Unpacking Inequality in Kindergarten Math Achievement: Cognitive and Contextual Predictors Using Random Coefficients Modelling

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Abstract

This study applied two-level random coefficient modeling to examine both student- and school- predictors of kindergarten math achievement. Grounded in Ecological Systems Theory, we asked two questions and tested two hypotheses to examine how individual characteristics interact with school-level factors to influence kindergarten mathematics achievement using ECLS-K:2011 data. Student-level factors particularly child cognitive and interpersonal factors exerted a greater effect on mathematics achievement than school-level factors. Variance component estimates with student-level residual variance (41.58) accounting for most of the unexplained variance, compared to school-level intercept variance (7.24). The intraclass correlation coefficient (ICC = 0.15) indicated that only 15% of the variance in math achievement existed between schools. Our study underscores the importance of centering child-focused interventions in early math learning.

Authors

• Abiodun Emmanuel Babalola, University of Alabama

• Alison Hooper, University of Alabama

• Joon-Ho Lee, University of Alabama