Paper Title:
Middle School Students Creativity Assessment with Neural Networks
  Abstract

Williams Creativity Test B (WCTB) and Adolescent Scientific Creativity Scale (ASCS) were used to measure the creative affective and scientific creativity for 550 middle school students. SOM network was used to cluster the measurement data of scientific creativity. 550 middle school students were clustered to three categories. In these students, 70% of them were used as training group, and the other as testing group. Probabilistic neural network (PNN) and multinomial logistic regression (MLR) were used for modeling and testing. Risk-taking, curiosity, imagination and complexity scores used as input and independent variable, scientific creative categories used as output and dependent variable. The result showed the Percent Correct (PC) of PNN was higher than the PC of MLR.

  Info
Periodical
Advanced Materials Research (Volumes 271-273)
Edited by
Junqiao Xiong
Pages
1443-1446
DOI
10.4028/www.scientific.net/AMR.271-273.1443
Citation
J. Y. Yu, "Middle School Students Creativity Assessment with Neural Networks", Advanced Materials Research, Vols. 271-273, pp. 1443-1446, 2011
Online since
July 2011
Authors
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Price
$32.00
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