Mixed-methods study shows cultural-linguistic congruence influences emotional responses of EFL teachers using AI tools, suggesting implications for technology implementation.
This mixed-methods sequential explanatory study examined emotional responses of Vietnamese English foreign language (EFL) teachers implementing artificial intelligence (AI) tools and investigated cultural–linguistic congruence as a moderator of these responses. Analysis of 326 participants revealed distinct emotional patterns characterized predominantly by cautious optimism, with teachers progressing through exploration, implementation challenge, and adaptation phases. Hierarchical multiple regression and Hayes’ PROCESS macro examined moderation effects, while thematic analysis identified five emotional themes. Cultural–linguistic congruence significantly moderated the relationship between control–value appraisals and emotional responses, with language alignment emerging as the strongest moderating dimension. Teachers with high cultural–linguistic congruence demonstrated substantially stronger positive associations between control appraisals and enjoyment compared to those with low congruence. Qualitative analysis identified five themes: technological fascination versus instructional uncertainty, professional identity negotiation, student response sensitivity, hierarchical approval seeking, and technological inequity awareness. These findings advance theoretical understanding by demonstrating how control–value appraisals operate within culturally specific interpretive frameworks that condition emotional impacts during technology implementation. The research suggests educational technology implementation should incorporate cultural–linguistic considerations to enhance teacher emotional engagement, particularly in non-Western contexts implementing technologies developed within different cultural–linguistic frameworks.
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Nguyễn Hữu Hoàng (2025) studied this question.
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