Modeling K–12 Teachers’ Adoption of AI Chatbots for Perceptual-Motor Language Instruction: Evidence From Chinese Teachers’ Pronunciation and Handwriting Teaching

BackgroundAI chatbots are increasingly used in language education, but their adoption for pronunciation and handwriting instruction remains underexplored. This study examined factors influencing Chinese K-12 foreign language teachers' adoption of AI chatbots for these perceptual-motor teaching tasks. MethodsSurvey data were collected from 615 teachers, with 526 valid responses analyzed using confirmatory factor analysis and structural equation modeling.ResultsTeachers mainly used AI chatbots for lesson planning and assignment design, while direct use for pronunciation and handwriting instruction was limited. Perceived ease of use positively predicted perceived usefulness, trust, self-efficacy, and behavioral intention. Perceived value strongly predicted perceived usefulness. Trust and self-efficacy predicted behavioral intention, which predicted actual use, whereas perceived usefulness had no significant direct effect on behavioral intention.DiscussionAdoption was influenced more by usability, trust, and implementation confidence than by perceived usefulness alone.ConclusionTeacher training should emphasize evaluating AI-generated feedback and translating chatbot outputs into reliable corrective guidance and repeated practice.