Year: 2025
Type: article
Abstract: 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: Zhanguo Su, Yiping Su
Institutions: Yunnan Nationalities University, University of Malaya
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4409692238