Against national digital-driven educational strategies, college English for non-English majors is troubled by fragmented resources, homogeneous teaching and limited personalized feedback. Targeting first-year non-English students, this study develops a knowledge-graph-enabled smart curriculum for General English. Combining top-down and bottom-up strategies, a two-tier knowledge graph is established: an ontology knowledge layer sorted from syllabus-centered five-skill knowledge points, and a data-resource layer built upon MOOC and SPOC resources on the Chaoxing Fanya platform. Based on a “teacher-student-machine” interactive framework, this paper presents the full-cycle teaching workflow covering pre-class guidance, in-class interaction and post-class adaptive push. Integrating ideological-political education and power-industry materials, this two-year research uses case studies. Pilot results show knowledge-graph visualization clarifies implicit links between language knowledge points, supports adaptive recommendation and multi-dimensional formative assessment. It offers feasible references for digital transformation of college foreign-language courses.

In order to address the challenge brought by artificial intelligence in traditional English teaching, we analyze the major challenges and problems faced by English teaching in the artificial intelligence environment. Based on practical teaching conditions, we put forward coping strategies from the perspectives of teachers, students, classroom teaching, categorized training, curriculum culture and usage specifications. By adopting these strategies in English teaching, the data reveal that the integration of AI has exerted positive impacts on teacher development, student growth, teaching modes, teaching resources and teaching effectiveness. The study shows that AI instructional design developed based on practical conditions and the integration of AI technologies and tools into teaching activities can exert positive effects.

As a type of linguistic variation, phonetic variation manifests universal characteristics in human linguistic communication, carries complex sociocultural connotations, and demonstrates significant academic research value. This phenomenon has long served as an important entry point for sociolinguistic research. This paper systematically reviews existing research findings, focusing on the motivational mechanisms and sociocultural background that may give rise to phonetic variation.

In order to address the challenge brought by artificial intelligence in traditional English teaching, we analyze the major challenges and problems faced by English teaching in the artificial intelligence environment. Based on practical teaching conditions, we put forward coping strategies from the perspectives of teachers, students, classroom teaching, categorized training, curriculum culture and usage specifications. By adopting these strategies in English teaching, the data reveal that the integration of AI has exerted positive impacts on teacher development, student growth, teaching modes, teaching resources and teaching effectiveness. The study shows that AI instructional design developed based on practical conditions and the integration of AI technologies and tools into teaching activities can exert positive effects.