The Link between Instructional Practice and the Racial Gap in Middle Schools

RMLE Online

Volumn 28, Issue 1, 2004, Pages 1-13

  Wenglinsky, Harold ^a  

^a CITY UNIVERSITY OF NEW YORK   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84863256650     PISSN: None     EISSN: 19404476     Source Type: Journal    
DOI: 10.1080/19404476.2004.11658172     Document Type: Article

References (29)

1. Bryk, A. S., & Raudenbush, S. W., (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park: Sage Publications.
2. Christie, K., (2002). States address achievement gaps. Phi Delta Kappan, 84(2): 102-103.
3. Cohen, D. K., & Hill, H. C., (2000). Instructional policy and classroom performance: The mathematics reform in California. Teachers College Record, 102(2), 294-343.
4. Cohen, D. K., McLaughlin, M. W., & Talbert, J. E., (1993). Teaching for understanding: Challenges for policy and practice. San Francisco: Jossey-Bass.
5. Ferguson, R. F., & Ladd, H. F., (1996). How and why money matters: An analysis of Alabama schools. In H. F., Ladd (Ed.), Holding school accountable: Performance-based reform in education (pp. 265-298). Washington, DC: The Brookings Institution.
6. Ferguson, R. F., (1991). Paying for public education: New evidence on how and why money matters. Harvard Journal of Legislation, 28(2), 465-498.
7. Goldhaber, D. D., & Brewer, D. J., (1996). Why don’t schools and teachers seem to matter? Assessing the impact of unobservables on educational productivity. Journal of Human Resources, 32(3), 505-520.
8. Greenwald, R., Hedges, L. V., & Laine, R. D., (1996). The effect of school resources on student achievement. Review of Educational Research, 66(3), 361-396.
9. Hanushek, E. A., (1989). The impact of differential expenditures on school performance. Educational Research, 18(4), 45-51.
10. Hanushek, E. A., (1996a). A more complete picture of school resource policies. Review of Educational Research, 66(3), 397-409.
11. Hanushek, E. A., (1996b). School resources and student performance. In G. T., Burtless (Ed.), Does money matter? The effect of school resources on student achievement and adult success (pp. 43-73). Washington, DC: The Brookings Institution.
12. Hanushek, E. A., (1997). Assessing the effects of school resources on student performance: An update. Educational Evaluation and Policy Analysis, 19(2), 141-164.
13. Hedges, L. V., Laine, R. D., & Greenwald, R., (1994). Does money matter? A meta-analysis of studies of the effects of differential school inputs on student outcomes. Educational Research, 23(3), 5-14.
14. Hedges, L. W., & Greenwald, R., (1996). Have times changed? The relation between school resources and student performance. In G. T., Burtless (Ed.), Does money matter? The effect of school resources on student achievement and adult success (pp. 74-92). Washington, DC: The Brookings Institution.
15. Jencks, C., & Phillips, M., (1998). Introduction. In C., Jencks & M., Phillips (Eds.) The Black-White test score gap (p. 1-51). Washington, DC: Brookings Institution Press.
16. Johnson, E., Mislevy, R. J., & Thomas, N., (1994). Scaling procedures. In E., Johnson & J., Carlson, The NAEP 1992 technical report (pp. 241-256). Princeton, NJ: Educational Testing Service.
17. Johnson, E. G., (1989). Considerations and techniques for the analysis of NAEP data. Journal of Education Statistics, 14(4), 303-334.
18. Lee, V. E., & Burkham, D. T., (2002). Inequality at the starting gate: Social background differences in achievement as children begin school. Washington, DC: Economic Policy Institute.
19. Lubienski, S. T., (2002). A closer look at Black-White mathematics gaps: Intersections of race and SES in NAEP achievement and instructional practices data. Journal of Negro Education, 71(4), 269-287.
20. Mayer, D. P., (1999). Measuring instructional practice: Can policymakers trust survey data? Educational Evaluation and Policy Analysis, 21(1), 29-45.
21. Monk, D. H., (1994). Subject area preparation of secondary mathematics and science teachers and student achievement. Economics of Education Review, 13(2), 125-145.
22. Moses, M., & Orfield, G., (2002). Embracing race: Why we need race-conscious education policy. New York: Teachers College Press.
23. National Center for Education Statistics. (1996). High school seniors’ instructional experiences in science and mathematics. Washington, DC: U.S. Government Printing Office.
24. North Carolina Advisory Commission on Raising Achievement and Closing Gaps. (2003). Implementation plan for recommendations from the North Carolina Advisory Commission on Raising Achievement and Closing Gaps. www.ncpublicschools.org/schoolimprovement/closingthegap/reports/downloads/implementation03.pdf
25. O’Reilly, P. E., Zelenak, C. A., Rogers, A. M., & Kline, D. L., (1996). 1994 trial state assessment program in reading secondary-use data files user guide. Washington, DC: U.S. Department of Education.
26. Phillips, M., Brooks-Gunn, J., Duncan, G. J., Klebanov, P., & Crane, J., (1998). Family background, parenting practices and the Black-White test score gap. C., Jencks & M., Phillips (Eds.) The Black-White test score gap (pp. 103-145). Washington, DC: Brookings Institution Press.
27. Von Secker, C., (2002). Effects of inquiry-based teacher practices on science excellence and equity. Journal of Educational Research, 95(3), 151-160.
28. Wenglinsky, H., (2003). Using large-scale research to gauge the impact of instructional practices on student reading comprehension: An exploratory study. Education Policy Analysis Archives, 11, 19.
29. Wenglinsky, H., (2002). How schools matter: The link between teacher classroom practices and student academic performance. Education Policy Analysis Archives, 10, 12.