Title :
Educational attainment trend analysis with the visual data mining tool
Author :
Nittaya Kerdprasop;Kittisak Kerdprasop
Author_Institution :
Knowledge Engineering and Data Engineering Research Units, School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand
Abstract :
We present in this paper the analysis results of prominent educational characteristics differentiating people from the two regions in the world: advanced economies versus east Asia and the pacific countries. The automatic multivariate analysis of classification trends has been demonstrated through the visual data mining tool called KNIME. We found from the empirical studies that from the years 1950 to 1980, percentage of population with no education is the sole factor accurately classifying advanced economies from the east Asia and pacific nations. But since the 1985 until 2010, the classification models have been shifted toward other four factors: (1) average years of schooling attained, (2) percentage of population completing primary school, (3) average years of tertiary schooling attained, and (4) percentage of population completing tertiary school. We illustrate graphical decision tree models of all 5-year intervals since 1950 to 2010.
Keywords :
"Biological system modeling","Sociology","Statistics","Accuracy","Data mining","Data models","Asia"
Conference_Titel :
Ubi-Media Computing (UMEDIA), 2015 8th International Conference on
DOI :
10.1109/UMEDIA.2015.7297451