Research on Evaluation of College Students' Professional Ability Based on K-means Clustering

Abstract

This paper presents a program to evaluate students' professional ability, which transforms the students and their teaching and practice activities during school into the form of topological graph, analyzes the similarity between student nodes, calculates teaching activities and students' professional ability through Apriori algorithm, and uses the K-means algorithm to cluster student data with different parameter sets based on different measurement goals. This paper analyzes the overall professional ability of students, compares cultivating differences among students in accordance with different professional ability, and finally gives the results of the analysis to facilitate teaching managers understand the distribution of students' professional ability to develop appropriate teaching plans.