政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/82628
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113303/144284 (79%)
Visitors : 50797352      Online Users : 696
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/82628


    Title: PISA 2009上海地區數據之多層次分析方法與應用
    Other Titles: The Application of Hierarchical Linear Model on PISA 2009 in Shanghai
    Authors: 吳政達;施佩吟
    Wu, Cheng-Ta
    Contributors: 教政所
    Keywords: 大數據;多層次分析模型;國際學生能力評量計畫
    Big data;Hierarchical linear modeling;Programme for international student assessment
    Date: 2015-11
    Issue Date: 2016-03-14 16:30:18 (UTC+8)
    Abstract: 大數據(big data)的時代來臨,讓我們以前所未有的觀點,並透過極大量的數據統計對教育進行分析。鑑於國際學生能力評量計畫(Programme for International Student Assessment, PISA)在教育評價的理念、技術和結果報告,對我國的大規模教育評價改革都有值得借鏡之處,本研究以PISA 2009上海地區數據為例,樣本為參與上海市2009年「國際學生能力評量計畫」正式施測的152所學校所屬的5,115名學生;研究方法採用多層次分析模型進行分析,以探討家庭社會經濟文化地位、學校教師品質對學生閱讀、數學及科學等三項素養之影響。研究結果顯示,上海市PISA 2009閱讀、數學及科學在不同學校的組間差異實不可忽略。對各學校而言,家庭社會經濟文化地位每增加一個單位,PISA成績可以有效提高五分左右;家庭社會經濟文化地位具有能夠正向解釋成績之差異的效果,當學生家庭社會經濟文化地位愈高,其PISA成績愈好;此外,當學校具有高品質的教師時,更能提高PISA閱讀、數學及科學方面的成績。
    Big data makes us collect and work with a large volume and variety of data and apply massive data analysis on education. Based on the missions, techniques and reports of PISA, it can be worthy as the mirror of our large-scale of educational evaluation reform. This study applies PISA 2009 in Shanghai. The subjects contain 5,115 students in 152 schools who attended in PISA 2009. The methodology is hierarchical linear modeling (HLM) and we analyze that the effect on index of economics and social and cultural status, proportion of qualified teacher to reading literacy, mathematical literacy and scientific literacy. The results show there are differences among reading, mathematical and scientific literacy in schools. To each school, once index of economics and social and cultural status raise one single unit, the outcome of PISA will promote approximately five points. Index of economics and social and cultural status positively explains the relationship with the scores. The higher index of economics and social and cultural status students are, the better PISA they perform. In addition, when school employ high proportion of qualified teacher, the students’ performances in reading, mathematical and scientific literacy are better.
    Relation: 教育研究月刊,259,100-108
    Data Type: article
    DOI link: http://dx.doi.org/10.3966/168063602015110259007
    DOI: 10.3966/168063602015110259007
    Appears in Collections:[Graduate Institute of Educational Administration and Policy] Periodical Articles

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML21419View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback