Human-Machine Collaboration and Emotional Labor Dilemmas: A Case Study of Foreign Language Teachers in the Northern Frontier Region (Journal of Interdisciplinary Insights, 2025)
The rapid integration of artificial intelligence into education has precipitated a shift towards human-machine collaborative teaching, a transition fraught with complex emotional challenges for educators. Existing research, predominantly focused on technological efficacy and generic teacher adaptation, lacks a nuanced understanding of how these challenges manifest within specific, marginalized socio-cultural contexts. This qualitative case study addresses this gap by investigating the unique emotional labor dilemmas experienced by foreign language teachers in universities in China’s Northern Frontier region—an area characterized by cultural diversity and relative resource scarcity. Drawing on in-depth interviews and documentary analysis with 12 teachers, the study identifies a core “triple tension”: the cultural-linguistic dilemma in aligning standardized technology with local learner needs, the double burden of mediating both cross-cultural understanding and digital interfaces, and the fragmentation of professional identity amidst technological demands. Moving beyond diagnostic analysis, the paper constructs and elaborates a situated, multi-tiered alleviation mechanism framework. This model advocates for synergistic interventions at the individual, organizational, and systemic levels. The study contributes to the international literature by foregrounding the critical dimensions of place and culture, arguing that teacher wellbeing in the digital age is a foundational condition for equitable educational futures.