Speaker
Description
Abstract:
The rapid integration of artificial intelligence into language classrooms has drawn increasing attention to AI literacy in education, yet its measurement in ESL/EFL contexts remains largely underexplored. Recent systematic reviews (e.g., Lintner, 2024; Jin et al., 2026) have broadly mapped AI literacy scales without ESL/EFL-specific analysis, while emerging EFL-focused reviews (e.g., Wulan & Santosa, 2026; Tsioukas & Kostas, 2026) have addressed teacher readiness or framework alignment rather than instrument-level evidence. To our knowledge, no review has systematically examined how AI literacy is conceptualized and measured in ESL/EFL contexts or the extent to which existing instruments demonstrate adequate measurement properties. This study addresses this gap through a systematic review of AI literacy instruments developed, adapted, validated, or applied in ESL/EFL contexts. Guided by PRISMA 2020 and a COSMIN-informed psychometric appraisal approach, searches are being conducted across ERIC, Scopus, and Google Scholar, supplemented by targeted searches, using Boolean combinations of AI literacy, ESL/EFL, and measurement-related terms for studies published from 2019 onward. The review addresses three questions: what AI literacy instruments are currently used in ESL/EFL contexts; how these instruments conceptualize and measure AI literacy; and what evidence is reported for their measurement properties. Preliminary screening suggests a strong reliance on self-report measures, a concentration on higher education and EFL teacher populations, and limited validation evidence. The completed review aims to provide an instrument-level map of AI literacy measurement in ESL/EFL contexts, offering practical guidance for instrument selection and adaptation and contributing a TESOL-specific perspective to AI literacy assessment.
