Danping Wang
This study reports on a national survey investigating language teachers’ attitudes toward generative AI in Aotearoa New Zealand. The survey combined closed and open-ended questions, and thematic analysis was used to identify key themes in teachers’ qualitative responses. Drawing on data from 124 teachers of high- and low-resource languages, the study reveals distinct patterns in teachers’ attitudes and rationales regarding AI integration in language teaching. The findings offer comparative insights across language groups. Chinese language teachers reported the most pragmatic attitudes toward AI, supported by broader access to China-based AI tools and potentially peer influence. Teachers of other high-resource languages, including English, French, Spanish, German, and Japanese, more frequently offered critical perspectives, including sustainability, digital trust, and academic integrity, often in the absence of clear policy guidance. Low-resource language teachers, particularly those working with te reo Māori and Pacific languages, cited infrastructure gaps, limited tool accuracy, and epistemic mismatches between AI systems and oral-based pedagogies as key barriers to integration. The study highlights a widening digital divide within language education and argues against one-size-fits-all approaches to AI policy and professional development. Teachers across all contexts called for differentiated support and strong leadership to guide inclusive and linguistically equitable AI integration.