基于信息熵的网络课程学生分类模型研究

Research on Students' Classification Models of Network Courses Based on Information Entropy

在网络课程教学中对学生进行分类,教师能为不同类别的学生制定相应的教学策略,提高教学质量。文章将信息熵理论运用于学生分类,在预处理之后的数据上,采用ID3算法构建了基于信息增益的决策树,生成相应的决策规则,为新的输入数据提供了分类依据。

According to the students＇ classification in the network courses teaching, teachers can make corresponding teaching strategies for different kind of students and improve teaching quality. The paper classifies students based on the information entropy theory, constructs decision tree based on information gain by using ID3 algorithm on thedata after preprocessing and generate the corresponding decision rules, which are the basis for the new input data.