Dr. Peng Peng's research reveals the cognitive mechanism of mathematics difficulties

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While mathematical competency is critical for competing successfully in today’s high-technology world, learning mathematics is challenging for many children. Converging evidence shows that approximately 6% of the school-aged population has some form of mathematics difficulties (MD) even with average or higher IQ and adequate instruction. Despite the prevalence of MD, MD is studied far less than reading difficulties. In recent years, an increasing number of studies have examined the factors associated with MD and suggested two major approaches to understanding the deficit profiles of MD. One is through the investigation of deficits in domain-specific skills The other is through the investigation of deficits in domain-general cognitive skills.

Through meta-analysis, Dr. Peng Peng and his colleagues (Wang CuiCui from Beijing Normal University and Dr. Jessica Namkung from UNL) systematically investigated the cognitive deficit profiles among individuals with MD and potential moderators and mechanism for these profiles. Seventy-five cognitive profiling studies on MD were included, representing a total of 13,001 individuals and 126 independent samples. Results showed that compared with typically developing individuals, individuals with MD showed deficits (from most severe to less severe) in phonological processing, processing speed, working memory, attention, short-term memory, executive functions, and visuospatial skills. Moderation analyses indicated that comorbidity (with reading disabilities) and types of MD screening affected the cognitive deficits. Severity of MD was related to processing speed deficits. Deficits in phonological processing and attention were more severe in younger individuals with MD. Deficits in processing speed and working memory were most severe in the numerical domain. Deficits in low-level cognitive skills (i.e., processing speed and short-term memory) could not completely explain the deficits in high-level skills (i.e., working memory, attention, and executive functions), partially supporting the bottleneck theory.

Findings from this study may have important implications for understanding MD. First, MD is associated with comprehensive cognitive deficits that are not specifically related to numerical processing, with exceptions that deficits in processing speed and working memory are more related to the numerical domain. Thus, the cognitive deficits of MD are generally not affected by domains of materials. Any individual who is identified with MD is likely to experience both domain-specific (numerical processing) and domain-general cognitive deficits. Second, MD is a categorical group with heterogeneity, which lies in two aspects. One is that there is heterogeneity among MD subgroups. MD identified with different screening measures also differ from each other. The other aspect of heterogeneity of MD is reflected by age. Deficits in attention and phonological processing are more severe among younger individuals with MD. This age effect may be attributed to the characteristics of early mathematics learning (or instruction) that emphasizes automatized arithmetic facts retrieval. Third, the severity of MD, in general, does not affect the deficit profiles of MD, and MD may be a discrete construct. Fourth, the deficits in the high-level cognitive deficits are relatively independent of the deficits in low-level cognitive skills of MD. Compared with the deficits in low-level skills (except for processing speed), MD is more strongly and stably related to the deficits in high-level cognitive skills. Thus, it is likely that for individuals with MD, both their basic information-processing system (e.g., numerical processing) and the complex information-processing system (e.g., forming strategies and understanding conceptual knowledge) in mathematics are impaired.

More details at: http://journals.sagepub.com.libproxy.unl.edu/doi/full/10.3102/0034654317753350