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AI-Enhanced Corpus-Driven Pedagogy for Intercultural Communicative Competence Development: A Theoretical Model and Feasibility Study

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  • Mengyao Wang

Abstract

This study proposes and evaluates an AI-enhanced, corpus-driven pedagogical framework designed to foster intercultural communicative competence (ICC) among vocational college students. The model, termed AI-Mediated Reflective Intercultural Learning (AMRIL), integrates intercultural competence theory, data-driven learning, and AI-assisted feedback. Forty-two non-English majors participated in a small-scale feasibility implementation, which involved AI-supported noticing, reflection, and reconstruction tasks. Results indicate that students became more culturally aware, improved their pragmatic appropriateness in writing, and expressed higher satisfaction with AI-mediated feedback. Learners demonstrated clearer understanding of tone, politeness strategies, and intercultural conventions. The study concludes that the AMRIL framework provides a viable and theoretically grounded approach for applying AI to intercultural pedagogy in vocational education.

Suggested Citation

  • Mengyao Wang, 2026. "AI-Enhanced Corpus-Driven Pedagogy for Intercultural Communicative Competence Development: A Theoretical Model and Feasibility Study," English Language Teaching, Canadian Center of Science and Education, vol. 19(1), pages 1-50, January.
    • Handle: RePEc:ibn:eltjnl:v:19:y:2026:i:1:p:50
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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