Mathematics and science course graduation requirement (CGR) increases in the 1980s and 1990s might have had both intended and unintended consequences. Using logistic regression with Census and American Community Survey (ACS) data (n = 2,892,444), we modeled CGR exposure on (a) high school dropout, (b) beginning college, and (c) obtaining any college degree. Possible between-groups differences were also assessed. We found that higher CGRs were associated with higher odds to drop out of high school, but results for the college-level outcomes varied by group. Some were less likely to enroll, whereas others who began college were more likely to obtain a degree. Increased high school dropout was consistent across the population, but some potential benefit was also observed, primarily for those reporting Hispanic ethnicity.
ACT. (2006). College and Workforce Training Readiness. Iowa City, IA: Author.
2.
AllensworthE.NomiT.MontgomeryN.LeeV. E. (2009). College preparatory curriculum for all: Academic consequences of requiring algebra and English I for ninth graders in Chicago. Educational Evaluation and Policy Analysis, 31(4), 367–391.
BeattyA.GreenwoodM.LinnR. L. (Eds.). (1999). Myths and tradeoffs: The role of tests in undergraduate admissions. Washington, DC: National Academies Press.
6.
BerryW. D.RingquistE. J.FordingR. C.HansonR. L. (1998). Measuring citizen and government ideology in the American states, 1960-93. American Journal of Political Science, 42(1), 327–348.
7.
BertrandM.DufloE.MullainathanS. (2002). How much should we trust differences-in-differences estimates? (Working Paper No. 8841). Cambridge, MA: National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w8841
8.
Center for Policy Research in Education. (1989). Graduating from high school: New standards in the States. A “bulletin” special. CPRE Policy Briefs (RB-02-04/89). Retrieved from http://www.eric.ed.gov/ERICWebPortal/detail?accno=EJ385300
9.
The Center for Public Education, & Change the Equation. (2013). Out of sync: Many common core states have yet to define a common core-worthy diploma. The Center for Public Education. Retrieved from http://changetheequation.org/sites/default/files/GradReqs_v5.pdf
10.
Daun-BarnettN.St. JohnE. P. (2012). Constrained curriculum in high schools: The changing math standards and student achievement, high school graduation and college continuation. Education Policy Analysis Archives, 20(5), n5.
GruczaR. A.HippP. R.NorbergK. E.RundellL.EvanoffA.Cavazos-RehgP.BierutL. J. (2012). The legacy of minimum legal drinking age law changes: Long-term effects on suicide and homicide deaths among women. Alcoholism: Clinical and Experimental Research, 36(2), 377–384. doi:10.1111/j.1530-0277.2011.01608.x
14.
GruczaR. A.PlunkA. D.HippP. R.Cavazos-RehgP.BrownsonR. C.BierutL. J. (2013). Long-term effects of laws governing youth access to tobacco. American Journal of Public Health, 103(8), 1493-1499.
15.
HeckD. J. (1998). Evaluating equity in statewide systemic initiatives: Asking the right questions. Journal of Women and Minorities in Science and Engineering, 4(2), 161–181.
16.
HeckmanJ. J.LaFontaineP. A. (2010). The American high school graduation rate: Trends and levels. The Review of Economics and Statistics, 92(2), 244–262. doi:10.1162/rest.2010.12366
17.
HellerD. E. (1997). Student price response in higher education: An update to Leslie and Brinkman. The Journal of Higher Education, 68(6), 624–659. doi:10.2307/2959966
18.
HofferT. (1997). High school graduate requirements: Effects on dropping out and student achievement. The Teachers College Record, 98(4), 584–607.
19.
KingM.RugglesS.AlexanderT.FloodS.GenadekK.SchroederM.… VickR. (2010). Integrated public use microdata series, current population survey: Version 3.0. (Machine-readable database). Minneapolis: University of Minnesota.
20.
KoberN.ZabalaD.ChudowskyN.ChudowskyV.GaylerK.McMurrerJ. (2006). State high school exit exams: A challenging year. Washington, DC: Center on Education Policy.
21.
KornhaberM. L.OrfieldG. (2001). High-stakes testing policies: Examining their assumptions and consequences. In Raising standards or raising barriers? Inequality in high stakes testing in public education (pp. 1–18). New York: Century Foundation Press.
22.
LillardD. R.DeCiccaP. P. (2001). Higher standards, more dropouts? Evidence within and across time. Economics of Education Review, 20(5), 459–473.
23.
LochnerL.MorettiE. (2001). The effect of education on crime: Evidence from prison inmates, arrests, and self-reports (no. w8605). Cambridge, MA: National Bureau of Economic Research.
24.
LumleyT. (2012). Survey: Analysis of complex survey samples. Journal of Statistical Software, 9(8).
25.
MeyerB. D. (1995). Natural and quasi-experiments in economics. Journal of Business & Economic Statistics, 13(2), 151–161. doi:10.1080/07350015.1995.10524589
26.
MillerM. L. S. (1997). An American imperative: Accelerating minority educational advancement. New Haven, CT: Yale University Press.
27.
MolloyR.SmithC. L.WozniakA. (2011). Internal migration in the United States. The Journal of Economic Perspectives, 25(3), 173–196. doi:10.1257/jep.25.3.173
National Commission on Excellence in Education. (1983). A nation at risk: The imperative for educational reform. Washington, DC: Author.
31.
National Research Council. (2007). Rising above the gathering storm: Energizing and employing America for a brighter economic future. Washington, DC: National Academies Press.
32.
National Research Council. (2011). Expanding underrepresented minority participation: America’s science and technology talent at the crossroads. Washington, DC: The National Academies Press.
33.
NichollsG. M.WolfeH.Besterfield-SacreM.ShumanL. J. (2010). Predicting STEM degree outcomes based on eighth grade data and standard test scores. Journal of Engineering Education, 99(3), 209–223.
34.
NobleJ.SchnelkerD. (2007). Using hierarchical modeling to examine course work and ACT score relationships across high schools. Iowa City, IA: ACT, Inc.
35.
NomiT. (2012). The unintended consequences of an algebra-for-all policy on high-skill students: Effects on instructional organization and students’ academic outcomes. Educational Evaluation and Policy Analysis, 34(4), 489–505. doi:10.3102/0162373712453869
36.
OreopoulosP.PageM. E.StevensA. H. (2006). The intergenerational effects of compulsory schooling. Journal of Labor Economics, 24(4), 729–760.
37.
PerkinsR.KleinerB.RoeyS.BrownJ. (2004). The high school transcript study: A decade of change in curricula and achievement, 1990–2000. Washington, DC: National Center for Education Statistics.
38.
PetersenM. A. (2009). Estimating standard errors in finance panel data sets: Comparing approaches. Review of Financial Studies, 22(1), 435–480. doi:10.1093/rfs/hhn053
39.
PlunkA. D.Cavazos-RehgP.BierutL. J.GruczaR. A. (2013). The persistent effects of minimum legal drinking age laws on drinking patterns later in life. Alcoholism: Clinical and Experimental Research, 37(3), 463–469.
40.
PongS.- L.JuD.- B. (2000). The effects of change in family structure and income on dropping out of middle and high school. Journal of Family Issues, 21(2), 147–169. doi:10.1177/019251300021002001
41.
R Development Core Team. (2012). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
42.
RobelenE. W. (2013). Questions arise about algebra 2 for all students. Education Week, 32(35), 1–29.
43.
RugglesS.AlexanderJ. T.GenadekK.GoekenR.SchroederM. B.SobekM. (2010). Integrated Public Use Microdata Series: Version 5.0 (Machine-readable database). Minneapolis: University of Minnesota.
44.
RumbautR. G.PortesA. (2001). Ethnicities: Children of immigrants in America. Berkeley: University of California Press.
45.
SecadaW. G. (1992). Race, ethnicity, social class, language, and achievement in mathematics. In GrouwsD. A. (Ed.), Handbook of research on mathematics teaching and learning. New York: Macmillan.
46.
SnyderT. D.HoffmanC. M. (1991a). Digest of education statistics 1990. Washington, DC: National Center for Education Statistics, Office of Educational Research and Improvement.
47.
SnyderT. D.HoffmanC. M. (1991b). Digest of education statistics 1991. Washington, DC: National Center for Education Statistics, Office of Educational Research and Improvement.
48.
SnyderT. D.HoffmanC. M. (2002). Digest of education statistics 2001. Washington, DC: National Center for Education Statistics, Office of Educational Research and Improvement.
49.
St. JohnE. P. (2006). Education and the public interest: School reform, public finance, and access to higher education (1st ed.). New York: Springer.
50.
TateW. F. (1997). Race-ethnicity, SES, gender, and language proficiency trends in mathematics achievement: An update. Journal for Research in Mathematics Education, 28(6), 652–679.
51.
TateW. F. (2006). Do the math: Cognitive demand makes a difference. Research Points: Essential Information for Education Policy, 4(2), 1–4.
52.
TateW. F.JonesB. D.Thorne-WallingtonE.HogrebeM. C. (2012). Science and the city: Thinking geospatially about opportunity to learn. Urban Education, 47(2), 399–433.
53.
TateW. F.Malancharuvil-BerkesE. (2006). A contract for excellence in scientific education: May I have your signature please?Journal of Teacher Education, 57(3), 278–285.
U.S. Census Bureau. (2009). American Community Survey design and methodology. Washington, DC: Author.
56.
WaldfogelJ.GarfinkelI.KellyB. (2007). Welfare and the costs of public assistance. In BelfieldC. R.LevinH. M. (Eds.), The price we pay: Economic and social consequences of inadequate education (pp. 160–174). Washington, DC: Brookings Institution Press.
57.
WebbN. L.KaneJ.KaufmanD.YangJ.- H. (2001). Study of the impact of the Statewide Systemic Initiatives Program. Madison: Wisconsin Center for Education Research.
58.
WooldridgeJ. M. (2010). Econometric analysis of cross section and panel data (2nd ed.). Cambridge, MA: MIT Press.
59.
ZuckerA. A.BlankR.GrossS. (1995). Evaluation of the National Science Foundation’s Statewide Systemic Initiatives (SSI) Program: Second year report: Cross-cutting themes. Arlington, VA: National Science Foundation.
60.
ZwickR.SklarJ. C. (2005). Predicting college grades and degree completion using high school grades and SAT scores: The role of student ethnicity and first language. American Educational Research Journal, 42(3), 439–464.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
