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Artificial Intelligence Assisted Dual-Teacher Model Constructing Practices

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  • Wang, Min

Abstract

This study explores the development and practical application of an innovative AI-assisted dual-teacher model for foreign language education. By introducing a dynamic framework that combines human educators with AI-driven teaching assistants, the research establishes a three-phase collaborative approach designed to meet the cognitive, linguistic, and cultural demands of language learners. The approach capitalizes on the complementary strengths of both human teachers and AI tools, offering a personalized and responsive learning experience. The findings of the study underscore the effectiveness of this model in leveraging AI's advanced capabilities, such as semantic generation and data analytics, to streamline and automate routine instructional tasks. This automation allows human instructors to focus their expertise on higher-level educational objectives, including fostering intercultural communication, nurturing emotional engagement, and cultivating critical thinking skills among students. As a result, the dual-teacher model significantly enhances the quality of foreign language instruction by diversifying teaching methods and creating opportunities for individualized learning trajectories. Furthermore, this approach promotes the development of digital literacy in both students and educators. The integration of AI technology empowers learners to navigate a variety of digital tools, while teachers are better equipped to manage and interpret the data generated by these systems. By blending the strengths of both human instruction and AI support, this model is positioned to transform traditional language education, providing a richer, more inclusive, and adaptive learning environment.

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Handle: RePEc:dba:ejacia:v:1:y:2025:i:2:p:110-117
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