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Education Research International
Volume 2014, Article ID 490371, 8 pages
http://dx.doi.org/10.1155/2014/490371
Research Article

A Structural Equation Modeling on Factors of How Experienced Teachers Affect the Students’ Science and Mathematics Achievements

1Department of Science and Mathematics Education, Education Faculty, Yüzüncü Yıl University, 65280 Van, Turkey
2Department of Science and Mathematics Education, Education Faculty, Dicle University, 21280 Diyarbakır, Turkey

Received 24 January 2014; Revised 27 May 2014; Accepted 2 June 2014; Published 24 June 2014

Academic Editor: Yi-Shun Wang

Copyright © 2014 Serhat Kocakaya and Ferit Kocakaya. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. K. Bos and W. Kuiper, “Modeling TIMSS data in a European comparative perspective: exploring influencing factors on achievement in mathematics in Grade 8,” Educational Research and Evaluation, vol. 5, no. 2, pp. 157–179, 1999. View at Google Scholar
  2. C. Shen, “Social values associated with cross-national differences in mathematics and science achievement,” Assessment in Education, vol. 8, no. 2, pp. 193–223, 1999. View at Google Scholar
  3. F. K. Leung, “Behind the high achievement of east Asian students,” Educational Research and Evaluation, vol. 8, pp. 87–108, 2002. View at Google Scholar
  4. G. Berberoğlu, Ö. Çelebi, E. Özdemir, E. Uysal, and B. Yayan, “Factors that affect the achievement levels of the Turkish students in Third International Mathematics and Science Study-TIMSS,” Educational Sciences and Application, vol. 2, no. 3, pp. 3–14, 2003 (Turkish). View at Google Scholar
  5. Ç. İş, A cross-cultural comparison of factors affecting mathematical literacy of students in programme for international student assessment (PISA) [M.S. thesis], Middle East Technical University.
  6. T. R. Koballa and S. M. Glynn, “Attitudinal and motivational constructs in science learning,” in Handbook for Research in Science Education, S. K. Abell and N. Lederman, Eds., Earlbaum, Mahwah, NJ, USA, 2004. View at Google Scholar
  7. B. Yayan and G. Berberoglu, “A re-analysis of the TIMSS 1999 mathematics assessment data of the Turkish students,” Studies in Educational Evaluation, vol. 30, no. 1, pp. 87–104, 2004. View at Publisher · View at Google Scholar · View at Scopus
  8. G. Akyüz, “Investigation of the effects of the teacher and classroom attributes on mathematics achievement in Turkey and the European Union countries,” Primary Education Online, vol. 5, no. 2, pp. 75–86, 2006 (Turkish). View at Google Scholar
  9. J. D. House, “Mathematics beliefs and achievement of elementary school students in Japan and the United States: results from the Third International Mathematics and Science study,” The Journal of Genetic Psychology, vol. 167, no. 1, pp. 31–45, 2006. View at Publisher · View at Google Scholar · View at Scopus
  10. E. Ceylan and G. Berberoğlu, “Factors that explain the science achievements of students: a modeling study,” Education and Science, vol. 32, no. 144, pp. 36–48, 2007 (Turkish). View at Google Scholar
  11. S. A. Altun and M. Çakan, “Factors that affect the central exam achievements of students: sample of successful provinces in ÖSS/LGS,” Primary Education Online, vol. 7, no. 1, pp. 157–173, 2008 (Turkish). View at Google Scholar
  12. İ. Üzkurt and M. Koçakoğlu, “Correlation between 7th grade students' school achievements and exam of determining the levels (SBS),” in Proceedings of the 1st International Congress of Educational Research, Çanakkale, Turkey, May 2009, (Turkish).
  13. S. Uzun, S. Ö. Bütüner, and N. Yigit, “Comparison of the 1999–2007 TIMSS's reports,” Primary Education Online, vol. 9, no. 3, pp. 1174–1188, 2010 (Turkish). View at Google Scholar
  14. D. F. Robitaille and E. D. Robeck, “The character and the context of TIMSS,” in Research Questions and Study Design. TIMSS Monograph N.2, D. F. Robitaille and R. A. Garden, Eds., Pasific Educational Press, Vancouver, Canada, 1996. View at Google Scholar
  15. M. O. Martin, K. D. Gregory, and S. E. Stemler, TIMSS 1999 Technical Report: IEA’s Repeat of the Third International Mathematics and Science Study at the Eighth Grade, Boston College, Chestnut Hill, Mass, USA, 2000.
  16. I. V. S. Mullis, M. O. Martin, E. J. Gonzales et al., TIMSS I999 International Mathematics Report: Findings fi-om IEA’s Repeat of the Third International Mathematics and Science Study at the Eighth Grade, Boston College, Chestnut Hill, Mass, USA, 2000.
  17. M. Çakan, “Examination of concepts of intelligence and cognitive styles and their importance in terms of student achievement,” Educational Researches, vol. 8, pp. 86–95, 2002 (Turkish). View at Google Scholar
  18. W. Wendling and J. Cohen, “Education resources and student achievement: good news for schools,” Journal of Education Finance, vol. 7, pp. 44–63, 1981. View at Google Scholar
  19. R. Greenwald, L. V. Hedges, and R. D. Laine, “The effect of school resources on student achievement,” Review of Educational Research, vol. 66, no. 3, pp. 361–396, 1996. View at Publisher · View at Google Scholar · View at Scopus
  20. D. D. Goldhaber and D. J. Brewer, “Evaluating the effect of teacher degree level on educational performance,” in Developments in School Finance, J. W. Fowler, Ed., US Department of Education, National Center for Education Statistics, Washington, DC, USA, 1997. View at Google Scholar
  21. A. J. Wayne and P. Youngs, “Teacher characteristics and student achievement gains: a review,” Review of Educational Research, vol. 73, no. 1, pp. 89–122, 2003. View at Publisher · View at Google Scholar · View at Scopus
  22. E. A. Hanushek and S. G. Rivkin, “How to improve the supply of high quality teachers,” in Brookings Papers on Education Policy 2004, D. Ravitch, Ed., Brookings Institution Press, Washington, DC, USA, 2004. View at Google Scholar
  23. E. A. Hanushek, “What if there are no “best practices”?” Scottish Journal of Political Economy, vol. 51, no. 2, pp. 156–172, 2004. View at Google Scholar
  24. V. Yılmaz, H. E. Çelik, and E. H. Ekiz, “Investigation of the factors that affect the Authority's Commitment with structural equation modeling; a sample of bank of primary and government,” Journal of Social Sciences, vol. 2, pp. 171–184, 2006 (Turkish). View at Google Scholar
  25. J. H. Hair, R. L. Tatham, and R. E. Anderson, Multivariate Data Analysis, Prentice Hall International, New York, NY, USA, 5th edition, 1998.
  26. Information Technology Services, “Structural Equation Modeling Using AMOS: An Introduction,” 2004, http://www.utexas.edu/its/rc/tutorials/stat/amos/.
  27. J. J. Hox and T. M. Bechger, “An introduction to structural equation modeling,” Family Science Review, vol. 11, pp. 354–373, 1995. View at Google Scholar
  28. J. G. Anderson, “The basic of structural equation model,” 2004, http://web.ics.purdue.edu/~janders1/assets/pdf/SOC_681_Structural_Equation_Models_Syllabus_2011.pdf .
  29. H. W. Marsh and D. Hocevar, “Application of confirmatory factor analysis to the study of self-concept. First- and higher order factor models and their invariance across groups,” Psychological Bulletin, vol. 97, no. 3, pp. 562–582, 1985. View at Publisher · View at Google Scholar · View at Scopus
  30. M. W. Browne, R. Cudeck, K. A. Bollen, and J. S. Long, “Alternative ways of assessing model fit,” in Testing Structural Equation Models, K. A. Bollen and J. S. Long, Eds., pp. 136–162, Sage, Newsbury Park, Calif, USA, 1993. View at Google Scholar
  31. B. M. Byrne, Structural Equation Modeling with EQS and EQS/Windows, Sage, Thousand Oaks, Calif, USA, 1994.
  32. K. G. Jöreskog and D. Sörbom, LISREL 7 User's Reference Guide, SPSS Publications, Chicago, Ill, USA, 1989.
  33. P. M. Bentler and D. G. Bonett, “Significance tests and goodness of fit in the analysis of covariance structures,” Psychological Bulletin, vol. 88, no. 3, pp. 588–606, 1980. View at Publisher · View at Google Scholar · View at Scopus
  34. K. A. Bollen, “A new incremental fit index for general structural equation models,” Sociological Methods and Research, vol. 17, pp. 303–316, 1989. View at Google Scholar
  35. K. A. Bollen, “Sample size and bentler and Bonett's nonnormed fit index,” Psychometrika, vol. 51, no. 3, pp. 375–377, 1986. View at Publisher · View at Google Scholar · View at Scopus
  36. R. W. Harbison and E. A. Hanushek, Educational Performance of the Poor: Lessons from Rural Northeast Brazil, Oxford University Press, The World Bank, New York, NY, USA, 1992.