Evaluation of Sino-foreign Cooperative Education Model by Big Data and Deep Learning

In the current situation that the development trend and scale of Chinese foreign cooperation in running schools are gradually improving and expanding, the evaluation of Chinese foreign cooperation in schools is analyzed from the qualitative aspect. There is less quantitative analysis and research through the establishment of mathematical models. Thus, we applied the correlation research between big data analysis and in-depth learning technology to the analysis. Under the background of big data analysis, the Chinese foreign cooperative school contains a large amount of data, which contains various knowledge and laws. With the data analysis of different dimensions, the convolution neural network in-depth learning technology is used to evaluate the Chinese foreign cooperative school running mode in China. Convolutional neural network (CNN) is used to establish the nonlinear relationship model between the proportion of "students trained under the Chinese foreign cooperative school running mode" and various influencing factors in "Chinese students studying abroad" from 2003 to 2020. The purpose is to evaluate and analyze the Chinese foreign cooperative school running mode in China and provide a reference for the development, decision-making, and reformation of Chinese foreign school running mode.