基于密度聚类算法的学情数据可视化分析研究

Research on Visualization Analysis of Learning Information Data Based on Density Clustering Algorithm

随着教育信息化的不断深入,如何从海量数据中挖掘出教育规律引起关注。本文以学情数据为基础,建立学情分析可视化系统,以密度聚类算法为依托,对学生考勤与学情隐含关系、学情稳定性进行了分析研究,并将分析结果可视化。利用DBSCAN聚类算法对数据集挖掘分析,结果表明,教育数据可为高校决策提供管理依据。

With the deepening of educational informatization, attention has been paid to how to mine educational laws from massive educational data. Based on the learning situation data, this paper establishes the visualization system of learning situation analysis, relies on the density clustering algorithm, analyzes and studies the implicit relationship between students’ attendance and learning situation, and the stability of learning situation, and visualizes the analysis results. The DBSCAN clustering algorithm is used to mine and analyze the data set, and the results show that the educational data can provide the management basis for the decision-making of colleges and universities.