The relevance of subtyping children with mathematical learning disabilities

Res Dev Disabil. 2020 Sep:104:103704. doi: 10.1016/j.ridd.2020.103704. Epub 2020 Jun 20.

Abstract

Background: Profiles of mathematical learning disability (MLD) have been conceptualized in the literature, but empirical evidence to support them based on academic and cognitive characteristics is lacking.

Aims: We examined whether profiles of mathematics performance can empirically be identified and whether the identified profiles also differ in underlying cognitive skills.

Methods and procedures: Latent profile analysis in 281 fourth-graders. Basic arithmetic and advanced mathematics were used to identify profiles. Cognitive skills were then described for each profile of mathematics performance.

Outcomes and results: Four profiles of mathematics performance were retrieved from the data, including one general low-achieving profile. Additional profiles of MLD were not found, possibly because individual variation was substantial.

Conclusions and implications: It is highly important to understand children's mathematics performance from an individual perspective, rather than by averaging these children over subgroups. These new insights can be used to better tend to the specific needs of children with mathematical difficulties.

Keywords: Academic profiles; Cognitive skills; Individual differences; Mathematical learning disability; Mathematics performance.

MeSH terms

  • Child
  • Humans
  • Learning Disabilities*
  • Mathematics