Artificial intelligence (AI) is deeply driving the systematic reform of foreign language education and teaching in local universities in China. This process is propelled by the synergistic logic of policy, technology, demand, and practice. The top-level design of national strategies provides direction for the reform, while local universities engage in localized innovative practices by closely integrating regional development needs with school-based resources. Technologies represented by generative AI not only enable personalized supply of language input and immersive training of communication skills, but also force a shift in teaching objectives from language skills to higher-order competencies such as critical thinking, creative expression, and human-machine collaboration. Meanwhile, the new demands of students, teachers, and the industrial market in the intelligent era converge and resonate, jointly constituting the endogenous driving force of the reform. At the practical level, the exploration from benchmarking to widespread diffusion is promoting a systematic evolution of the teaching ecosystem. In short, AI-driven reform is fundamentally a paradigm reconstruction, and the key to its success is to build a new holistic educational ecosystem that supports the cultivation of talents with core competencies in the digital and intelligent era.

Nawei Ma, Junfeng Zhang. The Multidimensional Logic of AI-Driven Reform in Foreign Language Education and Teaching Reform in Local Universities. Frontiers in Educational Research (2026), Vol. 9, Issue 3: 92-97. https://doi.org/10.25236/FER.2026.090314.

[1] Liu Bangqi, et al. Generative Artificial Intelligence and the Reshaping of Future Educational Forms [J]. Journal of Educational Technology Research, 2024(1).

[2] Xu Yuetin, Gu Yue. foreign language education and teaching and Teacher Professional Development in the Age of Artificial Intelligence: Challenges, Identity Crisis, and Pathways Forward [J]. Contemporary Foreign Language Studies, 2025(1).

[3] Yu Hongliang. Paradigm Shift and Path Reconstruction of foreign language education and teaching in Colleges and Universities in the Age of Intelligence [J]. Foreign language education and teaching and Research, 2024(3).

[4] Xu Hong, Zhou Lei. Theory and Practice of foreign language education and teaching Reform in Colleges and Universities under the Background of Smart Education [J]. Foreign Language Audio-Visual Teaching, 2024(2).

[5] Yuan Jun'e. Exploration of AI-Enabled Stratified Teaching Practice in College Foreign Language [J]. Journal of Beijing Union University, 2026(1).

[6] Wen Qiufang. AI Empowers POA foreign language education and teaching Reform: An Innovative Exploration of Shifting from Immediate Communication [J]. Frontiers in foreign language education and teaching Research, 2025.

[7] Wen Qiufang, Liang Maocheng. Human-Machine Interactive Negotiation Ability: ChatGPT and foreign language education and teaching [J]. Foreign language education and teaching and Research, 2024(2).

[8] Sun Youzhong, Liu Mexiao. Construction of Foreign Language Digital Textbooks in the AI Era: Challenges, Concepts, and Paths [J]. Modern Foreign Languages, 2026(2).

[9] Nawei Ma. Exploration of the Collaboration between Artificial Intelligence and Human Intelligence in Foreign Language Education[J]. Frontiers in Educational Research, 2025, 8 (3).

[10] Li Yingying. The Intelligentization Path of foreign language education and teaching in Higher Vocational Colleges in the AI Era and the Reshaping of Teacher Identity [J]. Vocational Education, 2025(12).

[11] Bie Dunrong. Theoretical Explanation of AI Technology Application in University Education and Teaching [J]. China University Teaching, 2024(5).