Cluster Analysis-Based Student Ability Portrait and Accurate Cultivation Path in Internet International Trade Competition in Higher Vocational Colleges and Universities

The development of vocational education cannot be separated from skill competitions, and skill competitions in higher vocational colleges and universities are an important platform for testing the improvement of students' skills.In this paper, we take the students of S higher vocational colleges in Guangdong Province, China, who are in the Internet international trade competition for higher vocational colleges as the research sample, and choose descriptive statistical analysis and correlation analysis as the data statistical methods of this research.From the perspective of learner portrait, we constructed a student ability portrait model based on the objective function of clustering algorithm FCM, calculated fuzzy division coefficients through the number of classifications and attribution probability matrix, determined the appropriate number of student clusters, and obtained the classification results of the portrait.In the analysis of student ability portrait, the optimal number of clusters is determined to be 4, and four groups of learners, namely, active catch-up, potential constructor, active collaborator and passive receiver, are classified, and at the same time, based on the group characteristics presented by different learning ability portraits, the precise cultivation paths are proposed for different groups of learners in preparation for the process of Internet International Trade Competition.