Abstract:
The purpose of this study is to explore personalized teaching strategies for international Chinese education based on data mining technology. By analyzing the data of students' learning behavior, the paper first divides students into different learning groups, including primary, intermediate and advanced learners. According to the characteristics and needs of different learning groups, corresponding personalized teaching strategies are put forward, including increasing interesting and interactive teaching activities, designing challenging learning tasks, providing advanced learning resources and challenging tasks. In addition, through the mining of association rules, the relationship between learning behaviors is found, which provides scientific basis and reference for the formulation of personalized teaching strategies. This study is of great significance for improving the teaching quality and effect of international Chinese education, and provides new ideas and methods for the innovation and development of education and teaching.
