Nonlinear Gompertz Curves of Mathematics, Reading, and Science Achievement

• In Event: AERA Roundtable Session 8
  In Roundtable Session: Academic Achievement Gaps (Table 28)

Abstract

We use nonlinear mixed-effects models to replicate prior work on the growth
trajectories of achievement, using more recent data from the ECLSK 2011 cohort. We replicate
work on mathematics and reading achievement and extend prior work by including science
achievement. We consider models with theoretically meaningful parameters, namely logistic,
Gompertz, and Richards growth curve models to capture the shape of the development of
achievement. We find the Gompertz curve is the best fit for mathematics, reading and
science. We also find that the most rapid growth in achievement occurs in first grade, and
that the rate of growth then predicts the total growth in achievement for students.
Policy and practical implications are discussed.

Authors

• William Murrah, Auburn University

• Svetlana Chesser, Auburn University

• Natalie M. Neugebauer, Auburn University