Title :
Data Mining in Teaching Quality Analysis: A Case Study in College English Teaching
Author :
Wu Yang ; Huang Hailiang
Author_Institution :
Sch. of Foreign Languages, Shanghai Univ., Shanghai, China
Abstract :
This paper presents an analysis of teaching quality improvement in college English language teaching using data mining for developing quality improvement strategies. Based on 1132 survey samples that were collected from a certain grade students during the period from April to June 2008, important factors impacting the teaching quality were identified via the decision tree method for data mining. Findings showed that the important factors for the percentage of making obvious progress were learning objectives, teaching measures and teaching modes. The nodes´ statistical indicators show us how the factors make effect on teaching quality and give analysts clues for improvement of teaching quality. A decision support system was developed to analyze and monitor trends of quality indicators.
Keywords :
data mining; decision support systems; decision trees; educational institutions; natural languages; teaching; total quality management; college English language teaching; data mining; decision support system; decision tree method; learning objectives; quality improvement strategies; quality indicators; teaching measures; teaching modes; teaching quality analysis; total quality management; Data mining; Data warehouses; Decision support systems; Decision trees; Delta modulation; Education; Educational institutions; Monitoring; Natural languages; Total quality management;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5367040
