基于K-均值算法的开放教育入学水平测试成绩分析

Analysis of the Test Results of Open Education Entrance Level Based on K-means Algorithm

数据挖掘在教育领域有着广泛地应用,其聚类分析技术可用来发现不同的学生群体,并描述群体特征.本文采用聚类分析中的K-均值算法,对开放教育的入学水平测试成绩进行分析、分类,发现学生成绩分布的特点,了解学生知识结构,为学生制定个性化学习计划提供依据,为组织教学与分类指导提供参考.

Data mining has been widely used in education.Its cluster analysis technology can be used to discover different student groups and describe group characteristics.This paper uses the K-means algorithm in cluster analysis to analyze and classify the scores of the entrance level test of open education.It finds the characteristics of student's score distribution,understands the student's knowl edge structure,provides a basis for students to develop a personalized learning plan,and provides reference for organizing teaching and classification guidance.