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

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/CISE.2009.5367040

Filename

5367040