采用非线性决策树的学生课堂教学满意度研究

学生反馈是评估高等院校课堂教学质量的重要指标。目前,对学生反馈的问卷仅进行主观理解和简单统计,无法提供准确定量的分析和支持依据。使用非线性决策树,对近3年本科必修双语课程《数字图像处理》的学生评教问卷进行数据挖掘,首先将其分成3类和10个不同输入,然后通过数据预处理、模型选择和建模,最后构建树状模型对其进行分析。分析结果符合对于该课程学生反应和争议较大的问题预期,为课程设计提供定量有效的教学分析工具。

Research on Student Satisfaction Using Non-linear Decision Tree Techniques

Student satisfaction is essential in evaluating the teaching quality.Current studies about student satisfaction only focus on simple statistic without quantitative analysis.This paper uses non-linear decision tree of data mining technique to analyze the questionnaires collected from the bilingual class of digital image process in Chengdu University of Information Technology.The duration of data collection lasts for three academic years.The data set is divided into three categories with 10 various inputs.The paper constructs tree model to analyze data set through data preprocessing,model choosing and modeling.The result shows that using non-linear decision tree model can provide effective quantitative analysis tool for class design.