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#generative ai Dataset Open access

DEVELOPING SCHOOL STUDENTS' INTERCULTURAL COMMUNICATIVE COMPETENCE THROUGH ARTIFICIAL INTELLIGENCE TOOLS IN ENGLISH LANGUAGE EDUCATION

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

The rapid development of artificial intelligence (AI), particularly generative artificial intelligence (GenAI), is transforming the pedagogical landscape of foreign language education. However, the educational value of AI should not be reduced to grammar correction, vocabulary support, or automated text generation. In increasingly multicultural and digitally mediated communication environments, English language learners also need the ability to interpret cultural meanings, negotiate differences, adapt communicative behaviour to diverse contexts, and critically evaluate cultural information. Against this background, the present study examines the pedagogical potential of AI tools for developing school students’ intercultural communicative competence (ICC) in English as a Foreign Language (EFL) education. The study employs a qualitative conceptual research design based on critical analysis and synthesis of established ICC frameworks, the CEFR Companion Volume, recent systematic reviews of AI-supported language learning, and recent empirical research on GenAI-mediated intercultural interaction. The analysis identifies five pedagogically significant functions of AI: simulation of intercultural encounters, dialogic interaction, adaptive feedback, cultural comparison and reflection, and mediation across linguistic and cultural boundaries. On this basis, the study proposes an AI-Mediated Intercultural Learning Cycle (AI-MILC) consisting of five interconnected stages: cultural activation, AI-mediated interaction, cultural comparison, critical verification, and reflective transfer. The article argues that AI should function as a pedagogically controlled mediator rather than as an authoritative source of cultural knowledge. Particular attention is therefore given to cultural stereotyping, hallucinated information, algorithmic bias, learner overreliance, privacy, age appropriateness, and teacher mediation. The proposed framework provides a theoretically grounded basis for integrating AI into school-level EFL instruction while preserving the central role of human agency, critical thinking, and intercultural reflection.

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