K-means cluster analysis of student performance at a Fujian Taiwan Cooperative University

Abstract

This study introduces the idea and basic workflow of the K-means clustering algorithm, which is then used to conduct a cluster analysis of the scores of financial-major students taking basic courses at Fujian Taiwan Cooperative University. Through a cluster analysis, the distribution of students' scores in each course is determined. It provides a basis on which teachers can formulate personalized guidance strategies and students can adjust their learning time and energy.