Artificial Intelligence Enabled Double Reduction Policy Path Analysis

Abstract

The “Double Reduction” policy starts from both inside and outside the school, with a view to combating the excessive academic burden of students and building a favourable educational ecology. However, the implementation of the policy has faced resistance and problems within and outside the school and in the general environment. The application of AI can provide new ideas in improving classroom quality, innovating educational tools, and evaluating and regulating education. At the same time, AI promotes the transformation of the education model and the innovation of education concepts. Artificial intelligence presents both opportunities and challenges for applications in education. This artical examines the obstacles in implementing the double reduction policy and explains the machine learning algorithms. By analysing pertinent education data, it explores AI’s role in aiding double reduction policy execution and potential risks.Whilst encouraging their integration, it is important to clarify the instrumental role of AI whilst addressing issues such as educational equity and Digital Gap problems.