Kindergarten readiness assessments are commonly used in schools nationwide. Prior work shows that the use of such assessments for class placement decisions has increased in recent years. This article uses the Early Childhood Longitudinal Study of 2011 to explore whether the use of readiness assessments for such purpose predicts differential sorting of students across classrooms by prior academic ability. Results from multilevel models as well as other sensitivity analyses suggest that the use of readiness assessments for classroom placements is predictive of slightly higher cross-class ability sorting, particularly in English/language arts. The implications for policy and practice are discussed.
AllanS. D. (1991). Ability grouping research reviews: What do they say about grouping and the gifted. Educational Leadership, 48(6), 60-65.
2.
CameronA. C.TrivediP. K. (2010). Microeconometrics using Stata (Vol. 2). College Station, TX: Stata Press.
3.
ChettyR.FriedmanJ. N.HilgerN.SaezE.SchanzenbachD. W.YaganD. (2011). How does your kindergarten classroom affect your earnings? Evidence from Project STAR. The Quarterly Journal of Economics, 126(4), 1593-1660.
4.
ChmielewskiA. K.DumontH.TrautweinU. (2013). Tracking effects depend on tracking type an international comparison of students’ mathematics self-concept. American Educational Research Journal, 50, 925-957.
5.
ClaessensA.DuncanG.EngelM. (2009). Kindergarten skills and fifth-grade achievement: Evidence from the ECLS-K. Economics of Education Review, 28, 415-427.
6.
ClaessensA.EngelM. (2013). How important is where you start? Early mathematics knowledge and later school success. Teachers College Record, 115(6), 1-29.
7.
ClaessensA.EngelM.CurranF. C. (2014). Academic content, student learning, and the persistence of preschool effects. American Educational Research Journal, 51, 403-434.
8.
ClotfelterC. T.LaddH. F.VigdorJ. L. (2006). Teacher-student matching and the assessment of teacher effectiveness. Journal of Human Resources, 41, 778-820.
9.
Cohen-VogelL.HarrisonC. (2013). Leading with data: Evidence from the National Center on Scaling Up Effective Schools. Leadership and Policy in Schools, 12, 122-145.
10.
Cohen-VogelL.RutledgeS. (2009). The pushes and pulls of new localism: School-level instructional arrangements, instructional resources, and family-community partnerships. Yearbook of the National Society for the Study of Education, 108(1), 70-103.
11.
CollinsC. A.GanL. (2013, February). Does sorting students improve scores? An analysis of class composition (NBER Working Paper No. w18848). Cambridge, MA: National Bureau of Economic Research.
12.
CondronD. J. (2007). Stratification and educational sorting: Explaining ascriptive inequalities in early childhood reading group placement. Social Problems, 54, 139-160.
Council of Chief State School Officers. (2010). State early childhood standards and assessments: Five years of development (Report of 2008 Survey by the Early Childhood State Collaborative on Assessment and Student Standards). Washington, DC: Author.
15.
DieterleS.GuarinoC. M.ReckaseM. D.WooldridgeJ. M. (2015). How do principals assign students to teachers? Finding evidence in administrative data and the implications for value added. Journal of Policy Analysis and Management, 34, 32-58.
EpsteinA. S.SchweinhartL. J.DeBruin-PareckiA.RobinK. B. (2004). Preschool assessment: A guide to developing a balanced approach. Preschool Policy Matters, 7, 1-2.
18.
GallagherL.MeansB.PadillaC. (2008). Teachers’ use of student data systems to improve instruction: 2005 to 2007. Washington, DC: US Department of Education.
19.
GamoranA.MareR. D. (1989). Secondary school tracking and educational inequality: Compensation, reinforcement, or neutrality?American Journal of Sociology, 94, 1146-1183.
20.
GarrettR.HongG. (2016). Impacts of grouping and time on the math learning of language minority kindergartners. Educational Evaluation and Policy Analysis, 38, 222-244.
GottfriedM. A. (2014). Peer effects in urban schools: Assessing the impact of classroom composition on student achievement. Educational Policy, 28, 607-647.
23.
HanushekE. A.KainJ. F.MarkmanJ. M.RivkinS. G. (2003). Does peer ability affect student achievement?Journal of Applied Econometrics, 18, 527-544.
24.
HarrisD. N.SassT. R. (2011). Teacher training, teacher quality and student achievement. Journal of Public Economics, 95, 798-812.
25.
HongG.CorterC.HongY.PelletierJ. (2012). Differential effects of literacy instruction time and homogeneous ability grouping in kindergarten classrooms who will benefit? Who will suffer?Educational Evaluation and Policy Analysis, 34, 69-88.
KalogridesD.LoebS. (2013). Different teachers, different peers the magnitude of student sorting within schools. Educational Researcher, 42, 304-316.
28.
KaneT. J.RockoffJ. E.StaigerD. O. (2008). What does certification tell us about teacher effectiveness? Evidence from New York City. Economics of Education Review, 27, 615-631.
29.
KulikJ. A. (1992). An analysis of the research on ability grouping: Historical and contemporary perspectives. Storrs, CT: National Research Center on the Gifted and Talented, University of Connecticut.
30.
LaddH. F.SorensenL. C. (2017). Returns to teacher experience: Student achievement and motivation in middle school. Education Finance and Policy, 12(2), 241-279.
LittleM. H.Cohen-VogelL.CurranF. C. (2016). Facilitating the transition to kindergarten: What ECLS-K data tell us about school practices then and now. AERA Open, 2(3), 1-18. doi:2332858416655766
33.
LouY.AbramiP. C.SpenceJ. C.PoulsenC.ChambersB.d’ApolloniaS. (1996). Within-class grouping: A meta-analysis. Review of Educational Research, 66, 423-458.
34.
LovelessT. (1998). The tracking and ability grouping debate (The Fordham report). Washington, DC: The Fordham Foundation.
35.
LovelessT. (2013). The resurgence of ability grouping and persistence of tracking: Part II of the 2013 Brown Center report on American education (Brookings Institution report). Washington, DC: Brown Center on Education Policy.
36.
LucasS. R. (1999). Tracking inequality: Stratification and mobility in American high schools. Sociology of Education Series. New York, NY: Teachers College Press.
37.
MarchJ. G.OlsenJ. P. (1984). The new institutionalism: Organizational factors in political life. The American Political Science Review, 78, 734-749.
38.
MatthewsM. S.RitchotteJ. A.McBeeM. T. (2013). Effects of schoolwide cluster grouping and within-class ability grouping on elementary school students’ academic achievement growth. High Ability Studies, 24, 81-97.
39.
McCoachD. B.O’ConnellA. A.LevittH. (2006). Ability grouping across kindergarten using an Early Childhood Longitudinal Study. The Journal of Educational Research, 99, 339-346.
40.
McEwanP. J. (2003). Peer effects on student achievement: Evidence from Chile. Economics of Education Review, 22, 131-141.
41.
MeansB.PadillaC.DeBargerA.BakiaM. (2009). Implementing data-informed decision making in schools: Teacher access, supports and use (Report prepared for U.S. Department of Education, Office of Planning, Evaluation and Policy Development. Prepared by SRI International, Menlo Park, CA).
42.
MerrillB.LittleM. H.SadlerJ.Cohen-VogelL.LeeK. (2018). A portrait of pre-k quality in the United States (Working Paper). Chapel Hill: University of North Carolina.
43.
MickelsonR.EverettB. (2008). Neotracking in North Carolina: How high school courses of study reproduce race and class-based stratification. The Teachers College Record, 110, 535-570.
MurnaneR. J.SharkeyN. S.BoudettK. P. (2005). Using student-assessment results to improve instruction: Lessons from a workshop. Journal of Education for Students Placed at Risk, 10, 269-280.
46.
NiemeyerJ.Scott-LittleC. (2001). Assessing kindergarten children: A compendium of assessment instruments. Washington, DC: Office of Educational Research and Improvement.
47.
NomiT.AllensworthE. (2014). Skill-based sorting in the era of college prep for all: Costs and Benefits (Research brief). Chicago, IL: Consortium on Chicago School Research, University of Chicago.
48.
OakesJ. (2005). Keeping track: How schools structure inequality. New Haven, CT: Yale University Press.
49.
OakesJ.GuitonG. (1995). Matchmaking: The dynamics of high school tracking decisions. American Educational Research Journal, 32, 3-33.
50.
OgawaR.GoldringE.CrowsonR. (1999). Enduring dilemmas of school organization. In MurphyJ.LouisK.S. (Eds.), Handbook of Research on Educational Administration (pp. 277-295). San Francisco, CA: Jossey-Bass.
51.
Osborne-LampkinL. T.Cohen-VogelL. (2014). “Spreading the wealth”: How principals use performance data to populate classrooms. Leadership and Policy in Schools, 13, 188-208.
52.
ParkV.DatnowA. (2017). Ability grouping and differentiated instruction in an era of data-driven decision making. American Journal of Education, 123, 281-306.
53.
PassowA. H. (1962). The maze of research on ability grouping. Educational Forum, 26, 281-288.
54.
PowellW.DiMaggioP. (1991). The new institutionalism in organizational analysis. Chicago, IL: University of Chicago Press.
55.
Public Citizens for Children and Youth. (2015). Assessing kindergarten readiness in Pennsylvania: How can the kindergarten entry inventory boost skills of young students?Philadelphia, PA: Public Citizens for Children and Youth.
56.
RaudenbushS. W.BrykA. S. (2002). Hierarchical linear models: Applications and data analysis methods (Vol. 1). Thousand Oaks, CA: Sage.
57.
RockoffJ. E. (2004). The impact of individual teachers on student achievement: Evidence from panel data. The American Economic Review, 94(2), 247-252.
58.
RoystonP.WhiteI. R. (2011). Multiple imputation by chained equations (MICE): Implementation in Stata. Journal of Statistical Software, 45(4), 1-20.
59.
RubinD. B. (1996). Multiple imputation after 18+ years. Journal of the American Statistical Association, 91, 473-489.
60.
SandersW. L.RiversJ. C. (1996). Cumulative and residual effects of teachers on future student academic achievement (Research progress report). Knoxville, TN: University of Tennessee Value-Added Research and Assessment Center.
61.
SharkeyN.MurnaneR. (2003, April). Helping K-12 educations learn from assessment data. Paper presented at the annual meeting of the American Educational Research Association, Chicago, IL.
62.
SlavinR. E. (1987). Ability grouping and student achievement in elementary schools: A best evidence synthesis. Review of Educational Research, 57, 293-336.
63.
SmylieM. A. (1995). New perspectives on teacher leadership. The Elementary School Journal, 96, 3-7.
64.
SnowC. E.Van HemelS. B. (Eds.). (2008). Early childhood assessment: Why, what, and how. Washington, DC: National Academies Press.
Steenbergen-HuS.MakelM. C.Olszewski-KubiliusP. (2016). What one hundred years of research says about the effects of ability grouping and acceleration K–12 students’ academic achievement findings of two second-order meta-analyses. Review of Educational Research, 86, 849-899.
67.
TachL. M.FarkasG. (2006). Learning-related behaviors, cognitive skills, and ability grouping when schooling begins. Social Science Research, 35, 1048-1079.
68.
TomlinsonC. (1995). How to differentiate in mixed ability classrooms. Alexandria, VA: Association for Supervision and Curriculum Development.
69.
TomlinsonC. (1999). The differentiated classroom. Responding to the needs of all learners. Alexandria, VA: Association for Supervision and Curriculum Development.
70.
TourangeauK.NordC.LêT.SorongonA. G.HagedornM. C.DalyP.NajarianM. (2015). Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K: 2011). User’s Manual for the ECLS-K: 2011 Kindergarten Data File and Electronic Codebook, Public Version. NCES 2015-074. Washington, DC: National Center for Education Statistics.
71.
WachenJ.HarrisonC.Cohen-VogelL. (2018). Data use as instructional reform: Exploring educators’ reports of classroom practice. Leadership and Policy in Schools, 17(2), 296-325.
