International Journal of Practical and Pedagogical Issues in English Education

International Journal of Practical and Pedagogical Issues in English Education

Exploring the Chain Mediation Model of Iranian EFL Teachers' Cognition, Attitudes, Skills, and Application of Generative AI in Language Teaching: A PLS-SEM Analysis

Document Type : Original Article

Author
English Department of Ilam University
10.22034/ijpie.2026.581556.1224
Abstract
With the increasing use of AI technologies in education, it has become important to examine teachers' readiness and ability to use these technologies. Despite numerous studies on the application of generative AI in language teaching, limited research has examined the sequential relationships among teachers' cognition, attitudes, AI skills, and pedagogical application and reflection, particularly in the Iranian EFL context. The present study aimed to examine these relationships from the perspective of language teachers. This study was conducted with a quantitative approach using partial least squares structural equation modeling (PLS-SEM). Data were collected from 300 Iranian EFL teachers through an online questionnaire in October and November 2025. The research instrument consisted of 11 items in four dimensions: cognitive, attitudinal, skill, and application and reflection, adapted from Zhen (2025). The results of the model evaluation showed that the structural model had an acceptable fit (SRMR = 0.047, NFI = 0.892). Path analysis revealed that the cognitive dimension had a strong positive relationship with teachers’ attitudes (β = 0.669, t = 21.022, p < 0.001), indicating that greater AI cognition was associated with more positive attitudes. Furthermore, positive attitudes significantly enhanced AI skills (β = 0.573, t = 15.092, p < 0.001), which in turn positively influenced pedagogical application and reflection (β = 0.588, t = 14.428, p < 0.001).
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Articles in Press, Accepted Manuscript
Available Online from 30 August 2026

  • Receive Date 13 May 2026
  • Revise Date 10 August 2026
  • Accept Date 30 August 2026