Spatial Pattern Recognition of School Performance Based on Anthropometric and Motor Parameters using Multivariate Analysis and Kriging Interpolation Technique
The purpose of this study is to determine spatial pattern recognition of school performance based on children’s anthropometric and motor skills component. This study involved 93 primary schools with a total 2237 male students aged 7.30±0.28 years in Pahang, Malaysia. The parameters of anthropometric (weight and height) and motor component included low muscular power (standing broad jump), flexibility (sit and reach), coordination (hand wall toss) and speed (20 meter run) were selected. Cluster Analysis (CA) and Discriminat Analysis (DA) under Multivariate Method and technique of Kriging Interpolation in Geographic Interpolation Software (GIS) were used. CA revealed two clusters of school performance. There are a total 34 high performance schools (HPS) and 60 low performance schools (LPS). Then, the assigned groups were treated as independent variable (IV) while anthropometric and motor parameters were treated as dependent variable (DV) in DA. Standard mode of DA obtained 95.74% correctness of classification matrix with three discriminated variables (height, standing broad jump and 20 meter run) out of six variables. Meanwhile, forward and backward stepwise mode of DA discriminated only one (standing broad jump) out of six variables with 96.81% of classification correctness. The map output of Kriging interpolation has shown graphically the pattern of discriminated variables that greatly influence school performance. It exposed the ability of children develop their motor skills in particular region is higher than another region. This finding would suggest that follow up studies must be carried up to investigate the factors of these pattern could happened.
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