Classification and Identification of Reading and Math Disabilities
Year: 2012
Type: article
Abstract: Much of learning disabilities research relies on categorical classification frameworks that use psychometric tests and cut points to identify children with reading or math difficulties. However, there is increasing evidence that the attributes of reading and math learning disabilities are dimensional, representing correlated continua of severity. We discuss issues related to categorical and dimensional approaches to reading and math disabilities, and their comorbid associations, highlighting problems with the use of cut points and correlated assessments. Two simulations are provided in which the correlational structure of a set of cognitive and achievement data are simulated from a single population with no categorical structures. The simulations produce profiles remarkably similar to reported profile differences, suggesting that the patterns are a product of the cut point and the correlational structure of the data. If dimensional approaches better fit the attributes of learning disability, new conceptualizations and better methods to identification and intervention may emerge, especially for comorbid associations of reading and math difficulties.
Source: Journal of Learning Disabilities
Institutions: Georgia State University, University of Houston
Language: English
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2096515475