Abstract
The OECD’s Programme for International Student Assessment (PISA) enables participating countries to monitor 15-year old students’ progress in reading, mathematics, and science literacy. The present study investigates persistent factors that contribute to science performance of Turkish students in PISA 2006 and PISA 2009. Additionally, the study investigates whether factors explaining science performance has changed between 2006 and 2009. Multilevel analyses of student level and school-level variables revealed that the variance in science performance explained by school-level variables is 13 % for PISA 2006 and 28 % for PISA 2009. Moreover, the variance in science performance explained by student-level variables is 19 % for PISA 2006 and 20 % for PISA 2009. The six most common student-level variables in PISA 2006 and 2009 were statistically significant predictors of science performance. At the school level, location of school was a significant predictor of science achievement in both PISA 2006 and 2009.
Similar content being viewed by others
References
Alacacı, C., & Erbaş, A. K. (2010). Unpacking the inequality among Turkish schools: Findings from PISA 2006. International Journal of Educational Development, 30(2), 182–192.
Anderson, J. O., Lin, H. S., Treagust, D. F., Ross, S. P., & Yore, L. D. (2007). Using large-scale assessment data sets for research in science and mathematics education: Programme for International Student Assessment (PISA). International Journal of Science and Mathematics Education, 5(4), 591–614.
Anıl, D. (2009). Factors effecting science achievement of science students in Programme for International Students’ Achievement (PISA) in Turkey. Education and Science, 34(152), 87–100.
Barone, C. (2006). Cultural capital, ambition and the explanation of inequalities in learning outcomes: A comparative analysis. Sociology, 40(6), 1039–1058.
Boyd, W. L. (1991). What makes ghetto schools succeed or fail? Teachers College Record, 92, 331–362.
Chevalier, A., & Lanot, G. (2002). The relative effect of family characteristics and financial situation on educational achievement. Education Economics, 10(2), 165–181.
Coleman, J. S., Campbell, E. Q., Hobson, C. J., McPartlant, J., Mood, A. M., Weinfall, F. D., et al. (1966). Equality of educational opportunity. Washington, DC: Department of Health, Education and Welfare.
Cordero, J. M., Crespo, E., & Santín, D. (2010). Factors affecting educational attainment: Evidence from Spanish PISA 2006 results. Regional and Sectorial Economic Studies, 10(3), 55–76.
Delen, E., & Bulut, O. (2011). The relationship between students’ exposure to technology and their achievement in science and math. Turkish Online Journal of Educational Technology, 10(3), 311–317.
Engin-Demir, C. (2009). Factors influencing the academic achievement of the Turkish urban poor. International Journal of Educational Development, 29, 17–29.
Fuchs, T., & Wößmann, L. (2007). What accounts for international differences in student performance? A re-examination using PISA data. Empirical Economics, 32, 433–464.
Gilleece, L., Cosgrove, J., & Sofroniou, N. (2010). Equity in mathematics and science outcomes: Characteristics associated with high and low achievement on PISA 2006 in Ireland. International Journal of Science and Mathematics Education, 8, 475–496.
Gürsakal, S. (2012). An evaluation of PISA 2009 student achievement levels’ affecting factors. Süleyman Demirel University the Journal of Faculty of Economics and Administrative Sciences, 17(1), 441–452.
Hallinan, M. T. (1994). Tracking: From theory to practice. Sociology of Education, 67(2), 79–84.
Hanushek, E. A. (2003). The failure of input based schooling policies. The Economic Journal, 113(485), 64–98.
Hanushek, E. A., & Luque, J. (2003). Efficiency and equity in schools around the world. Economics of Education Review, 22, 481–502.
Heyneman, S. P., & Loxley, W. (1983). The effect of primary school quality on academic achievement across twenty-nine high- and low-income countries. American Journal of Sociology, 88(6), 1162–1194.
Ho, S. C. (2010a). Family influences on science learning among Hong Kong adolescents: What we learned from PISA. International Journal of Science and Mathematics Education, 8, 409–428.
Ho, S. C. (2010b). Assessing the quality and equality of Hong Kong basic education results from PISA 2000+ to PISA 2006. Frontiers of Education in China, 5(2), 238–257.
Kalender, I., & Berberoglu, G. (2009). An assessment of factors related to science achievement of Turkish students. International Journal of Science Education, 31(10), 1379–1394.
Knipprath, H. (2010). What PISA tells us about the quality and inequality of Japanese education in mathematics and science. International Journal of Science and Mathematics Education, 8, 389–408.
Krueger, A. (1999). Experimental estimates of education production functions. The Quarterly Journal of Economics, 114, 497–532.
Kuziemko, I. (2006). Using shocks to school enrollment to estimate the effect of school size on student achievement. Economics of Education Review, 25(1), 63–75.
Ma, X. (2003). Measuring up: Academic performance of Canadian immigrant children in reading, mathematics and science. Journal of International Migration and Integration, 4(4), 541–576.
Maas, C. J. M., & Hox, J. J. (2005). Sufficient sample sizes for multilevel modeling. Methodology, 1, 86–92.
Ministry of National Education of Turkey (MONE) (2005). Science and technology curriculum of elementary schools (6th–8th grades) [in Turkish]. Board of Education.
Organisation for Economic Co-operation and Development (OECD) (2010b). PISA 2009 results: Learning trends: Changes in student performance since 2000, vol. V. Paris.
Organization for Economic Co-operation and Development (OECD) (2004). Learning for tomorrow’s world. First results from PISA 2003. Paris.
Organization for Economic Co-operation and Development (OECD) (2005). School sampling preparation manual. [Online] Retrieved May 02, 2013, from http://www.oecd.org/education/school/programmeforinternationalstudentassessmentpisa/39829698.pdf.
Organization for Economic Co-operation and Development (OECD) (2007a). PISA 2006: Science competencies for tomorrow’s world. Paris.
Organization for Economic Co-operation and Development (OECD) (2010a). PISA 2009 Results: What students know and can do—Student performance in reading, mathematics and science, vol. I. Paris.
Organization for Economic Co-operation and Development (OECD) (2010c). PISA 2009 results: Overcoming social background—Equity in learning opportunities and outcomes, vol. II. Paris.
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models (2nd ed.). Thousand Oaks, CA: Sage.
Raudenbush, S. W., Bryk, A. S., Cheong, Y. F., Congdon, R. T., & du Toit, M. (2011). HLM 7: Hierarchical linear and nonlinear modeling. Chicago, IL: Scientific Software International.
Rivkin, S. G., Hanushek, E. A., & Kain, J. F. (2005). Teachers, schools and academic achievement. Econometrica, 73(2), 417–458.
Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75, 417–453.
Sousa, S., Park, E. J., & Armor, D. J. (2012). Comparing effects of family and school factors on cross-national academic achievement using the 2009 and 2006 PISA surveys. Journal of Comparative Policy Analysis: Research and Practice, 14(5), 449–468.
Stewart, E. B. (2008). School structural characteristics, student effort, peer associations, and parental involvement: The influence of school-and individual-level factors on academic achievement. Education and Urban Society, 40(2), 179–204.
Xia, N. (2009). Family factors and student outcomes. Unpublished doctoral dissertation, Pardee RAND Graduate School, Santa Monica, CA.
Yalcin, M., Aslan, S., & Usta, E. (2012). Analysis of PISA 2009 exam according to some variables. Mevlana International Journal of Education, 2(1), 64–71.
Yayan, B., & Berberoglu, G. (2004). A re-analysis of the TIMSS-1999 mathematics assessment data of the Turkish students. Studies in Educational Evaluation, 30, 87–104.
Yılmaz, H. B. (2009). Turkish students’ scientific literacy scores: A multilevel analysis of data from program for international student assessment. Unpublished doctoral dissertation, The Ohio State University, Columbus, OH.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Topçu, M.S., Arıkan, S. & Erbilgin, E. Turkish Students’ Science Performance and Related Factors in PISA 2006 and 2009. Aust. Educ. Res. 42, 117–132 (2015). https://doi.org/10.1007/s13384-014-0157-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13384-014-0157-9