Tong CHU

Abstract Artificial intelligence is changing higher education across the Asia-Pacific region, influencing how students learn, communicate, and engage with knowledge. As AI becomes increasingly integrated into educational practice, questions remain about how institutions can maintain human relationships, cultural engagement, and teacher-student interaction. This session brings together four empirical studies from Jilin University, China, examining these issues across different facets of foreign language higher education. The first explores how engagement with local place-based culture contributes to student wellbeing and intercultural belonging. The second investigates teacher-student disconnection in ICT-integrated classrooms. The third considers how lightweight AI tools can be incorporated into English-language teaching while preserving student wellbeing. The fourth examines how collaborative lesson study strengthens teacher-student relations and teacher self-efficacy during digital transformation. For institutions outside China, these empirical lessons provide applicable blueprints for navigating digital transition while safeguarding human-centred values. The session concludes by delineating context-specific findings from universal takeaways: • Jilin/China-Specific Findings: Insights tied to large-scale class dynamics, specific institutional governance models, local place-based cultural pedagogy, and national digital infrastructure norms in Chinese higher education. • Asia-Pacific & Cross-System Applicability: Principles for mitigating AI-induced teacher-student alienation, lightweight tool integration workflows, protecting learner wellbeing, and using collaborative teacher inquiry (lesson study) to sustain pedagogical humanism across diverse international contexts. Learning Objectives By attending this session, participants will be able to: 1. Examine how AI-mediated educational environments influence student wellbeing, belonging, and human connection in higher education. 2. Understand the emotional challenges and opportunities experienced by teachers in digitally mediated classrooms. 3. Identify practical, lightweight approaches for integrating AI into language education while preserving humanistic and intercultural learning goals. 4. Translate Institutional Lessons (Outside China): Evaluate what the Jilin University case studies mean for foreign language and international education programs in other institutional and regional contexts. 5. Distinguish Contextual vs. Universal Insights: Differentiate which findings are specific to the Chinese/Jilin policy and institutional ecosystem from those universally applicable across broader Asia-Pacific educational systems. Target audience: International educators, academic leaders, student support professionals, internationalisation practitioners, language educators, teaching and learning specialists, and researchers interested in AI, student wellbeing, intercultural engagement, educational technology, and staff development in higher education.