English Language Education and AI Literacy Role: Perspectives from EFL Faculty Members

Abstract

This mixed-methods study investigates the multidimensional role of AI literacy in English Language Teaching (ELT) among 50 faculty members in Saudi preparatory year programs, of whom 47 provided complete survey responses for quantitative analysis. Employing an explanatory sequential design grounded in the Technological Pedagogical Content Knowledge (TPACK) and Technology-Organization-Environment (TOE) frameworks, the research compares standardized AI literacy scores derived from a 17-item AI Awareness and Understanding (AIAU) scale with a single self-reported AI literacy rating and explores the structural determinants of adoption. Quantitative analysis showed a non-significant trend toward a perception-competence misalignment between self-reported and AIAU scale-based AI literacy scores F(2,44) = 2.83, p = 0.070, alongside stark demographic disparities: male faculty demonstrated significantly higher AI literacy than female colleagues (d = 1.11, p < 0.001), and faculty with more than 10 years of teaching experience outperformed those with 6–10 years F(1,45) = 11.31, p = 0.002, trends attributed to systemic access barriers rather than individual capability. Qualitative findings expose an “ethical competence paradox,” where faculty with high ethical concerns regarding data privacy (68.1%) and cultural misalignment (38.3%) demonstrate more sophisticated adoption reasoning. The study argues that institutional readiness—defined by equitable access, policy clarity, and tiered professional development—is more determinative of successful integration than technological sophistication. Recommendations include gender-intentional support structures and policy-grounded capacity building to align AI adoption with Vision 2030 goals.