Research On The Impact Of "Double Reduction" Policy On The After-School Tutoring Burden

Along with socio-economic development and the marketization of education,more and more families are using after-school tutoring to assist their children’s academic growth,giving rise to the rapid development of after-school tutoring institutions.However,after-school tutoring is gradually being "held hostage" by capital,and trafficking in education anxiety has led parents to follow the trend of training,and many families are beginning to fall under the heavy burden of after-school tutoring.In this context,the Party Central Committee and the General Office of the State Council issued the "double reduction" policy in July 2021,aiming to reduce the academic burden of children and after-school tutoring burden of families.This thesis seeks to investigate the impact of the "double reduction" policy on the burden of out-of-school training on families and its mechanism of action.Based on the fuzzy-conflict framework theory,supply-demand theory,and policy instrument theory,this thesis investigates whether the "double reduction" policy reduces the burden of after-school tutoring on families and its mechanism of action.First,the study analyzes the objectives,contents,and instruments of the policy to investigate how the "double reduction" policy itself affects after-school tutoring burden.Second,based on the results of the econometric analysis of the large database 2014 CEPS,this thesis investigates the participation of different types of families in subject-based after-school tutoring before the "double reduction",analyzes the types of families with a higher training burden,and selects them as the key interviewees;then,we focus on these families in the follow-up interviews to understand Then,in the follow-up interviews,we focused on these families to understand the changes in the number of subjects,hours,and financial expenditure of subject-based after-school tutoring before and after the "double reduction",so as to draw the impact of the "double reduction" on families’ burden of after-school tutoring.Finally,we combine the policy features and interviews on the after-school tutoring burden of families after the "double reduction" policy to obtain the mechanism of the "double reduction" on the change of the after-school tutoring burden of families and make relevant policy suggestions.The thesis found that the burden of after-school tutoring on families generally decreased after the "double reduction",but the change in the burden of after-school tutoring on high-income families,white-collar families and families with higher cultural capital was relatively small.This thesis finds that the "double reduction" affects the burden of after-school tutoring through the following three paths: first,the policy objective is relatively single and clear,and is highly recognized by parents;second,the policy content reduces the after-school tutoring burden of families from both the supply and demand sides,increasing the supply of after-school services on the one hand,and weakening the demand of parents to participate in after-school tutoring on the other;third,the policy instrument is authoritative and regulates the after-school tutoring burden of families.the authority of the policy tool is strong,regulating out-of-school training institutions and reducing the supply of tuition services.Based on the above research findings,this thesis proposes the following three policy recommendations to sustainably reduce the burden of after-school tutoring on families: First,in terms of policy objectives,tracking the impact of policies to improve policy objectives and strengthen policy communication to enhance parental recognition of goals;second,in terms of policy content,enhance the quality of school education and the role of the main front,optimize the supply and evaluation system of quality education;third,in terms of policy tools,reasonably configure the use of policy tools,improve the policy The implementation of the whole process of supervision system,strengthen the fight against invisible variant training.