Mathematical learning disabilities (MLD) have been reported for elementary school age girls with fragile X syndrome who do not have mental retardation. Yet girls with fragile X demonstrate age-appropriate rote math skills, sometimes outperforming other children with MLD. We examined whether MLD and strengths in rote math skills persist during middle school among girls with fragile X. Middle school children were individually administered the Ranking Proportions Task (RPT), which involves fractions and decimals. Such problems, although difficult for many students, yield different performance profiles between children with versus without MLD. We hypothesized that girls with fragile X would outperform children with MLD on rote skills (e.g., naming decimals) despite conceptual difficulties, regardless of effects of FSIQ. To address the influence of fragile X versus MLD or FSIQ, several comparison groups were included. Children from a normative sample outperformed girls with fragile X on conceptual, but not rote, skills. However, their performance resembled that of children with MLD on conceptual skills, such as identifying equal quantities with different symbols (e.g., 0.5 and 1/2). Fragile X syndrome provides a compelling model of the heterogeneity of MLD, as the associated profile resembles that of both children with or without MLD. In terms of applications to serving girls with fragile X, it is important to consider that efficient rote skills may not only fail to enhance math achievement, they may hinder achievement by masking underlying conceptual deficiencies.
Bibliographical noteFunding Information:
This research was supported by grant R01 034061-01 to 09 from the National Institute of Child Health and Human Development awarded to Dr. Mazzocco. Dr. Murphy, who completed this research during her postdoctoral fellowship, is now at the College of Notre Dame of Maryland. The authors thank the children and parents participating in this research; and the faculty and staff from the Baltimore County Public School District; former research coordinators Gwen F. Myers and Kate T. Devlin; and both former and current research assistants Martha Early, Anne Henry, Jennifer Siegler, and Sarah J. McKenney. The authors are indebted to Dr. Peter Killeen, who provided assistance with, and tutorial support for, calculating and verifying values of prep both in general and in the more challenging instances associated with non-normally distributed data.