This study examined children's trajectories of mathematics and reading achievements from kindergarten to eighth grade along with the gender differences in these trajectories. A total of 8503 participants drawn from the Early Childhood Longitudinal Study-Kindergarten Cohort (ECLS-K) formed the sample of the study. The results of the latent growth curve modeling indicate that (a) children's growth is curvilinear, specially, quadratic for both mathematics and reading achievement, and their growth in reading demonstrate a more complex pattern than that of mathematics; (b) there appear to be positive correlations between the intercept parameter (i.e. initial status) and the slope parameter (i.e. growth rate) in both reading and mathematics trajectories, indicating the ‘Matthew effects’ in education; (c) despite the statistically equivalent initial status in mathematics, boys outperform girls as early as first grade in both achievement score and positive growth rate; (d) for reading trajectories, girls outperform boys in both initial status and positive growth rate starting the baseline measurement. Finally, limitations and recommendations for future studies are discussed.
AiX. (2002), ‘Gender Differences in Growth in Mathematics Achievement: Three-Level Longitudinal and Multilevel Analyses of Individual, Home, and School Influences’, Mathematical Thinking and Learning, 4 (1), 1–22.
2.
AikensN. L.BarbarinO. (2008), ‘Socioeconomic Differences in Reading Trajectories: The Contribution of Family, Neighborhood, and School Contexts’, Journal of Educational Psychology, 100 (2), 235–51.
3.
BaltesP. B.NesselroadeJ. R. (1979), ‘History and Rationale of Longitudinal Research’, in NesselroadeJ. R.BaltesP. B. (eds), Longitudinal research in the study of behavior and development, New York: Academic Press, pp. 1–39.
4.
BullR.EspyK. A.WiebeS. A. (2008), ‘Short-Term Memory, Working Memory, and Executive Functioning in Preschoolers: Longitudinal Predictors of Mathematical Achievement at Age 7 Years’, Developmental Neuropsychology, 33 (3), 205–28.
5.
ByrneB. M. (2012), Structural equation modeling with Mplus: Basics, concepts, applications, and programming, New York, NY: Routledge.
6.
CrosnoeR.MorrisonF.BurchinalM.PiantaR.KeatingD.FriedmanS. L.Clarke-StewartK. A. and The Eunice Kennedy Shriver National Institute of Child Health and Human Development Early Child Care Research Network (2010), ‘Instruction, Teacher-Student Relations, and Math Achievement Trajectories in Elementary School’, Journal of Educational Psychology, 102 (2), 407–17.
7.
DywerC. (1973), ‘Sex Differences in Reading: An Evaluation and a Critique of Current Theories’, Review of Educational Research, 43 (4), 455–67.
8.
FletcherJ. M.LyonG. R.FuchsL. S.BarnesM. A. (2007), Learning disabilities: From identification to intervention, New York, NY: The Guilford Press.
9.
HanW.FoxL. E. (2011), ‘Parental Work Schedules and Children's Cognitive Trajectories’, Journal of Marriage and Family, 73, 962–80.
10.
HanlineM. F.MiltonS.PhelpsP. C. (2010), ‘The Relationship Between Preschool Block Play and Reading and Maths Abilities in Early Elementary School: A Longitudinal Study of Children With and Without Disabilities’, Early Child Development and Care, 180 (8), 1005–17.
11.
HooperS. R.RobertsJ.SiderisJ.BurchinalM.ZeiselS. (2010), ‘Longitudinal Predictors of Reading and Math Trajectories Through Middle School for African Versus Caucasian Students Across Two Samples’, Developmental Psychology, 46 (5), 1018–29.
12.
HuL.BentlerP. M. (1999), ‘Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus new Alternatives’, Structural Equation Modeling, 6, 1–55.
13.
JöreskogK. G. (1993), ‘Testing Structural Equation Models’, in BollenK. A.LongJ. S. (eds), Testing structural equation models, Newbury Park, CA: Sage, pp. 294–316.
14.
LeaheyE.GuoG. (2001), ‘Gender Differences in Mathematical Trajectories’, Social Forces, 80 (2), 713–32.
15.
Li-GriningC. P.Votruba-DrzalE.Maldonado-CarreñoC.HaasK. (2010), ‘Children's Early Approaches to Learning and Academic Trajectories Through Fifth Grade’, Developmental Psychology, 46 (5), 1062–77.
16.
MarksG. N. (2008), ‘Accounting for the Gender Gaps in Student Performance in Reading and Mathematics: Evidence from 31 Countries’, Oxford Review of Education, 34 (1), 89–109.
17.
McClellandM. M.AcockA. C.MorrisonF. J. (2006), ‘The Impact of Kindergarten Learning-Related Skills on Academic Trajectories at the End of Elementary School’, Early Childhood Research Quarterly, 21, 471–90.
18.
MickelsonR. (1989), ‘Why Does Jane Read and Write so Well? The Anomaly of Women's Achievement’, Sociology of Education, 62, 47–63.
19.
MoserS. E.WestS. G.HughesJ. N. (2012), ‘Trajectories of Math and Reading Achievement in low-Achieving Children in Elementary School: Effects of Early and Later Retention in Grade’, Journal of Educational Psychology, 104 (3), 603–21.
20.
MuthénL. K.MuthénB. O. (2010), Mplus user's guide (6th ed.,), Los Angeles, CA: Muthén & Muthén.
21.
RetelsdorfJ.KöllerO.MöllerJ. (2011), ‘On the Effects of Motivation on Reading Performance Growth in Secondary School’, Learning and Instruction, 21, 550–9.
22.
RobinsonK. (2010), ‘Black-White Inequality in Reading and Math Across K-12 Schooling: A Synthetic Cohort Perspective’, Review of Black Political Economy, 37, 263–73.
23.
Shorrocks-TaylorD.JenkinsE. W. (2002), Learning from others: International comparisons in education, Dordrecht, The Netherlands: Kluwer.
24.
SnowC. E.BurnsM. S.GriffinP. (1998), Preventing reading difficulties in young children, Washington, DC: National Academy Press.
25.
SonnenscheinS.StapletonL. M.BensonA. (2010), ‘The Relation Between the Type and Amount of Instruction and Growth in children's Reading Competencies’, American Educational Research Journal, 47, 358–89.
StanovichK. E. (1986), ‘Matthew Effects in Reading: Some Consequences of Individual Differences in the Acquisition of Literacy’, Reading Research Quarterly, 21 (4), 360–407.
28.
TourangeauK.NordC.LêT.SorongonA. G.NajarianM. (2009), Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K), combined user's manual for the ECLS-K eighth-grade and K-8 full sample data files and electronic codebooks (NCES 2009-04). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.
29.
WalbergH. J.TsaiS. (1983), ‘Matthew Effects in Education’, American Educational Research Journal20, 359–73.
30.
WattH. M. G. (2006), ‘The Role of Motivation in Gendered Educational and Occupational Trajectories Related to Maths’, Educational Research and Evaluation, 12 (4), 305–22.
31.
WigfieldA.EcclesJ. S. (2000), ‘Expectancy-Value Theory of Achievement Motivation’, Contemporary Educational Psychology, 25 (1), 68–81.
