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

Tin Yau Terry WONG, Suk Han Connie HO, Joey TANG

Research output: Contribution to journalArticles

16 Citations (Scopus)

Abstract

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. Copyright © 2014 Elsevier Ltd.
Original languageEnglish
Pages (from-to)2906-2920
JournalResearch in Developmental Disabilities
Volume35
Issue number11
Early online dateAug 2014
DOIs
Publication statusPublished - 2014

Citation

Wong, T. T.-Y., Ho, C. S.-H., & Tang, J. (2014). Identification of children with mathematics learning disabilities (MLDs) using latent class growth analysis. Research in Developmental Disabilities, 35(11), 2906–2920.

Keywords

  • Numerical cognition
  • Mathematics learning disability
  • Latent class growth analysis
  • Approximate number system

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