Advertisement

AN EXAMINATION OF THE IMPACT OF TEACHER QUALITY AND “OPPORTUNITY GAP” ON STUDENT SCIENCE ACHIEVEMENT IN CHINA

  • Danhui Zhang
  • Todd CampbellEmail author
Article

Abstract

This study aims to better understand questions related to the impact of teacher quality and access to qualified teachers in China. A large-scale data set collected in 2010 in China was used along with concurrently collected teacher questionnaires. In total, surveys from 9,943 8th grade students from 343 middle schools in 6 provinces were used, along with 2,084 teacher questionnaires from each of the sampled schools. Multilevel (or hierarchical linear) statistical modeling analyses along with multivariate analysis of variance were completed to investigate the impact of science teacher characteristics on student achievement and whether there was an “opportunity gap” between high and low socioeconomic status (SES) students’ access to qualified science teachers in the subject of biology, physics, and earth and space science. In this research, little evidence was found to support the claim that teacher-related factors are consistently related to student achievement in science, while school-level SES was considered in the model. However, school-level SES was consistently found to be an influential factor of student science achievement. In addition, it was discovered that, in China, a disparity was found between high and low SES schools with respect to access to quality teachers.

Key words

opportunity gap science teacher characteristics science teacher quality student achievement 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Akiba, M., LeTendre, G. K. & Scribner, J. P. (2007). Teacher quality, opportunity gap, and national achievement in 46 countries. Education Researcher, V36(7), 369–387.CrossRefGoogle Scholar
  2. American Association for the Advancement of Science (1993). Benchmarks for science literacy. New York: Oxford University Press.Google Scholar
  3. Ascher, C. & Fruchter, N. (2001). Teacher quality and student performance in New York City’s low-performing schools. Journal of Education for Students Placed at Risk, 6(3), 199–214.CrossRefGoogle Scholar
  4. Author (2008). Testing teacher candidates: The role of licensure tests in improving teacher quality. Doctoral dissertation.Google Scholar
  5. Board on Testing and Assessment (2001). Testing teacher candidates: The role of licensure tests in improving teacher quality. Washington, DC: The National Academies Press.Google Scholar
  6. Bybee, R. W. (2013). The case for STEM education: Challenges and opportunities. Arlington: NSTA Press.Google Scholar
  7. Campbell, T., Lee, H., Kwon, H., & Kyungsuk, P. (2012). Student motivation and interests as proxies for forming STEM identities. Journal of the Korean Association for Science Education, 32(3), 532–540.Google Scholar
  8. Darling-Hammond, L. (2000). Teacher quality and student achievement: A review of state policy evidence. Education Policy Analysis Archives, 8(1), 1–44.Google Scholar
  9. Darling-Hammond, L. (2002). The research and rhetoric on teacher certification: A response to “Teacher certification reconsidered.” Educational Policy Analysis Archives, 10(36), 1–55.Google Scholar
  10. Darling-Hammond, L. (2004). Inequality and the right to learn: Access to qualified teachers in California’s public schools. Teachers College Record, 106(10), 1936–1966.CrossRefGoogle Scholar
  11. Darling-Hammond, L. (2006). Securing the right to learn: Policy and practice for powerful teaching and learning. Educational Researcher, 35(7), 13–24.CrossRefGoogle Scholar
  12. Dossett, D. & Munoz, M.A. (2003). Classroom accountability: A value-added methodology. Paper presented at the Annual meeting of the American Educational Research Association, Chicago, IL, April 21–25Google Scholar
  13. Drummond, D. (2010). An analysis of the relationships between school district salary supplements and selected teacher characteristics and student achievement in Georgia. Doctoral dissertation, Mercer University.Google Scholar
  14. Ferguson, R. F. (1991). Paying for public education: New evidence on how and why money matters. Harvard Journal on Legislation, 28(2), 465–498.Google Scholar
  15. Ferguson, R. F. & Ladd, H. F. (1996). How and why money matters: An analysis of Alabama schools. In H. F. Ladd (Ed.), Holding schools accountable: Performance-based reform in education (pp. 265–298). Washington, DC: BrookingsGoogle Scholar
  16. Goldhaber, D. E. (2004). Indicators of teacher quality. New York: ERIC Clearinghouse on Urban Education.Google Scholar
  17. Goldhaber, D. D. & Brewer, D. J. (1996). Why don’t schools and teachers seem to matter? Assessing the impact of unobservables on educational productivity. Revised version of a paper presented at Meetings of the Econometric Society, San Francisco, CA, January 1996.Google Scholar
  18. Goldhaber, D. D. & Brewer, D. J. (2000). Does teacher certification matter? High school teacher certification status and student achievement. Educational Evaluation and Policy Analysis, 22(2), 129–145.CrossRefGoogle Scholar
  19. US Government Accountability Office (2005). Federal science, technology, engineering, and mathematics programs and related trends. GAO-06-114.Google Scholar
  20. Greenberg, E., Rhodes, D., Ye, X. & Stancavage, F. (2004). Prepared to teach: Teacher preparation and student achievement in eighth-grade mathematics. Washington, DC: American Institute for Research.Google Scholar
  21. Greenwald, R., Hedges, L. V. & Lain, R. D. (1996). The effects of school resources on student achievement. Review of Educational Research, 66(3), 361–396.CrossRefGoogle Scholar
  22. Hanushek, E. A. (1989). The impact of differential expenditures on school performance. Educational Researcher, 18(4), 45–65.CrossRefGoogle Scholar
  23. Hanushek, E. A. (1997). Assessing the effects of school resources on student performance: An update. Educational Evaluation and Policy Analysis, 19(2), 141–164.CrossRefGoogle Scholar
  24. Hedges, L. V., Lain, R. D. & Greenwald, R. (1994). Does money matter? A meta-analysis of studies of the effects of differential school inputs on student outcomes. Educational Researcher, 23(3), 5–14.CrossRefGoogle Scholar
  25. Hill, H. (2007). Mathematical knowledge of middle school teachers: Implications for the No Child Left Behind policy initiative. Educational Evaluation and Policy Analysis, 29(2), 95–114.Google Scholar
  26. Hill, H. C., Rowan, R., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42(2), 371–406.Google Scholar
  27. Holbrook, K. (2008). The global STEM imperative. Educause Review, 2, 8–9.Google Scholar
  28. Konstantopoulos, S. (2006). Trends of school effects on student achievement: Evidence from NLS:72, HSB:82, and NELS:92. Teachers College Record, 108, 2550–2581.CrossRefGoogle Scholar
  29. Kuenzi, J. J. (2008). Science, Technology, Engineering, and Mathematics (STEM) education: Background, federal policy, and legislative action. Congressional Research Service Reports. Paper 35. http://digitalcommons.unl.edu/crsdocs/35.
  30. Lederman, N., Lederman, J. & Antink, A. (2013). Nature of science and scientific inquiry as contexts for the learning of science and achievement of science literacy. International Journal of Education in Mathematics, Science, and Technology, 1(3), 138–147.Google Scholar
  31. Lees, L. H. (1994). Educational inequality and academic achievement in England and France. Comparative Education Review, 38, 65–87.CrossRefGoogle Scholar
  32. Luschei, T. F. & Chudgar, A. (2011). Teachers, student achievement and national income: A cross-national examination of relationships and interactions. Prospects, 41, 507–533.CrossRefGoogle Scholar
  33. Ma, X., Ma, L. & Bradley, K. D. (2008). Using multilevel modeling to investigate school effects. In A. A. O’Connell & D. B. McCoach (Eds.), Multilevel modeling of educational data (pp. 59–110). Charlotte, NC: Information Age.Google Scholar
  34. Ma, X. & Wilkins, J. M. (2002). The development of science achievement in middle and high school. Education Review, V26(4), 395–417.Google Scholar
  35. Monk, D. H. (1994). Subject area preparation of secondary mathematics and science teachers and student achievement. Economics of Education Review, 13(2), 125–145.CrossRefGoogle Scholar
  36. National Research Council (NRC). (1996). National Science Education Standards. Washington, DC: National Academy Press.Google Scholar
  37. National Research Council (2007). Rising above the gathering storm: Energizing and employing America for a brighter economic future. Washington, DC: The National Academies.Google Scholar
  38. No Child Left Behind Act (2001). Pub L. No. 107–110.Google Scholar
  39. OECD [Organization for Economic Cooperation, Development]. (2005). Teachers matter: Attracting, developing, and retaining effective teachers. Paris: OECD.Google Scholar
  40. Peske, H. G. & Haycock, K. (2006). Teaching inequality: How poor and minority students are shortchanges on teacher quality. Washington, DC: Education Trust.Google Scholar
  41. Reiser, B. J., Tabak, I., Sandoval, W. A., Smith, B. K., Steinmuller, F. & Leone, A. J. (2001). BGuILE: Strategies and conceptual scaffolds for scientific inquiry in biology classroom. In S. M. Carver & D. Klahr (Eds.), Cognition and instruction: Twenty-five years of progress (pp. 263–305). Mahwah: Lawrence Erlbaum Association.Google Scholar
  42. Rice, J. K. (2003). Teacher quality: Understanding the effectiveness of teacher attributes. Washington, DC: Economic Policy Institute.Google Scholar
  43. Rivkin, S., Hanushek, E. & Kain, J. (2005). Teachers, schools and academic achievement. Econometrica, 73(2), 417–458.CrossRefGoogle Scholar
  44. Rowan, B., Chiang, F. & Miller, R. J. (2002). What large-scale survey research tells us about teacher effects on students’ achievement. Sociology of Education, 70(4), 256–284.CrossRefGoogle Scholar
  45. State Guidelines for Medium- to Long-Term Educational Reform and Development Plan (2010). http://www.gov.cn/jrzg/2010-07/29/content_1667143.html.
  46. Teachers Law of the People’s Republic of China (1994). http://www.people.com.cn/item/flfgk/rdlf/1993/111603199341.html.
  47. UNESCO Institute for Statistics (2008). A view inside primary schools a world education indicators (WEI) cross-national study. Retrieved from http://unesdoc.unesco.org/images/0016/001624/162406e.pdf.
  48. USAID (2009a). About DBE. http://dbe.rti.org/about/.
  49. USAID (2009b). Education in Pakistan. http://www.usaid.gov/pk/education/index.htm.
  50. Wang, Q. (2012). How different stakeholders perceive “teacher rotation system”? Teacher Education Research, V24(3), 74–78.Google Scholar
  51. Wang, C. & Fang, T. (2005). Implications of Japanese teacher rotation system on local teacher resource equity. Journal of Chinese Society Education, V4(4), 59–62.Google Scholar
  52. Wayne, A. J. & Youngs, P. (2003). Teacher characteristics and student achievement gains: A review. Review of Educational Research, 73(1), 89–122.CrossRefGoogle Scholar
  53. Wei, R. C., Darling-Hammond, L., Andree, A., Richardson, N. & Orphanos, S. (2009). Professional learning in the learning profession: A status report on teacher development in the United States and abroad. Dallas, TX: National Staff Development Council.Google Scholar
  54. Wenglinsky, H. (2002). The link between teacher classroom practices and student academic performance. Education Policy Analysis Archives, 10(12), 1–30.Google Scholar
  55. White, K. R. (1982). The relation between socioeconomic status and academic achievement. Psychological Bulletin, 91, 461–481.CrossRefGoogle Scholar
  56. Winheller, S., Hattie, J. A. & Brown, G. T. L. (2013). Factors influencing early adolescents’ mathematics achievement: High-quality teaching rather than relationships. Learning Environments Research, 16(1), 49–69.CrossRefGoogle Scholar
  57. Xin, T., Xu, Z. & Tatsuoka, K. (2004). Linkage between teacher quality, student achievement, and cognitive skills: A rule-space model. Studies in Educational Evaluation, 30, 205–223.CrossRefGoogle Scholar
  58. Ye, R. M. (2000). The effect of teacher characteristics, beliefs, relations with students, and in-service education on student science achievement. Doctoral dissertation. Texas Technology University.Google Scholar
  59. Young, D. J. & Fraser, B. J. (1993). Socioeconomic and gender effects on science achievement: An Australian perspective. School Effectiveness and School Improvement, 4, 265–289.CrossRefGoogle Scholar

Copyright information

© National Science Council, Taiwan 2014

Authors and Affiliations

  1. 1.Beijing Normal UniversityBeijingChina
  2. 2.University of ConnecticutStorrsUSA

Personalised recommendations