期刊論文
| 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 | en_US |
| ISSN | 2185-2766 |
| 期刊性質 | 國外 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 是 |
| 國別 | JPN |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/115168 ) |