National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. (2011b). Expanding underrepresented minority participation: America’s science and technology talent at the crossroads. Committee on Underrepresented Groups and the Expansion of the Science and Engineering Workforce Pipeline, Committee on Science, Engineering, and Public Policy, Policy and Global Affairs, Washington, DC: The National Academies Press.

20 U.S. Department of Labor. (2007). The STEM workforce challenge: The role of the public workforce system in a national solution for a competitive science, technology, engineering, and mathematics (STEM) workforce. Washington, DC: Author. Available at:

21 Lacey and Wright. (2009). See note 5.

22 Ibid.

23 National Research Council. (1996). National science education standards. Washington, DC: National Academy Press.

24 Hansen. M., and Choi, K. (2011). Chronically low-performing schools and turnaround: Evidence from three states. CALDER Working Paper #60. Washington, DC: Center for the Analysis of Longitudinal Data in Education Research.

25 Subotnik, R.F., and Tai, R.H. (2011, May). Successful education in the STEM disciplines: An examination of selective specialized science mathematics and technology-focused high schools. [Presentation slides]. Presented at the National Research Council Workshop on Successful STEM Education in K-12 Schools. Available at:

26 Ibid.

27 The study, being prepared by Rena Subotnik and Robert Tai, is using a quasi-experimental design to determine whether graduates of selective STEM secondary schools are more likely to remain in the STEM pipeline than students with similar achievement and interests who attended more comprehensive public secondary schools.

28 Subotnik, R.F., and Tai, R.H. (2011, May). See note 25.

29 Young, V.M., House, A., Wang, H., Singleton, C., and Klopfenstein, K. (2011). Inclusive STEM schools: Early promise in Texas and unanswered questions. Paper presented at the National Research Council Workshop on Successful STEM Education in K-12 Schools. Available at: This quote was taken from page 2.

30 Ibid.

31 Ibid.

32 Young et al. (2011) (see note 29) used propensity score matching to identify comparison schools (this method is described in their report). Student and school characteristics also were entered as statistical controls to further disentangle school effects from differences among student populations.

33 Stone, J.R., III. (2011). Delivering STEM education through career and technical education schools and programs. Paper presented at the National Research Council Workshop on Successful STEM Education in K-12 Schools. Available at:

34 Stone, J.R., III, Alfeld, C., and Pearson, D. (2008). Rigor and relevance: Testing a model of enhanced math learning in career and technical education. American Education Research Journal, 45, 767-795.

35 Council of Chief State School Officers. (2008). Key state education policies on PK-12 education: 2008. Washington, DC: Author.

36 Lee, J.M., Jr., and Rawls, A. (2010). The College Board completion agenda: 2010 progress report. New York: The College Board Advocacy and Policy Center. Available at:

37 Pellegrino, J. (2010, January). Redesign for Advanced Placement science curriculum. [Presentation slides]. Presented at a meeting of the National Research Council’s Conceptual Framework for New Science Education Standards Committee. Available at:

38 Ibid.

39 National Research Council. (2002). Learning and understanding: Improving advanced study of mathematics and science in U.S. high schools. Committee on Programs for Advanced Study of Mathematics and Science in American High Schools. Washington, DC: The National Academies Press. Quote taken from page 5.

40 Many other issues are also important to STEM learning for which we lacked the time and available research syntheses to address. These issues include but are not limited

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