Contextualizing Teacher AI Literacy in English Language Teaching: Developing an AI Literacy Framework for College English Teachers

Abstract

As generative artificial intelligence continues to be integrated into higher education, teacher AI literacy has become a critical foundation for promoting AI-enhanced English language teaching. However, existing frameworks have been developed primarily within general educational contexts, with insufficient attention to the disciplinary characteristics of college English teaching. Employing a qualitative framework development design, this study established an initial analytical framework based on TPACK, AI-TPACK, the AI Literacy Framework, DigCompEdu, and the UNESCO AI Competency Framework for Teachers, and then refined it through semi-structured interviews with eight university English teachers and thematic analysis. The findings reveal that college English teachers' AI literacy consists of five dimensions, namely cognitive understanding, AI application, pedagogical integration, reflective development, and ethical responsibility, which are further elaborated into fifteen contextualized domains. The findings further demonstrate that teacher AI literacy is not a simple transfer of general AI competencies but a contextualized competency system shaped by language teaching objectives, principles of language learning, and teachers' professional knowledge, as college English teachers emphasized competencies closely related to English teaching practices, including professional evaluation of AI-generated language content, AI-supported activity design, instructional feedback analysis, and guidance for students' responsible AI use. This study extends the contextualized perspective of teacher AI literacy research and provides theoretical insights and practical implications for college English teacher professional development, teacher training, and AI-enhanced language education.