Document Type : Original Research Paper-English Issue

Author

English Department, Faculty of Humanities, Shahid Rajaee Teacher Training University, Tehran, Iran

10.22061/tej.2026.12990.3369

Abstract

Background and Objectives: The integration of information and communication technologies (ICTs) into English as a foreign language (EFL) instruction is now a routine aspect of educational practice. It may be related to teachers’ motivation, emotional experiences, and professional well-being. Previous research has mainly focused on issues such as technology adoption, technical skills and attitudes toward ICT. Much less attention has been paid to the emotional consequences of technology use. In particular, positive emotions such as teaching enjoyment remain underexplored. Age may be especially relevant in this respect. The present study examined the relationships among ICT self-efficacy, ICT engagement, and teaching enjoyment among Iranian high school EFL teachers. The study tested whether ICT engagement mediates the relationship between ICT self-efficacy and teaching enjoyment. It also investigated whether age moderates both the direct and indirect associations among these variables.
Materials and Methods: A cross-sectional correlational design was employed. Participants comprised 194 Iranian high school EFL teachers recruited through purposive sampling via social networking platforms. Participation was voluntary and anonymous. Teachers completed three self-report questionnaires assessing ICT self-efficacy, ICT engagement, and foreign language teaching enjoyment. All instruments were administered in Persian following a rigorous translation, back-translation, and content validation procedure. Teaching enjoyment was measured using a scale capturing personal enjoyment, student-related enjoyment, and collegial enjoyment. ICT engagement assessed teachers’ behavioral, cognitive, motivational, and social involvement with digital technologies. ICT self-efficacy measured teachers’ perceived capability to use ICT for instructional, professional, and communicative purposes. Age was operationalized as a categorical variable. Before analysis, data were screened for normality, multicollinearity, and suitability for parametric procedures. Structural equation modeling and regression-based analyses were conducted to test mediation, moderation, and moderated mediation associations. Indirect associations were evaluated using bootstrapped confidence intervals to ensure robust estimation of conditional relationships.
Findings: The results indicated that ICT self-efficacy was positively associated with both ICT engagement and teaching enjoyment. ICT engagement was also positively associated with teaching ICT self-efficacy and teaching enjoyment. Age significantly moderated the relationship between ICT engagement and teaching enjoyment. Among younger teachers, higher levels of ICT engagement were associated with greater teaching enjoyment. Among older teachers, this relationship was weak and not statistically significant. ICT self-efficacy was negatively related to ICT engagement among older teachers. Moderated mediation analyses further showed that ICT engagement mediated the relationship between ICT self-efficacy and teaching enjoyment only among younger teachers. For older teachers, the indirect association did not reach statistical significance. After accounting for engagement, the relationship between ICT self-efficacy and teaching enjoyment is partially moderated by age.
Conclusions: These findings suggest that ICT engagement plays a crucial role in translating teachers’ ICT self-efficacy into teaching enjoyment, but this process is partially moderated by age. For younger teachers, engagement with technology appears to be an emotionally meaningful activity through which confidence in ICT use is associated with teaching enjoyment. For older teachers, ICT use may be more selective or instrumental, carrying less affective significance. The results underscore the importance of adopting an age-sensitive perspective in professional development and technology integration policies. Teaching enjoyment is associated with more than improving technical skills. It is also associated with meaningful, autonomy-supportive forms of ICT engagement that align with teachers’ pedagogical values and professional identities. Limitations include reliance on self-report measures, non-probability sampling and a cross-sectional design that precludes causal inference. Future research would benefit from longitudinal designs to explore how technology-related emotions are associated across teachers’ age groups and how contextual factors shape these experiences in diverse educational settings.

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© 2026 The Author(s).  This is an open-access article distributed under the terms and conditions of the Creative Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/)  

doi:10.1016/j.compedu.2018.09.009.
doi:10.1016/j.tate.2023.104318.
doi:10.1007/s10639-016-9552-8.
doi:10.1057/s41599-025-04524-5.
doi:10.1086/268109.
doi:10.1207/S15327825MCS0301_02.
doi:10.1177/0270467610380009.
[12] Lee ASH, Thi LS, Lin MH. Affective technology acceptance model: extending technology acceptance model with positive and negative affect. In: Knowledge management strategies and applications. London: IntechOpen; 2017. p. 147-165.
[14] Bandura A. Self-efficacy: the exercise of control. New York: WH Freeman; 1997.
[26] Csikszentmihalyi M. Flow: the psychology of optimal experience. New York: Harper & Row; 1990.
doi:10.1037/0003-066X.56.3.218.
[34] Selwyn N. Is technology good for education? Cambridge: Polity Press; 2016.
[35] Cuban L. Oversold and underused: computers in the classroom. Cambridge (MA): Harvard University Press; 2001.
[39] Joo YJ, Park S, Lim E. Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. J Educ Technol Soc. 2018;21(3):48-59.
[41] Huberman AM. The lives of teachers. London: Cassell; 1993.
[43] Howard SK, Mozejko A. Teachers: technology, change and resistance. In: Knezek G, Christensen R, editors. Teaching and digital technologies. Cambridge: Cambridge University Press; 2015. p. 307-317.
doi:10.1016/j.compedu.2017.11.009.
[46] Aref A, Aref K. The barriers of educational development in rural areas of Iran. Indian J Sci Technol. 2012;5(2):2191-2193.
[47] Ahmadi S, Hosseini SM, Shirbagi N. A systematic literature review of ICT in the educational system of Iran. Sch Adm. 2023;10(4):109-135.
doi:10.31470/2309-1797-2022-32-1-29-50.
[49] Frenzel AC. Teacher emotions. In: Linnenbrink-Garcia EA, Pekrun R, editors. International handbook of emotions in education. New York: Routledge; 2014. p. 494-519.
doi:10.1016/j.compedu.2009.05.001.
[55] Dewaele JM, Li C. Emotions in second language acquisition: a critical review and research agenda. Foreign Lang World. 2020;196(1):34-49.
doi:10.3390/educsci13101001.
[59] Tabachnick BG, Fidell LS. Using multivariate statistics. 7th ed. Harlow: Pearson Education; 2019.
[60] Kline RB. Principles and practice of structural equation modeling. 5th ed. New York: Guilford Press; 2023.
doi:10.1037/0003-066X.55.1.5.
doi:10.1017/S0261444825000205.
doi:10.1016/j.stueduc.2020.100982.
doi:10.6007/IJARBSS/v8-i8/4611.
[66] Sang G, Valcke M, van Braak J, Tondeur J. Explaining teachers’ intention to use technology: a path analysis model. Educ Inf Technol. 2010;15(4):301-319. doi:10.1007/s10639-010-9119-2.
[67] Aiken LS, West SG. Multiple regression: testing and interpreting interactions. Thousand Oaks (CA): Sage Publications; 1991.
[68] Hayes AF. Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. 3rd ed. New York: Guilford Press; 2022.
[71] DeVellis RF. Scale development: theory and applications. 4th ed. Thousand Oaks (CA): Sage Publications; 2016.
[72] Hair JF, Hult GTM, Ringle CM, Sarstedt M. A primer on partial least squares structural equation modeling (PLS-SEM). 3rd ed. Thousand Oaks (CA): Sage Publications; 2022.
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