基于K-means聚类算法的校园在线学习行为分析

Analysis of Campus Online Learning Behavior Based on K-means Clustering Algorithm

阐述学生在线学习行为的问题分析,引入K-means聚类算法,为学生在线学习行为研究提供更加准确高效的选择。分析表明,统计数据可以帮助教师掌握学生的在线学习状况,发现在线学习中存在的问题,从而实施针对性的干预和指导。

This paper expounds the problem analysis of students'online learning behavior,introduces K-means clustering algorithm,and provides more accurate and efficient choices for students'online learning behavior research.Analysis shows that statistical data can help teachers grasp students'online learning status,identify problems in online learning,and implement targeted interventions and guidance.