Analysis of ESP Demand and Vocational Skills Cultivation Path of Chinese+Vocational Skills Courses Based on Big Data Algorithms–A Case Study of a Guangdong University

With the continuous development of vocational education, accurately grasping students' ESP needs has become a necessary path for optimizing students' vocational skills training path.Based on the Apriori algorithm, this paper mines the association rules between the vocational skills learning data of students in a university in Guangdong, reveals the intrinsic connection between students' vocational skills and students' ESP needs for Chinese+vocational skills courses, and designs the students' vocational skills cultivation path based on the TPACK framework.Then, social network analysis was used to visualize the relationship data in the vocational skills cultivation path network, analyze the differences of different individual centrality indexes in different student nodes, and explain the key roles played by different student nodes in the vocational skills cultivation path.The study shows that based on Apriori algorithm, we can effectively identify students' Chinese+vocational skills related features, and the improvement between "public liability" and "litigation" is as high as 1474.23%.1474.23%, and there is a high degree of intrinsic connection between the two.Based on the network architecture analysis of vocational skills training path based on the social network analysis method, it is accurately identified that among the different students, the point degree centrality of the students who are in the core position in the class is higher, and the leadership role of this kind of students can be given full play to, and the optimization of the vocational skills training path can be provided to the students in a targeted way.