DocumentCode
514799
Title
Notice of Retraction
Cluster Analysis and its Application in Student Grants
Author
Mei-Lan Chen
Author_Institution
Inf. & Educ. Technol. Center, Foshan Univ., Foshan, China
Volume
1
fYear
2010
fDate
6-7 March 2010
Firstpage
631
Lastpage
634
Abstract
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.
Nowadays there still exists many problems with regard to student grants in higher education in practice, especially the judgement standard related to poor students. Aiming at the issue, we make use of the data from campus smart card system of certain college, and carry out data mining of poor students to derive groups with different characteristics by clustering analysis. Different groups have adopted different subsidizing ways, which could help grant centre´s administrator to make rational decision. The results show that the method presented in this paper can improve the discrimination accuracy, and reduce the impact of subjective factors, so as to better reflect the fairness of education.
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.
Nowadays there still exists many problems with regard to student grants in higher education in practice, especially the judgement standard related to poor students. Aiming at the issue, we make use of the data from campus smart card system of certain college, and carry out data mining of poor students to derive groups with different characteristics by clustering analysis. Different groups have adopted different subsidizing ways, which could help grant centre´s administrator to make rational decision. The results show that the method presented in this paper can improve the discrimination accuracy, and reduce the impact of subjective factors, so as to better reflect the fairness of education.
Keywords
data mining; decision making; educational administrative data processing; educational institutions; pattern clustering; smart cards; campus smart card system; cluster analysis; college; data mining; discrimination accuracy; higher education; judgement standard; rational decision making; student grants; subjective factors; Application software; Computer science; Computer science education; Databases; Educational institutions; Educational technology; Information analysis; Measurement standards; Power capacitors; Smart cards; clustering analysis; higher education; student grants;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6388-6
Type
conf
DOI
10.1109/ETCS.2010.189
Filename
5459078
Link To Document