Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/28428
標題: 影響中學生PISA成績因素之估計-臺灣、香港、日本、韓國之比較
Estimate the Effects of High School Students' PISA Performances-The Case of Taiwan, Hong Kong, Japan and Korea
作者: 許宏綺
Hsu, Hong-Chii
關鍵字: PISA
國際學生能力評量計畫
Education production function
Probit two stage least squares
教育生產函數
Probit兩階段最小平方法
出版社: 應用經濟學系所
引用: 一、中文部分 江芳盛、李懿芳,2009,「國際學生評量計畫(PISA)試題特色分析及對我國教育之啟示」,教育資料與研究雙月刊,87:27-50。 余民寧,2006,「影響學習成就因素之探討」,教育資料與研究雙月刊,73:11-24。 林煥祥主編,2008,臺灣參加PISA2006成果報告,行政院國家科學委員會。 林曉芳,2009,「影響中學生科學素養差異之探討:以臺灣日本南韓和香港在PISA2006資料為例」,教育研究與發展期刊,5(4):77-108。 陳吉仲、郭曉怡、李佩倫,2007「影響國中基本學力測驗分數的因素之分析」,教育政策論壇,10(4):119-142。 陳奕奇、劉子銘,2008,「教育成就與城鄉差距:空間群聚之分析」,人口月刊,37:1-43。 黃彥超,2009,「影響學生學習表現之學校與系統因素探討:以PISA 2006年之結果為例」,學校行政雙月刊,63:115-130。 張秋男主編,2005,國際數學與科學教育成就趨勢調查2003,行政院國家科學委員會。 張鈿富、吳慧子、吳舒靜,2009,「國際學生評量計畫(PISA)表現頂尖五國優勢條件分析」,教育資料與研究雙月刊,87:1-26。 二、英文部分 Björklund, A., M. Lindahl and K. Sund, 2003,“Family Background and School Performance during a Turbulent Era of School Reforms”, Stockholm, Swedish Economic Council. Borg, M. O., P. M. Mason and S. L. Shapiro, 1989, “The Case of Effort Variables in Student Performance”, Journal of Economic Education, 20(3), 308-313. Brunello, C. and D. Checchi, 2003, “School Quality and Family Background in Italy”, IZA Discussion Paper 705, Institute for the Study of Labor, Bonn. Caldas, S. J. and C. Bankston III, 1997, “Effect of School Population Socioeconomic Status on Individual Academic Achievement”, Journal of Educational Research, 90(5), 43-55. Feinstein, L. and J. Symons, 1999, “Attainment in Secondary School”, Oxford Economic Papers, 51(2), 300-321. Fertig, M., 2003, “Who’s to Blame? The Determinants of German Students’ Achievement in the PISA 2000 Study”, IZA Discussion Paper 739, Institute for the Study of Labor, Bonn. Goldhaber, D. D, 1996, “Public and Private High Schools:Is School Choice an Answer to the Productivity Problem?”Economics of Education Review, 15(2), 93-109. Häkkinen, I., T. Kirjavainen and R. Uusitalo, 2003, “School Resources and Student Achievement Revisited: New Evidence from Panel Data”, Economics of Education Review, 22(3), 329-355. Hanushek, E. A., 1997, “Assessing the Effects of School Resources on Student Performance: An Update”, Educational Evaluation and Policy Analysis, 20(3), 141-164. McEwan, P. J., 2003, “Peer Effects on Student Achievement: Evidence from Chile”, Economics of Education Review, 22, 131-141. Sander, W., 1999, “Endogenous Expenditures and Student Achievement”, Economics Letters, 64, 223-231. Schneeweis, N. and R. Winter-Ebmer, 2005, “Peer Effects in Austrian Schools”, Institute for Advanced Studies in its Series Economics Series with number 170. Stevans, L. K. and D. N. Sessions, 2000,“Private/Public School Choice and Student Performance Revisited”, Education Economics, 8(2), 169-184. Wößmann L., 2003, European “Education Production Functions”: What Makes a Difference for Student Achievement in Europe, European Commission, Brussels. Wößmann L., 2003a, Educational Production in East Asia: The Impact of Family Background and Schooling Policies on Student Performance, Kiel Working Paper, 1152, Institute for World Economics, Kiel. Wolter, S. C. and M. C. Vellacot, 2002, “Sibling Rivalry: A Look at Switzerland with PISA Data”, IZA Discussion Paper, 594, Institute for the Study of Labor, Bonn. Wolter, S. C., 2003, “Sibling Rivalry: A Six Country Comparison”, IZA Discussion Paper, 734, Institute for the Study of Labor, Bonn.
摘要: 本研究以臺灣、香港、日本、韓國參加2006年國際學生能力評量計畫之資料為例,探討影響學習成就的因素,並進行跨國比較。在研究方法上利用Probit兩階段最小平方法進行公私立學校選擇及教育生產函數的估計。估計結果發現同樣是15歲學生,但就讀的年級愈高,成績的表現愈好,這代表受教育的時間愈長對學習成果有顯著影響;在性別方面,男生在數學、自然科學的表現優於女生,女生在閱讀的表現優於男生,但日本及韓國在自然科學的表現例外;另外,以學區所在位置人口數代表的城鄉差距變數估計結果顯示,韓國在數學及閱讀的城鄉差距最大,臺灣在科學的城鄉差距最大,所以增加偏遠地區的資源投入,以降低城鄉差距的影響,應是教育當局的要務。但如果深入探討其原因,除了教育資源差異外,家長的社經地位或許才是造成城鄉差距的主因;將公私立學校選擇當作內生變數處理後,除了韓國的私立學校在數學及閱讀的表現較好外,其餘私立學校的學生表現並未優於公立學校。最後,在家庭因素方面,家庭的藏書量與家長的教育程度對中學生的評量成績有顯著的影響,所以家長對教育的重視程度與學生的學習表現具有明顯關係。
This thesis applied PISA 2006 dataset to estimate the effects of high school students' performances in four Asian countries. To do this end, the Probit two-stage least square approach is adopted to estimate the selection of school choice and the education production function. We found that the higher grade, the better grades in the fifteen-year-old students which means the better performances as more education. Regards to gender, male students do better in mathematics and science while female students do better in reading except Japan and Korea. Besides, the significant gap between urban-rural distance for mathematics and reading in Korea and science in Taiwan. These empirical results imply that more resources need to be invested in the rural areas. Furthermore, the family factors including education expenditure and parents' education level play important roles of influencing the PISA scores.
URI: http://hdl.handle.net/11455/28428
其他識別: U0005-0308201009390100
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-0308201009390100
Appears in Collections:應用經濟學系

文件中的檔案:

取得全文請前往華藝線上圖書館



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.