortaya koymuştur. Ayrıca öğretmenlerin düşük düzeydeki yapay zekâ okuryazarlığı ile teknostres düzeyleri arasında anlamlı bir ilişki bulunmamıştır. Elde edilen sonuçların, eğitim politikalarının geliştirilmesine ve öğretmenlere yönelik mesleki gelişim programlarının planlanmasına katkı sağlayacağı düşünülmektedir.

Keywords

teknostres, öğretmenler, yapay zeka, okuryazarlık

References

Al-Abdullatif, A. M. (2024). Modeling teachers’ acceptance of generative artificial intelligence use in higher education: The role of AI literacy, intelligent TPACK, and perceived trust. Education Sciences, 14(11), 1209. https://doi.org/10.3390/educsci14111209
Al-Fudail, M., & Mellar, H. (2008). Investigating teacher stress when using technology. Computers & Education, 51(3), 1103–1110. https://doi.org/10.1016/j.compedu.2007.11.004
Aldemir, T., Bicer, A., Kilinc, S., Moon, J., & Kwok, M. (2025). Exploring emergent AI-TPACK competencies in a two-week AI literacy module for preservice teachers. Teaching and Teacher Education, 168, 105231. https://doi.org/10.1016/j.tate.2025.105231
Arık, G., & Seferoğlu, S. S. (2020). Eğitimde yapay zekâ çalışmaları: Araştırma eğilimleri, karşılaşılan zorluklar ve çözüm önerileri [Artificial intelligence studies in education: Research trends, challenges, and proposed solutions]. In V. Nabiyev & A. K. Erümit (Eds.), Eğitimde yapay zekâ: Kuramdan uygulamaya [Artificial intelligence in education: From theory to practice] (pp. 260–280). Pegem Akademi. https://doi.org/10.14527/9786257052986
Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological antecedents and implications. MIS Quarterly, 35(4), 831–858. https://doi.org/10.2307/41409963
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
Borko, H. (2004). Professional development and teacher learning: Mapping the terrain. Educational Researcher, 33(8), 3–15. https://doi.org/10.3102/0013189X033008003
Brod, C. (1984). Technostress: The human cost of the computer revolution. Addison-Wesley.
Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2022.100118

Çoklar, A. N., Efilti, E., & Şahin, Y. L. (2017). Defining teachers’ technostress levels: A scale development. Journal of Education and Practice, 8(21), 28–41. https://eric.ed.gov/?id=ED579062
Çoklar, A. N., Efilti, E., Şahin, Y. L., & Akçay, A. (2016). Determining the reasons of technostress experienced by teachers: A qualitative study. Turkish Online Journal of Qualitative Inquiry, 7(2), 71–96. https://doi.org/10.17569/tojqi.96082
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. https://doi.org/10.2307/249688
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
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
Facer, K., & Selwyn, N. (2021). Digital technology and the futures of education: Towards “non-stupid” optimism [Paper commissioned for the UNESCO Futures of Education report]. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000377071
Gökbulut, B. (2021). Öğretmenlerin teknostres ve teknopedagojik yeterlikleri arasındaki ilişki [The relationship between teachers’ technostress and technopedagogical competencies]. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 22(1), 472–496. https://doi.org/10.29299/kefad.929603
Huck, S. W. (2012). Reading statistics and research (6th ed.). Pearson.
Humble, N., & Mozelius, P. (2019). Teacher-supported AI or AI-supported teachers? In P. Griffiths & M. N. Kabir (Eds.), Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics (ECIAIR 2019) (pp. 157–164). Academic Conferences and Publishing International Limited.
Johnston, K. (2021). Key skills in the context of twenty-first-century teaching and learning. In D. Murchan & K. Johnston (Eds.), Curriculum change within policy and practice: Reforming second-level education in Ireland (pp. 85–104). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-50707-7_5
Kaplan-Rakowski, R., Grotewold, K., Hartwick, P., & Papin, K. (2023). Generative AI and teachers’ perspectives on its implementation in education. Journal of Interactive Learning Research, 34(2), 313–338. https://www.learntechlib.org/primary/p/222363/
Karaoğlan Yılmaz, F. G., & Yılmaz, R. (2023). Yapay zekâ okuryazarlığı ölçeğinin Türkçeye uyarlanması [Adaptation of the artificial intelligence literacy scale into Turkish]. Bilgi ve İletişim Teknolojileri Dergisi, 5(2), 172–190. https://doi.org/10.53694/bited.1376831
Knowles, M. S., Holton, E. F., III, & Swanson, R. A. (2015). The adult learner: The definitive classic in adult education and human resource development (8th ed.). Routledge.
Kong, S. C., Cheung, W. M. Y., & Zhang, G. (2021). Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds. Computers & Education: Artificial Intelligence, 2, 100026. https://doi.org/10.1016/j.caeai.2021.100026
Korucu, A. T., & Biçer, H. (2020). Eğitimde yapay zekânın rolleri ve eğitsel yapay zekâ uygulamaları [The roles of artificial intelligence in education and educational artificial intelligence applications]. In V. Nabiyev & A. K. Erümit (Eds.), Eğitimde yapay zekâ: Kuramdan uygulamaya [Artificial intelligence in education: From theory to practice] (pp. 38–56). Pegem Akademi. https://doi.org/10.14527/9786257052986
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
Li, L., & Wang, X. (2021). Technostress inhibitors and creators and their impacts on university teachers’ work performance in higher education. Cognition, Technology & Work, 23(2), 315–330. https://doi.org/10.1007/s10111-020-00625-0
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727
Longman, S. M. D. (2013). A comparison of the perceptions of technostress experienced by teachers versus technology used by teachers in elementary education in a southeastern school district [Doctoral dissertation, Southeastern Louisiana University]. ERIC. https://eric.ed.gov/?id=ED558333
Ministry of National Education. (2018). 2023 eğitim vizyonu [2023 education vision]. https://www.gmka.gov.tr/dokumanlar/yayinlar/2023_E%C4%9Fitim%20Vizyonu.pdf
Ministry of National Education. (2023, August 24). İlköğretim kurumları (ilkokul ve ortaokul) haftalık ders çizelgesi [Weekly course schedule for primary education institutions (primary and lower secondary schools)] (Board Decision No. 43). Millî Eğitim Bakanlığı Tebliğler Dergisi, 86(2789- Suppl. 2), 1420–1422. https://dhgm.meb.gov.tr/tebligler-dergisi/2023/2789_Agustos_2023_ek-2.pdf
Ministry of National Education. (2024). Eğitimde kullanılan yapay zekâ araçları: Öğretmen el kitabı [Artificial intelligence tools used in education: Teacher’s handbook]. General Directorate of Innovation and Educational Technologies. https://yegitek.meb.gov.tr/meb_iys_dosyalar/2024_07/12172521_meb_nek_yapay_zek_araclari_12072024_web.pdf
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). AI literacy: Definition, teaching, evaluation and ethical issues. Proceedings of the Association for Information Science and Technology, 58(1), 504–509. https://doi.org/10.1002/pra2.487
Penado Abilleira, M., Rodicio-García, M.-L., Ríos-de Deus, M. P., & Mosquera-González, M. J. (2021). Technostress in Spanish university teachers during the COVID-19 pandemic. Frontiers in Psychology, 12, Article 617650. https://doi.org/10.3389/fpsyg.2021.617650
Salanova, M., Llorens, S., Cifre, E., & Nogareda, C. (2006). Tecnoestrés: Concepto, medida e intervención psicosocial [Technostress: Concept, measurement, and psychosocial intervention] (Nota Técnica de Prevención No. 730). Instituto Nacional de Seguridad e Higiene en el Trabajo. https://www.insst.es/documents/94886/196283/NTP%2B730%2BTecnoestr%C3%A9s.%2Bconcepto%2C%2Bmedida%2Be%2Bintervenci%C3%B3n%2Bpsicosocial.pdf
Schiavo, G., Businaro, S., & Zancanaro, M. (2024). Comprehension, apprehension, and acceptance: Understanding the influence of literacy and anxiety on acceptance of artificial intelligence. Technology in Society, 77, 102537. https://doi.org/10.1016/j.techsoc.2024.102537
Syvänen, A., Mäkiniemi, J.-P., Syrjä, S., Heikkilä-Tammi, K., & Viteli, J. (2016). When does the educational use of ICT become a source of technostress for Finnish teachers? Seminar.net, 12(2), 95–109. https://doi.org/10.7577/seminar.2281
Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson.
Tarafdar, M., Cooper, C. L., & Stich, J.-F. (2019). The technostress trifecta—techno eustress, techno distress and design: Theoretical directions and an agenda for research. Information Systems Journal, 29(1), 6–42. https://doi.org/10.1111/isj.12169
Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328. https://doi.org/10.2753/MIS0742-1222240109

Details

Primary Language

English

Subjects

Instructional Technologies, Teacher Education and Professional Development of Educators, Education Policy

Journal Section

Research Article

Authors

Ali Kaya
0009-0004-6607-7999
Türkiye

Yusuf Levent Şahin
0000-0002-3261-9647
Türkiye

Gülçin Elif Turan ^*
0000-0003-0976-6873
Türkiye

Kadriye Kobak
0000-0003-4909-416X
Türkiye

Publication Date

July 31, 2026

Submission Date

March 14, 2026

Acceptance Date

July 21, 2026

Published in Issue

Year 2026 Volume: 34 Number: 3

DOI

https://doi.org/10.24106/kefdergi.1909844

IZ

https://izlik.org/JA35KL69RM

APA

Kaya, A., Şahin, Y. L., Turan, G. E., & Kobak, K. (2026). Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels. Kastamonu Education Journal, 34(3), 698-719. https://doi.org/10.24106/kefdergi.1909844

AMA

1.Kaya A, Şahin YL, Turan GE, Kobak K. Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels. Kastamonu Education Journal. 2026;34(3):698-719. doi:10.24106/kefdergi.1909844

Chicago

Kaya, Ali, Yusuf Levent Şahin, Gülçin Elif Turan, and Kadriye Kobak. 2026. “Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels”. Kastamonu Education Journal 34 (3): 698-719. https://doi.org/10.24106/kefdergi.1909844.

EndNote

Kaya A, Şahin YL, Turan GE, Kobak K (July 1, 2026) Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels. Kastamonu Education Journal 34 3 698–719.

IEEE

[1]A. Kaya, Y. L. Şahin, G. E. Turan, and K. Kobak, “Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels”, Kastamonu Education Journal, vol. 34, no. 3, pp. 698–719, July 2026, doi: 10.24106/kefdergi.1909844.

ISNAD

Kaya, Ali - Şahin, Yusuf Levent - Turan, Gülçin Elif - Kobak, Kadriye. “Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels”. Kastamonu Education Journal 34/3 (July 1, 2026): 698-719. https://doi.org/10.24106/kefdergi.1909844.

JAMA

1.Kaya A, Şahin YL, Turan GE, Kobak K. Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels. Kastamonu Education Journal. 2026;34:698–719.

MLA

Kaya, Ali, et al. “Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels”. Kastamonu Education Journal, vol. 34, no. 3, July 2026, pp. 698-19, doi:10.24106/kefdergi.1909844.

Vancouver

1.Ali Kaya, Yusuf Levent Şahin, Gülçin Elif Turan, Kadriye Kobak. Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels. Kastamonu Education Journal. 2026 Jul. 1;34(3):698-719. doi:10.24106/kefdergi.1909844

Kastamonu Education Journal is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Examining the Relationship Between Teachers’ Artificial Intelligence Literacy and Technostress Levels

Abstract

Keywords

Öğretmenlerin Yapay Zekâ Okuryazarlığı ile Teknostres Düzeyleri Arasındaki İlişkinin İncelenmesi

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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