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An In-depth Survey Analysis Applying Data Mining Techniques  

Kim, Wan-Seop (School of Computing, Soongsil University)
Lee, Soo-Won (School of Computing, Soongsil University)
Publication Information
Journal of Engineering Education Research / v.9, no.4, 2006 , pp. 71-82 More about this Journal
Abstract
To accomplish the educational objectives of a department, a system for CQI(Continuous Quality Improvement) is necessary. Improving the educational system by survey analysis is one of the most important factors for accomplishing the educational objectives. In general, survey analysis is carried out by using statistical distribution on an attribute or correlation analysis between two attributes. However, these analysis schemes have a limitation that they cannot find relations among various attributes. In this paper, an in-depth survey analysis method applying data mining techniques is presented. Data mining is a technique for extracting interesting knowledges from a large set of data. Survey from undergraduate students in the School of Computing of Soongsil University is analyzed in this paper by using a data mining tool, called Clementine. Results of Clementine analysis show the relationship between 'grade', and other attributes hierarchically, and provide useful information that can be applied in student consulting and program improvement.
Keywords
Survey Analysis; Data Mining; Classification; Decision Tree;
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