Psychological barriers and pedagogical implications of artificial intelligence-induced anxiety among English lecturers in higher education

Abstract

The growing integration of Generative Artificial Intelligence (AI) into higher education has provided new pedagogical opportunities while also raising psychological concerns among university lecturers. This study explored Artificial Intelligence-Induced Anxiety (AIA) among Iranian English language lecturers. In so doing, the multidimensional structure of AIA was investigated examining moderating role of gender. A cross-sectional survey design was employed with a sample of 450 English lecturers from Iranian higher education institutions. Data were collected using an adapted version of Liu and Liu’s (2025) 21-item AIA Scale, estimating five dimensions: technical proficiency, job displacement, technological support, student experience, and research development. Confirmatory factor analysis (CFA) supported the five-factor structure of the instrument in the Iranian context. To further evaluate its cultural appropriateness, cognitive interviews were conducted with 45 participants. Descriptive analyses indicated moderate overall levels of AIA, with job displacement constituting the primary source of anxiety. Independent-samples t-tests revealed gender differences with female lecturers reporting higher levels of anxiety related to technical proficiency and technological support. Multiple regression and Structural Equation Modeling (SEM) further demonstrated that gender meaningfully moderated the relationships between overall AIA and both technical proficiency and technological support, whereas no moderating effects were found for the remaining dimensions. A second-order SEM exhibited appropriate model fit and identified job displacement as the strongest indicator of the higher-order AIA construct. The results demonstrate the context-dependent nature of AI-related anxiety among resource-limited higher education organizations. In addition, the research draws attention to the necessity of developing gender-sensitive AI literacy resources for students. Overall, the study makes an important contribution to existing knowledge on AI-Induced Anxiety as it provides a multidimensional model that can be used to understand AIA across different cultures. This study provides one of the first empirical investigations of AI-induced anxiety (AIA) among Iranian EFL lecturers in higher education. Job displacement is identified as the most significant source of AIA in resource-constrained EFL contexts. Gender moderates AIA specifically in technical proficiency and technological support, with female lecturers reporting higher anxiety. The study contributes a validated, multidimensional framework for understanding AIA beyond general technostress or foreign language anxiety. Gender-sensitive AI literacy programs are proposed as targeted interventions to reduce AIA in Middle Eastern educational settings.