The Teaching Transformation Enabled by Generative AI in Foreign Language Intercultural Education

DOI: https://doi.org/10.62517/jhet.202615428

Author(s)

Chen Qingxia

Affiliation(s)

Guangdong University of Science and Technology, Guangdong, China

Abstract

Generative large language models bring new opportunities, such as resource expansion, situational simulation, and personalized learning to foreign language intercultural communication education, promoting the transformation of intercultural teaching from text study to human-AI collaborative practice. However, large language models are limited by training data and have risks such as Western-centric cultural bias, cultural stereotypes, and factual illusions, which interfere with students' cultural cognition construction and weaken their intercultural critical discrimination ability. This paper explores the intrinsic value of AI empowering intercultural education, analyzes the teaching dilemmas brought about by technological intervention, and takes the core of human-AI interactive negotiation competence as the handle, proposing to integrate intercultural critical thinking and AI discrimination ability into teaching goals. From the four dimensions of teaching goal reconstruction, classroom task design, evaluation system innovation, and improvement of teachers' digital literacy, it explores the educational transformation path of foreign language intercultural teaching in the AI era, achieving the subordination of technical tools to the value of intercultural education.

Keywords

Generative AI; Foreign Language Intercultural Education; Intercultural Critical Thinking; Human-AI Interactive Negotiation Competence

References

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