Student Academic Performance

Topics: Regression analysis, Education, High school Pages: 15 (3943 words) Published: April 4, 2011

Chinese eduCation and soCiety

Chinese education and society, vol. 41, no. 5, September/October 2008, pp. 8–20. © 2009 M.E. Sharpe, Inc. All rights reserved. ISSN 1061–1932 / 2009 $9.50 + 0.00. DOI 10.2753/CED1061-1932410501

1 Yuhong Du anD Yongmei hu

Student Academic Performance and the Allocation of School Resources Results from a Survey of Junior Secondary Schools
Abstract: since the 1980s, the increasing cost of education has been a global trend, and there is a growing demand for increasing efficiency in different countries. as a result, education economists began focusing on the issue of efficient allocation of educational resources and borrowed production function from economics to study educational production issues in order to provide empirical evidence for maximization of the effectiveness of educational resources. this paper employs the multiple linear regression model to build a model for the relationship between the allocation of educational resources and student academic performance in public junior secondary schools in rural areas of China’s western region. it also provides a decision basis for different levels of government Translation ©2009 M.E. Sharpe, Inc., from the Chinese text, “Xuexiao ziyuan peizhi yu xuesheng xueye chengji guanxi: jiyu Zhongguo xibu nongcun chuzhong de diaocha.” Translated by Ted Wang. Yuhong Du and Yongmei Hu, Ph.D., are professors at the College of Education Administration at Beijing Normal University. 8

september/oCtober 2008


and schools to draw educational resources allocation policies for junior secondary schools in rural areas of China’s western region and to improve the quality of education. The Coleman Report from the 1960s, which was an analysis of factors causing differences in academic performance among students, raised great controversy in the academic world. Because this conclusion shook the foundation of many education policies, people began questioning the impact of different types of education on the academic performance of students. These inquiries led to extensive studies conducted on school resources and academic performance. However, these studies could not provide a satisfying answer to the question, and conclusions of the different studies varied enormously. In 1989, Hanushek analyzed the research results of the 187 education production functions before 1988 and found that, in these studies, the relationship between student academic performance and inputs of student–teacher ratio, education level of the teachers, years of teaching experience of teachers, teacher salaries, expenditure per student, administration, equipment, and so on was uncertain and suggested that “there is no strong, continuous link between school resources and student academic performance” (Hanushek 1997, 148). During the mid-1990s, Hedges, Laine, and Greenwald (1994) adopted a meta-analysis and posed questions regarding Hanushek’s statistical process. They repeated the analysis, and research results indicated that expenditures per student had a relatively large degree of positive effect on student academic performance. Monk (1991) and others also suggested that improving data and statistical methods could help determine the relationship between school resources and output. Monk came to the conclusion that after controlling for family background, school input has a great impact on education output. After Anna Vignoles et al. (2000) from the Center for Economics of Education at the University of London analyzed the research results of Dewey et al. (2000), they came to the following conclusion: There is not yet sufficient evidence to show that a link exists between educational expenditures and output of student academic performance, thus high educational expenditures do not necessarily


Chinese eduCation and soCiety

translate into the output of higher quality school education. Because the majority of educational expenditures go to school districts and...
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