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https://doi.org/10.62836/jissh.v2i1.357
Zhanguo Su, & Yiping Su. (2025). AI-Empowered Learning Ecology Under China’s ‘Double Reduction’ Policy. Journal of Integrated Social Sciences and Humanities, 1–13. https://doi.org/10.62836/jissh.v2i1.357
Volume 2, Issue 1, 2025

AI-Empowered Learning Ecology Under China’s ‘Double Reduction’ Policy

China’s 2021 “Double Reduction” policy reduces student academic burdens and regulates tutoring, yet challenges remain in equitable education access and student well-being. This study proposes a digital education model—the Health Learning Chain (HLC)—using biological-behavioral big data to optimize learning through physiological, psychological, and behavioral insights. Employing mixed methods (interviews, surveys, and system dynamics modeling), it explores multi-agent collaboration and resource sharing in sports-education integration. Key findings highlight stakeholder cooperation and resource optimization as vital for success. Policy simulations show short-term gains from increased resources but emphasize long-term reliance on governance and policy support. Recommendations include boosting resources, enhancing collaboration, and establishing sustainable policy frameworks, offering actionable strategies for a balanced educational ecosystem under “Double Reduction”.

AI-empowered; learning ecology; double reduction policy

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Supporting Agencies

  1. Funding: This research received no external funding.