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<p>Generative artificial intelligence (GenAI) has made many language-production and language-support tasks more accessible, prompting foreign language education (FLE) to reconsider its educational contribution beyond discrete linguistic skills. In Chinese higher education, this technological pressure intersects with ongoing debates about the restructuring and repositioning of foreign language programs. This study examines GenAI-era FLE transformation as a mediated process involving policy guidance, academic discourse, teacher interpretation, and student learning experience. Drawing on an integrated mixed-methods design, the study analyzes China’s Guidelines for Teachers’ Application of Generative Artificial Intelligence, applies BERTopic modeling to 93 peer-reviewed Chinese journal articles, and examines data from a student questionnaire survey (N = 200) and semi-structured teacher interviews (N = 8). The findings suggest that the Guidelines articulate a dual logic of facilitation and regulation by creating space for AI-supported pedagogical experimentation while emphasizing teacher responsibility, ethical governance, data protection, and academic integrity. The selected academic corpus indicates a tendency toward separation between technology-oriented and purpose-oriented discussions, suggesting uneven integration between AI affordances and competence-oriented goals. Student self-reports show frequent AI use and strong endorsement of AI-supported competence-oriented learning, but also limited teacher-guided deep learning activities and only moderate clarity about AI-use norms. Teacher interviews further suggest that teachers translate policy expectations into practice through competence upgrading, responsibility reinforcing, value protection, and technological boundary-setting. The study argues that sustainable transformation in GenAI-era FLE depends less on technology adoption itself than on the alignment of policy guidance, teacher agency, classroom task design, assessment norms, and ethically responsible student use.</p>

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GenAI, policy mediation, and sustainable transformation in China’s foreign language education

  • 期刊论文

  • 发表日期：

    2026年7月23日

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  • Chen Xuhai,
  • Lv Jiaxuan,
  • Zheng Zhiheng

摘要

Generative artificial intelligence (GenAI) has made many language-production and language-support tasks more accessible, prompting foreign language education (FLE) to reconsider its educational contribution beyond discrete linguistic skills. In Chinese higher education, this technological pressure intersects with ongoing debates about the restructuring and repositioning of foreign language programs. This study examines GenAI-era FLE transformation as a mediated process involving policy guidance, academic discourse, teacher interpretation, and student learning experience. Drawing on an integrated mixed-methods design, the study analyzes China’s Guidelines for Teachers’ Application of Generative Artificial Intelligence, applies BERTopic modeling to 93 peer-reviewed Chinese journal articles, and examines data from a student questionnaire survey (N = 200) and semi-structured teacher interviews (N = 8). The findings suggest that the Guidelines articulate a dual logic of facilitation and regulation by creating space for AI-supported pedagogical experimentation while emphasizing teacher responsibility, ethical governance, data protection, and academic integrity. The selected academic corpus indicates a tendency toward separation between technology-oriented and purpose-oriented discussions, suggesting uneven integration between AI affordances and competence-oriented goals. Student self-reports show frequent AI use and strong endorsement of AI-supported competence-oriented learning, but also limited teacher-guided deep learning activities and only moderate clarity about AI-use norms. Teacher interviews further suggest that teachers translate policy expectations into practice through competence upgrading, responsibility reinforcing, value protection, and technological boundary-setting. The study argues that sustainable transformation in GenAI-era FLE depends less on technology adoption itself than on the alignment of policy guidance, teacher agency, classroom task design, assessment norms, and ethically responsible student use.