A structural model of Vietnamese EFL teachers’ readiness to integrate AI in English language teaching
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Abstract
This study explores the readiness of English language teachers to integrate artificial intelligence into teaching, addressing the limited understanding of how competence, attitudes, and institutional support interact in this process. The objective was to determine the relative influence of these factors on teachers’ preparedness for AI adoption in language education. A survey of 312 teachers from public and private institutions was analyzed using descriptive statistics and structural equation modeling. Results indicated moderate competence and attitudes toward AI, but limited institutional support. Perceived competence was identified as the strongest predictor of readiness, followed by attitudes, with institutional support exerting a weaker yet significant influence. Younger teachers and those in private institutions reported higher readiness. The findings underscore the need for professional development that enhances teachers’ skills while ensuring systemic backing, thereby promoting sustainable integration of AI into language teaching practices.
Keywords: Artificial intelligence; English language teaching; institutional support; teacher competence; technology adoption
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