基于模糊C均值聚类的学生表现评估  

Student performance evaluation based on fuzzy C-means clustering

作　　者：贾燕[1] JIA Yan(Qinghai Health College,Xining 810000,China)

机构地区：[1]青海卫生职业技术学院,西宁810000

出　　处：《信息技术》2020年第11期55-59,65,共6页Information Technology

基　　金：青海省“十三五”教育科学规划2018年度课题(18-QJG45)。

摘　　要：教育机构需要为学生提供高质量的教育,因此从教育数据中获取有用信息是非常关键的。然而,由于教育数据来源和结构的不同,准确评价学生的学习成绩是很难的。此外,由于学生的学习能力不同,采取的教学方法也是不一样的。因此为了解决以上问题,找到教育数据中的相似性,文中研究提出一种基于模糊C-均值的聚类算法,将学生成绩进行聚类,利用二维与三维可视化,展示其结果。实验结果表明,教育者可以通过该方法更好的掌握学生成绩,从而为教学提供决策依据。Educational institutions need to provide students with high-quality education.Therefore,it is critical to obtain useful information from educational data.However,due to the different sources and structure of educational data,it is difficult to accurately evaluate students’academic performance.In addition,due to different learning abilities of students,the teaching methods adopted are also different.Therefore,in order to solve the above problems,find the similarity in the education data.Therefore,a clustering algorithm based on fuzzy C-means is proposed to cluster student grades and use 2D and 3D visualization to show the results.The experimental results show that educators can better grasp student achievements through this method,thus providing decision-making basis for teaching.

关 键 词：数据挖掘 聚类算法 学生表现 教育 可视化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]