教師資料查詢 | 類別: 期刊論文 | 教師: 張鈿富 Dian-fu Chang (瀏覽個人網頁)

標題:Cluster Analysis for Student Performance in PISA2015 among OECD Economies
學年107
學期1
出版(發表)日期2018/11/01
作品名稱Cluster Analysis for Student Performance in PISA2015 among OECD Economies
作品名稱(其他語言)
著者Dian-Fu Chang; Chia-Chi Chen
單位
出版者
著錄名稱、卷期、頁數ICIC Express Letters Part B: Applications, 9(11), pp.1139-1146
摘要This study selected OECD 35 economy members’ science, math, and reading scores and related impact factors as targets to mining the patterns and explore the main factors impact on the PISA2015 performance. The data selection was the first step; then this study applied observation clustering function with Minitab to determine the optimal clusters. The 3D scatterplot and 3D surface plot have been used to display the data structure. The dendrogram with three clusters drew by Ward linkage and Euclidean distance has a relatively high similarity level and a relatively low distance level in this study. The result reveals OECD economies in the cluster1 and cluster2 are needed to improve their students’ performance. The teaching hours per year in OECD economies has negative relationship with PISA2015 performance. While the teaching hours per year in economies can explain only 12.50% of the OECD/PISA2015 performance in the regression model. The OECD/PISA data provides an excellent databank for mining practices.
關鍵字Cluster analysis, Data mining, Regression analysis, OECD, PISA2005, OECD/PISA2015
語言英文(美國)
ISSN2185-2766
期刊性質國外
收錄於
產學合作
通訊作者
審稿制度1
國別日本
公開徵稿
出版型式,電子版
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