数据挖掘在大学英语教学质量分析中的应用研究

The Application of Data Mining in College English Teaching Quality Analysis

该文将数据挖掘应用于大学英语教学质量分析中，运用CHAID算法对1132名学生的调查数据进行计算，从涵盖大学英语教学过程、条件和环境的大量数据中，发现了影响学生进步率的最重要因素包括学习动机，教学手段和教学模式。该方法得到的决策树可以量化地反映各教学因素对学习质量的影响效果，为提出针对性的改进措施提供了直观而坚实的依据。

This paper presents a method for English language teaching (ELT) quality improvement analysis by using data mining techniques. CHAID algorithm is employed to analyze the survey data collected from 1132 college students， which cover the aspects of English teaching processes， condition and environment. Findings showed that the most important factors impacting the percentage of making notable progress were learning objectives， teaching measures and teaching modes. According to the decision tree resulted from this method， various factors’ effect on ELT quality can be quantitatively analyzed and more proper quality improving strategies can be put forward.