Reducing social distance through generative AI: instructional leadership in grammar-dominated Spanish curricula in Chinese universities

The rapid development of artificial intelligence (AI) in higher education is reshaping foreign language teaching and placing new demands on instructional leadership. In Spanish majors at Chinese universities, frontline teachers must work within a grammar-centred textbook system while simultaneously responding to students’ needs for communicative competence and AI literacy. This tension is further exacerbated by the significant “social distance” between learners and the Spanish-speaking world. This study employs a mixed-methods approach, combining analysis of two sets of textbooks, and questionnaire data from 108 students and 21 teachers, to explore potential pathways for change. The results show that domestic textbooks have advantages in grammatical progression but limited effectiveness in bridging interaction gaps, whereas international textbooks are often simplified into mechanical grammar drills in exam-oriented classrooms, thus diminishing their communicative potential. Students generally hold an open attitude towards generative AI tools, believing they help with personalized practice and alleviate anxiety, while teachers value the role of AI in extending textbook content and supporting the development of AI literacy. However, both groups are concerned that over-reliance on AI may weaken independent thinking and language production and pose risks to academic integrity. Building on these findings, the study proposes a teacher-led generative AI-textbook integration framework, positioning AI as a “communicative compensation and cultural mediation mechanism” to supplement limited communicative input, reduce distance from the Spanish-speaking community, and align the goals of self-directed learning, AI literacy and cross-cultural development.