DocumentCode :
3166442
Title :
Application of Data Mining for emotional intelligence based on cluster analysis
Author :
Jing, Feng ; Shiying, Kang
Author_Institution :
Chongqing Vocational Inst. of Electron. Eng., Chongqing, China
fYear :
2010
fDate :
29-30 Oct. 2010
Firstpage :
512
Lastpage :
515
Abstract :
Combining with the emotional intelligence theory, the Clustering Data Mining techniques was applied to individualized education research of Chongqing vocational Institute. through the emotional intelligence survey and its data collection, we dissected the characteristics of emotional intelligence data, analysed 804 samples of 5 Chongqing vocational Institute using K-means cluster analysis method. The 5 inner types of vocational students were dig out, including the balanced-type, strong adaptation-type, strong evaluation - type and weak regulation - type, strong adaptation-assessment-type, and weak awareness -strong evaluation-adaptation-type, etc. to provide the research basis for the development of more effective educational strategies.
Keywords :
artificial intelligence; data mining; emotion recognition; further education; statistical analysis; vocational training; K-means cluster analysis; data mining; emotional intelligence; higher vocational education; vocational students; Data mining; Educational institutions; Gravity; Psychology; Cluster analysis; Data mining; Emotional intelligence; Higher vocational education;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Education (ICAIE), 2010 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-6935-2
Type :
conf
DOI :
10.1109/ICAIE.2010.5640962
Filename :
5640962
Link To Document :
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