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Data Mining in Teaching Quality Analysis: A Case Study in College English Teaching

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2 Author(s)
Wu Yang ; Sch. of Foreign Languages, Shanghai Univ., Shanghai, China ; Huang Hailiang

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.

Published in:

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Date of Conference:

11-13 Dec. 2009

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