Students Creativity Modeling with Gene Expression Programming

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. In these students, 70% of them were selected to be as training samples, and the others to be as testing samples. Gene expression programming (GEP), generalized regression neural network (GRNN) and multivariable linear regression (MLR) were used for modeling and testing. The result showed the fitting error of GEP model was the lowest compared with the errors of GRNN and MLR models.