Abstract

Under the background of the rapid development of big data technology, the issue of how to use big data technology and the integration of Chinese international education has become a hot topic of current social concern. Firstly, the XGBoost-Logistic combination model is optimized based on pos algorithm, and firstly, the requirement analysis is carried out through the evaluation system of Chinese international education. The five modules are mainly analyzed: login module, basic data management, evaluation module, comprehensive statistics and system management. Then by dividing the original data into three aspects, specifically teacher evaluation, expert evaluation and student evaluation, according to the data and establish the evaluation index system, the evaluation index includes 3 primary indexes, 9 secondary indexes and 24 tertiary indexes. The evaluation index system was used as the evaluation standard, and finally the accuracy rate analysis was conducted on the secondary and tertiary indicators of Chinese international education evaluation based on the logistic regression model, XGBoost model and combined logistic-XGBoost model. The results show that:In the XGBoost-Logistics model, the accuracy rates of all indicators are maintained in the range of 83.71%~91.39%, and the accuracy rate of D13 indicators is the highest among all indicators, with an average accuracy rate of 87.81%. In general, the accuracy of the combined XGBoost-Logistics model performed better than the other two models. By creating an evaluation system for Chinese language international education management, this study improves the efficiency and accuracy of education management, which is historically important for the international communication and dissemination of Chinese language.