Socioeconomic Influences to the School Performance: Case Study of O-NET Test Result in the Provincial Level
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Published
Mar 17, 2017
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Abstract
The article was aimed to estimate the influences of socioeconomic factors towards the O-NET test results in Thailand. The purpose of this research was to study the effect of socioeconomic status toward the O-NET test results of the 6th grade, 9th grade, and 12th grade in Thailand. A simple linear regression was adopted to analyze the cross sectional data at the provincial level. The data was retrieved from various surveys by the National Statistical Organization during 2010 such as the Household Expenditure survey, Labor Force survey and Employment survey. The results found that the household income and household expenditures were unable to describe the test score. The internet accessibility and unemployment provided significantly effects to the test results. Nevertheless, the absence of the relationship between the income and the school performance may be diluted by the application of average score as a provincial proxy. In this study, the household income and expenditure took no part in the education performance in the provincial level. To overcome the diluted scores, using of the small area estimation may point out the effect of the socioeconomic status toward the O-NET test scores explicitly.
References
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Peña-López, I. (2015). Students, Computers and Learning. Making the Connection. Paris: OECD Publishing.
Pitiyanuwat, S., & Campbell, J. R. (1994). Socio-economic status has major effects on math achievement, educational aspirations and future job expectations of elementary school children in Thailand. International. Journal of Educational Research, 21(7), 713-721. doi: http://dx.doi.org/10.1016/0883-0355(94)90044-2
Rau, P.-L. P., Gao, Q., & Wu, L.-M. (2008). Using mobile communication technology in high school education: Motivation, pressure, and learning performance. Computers & Education, 50(1), 1-22.
Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. Whither opportunity. New York: RUSSELL Sage Foundation.
Uline, C. L., & Crampton, F. E. (2009). Spending on school infrastructure: does money matter?. Journal of Educational Administration, 47(3), 305-322.
White, K. R. (1982). The relation between socioeconomic status and academic achievement. Psychological bulletin, 91(3), 461.
Wilson, W. J. (1998). The Role of the Environment in the Black-White Test Score Gap. In J. Christopher & P. Meredith (Eds.), The Black-White test score gap (pp. 501-510). Washington, DC: Brookings Institution Press. Retrieved from http://scholar.harvard.edu/wwilson/publications?page=3, https://www.amazon.com/Black-White-Test-Score-Gap/dp/0815746091
Andrews, B., & Wilding, J. M. (2004). The relation of depression and anxiety to life‐stress and achievement in students. British Journal of Psychology, 95(4), 509-521.
Battle, P. A., Juan. (1999). Home computers and school performance. The information society, 15(1), 1-10.
Coley, R. J. (2002). An Uneven Start: Indicators of Inequality in School Readiness. Policy Information Report. Retrieved from http://files.eric.ed.gov/fulltext/ED466473.pdf
Collins, T. (1999). Attracting and Retaining Teachers in Rural Areas. USA, West Virginia: ERIC Digest/CRESSC.
Dahl, G. B., & Lochner, L. (2005). The impact of family income on child achievement. Retrieved from http://www.nber.org/papers/w11279.pdf
Davis-Kean, P. E. (2005). The influence of parent education and family income on child achievement: the indirect role of parental expectations and the home environment. Journal of family psychology, 19(2), 294.
Dede, C. (2000). Emerging influences of information technology on school curriculum. Journal of Curriculum Studies, 32(2), 281-303.
DeFrain, J., & Asay, S. M. (2007). Strong families around the world: An introduction to the family strengths perspective. Marriage & Family Review, 41(1-2), 1-10.
Dewen, W. (2003). China’s rural compulsory education: Current situation, problems and policy alternatives. Beijing, China: Working Paper Series 36, Institute of Population and Labor Economy of Social Sciences.
Grissmer, D. W., & Flanagan, A. (1998). Exploring rapid achievement gains in North Carolina and Texas: National Education Goals Panel Washington, DC. Washington DC: National Education Goals Panel (ED).
Hallak, J., & Poisson, M. (2007). Corrupt schools, corrupt universities: What can be done?: International Institute for Education Planning. Paris: IIEP’s printshop.
Harris, A. (2009). Improving schools in challenging contexts Second international handbook of educational change. London: Springer.
Helge, D. (1984). The state of the art of rural special education. Exceptional Children, 50(4), 294-305.
Javeed, D. Q. S. (2012). Effect of education on achievement motivation among high profile and low profile college students. Review of research, 1(IX), 1-4.
Jensen, B. T. (2006). Mathematics Achievement of Spanish-speaking Kindergartners and the Impact of Teacher Characteristics: A Mediation Hypothesis. (Master’s thesis). Department of Graduate Study, Arizona State University, Tempe, AZ.
Kafai, Y. B., & Sutton, S. (1999). Elementary school students' computer and internet use at home: Current trends and issues. Journal of Educational Computing Research, 21(3), 345-362.
Kitsawad, K. (2013). An investigation of factors affecting high school student’s choice of university in Thailand. (Doctoral dissertation). Faculty of Education, University of Wollongong, New South Wales, Australia.
Lee, V. E., & Burkam, D. T. (2002). Inequality at the starting gate: Social background differences in achievement as children begin school: ERIC. Washington DC: Economic Policy Institute.
Lounkaew, K. (2013). Explaining urban–rural differences in educational achievement in Thailand: Evidence from PISA literacy data. Economics of Education Review, 37, 213-225. doi: http://dx.doi.org/10.1016/j.econedurev.2013.09.003
Lupton, R. (2004). Schools in disadvantaged areas: recognising context and raising quality. LSE STICERD Research Paper No. CASE076. London: University of London-Institute of Education.
Macho, S. (2006). The Impact of Home Internet Access on Test Scores. Yongstown, New York: Cambria Press.
Nitiwong, B. (2015). Cost and Pricing Towards Education Industry and Business in Thailand. th 5th Business, Economics and Communication International Conference 2015 (pp. 36-47). Phitsanulok: Naresuan University.
Peña-López, I. (2015). Students, Computers and Learning. Making the Connection. Paris: OECD Publishing.
Pitiyanuwat, S., & Campbell, J. R. (1994). Socio-economic status has major effects on math achievement, educational aspirations and future job expectations of elementary school children in Thailand. International. Journal of Educational Research, 21(7), 713-721. doi: http://dx.doi.org/10.1016/0883-0355(94)90044-2
Rau, P.-L. P., Gao, Q., & Wu, L.-M. (2008). Using mobile communication technology in high school education: Motivation, pressure, and learning performance. Computers & Education, 50(1), 1-22.
Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. Whither opportunity. New York: RUSSELL Sage Foundation.
Uline, C. L., & Crampton, F. E. (2009). Spending on school infrastructure: does money matter?. Journal of Educational Administration, 47(3), 305-322.
White, K. R. (1982). The relation between socioeconomic status and academic achievement. Psychological bulletin, 91(3), 461.
Wilson, W. J. (1998). The Role of the Environment in the Black-White Test Score Gap. In J. Christopher & P. Meredith (Eds.), The Black-White test score gap (pp. 501-510). Washington, DC: Brookings Institution Press. Retrieved from http://scholar.harvard.edu/wwilson/publications?page=3, https://www.amazon.com/Black-White-Test-Score-Gap/dp/0815746091
Keywords
School Performance, Socioeconomic Factors, O-NET Test
Section
Research Articles
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How to Cite
TONBOOT, Sila.
Socioeconomic Influences to the School Performance: Case Study of O-NET Test Result in the Provincial Level.
Journal of Community Development Research (Humanities and Social Sciences), [S.l.], v. 10, n. 1, p. 42-49, mar. 2017.
ISSN 2985-0231.
Available at: <https://www.journal.nu.ac.th/JCDR/article/view/1719>. Date accessed: 25 apr. 2024.