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”.
Authors
- Yiping Su (ORCID: https://orcid.org/0000-0002-7514-2180)
- Zhiyao Su (ORCID: https://orcid.org/0000-0003-4534-7502)
Publication Details
- Journal
- Journal of Integrated Social Sciences and Humanities
- Published
- 2025-04-18
- DOI
- https://doi.org/10.62836/jissh.v2i1.357
- Primary Topic
- Global Educational Reforms and Inequalities
- Type
- article
- Field-Weighted Citation Impact
- 0.00