Developing and Validating an AI Literacy Scale for English Language Teachers: A Mixed-Methods Study

Abstract

The rapid integration of artificial intelligence (AI) into English language teaching (ELT) necessitates a specialized framework to assess teachers’ readiness to navigate these technologies. This study develops and validates an AI Literacy Scale tailored specifically for English language teachers, addressing the gap in existing frameworks that often lack specificity for ELT’s linguistic, cultural, and pedagogical demands of ELT. Through a four-phase mixed-methods approach (item generation, content validation, pilot testing, and factor analysis) the scale was refined to a psychometrically acceptable five-factor model: Understanding AI in Education, Proficiency in Using AI, Pedagogical Alignment, Ethical Awareness, and AI for Feedback and Assessment. Participants included 150 in-service English language teachers, all with at least five years of teaching experience, who demonstrated C2 proficiency in English according to the Common European Framework of Reference (CEFR). They were selected using purposive sampling to ensure a diverse representation across urban, semi-urban, and rural settings. Validated with 150 in-service teachers, the scale demonstrated strong fit indices (χ² = 140.174, df = 125, p = 0.167; CFI = 0.949; RMSEA = 0.032). This tool not only measures technical and ethical competencies but also guides professional development by identifying gaps in AI literacy. The study used exploratory and confirmatory factor analysis to ensure the scale's construct validity and reliability. By fostering reflective and equitable AI integration, the scale empowers teachers to enhance instruction while preserving learner-centered practices, contributing to the broader discourse on educational innovation in ELT.