Influence Analysis of Education Policy on Migrant Children’s Education Integration Using Artificial Intelligence and Deep Learning - Chen, Zhen; Song, Zhitian; Yuan, Sihan; Chen, Wei (Frontiers in Psychology, 2022)
This work intends to solve the problem that the traditional education system cannot reasonably adjust the educational integration of children with the arrival of labor force in a short time, and support the education of migrant children in the education policy to integrate them into the local educational environment as soon as possible. Firstly, this work defines the surplus labor force and migrant children. Secondly, the principles of Artificial Intelligence (AI) and Deep Learning (DL) are introduced. Thirdly, it analyzes the education of migrant children and relevant policies, and the data of the education effect of migrant children are collected and the evaluation effect model is built. Finally, the evaluation model of migrant children's education effect is applied to test the effect of education policy. The results show that using AI technology combined with DL technology to model the education effect of migrant children can establish an effective and accurate evaluation model of the education effect of migrant children, effectively evaluate the impact of local education policies on the education of migrant children, and give an effective effect analysis of relevant education policies in each period. The result of Adaptive Resonance Theory - Back Propagation algorithm is 65% ~ 96%, which is much higher than the efficiency of traditional algorithms. This shows that the education integration evaluation model of migrant children based on AI technology and DL technology can effectively and accurately evaluate the integration effect of migrant children on the local education system, and then provide reference for local and even national adjustment of education policies. The results provide a new idea for the application of new technology in education policy.