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Notice of Retraction
Apply Data Mining to Students' Choosing Teachers Under Complete Credit Hour

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1 Author(s)
Fangjun Wu ; Sch. of Inf. Technol., Jiangxi Univ. of Finance & Econ., Nanchang, China

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Data mining is a new information process technology; it has gained some impressive results in higher education, such as students' elective courses, course scheduling, analysis of students' achievement, test paper quality evaluation, evaluating overall quality of students and their graduation. However, it doesn't start its research and application in students' selecting teachers under complete credit hour. Hereon, this paper utilizes the famous data mining software SPSS Clementine to mine the factors that affect students' selecting teachers, apply cluster analysis to classify students into different categories and give corresponding advises to different categories of students in order to direct students' course selection. On the other hand, this paper can provide strong information support, decision support and work direction for administrators thus improve the pertinence, science and high efficiency and finally promote the comprehensive development of educational system's deepen reformation and construction.

Published in:

Education Technology and Computer Science (ETCS), 2010 Second International Workshop on  (Volume:1 )

Date of Conference:

6-7 March 2010