English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 53693/88315 (61%)
造訪人次 : 9969512      線上人數 : 19
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/115168

    題名: Cluster Analysis for Student Performance in PISA2015 among OECD Economies
    作者: Chang, Dian-Fu;Chen, Chia-Chi
    關鍵詞: Cluster analysis;Data mining;Regression analysis;OECD;PISA2005;OECD/PISA2015
    日期: 2018-11
    上傳時間: 2018-10-11 12:10:14 (UTC+8)
    出版者: ICIC International
    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.
    關聯: ICIC Express Letters Part B: Applications, 9(11), pp.1139-1146
    DOI: 10.24507/icicelb.09.11.1139
    顯示於類別:[教育政策與領導研究所] 期刊論文


    檔案 描述 大小格式瀏覽次數
    Cluster Analysis for Student Performance in PISA2015 among OECD Economies.pdf157KbAdobe PDF0檢視/開啟



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋