Examining the relationship between teacher candidates' techno-stress levels and information and communication technologies competencies
Downloads
This study was conducted using a quantitative correlational survey model to determine pre-service teachers' levels of technostress and their information and communication technology (ICT) competencies and to examine them according to various variables. Data were collected from 427 pre-service teachers in their third and fourth years from nine programs at the Faculty of Education, Akdeniz University, in 2024–2025. Measurements were made using the Teacher Technostress Level Determination Scale and the ICT Competence Scale; following descriptive statistics and normality checks, Spearman correlation, Mann–Whitney U, and Kruskal–Wallis H tests were applied. The findings showed that ICT competencies were low, technostress was high, and there was a negative, significant relationship between the two variables. Only in instructional design did males score higher. Technostress was higher and digital competency was lower in the Science Education and Guidance programs. The use of technological tools and mobile devices has been linked to higher ICT competencies and lower levels of technostress. The findings suggest that enhancing digital competencies may be a critical factor in alleviating technostress.
Downloads
Akay, C., & İnci̇k, E. Y. (2017). A comprehensive analysis on technopedagogical education competency and technology perception of pre-service teachers: Relation, levels and views. Contemporary Educational Technology, 8(3), 232–248. https://doi.org/10.30935/cedtech/6198
Aktan, O., & Toraman, Ç. (2022). The relationship between technostress levels and job satisfaction of teachers within the COVID-19 period. Education and Information Technologies, 27, 10429–10453. https://doi.org/10.1007/s10639-022-11027-2
Alastor, E., Guillén-Gámez, F. D., & Ruiz-Palmero, J. (2025). Study on the digital competencies of prospective pre-school and primary school teachers and the influence of gender and academic performance. Journal of Technology and Science Education, 15(1), 64–77. https://doi.org/10.3926/jotse.2856
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
Alkan, M. F., & Emmioğlu-Sarıkaya, E. (2018). Adaptation of preservice teachers’ information and communication technology competencies scale into Turkish culture. Bartın University Journal of Faculty of Education, 7(2), 665–691. https://doi.org/10.14686/buefad.375745
Atanasoff, L., & Venable, M. A. (2017). Technostress: Implications for adults in the workforce. The Career Development Quarterly, 65(4), 326–338. https://doi.org/10.1002/cdq.12111
Bağcı, H., & Atar, C. (2019). An investigation of pre-service English teachers’ self-efficacy in web pedagogical content knowledge. Sakarya University Journal of Education, 9(3), 550-566.
Basarmak, U., Hamutoglu, N. B., & Sahin, Y. L. (2020). The effects of perceived internal and external barriers to technology integration on lifelong learning tendencies among teacher candidates. International Online Journal of Educational Sciences, 12(2), 169–187. https://doi.org/10.15345/iojes.2020.02.011
Berrett, T. B., Bordino, A., Duisenbekov, D., Jaffe, S., & Samworth, R. J. (2025). MCARtest: Optimal nonparametric testing of missing completely at random (R package version 1.3). https://doi.org/10.32614/CRAN.package.MCARtest
Bordi, L., & Nuutinen, S. (2023). Experiences of technostressors during the Covid-19 pandemic among Finnish comprehensive school teachers. Seminar.net. https://doi.org/10.7577/seminar.5257
Brod, C. (1984). Technostress: The human cost of the computer revolution. Addison-Wesley. Retrieved from: https://archive.org/details/technostresshuma0000brod
Broos, A. (2005). Gender and information and communication technologies (ICT) anxiety: Male self-assurance and female hesitation. CyberPsychology & Behavior, 8(1), 21–31. https://doi.org/10.1089/cpb.2005.8.21
Büyüköztürk, Ş., Çokluk, Ö., & Köklü, N. (2018). Sosyal bilimler için istatistik (7. baskı). Pegem Akademi.
Cahapay, M., & Bangoc, N. F. (2021). Technostress, work performance, job satisfaction, and career commitment of teachers amid COVID-19 crisis in the Philippines. International Journal of Educational Research and Innovation. 16, 260-275. https://doi.org/10.46661/ijeri.6145
Çalışkan, M., & Çoklar, A. N. (2022). Öğretmen adaylarının teknostres düzeylerinin belirlenmesi. Anadolu Üniversitesi Eğitim Fakültesi Dergisi, 6(3), 341-354. https://doi.org/10.34056/aujef.1106453
Çetin, Ç. (2017). Din kültürü ve ahlak bilgisi öğretmen adaylarının bilgi ve iletişim teknolojilerine yönelik öz-yeterlik algı düzeylerinin incelenmesi. Journal of Human Sciences, 14(4), 4753–4767. https://doi.org/10.14687/jhs.v14i4.5081
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.
Dai, Y. (2023). An empirical study on English preservice teachers’ digital competence regarding ICT self-efficacy, collegial collaboration and infrastructural support. Heliyon, 9(11), e19538. https://doi.org/10.1016/j.heliyon.2023.e19538
Dong, Y., Xu, C., Chai, C. S., & Zhai, X. (2020). Exploring the structural relationship among teachers’ technostress, technological pedagogical content knowledge (TPACK), computer self‑efficacy and school support. The Asia‑Pacific Education Researcher, 29, 147–157. https://doi.org/10.1007/s40299-019-00461-5
Estrada-Muñoz, C., Vega-Muñoz, A., Castillo, D., Müller-Pérez, S., & Boada-Grau, J. (2021). Technostress of Chilean teachers in the context of the COVID-19 pandemic and teleworking. International Journal of Environmental Research and Public Health, 18(10), 5458. https://doi.org/10.3390/ijerph18105458
Feng, M., & Xia, X. (2023, March). Examining the association between pre‑service teachers’ self‑efficacy and TPACK competencies in online internships under COVID‑19. 2023 11th International Conference on Information and Education Technology (ICIET), 354–359. https://doi.org/10.1109/ICIET56899.2023.10111329
Fox, J. (2002). An R and S-Plus Companion to Applied Regression, SAGE Publications.
Gabbiadini, A., Paganin, G., & Simbula, S. (2023). Teaching after the pandemic: The role of technostress and organizational support on intentions to adopt remote teaching technologies. Acta Psychologica, 236, 103936. https://doi.org/10.1016/j.actpsy.2023.103936
Galorport, M. U., & Estela, C. (2022). A structural equation model of technological pedagogical content knowledge (TPACK), school culture and ICT literacy on the technostress of science teachers. International Journal of Scientific Research, 11(12), 10-14. https://doi.org/10.36106/ijsr/3226651
Galustyan, O. V., Vyunova, N., Komarova, E. P., Shusharina, E., Gamisonija, S. S., & Sklyarova, O. N. (2019). Formation of media competence of future teachers by means of ICT and mobile technologies. International Journal of Interactive Mobile Technologies, 13(11), 184–196. https://doi.org/10.3991/ijim.v13i11.11350
Gökbulut, B. (2021). Öğretmenlerin teknostres ve teknopedagojik yeterlikleri arasındaki ilişki. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 22(1), 472–496. https://dergipark.org.tr/tr/pub/kefad/issue/60452/929603
Harakchiyska, T. (2023). Self-assessment of pre-service english teachers’ digital competence. MIPRO 2023 Proceedings. https://doi.org/10.23919/MIPRO57284.2023.10159858
JASP Team. (2024). JASP (Version 0.18) [Computer software]. https://jasp-stats.org
Kerby, D. S. (2014). The simple difference formula: An approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3. https://doi.org/10.2466/11.IT.3.3
Khlaif, Z. N., Sanmugam, M., Joma, A. I., Odeh, A., & Barham, K. (2022). Factors influencing teacher’s technostress experienced in using emerging technology: A qualitative study. Technology, Knowledge and Learning, 28(3), 865–899 https://doi.org/10.1007/s10758-022-09607-9
Koğar, H., & Yılmaz Koğar, E. (2016). Comparison of different estimation methods for categorical and ordinal data in confirmatory factor analysis. Journal of Measurement and Evaluation in Education and Psychology, 7(2), 351–363.
Korkmaz, S., Goksuluk, D., & Zararsiz, G. (2014). MVN: An R package for assessing multivariate normality. The R Journal, 6(2), 151–162.
König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608–622. https://doi.org/10.1080/02619768.2020.1809650
Malaquias, F. F. de O., & de Souza Júnior, R. C. (2023). Technostress, burnout and job satisfaction among teachers during the COVID-19 pandemic: The role of literacy facilitation. Information Development. https://doi.org/10.1177/02666669231208100
Marrinhas, D., Santos, V., Salvado, C., Pedrosa, D., & Pereira, A. (2023). Burnout and technostress during the COVID-19 pandemic: The perception of higher education teachers and researchers. Frontiers in Education, 8, 1144220 https://doi.org/10.3389/feduc.2023.1144220
McGarr, O., & McDonagh, A. (2020). Exploring the digital competence of pre-service teachers on entry onto an initial teacher education programme in Ireland. Irish Educational Studies, 40(3), 1-14. https://doi.org/10.1080/03323315.2020.1800501
Nang, A. F. M., Maat, S. M., & Mahmud, M. S. (2022). Teacher technostress and coping mechanisms during COVID 19 pandemic: A systematic review. Pegem Journal of Education and Instruction, 12(2), 200–212. https://doi.org/10.47750/pegegog.12.02.20
Panisoara, I. O., Lazar, I., Panisoara, G., Chirca, R., & Ursu, A. S. (2020). Motivation and continuance intention towards online instruction among teachers during the COVID-19 pandemic: The mediating effect of burnout and technostress. International Journal of Environmental Research and Public Health, 17(21), 8002. https://doi.org/10.3390/ijerph17218002
R Core Team. (2023). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/
Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B. S., & Tu, Q. (2008). The consequences of technostress for end users in organizations: Conceptual development and empirical validation. Information Systems Research, 19(4), 417–433. https://doi.org/10.1287/isre.1070.0165
Saltan, F., Bozbey, Ç., Bozyokuş, F., Koçak, S., & Özdemir, M. (2024). Investigation of classroom teachers' technostress levels in terms of ICT competence perceptions and various variables. Journal of Teacher Education and Lifelong Learning, 6(1), 91-99. https://doi.org/10.51535/tell.1429701
Suárez-Rodríguez, J., Almerich, G., Orellana, N., & Díaz-García, I. (2018). A basic model of integration of ICT by teachers: Competence and use. Educational Technology Research and Development, 66(5), 1165-1187. https://doi.org/10.1007/s11423-018-9591-0
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(1). https://doi.org/10.7577/seminar.2281
Şen, S., & Yıldırım, İ. (2021). Eğitimde araştırma yöntemleri: Nicel, nitel ve karma yaklaşımlar (2. Baskı). Pegem Akademi.
Tabachnick, B. G., & Fidell, L. S. (2012). Using multivariate statistics (6th ed.). Pearson.
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
The jamovi project. (2023). Jamovi (Version 2.3) [Computer software]. https://www.jamovi.org
Tonbuloglu, I., & Kiyici, M. (2018). Opinions of preservice teachers on their acceptance of the use of mobile technologies for teaching purposes. Journal of Education and Training Studies, 6(6), 94–110. https://doi.org/10.11114/jets.v6i6.3230
Tondeur, J., Aesaert, K., Pynoo, B., van Braak, J., Fraeyman, N., & Erstad, O. (2017). Developing a validated instrument to measure preservice teachers’ ICT competencies: Meeting the demands of the 21st century. British Journal of Educational Technology, 48(2), 462–472. https://doi.org/10.1111/bjet.12380
Tondeur, J., Scherer, R., Baran, E., Siddiq, F., Valtonen, T., & Sointu, E. (2019). Teacher educators as gatekeepers: Preparing the next generation of teachers for technology integration in education. British Journal of Educational Technology, 50(3), 1189–1209. https://doi.org/10.1111/bjet.12748
Wang, X., & Li, B. (2019). Technostress among university teachers in higher education: A study using multidimensional person-environment misfit theory. Frontiers in Psychology, 10, 1791. https://doi.org/10.3389/fpsyg.2019.01791
Wang, Z., Zhang, L., Wang, X., Liu, L., & Lv, C. (2023). Navigating technostress in primary schools: A study on teacher experiences, school support, and health. Frontiers in Psychology, 14, 1-16. https://doi.org/10.3389/fpsyg.2023.1267767
Copyright (c) 2026 Osman Akhan, Gökhan Ayçilek

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Jurnal Cakrawala Pendidikan, Jurnal Ilmiah Pendidikan, with ISSN: 0216-1370, is published by the Institute of Education Development and Quality Assurance (LPPMP UNY). Cakrawala Pendidikan has been recently has been re-accredited by Indonesian Ministry of Education and Culture decision Number 230/E/KPT/2022 which is valid for five years since enacted on 30 December 2022.





