Identification of children with mathematics learning disabilities (MLDs) using latent class growth analysis

The traditional way of identifying children with mathematics learning disabilities (MLDs) using the low-achievement method with one-off assessment suffers from several limitations (e.g., arbitrary cutoff, measurement error, lacking consideration of growth). The present study attempted to identify children with MLD using the latent growth modelling approach, which minimizes the above potential problems. Two hundred and ten Chinese-speaking children were classified into five classes based on their arithmetic performance over 3 years. Their performance on various number-related cognitive measures was also assessed. A potential MLD class was identified, which demonstrated poor achievement over the 3 years and showed smaller improvement over time compared with the average-achieving class. This class had deficits in all number-related cognitive skills, hence supporting the number sense deficit hypothesis. On the other hand, another low-achieving class, which showed little improvement in arithmetic skills over time, was also identified. This class had an average cognitive profile but a low SES. Interventions should be provided to both low-achieving classes according to their needs.