Taking advanced courses in high school predicts many positive outcomes, yet low-income students and students who identify as Black and Hispanic are underrepresented. Policies such as “algebra for all” that accelerate middle school students into advanced courses are well-studied, but little is known about newer academic acceleration policies that target older students. Between 2014–2015 and 2016–2017, 72 districts in Washington implemented Academic Acceleration policies, which identified proficient 11th- and 12th-grade students for automatic acceleration into AP, IB, and other dual credit courses. We used difference-in-differences models to examine changes in advanced course enrollments, GPAs, and high school graduation between districts that began implementing the policy at different times. We found advanced course enrollment increased and became more equitable postpolicy.
AdelmanC. (2006). The toolbox revisited: Paths to degree completion from high school through college. U.S. Department of Education, National Center for Education Statistics. https://eric.ed.gov/?id=ED490195
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. https://doi.org/10.3102/0162373709343471
4.
AnB. P. (2013a). The impact of dual enrollment on college degree attainment: Do low-SES students benefit?Educational Evaluation and Policy Analysis, 35(1), 57–75. https://doi.org/10.3102/0162373712461933
5.
AnB. P. (2013b). The influence of dual enrollment on academic performance and college readiness: Differences by socioeconomic status. Research in Higher Education, 54(4), 407–432. https://doi.org/10.1007/s11162-012-9278-z
6.
AnB. P.TaylorJ. L. (2019). A review of empirical studies on dual enrollment: Assessing educational outcomes. In PaulsenM. B.PernaL. W. (Eds.), Higher education: Handbook of theory and research (pp. 99–151). Springer.
7.
AndersonK. P. (2022). Biased opportunities: The role of implicit and explicit bias in Advanced Placement and dual enrollment (EdWorkingPaper 22-554). Brown University, Annenberg Institute. https://doi.org/10.26300/g600-0d47
8.
AttewellP.DominaT. (2008). Raising the bar: Curricular intensity and academic performance. Educational Evaluation and Policy Analysis, 30(1), 51–71. https://doi.org/10.3102/0162373707313409
9.
AustinM. J. (2017). High school curricular intensity: Inequalities in access and returns over three cohorts [Unpublished doctoral dissertation]. University of Notre Dame.
10.
AustinM. J. (2020). Measuring high school curricular intensity over three decades. Sociology of Education, 93(1), 65–90. https://doi.org/10.1177/0038040719885123
11.
AveryC.GoodmanJ. (2022). Ability signals and rigorous coursework: Evidence from AP Calculus participation (Working paper No. 2022-1). Boston University Wheelock Educational Policy Center.
12.
AveryC.GurantzO.HurwitzM.SmithJ. (2018). Shifting college majors in response to advanced placement exam scores. Journal of Human Resources, 53(4), 918–956. https://doi.org/10.3368/jhr.53.4.1016-8293r
13.
BowlesS.GintisH. (1976). Schooling in capitalist America: Educational reform and the contradictions of economic life. Haymarket Books.
CardD.GiulianoL. (2014). Does gifted education work? For which students? (WP 20453). National Bureau of Economic Research. https://www.nber.org/papers/w20453
16.
CardD.GiulianoL. (2016). Universal screening increases the representation of low-income and minority students in gifted education. Proceedings of the National Academy of Sciences, 113(48), 13678–13683. https://doi.org/10.1073/pnas.1605043113
17.
CastlemanB. L.PageL. C. (2015). Summer nudging: Can personalized text messages and peer mentor outreach increase college going among low-income high school graduates?Journal of Economic Behavior & Organization, 115, 144–160. https://doi.org/10.1016/j.jebo.2014.12.008
18.
CastlemanB. L.PageL. C. (2016). Freshman year financial aid nudges: An experiment to increase FAFSA renewal and college persistence. Journal of Human Resources, 51(2), 389–415. https://doi.org/10.3368/jhr.51.2.0614-6458r
19.
ChinM. J.QuinnD. M.DhaliwalT. K.LovisonV. S. (2020). Bias in the air: A nationwide exploration of teachers’ implicit racial attitudes, aggregate bias, and student outcomes. Educational Researcher, 49(8), 566–578. https://doi.org/10.3102/0013189x20937240
20.
ClotfelterC. T.LaddH. F.VigdorJ. L. (2015). The aftermath of accelerating algebra: Evidence from district policy initiatives. Journal of Human Resources, 50(1), 159–188. https://doi.org/10.1353/jhr.2015.0005
CongerD.LongM.IatarolaP. (2009). Explaining race, poverty, and gender disparities in advanced course-taking. Journal of Policy Analysis and Management, 28, 555–576. https://doi.org/10.1002/pam.20455
23.
ConwellJ. (2021). Diverging disparities: Race, parental income, and children's math scores, 1960 to 2009. Sociology of Education, 94(2), 124–142. https://doi.org/10.1177/0038040720963279
DarityW.CastellinoD.TysonK. (2001). Increasing opportunity to learn via access to rigorous courses and programs: One strategy for closing the achievement gap for at-risk and ethnic minority students. North Carolina State Department of Public Instruction. https://eric.ed.gov/?id=ED459303
26.
de ChaisemartinC.d’HaultfoeuilleX. (2020). Two-way fixed effects estimators with heterogeneous treatment effects. American Economic Review, 110(9), 2964–2996. https://doi.org/10.1257/aer.20181169
27.
DiamondJ. B.LewisA. E. (2022). Opportunity hoarding and the maintenance of “white” educational space. American Behavioral Scientist, 66(11), 1470–1489. https://doi.org/10.1177/00027642211066048
28.
DominaT.McEachinA.HanselmanP.AgarwalP.HwangN.LewisR. W. (2019). Beyond tracking and detracking: The dimensions of organizational differentiation in schools. Sociology of Education, 92(3), 293–322. https://doi.org/10.1177/0038040719851879
29.
DominaT.McEachinA.PennerA. M.PennerE. K. (2015). Aiming high and falling short: California's 8th grade algebra-for-all effort. Educational Evaluation and Policy Analysis, 37(3), 275–295. https://doi.org/10.3102/0162373714543685
DoughertyS. M.GoodmanJ. S.HillD. V.LitkeE. G.PageL. C. (2015). Middle school math acceleration and equitable access to eighth-grade algebra: Evidence from the Wake County Public School System. Educational Evaluation and Policy Analysis, 37(1S), 80S–101S. https://doi.org/10.3102/0162373715576076
32.
DoughertyS. M.GoodmanJ. S.HillD. V.LitkeE. G.PageL. C. (2017). Objective course placement and college readiness: Evidence from targeted middle school math acceleration. Economics of Education Review, 58, 141–161. https://doi.org/10.1016/j.econedurev.2017.04.002
EvansB. J. (2018). How college students use Advanced Placement credit. American Educational Research Journal, 56(3), 925–954. https://doi.org/10.3102/0002831218807428
35.
FergusonR. (2007). Toward excellence with equity: An emerging vision for closing the achievement gap. Harvard Education Press.
36.
GagnonD. J.MattinglyM. J. (2016). Advanced placement and rural schools: Access, success, and exploring alternatives. Journal of Advanced Academics, 27(4), 266–284. https://doi.org/10.1177/1932202x16656390
37.
GamoranA.HanniganE. C. (2000). Algebra for everyone? Benefits of college-preparatory mathematics for students with diverse abilities in early secondary school. Educational Evaluation and Policy Analysis, 22(3), 241–254. https://doi.org/10.2307/1164242
38.
GershensonS.HoltS. B.PapageorgeN. W. (2016). Who believes in me? The effect of student-teacher demographic match on teacher expectations. Economics of Education Review, 52, 209–224. https://doi.org/10.1016/j.econedurev.2016.03 .002
GrissomJ. A.ReddingC. (2016). Discretion and disproportionality: Explaining the underrepresentation of high-achieving students of color in gifted programs. AERA Open, 2(1), 1–25. https://doi.org/10.1177/2332858415622175
41.
GrissomJ. A.ReddingC.BleibergJ. F. (2019). Money over merit? Socioeconomic gaps in receipt of gifted services. Harvard Educational Review, 89(3), 337–369. https://doi.org/10.17763/1943-5045-89.3.337
HirschlN.SmithC. M. (2023). Advanced placement gatekeeping and racialized tracking. Sociology of Education, 96(3), 169–252. https://doi.org/10.1177/00380407231161334
HymanJ., (2020). Can light-touch college-going interventions make a difference? Evidence from a statewide experiment in Michigan. Journal of Policy Analysis and Management, 39(1), 159–190. https://doi.org/10.1002/pam.22155
46.
JacksonC. K. (2014). Do college-prep programs improve long-term outcomes?Journal of Economic Inquiry, 52(1), 72–99. https://doi.org/10.1111/ecin.12040
47.
KalogridesD.LoebS. (2013). Different teachers, different peers: The magnitude of student sorting within schools. Educational Researcher, 42(6), 304–316. https://doi.org/10.3102/0013189x13495087
KarpM. M.CalcagnoJ. C.HughesK. L.JeongD. W.BaileyT. R. (2007). The postsecondary achievement of participants in dual enrollment: An analysis of student outcomes in two states. National Research Center for Career and Technical Education, University of Minnesota.
KellyS.CarbonaroW. (2012). Curriculum tracking and teacher expectations: Evidence from discrepant course taking models. Social Psychology of Education: An International Journal, 15(3), 271–294. https://doi.org/10.1007/s11218-012-9182-6
52.
KellyS.PriceH. (2011). The correlates of tracking policy: Opportunity hoarding, status competition, or a technical-functional explanation?American Educational Research Journal, 48(3), 560–585. https://doi.org/10.3102/0002831210395927
53.
KerckhoffA. C. (1995). Institutional arrangements and stratification processes in industrial societies. Annual Review of Sociology, 21, 323–347. https://doi.org/10.1146/annurev.soc.21.1.323
54.
KimJ.GeesaR. L.McDonaldK. (2020). School principals’ and counselors’ focus on college-going: The impact of school leader expectations and primary counseling goals on postsecondary education. Journal of College Access, 5(2), 32–51. https://files.eric.ed.gov/fulltext/EJ1279397.pdf
55.
KolluriS. (2018). Advanced Placement: The dual challenge of equal access and effectiveness. Review of Educational Research, 88(5), 671–711. https://doi.org/10.3102/0034654318787268
56.
LeeJ.FernandezF.RoH. K.SuhH. (2022). Does dual enrollment influence high school graduation, college enrollment, choice, and persistence?Research in Higher Education, 63(5), 825–848. https://doi.org/10.1007/s11162-021-09667-3
57.
LewisA. E.DiamondJ. B. (2015). Despite the best intentions: How racial inequality thrives in good schools. Oxford University Press.
58.
LiangJ-H.HeckmanP. E.AbediJ. (2012). What do the California standards test results reveal about the movement toward eighth-grade algebra for all?Educational Evaluation and Policy Analysis, 34(3), 328–343. https://doi.org/10.3102/0162373712443307
59.
LongM. C.CongerD.IatarolaP. (2012). Effects of high school course-taking on secondary and postsecondary success. American Educational Research Journal, 49(2), 285–322. https://doi.org/10.3102/0002831211431952
60.
LucasS. R. (1999). Tracking inequality: Stratification and mobility in American high schools. Sociology of education series. Teachers College Press.
61.
LucasS. R. (2001). Effectively maintained inequality: Education transitions, track mobility, and social background effects. American Journal of Sociology, 106(6), 1642–1690. https://doi.org/10.1086/321300
62.
LucasS. R.BerendsM. (2002). Sociodemographic diversity, correlated achievement, and de facto tracking. Sociology of Education, 75(4), 328–348. https://doi.org/10.2307/3090282
63.
LucasS. R.BerendsM. (2007). Race and track location in US public schools. Research in Social Stratification and Mobility, 25(3), 169–187. https://doi.org/10.1016/j.rssm.2006.12.002
64.
McBeeM. T. (2016). What you don't look for, you won't find: A commentary on Card and Guiliano's examination of universal screening. Journal of Advanced Academics, 27(2), 131–138. https://doi.org/10.1177/1932202x16634141
65.
McBeeM. T.PetersS. J.MillerE. M. (2016). The impact of the nomination stage on gifted program identification. Gifted Child Quarterly, 60(4), 258–278. https://doi.org/10.1177/0016986216656256
66.
McEachinA.DominaT.PennerA. (2020). Heterogeneous effects of early algebra across California middle schools. Journal of Policy Analysis and Management, 39(3), 772–800. https://doi.org/10.1002/pam.22202
National Center for Education Statistics. (2011). The status of rural education. U.S. Department of Education, Institute of Education Sciences. https://nces.ed.gov/programs/coe/pdf/coe_tla.pdf
70.
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. https://doi.org/10.3102/0162373712453869
71.
NomiT.AllensworthE. (2009). Double-dose algebra as an alternative to remediation: Effects on students’ academic outcomes. Journal of Research on Educational Effectiveness, 2(2), 111–148. https://doi.org/10.1080/19345740802676739
72.
NomiT.RaudenbushS. W.SmithJ. J. (2021). Effects of double-dose algebra on college persistence and degree attainment. Proceedings of the National Academy of Sciences, 118(27), e2019030118. https://doi.org/10.1073/pnas.2019030118
73.
OakesJ. (2005). Keeping track: How schools structure inequality (2nd ed.). Yale University Press.
74.
PageL. C.CastlemanB. L.MeyerK. (2020). Customized nudging to improve FAFSA completion and income verification. Educational Evaluation and Policy Analysis, 42(1), 3–21. https://doi.org/10.3102/0162373719876916
PotterD.MorrisD. S. (2017). Family and schooling experiences in racial/ethnic academic achievement gaps. Sociological Perspectives, 60(1), 132–167. https://doi.org/10.1177/0731121416629989
77.
PriceH. (2021). The fractured college prep pipeline. Teachers College Press.
78.
QuinnD. M.DesruisseauxT. (2022). Replicating and extending effects of “achievement gap” discourse (EdWorkingPaper 22-628). Brown University, Annenberg Institute. https://doi.org/10.26300/2pky-ch12
79.
ReardonS. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. In DuncanG.MurnaneR. (Eds.), Whither opportunity? Rising inequality, schools, and children's life chances (pp. 91–116). Russell Sage Foundation.
80.
RicklesJ. H. (2011). Using interviews to understand the assignment mechanism in a nonexperimental study: The case of eighth grade algebra. Evaluation Review, 35(5), 490–522. https://doi.org/10.1177/0193841x11428644
81.
SchneiderB.SawG. (2016). Racial and ethnic inequities in postsecondary aspirations and enrollment. Russell Sage Foundation Journal of the Social Sciences, 2(5), 58–82. https://doi.org/10.7758/rsf.2016.2.5.04
82.
ShoresK.KimH. E.StillM. (2020). Categorial inequality in black and white: Linking disproportionality across multiple educational outcomes. American Educational Research Journal, 57(5), 2089–2131. https://doi.org/10.3102/0002831219900128
83.
Stand for Children. (2019). Breaking down barriers: Academic Acceleration resource guide. https://stand.org/washington/wp-content/uploads/sites/10/2023/01/wa_2019_guide_academic-acceleration_FINAL_v2.pdf
84.
SweeneyD. (2016). Professional school counselors: Integral stakeholders in the recruitment, retention, and support of African American, Latino, and low-income students in advanced placement programs [Unpublished doctoral dissertation]. University of Louisville.
TillyC. (1999). Durable inequality. University of California Press.
87.
TysonK. (2011). Integration interrupted: Tracking, Black students, and acting White after Brown. Oxford University Press.
88.
VanfossenB. E.JonesJ. D.SpadeJ. Z. (1987). Curriculum tracking and status maintenance. Sociology of Education, 60(2), 104–122. https://doi.org/10.2307/2112586
89.
WalkerE. N. (2007). Why aren't more minorities taking advanced math?Educational Leadership, 65(3), 48–53. https://citeseerx.ist.psu.edu/document?repid=rep1& type=pdf&doi=9ea8a185ad282681169826c1d09b47950aec2af9
90.
WangM.EcclesJ. S. (2013). School context, achievement motivation, and academic engagement: A longitudinal study of school engagement using a multidimensional perspective. Learning and Instruction, 28, 12–23. https://doi.org/10.1016/j.learninstruc.2013.04.002
Washington Office of Superintendent of Public Instruction. (n.d.). Report Card. Retrieved from https://reportcard.ospi.k12.wa.us/ReportCard/ViewSchoolOr District/103300
WilliamsR. (2012). Using the margins command to estimate and interpret adjusted predictions and marginal effects. The Stata Journal, 12(1), 169–352. https://doi.org/10.1177/1536867x1201200209
95.
WolfersJ. (2006). Did unilateral divorce laws raise divorce rates? A reconciliation and new results. American Economic Review, 96(5), 1802–1820. https://doi.org/10.1257/aer.96.5.1802
96.
XuD.SolankiS.FinkJ. (2021). College acceleration for all? Mapping racial gaps in Advanced Placement and dual enrollment participation. American Educational Research Journal, 58(5), 954–992. https://doi.org/10.3102/0002831221991138
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