Abstract
The Matthew effect, where good readers get increasingly better over time compared to relatively lower-ability readers, is an often cited phenomenon in reading research. However, researchers have not always found empirical evidence supporting a Matthew effect. We used hierarchical growth curve modeling to test for the presence of the Matthew effect using a longitudinal sample of 1,573 children in high-poverty, low-performing schools. Our results failed to support the presence of a Matthew effect, but instead we found a compensatory growth trajectory whereby reading achievement gaps closed over time. We discuss several possible explanations for the growth patterns.
Notes
1Title I is a federal program that is designed to assist specific schools with high percentages of economically disadvantaged students and provides additional funding to assist students in meeting academic benchmarks.
Note. FRPL = free or reduced price lunch.
Note. FRPL = free or reduced price lunch.
2The Level 1 model was Y tij = π0ij + π1ij (GRADE −2) +e tij , where Y tij was the reading scaled score of student i in school j at time t; π0ij was the ending status of student i in school j; π1ij was the slope of student i in school j; and e tij was the time-specific error term of student i in school j at time t. GRADE was recentered (where kindergarten was originally GRADE = 0) so that the intercept represented scores at the end of the second grade, and the slope still indicated the growth rate over time (Singer & Willett, Citation2003).
The slope (i.e., π 1ij , or the growth estimate) was of particular interest in the study. If the high-performing group had a positive association with the slope and the low-performing group had a negative association with the slope, then a widening of the gap was evident and empirically supported the presence of a Matthew effect. However, if the association with the slope estimates of the high-performing group was negative and the growth for the low-performing group was positive, a compensatory trajectory was present, as gaps were narrowing over time.
For the intercept term and the reading slope, the Level 2 models were
Note. FRPL = free or reduced price lunch.
*p < .05. **p < .01. ***p < .001.
Note. FRPL = free or reduced price lunch.
*p < .05. **p < .01. ***p < .001.