Analyzing creativity of students with neural networks

Author

Yu, Jiayuan

Author_Institution

Dept. of Psychol., Nanjing Normal Univ., Nanjing, China

Volume

1

fYear

2010

fDate

29-31 Oct. 2010

Firstpage

118

Lastpage

121

Abstract

Creativity of middle school students was measured with Williams Creativity Test B (WCTB) and Adolescent Scientific Creativity Scale (ASCS). The SOM neural network was used to cluster the data, and three categories were obtained. 70% of the students were used as modeling group, and the other as testing group. Using generalized regression neural network (GRNN) and multivariable linear regression (MLR) to set model and test respectively. Scores of WCTB were used as input and independent variable, ASCS scores used as output and dependent variable. The result showed GRNN was better than MLR.

Keywords

cognition; educational administrative data processing; pattern clustering; regression analysis; self-organising feature maps; Adolescent Scientific Creativity Scale; SOM neural network; Williams Creativity Test B; data clustering; generalized regression neural network; middle school student; multivariable linear regression; scientific creativity; Analysis of variance; clustering; creativity measurement; multivariable regression; neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on

Conference_Location

Xiamen

Print_ISBN

978-1-4244-6582-8

Type

conf

DOI

10.1109/ICICISYS.2010.5658709

Filename

5658709