Identifying Subtypes of Mathematical learning Disability in Iranian Students: Model-Based Clustering Approach

The aim of the present study was identifying cognitive subgroups of mathematical disability using model- based clustering in a clinical sample. Participants were 41 mathematical disabled students studying in third, fourth, and fifth grades with mean age of 9.93 years and age standard deviation of 1.11 years (13.33 months) that received special education as learning disables in the centers of learning disabilities treatment of education organization. Utilizing a battery of paper and pencil and computerized tests and tasks, the researchers assessed participants individually during two sessions. Model- based data clustering revealed four distinct clusters of students that their statistical and empirical validity was confirmed: symbolic processing deficit (31.1 percent), visuo-spatial deficit (26.8 percent), executive functions and processing speed deficit (26.8 percent), non-symbolic processing deficit (12.2 percent). These results have implications for presenting positive definitions of mathematical learning disability and are able to motivate future researches for preparing interventions appropriate to each subgroups.