Margarita Kanevski

Project Title: Identification of cognitive predictors to tailor mathematics learning interventions for children with Attention Deficit Hyperactivity Disord

Early mathematics achievement predicts a variety of outcomes in adulthood, including progression into higher education, mental health, as well as occupational and socioeconomic status. Numerical illiteracy has been estimated to cost the UK economy around £20.2 billion per year, equating to around 1.3% of GDP (Pro Bono Economics, 2014; in Scottish Government, 2016). This renders the successful development of numerical skill as a compelling priority from both the individual and societal perspective.

Children with Attention Deficit Hyperactivity Disorder (ADHD) are at higher risk for developing a learning difficulty than their typically developing peers.  Previous research has focused on exploring the relationship between ADHD and reading difficulties, with mathematics remaining largely neglected. Children with ADHD show impairments on tasks measuring memory and attention – processes that are crucial for successful math computations and reasoning. However, ADHD is a diverse condition with just under a third showing memory impairments, less than a quarter showing attentional deficits, and 25-50% showing no impairments at all.  Similarly, mathematics knowledge is not a unitary process, with research showing that there are several related, yet distinct, components including (1) knowledge of mathematical facts, (2) abstract thinking, and (3) mathematical operations. Successful performance across these components relies on different cognitive processes (e.g. memory, attention, or impulse control). The current literature however lacks a comprehensive investigation into the links between cognition and components of mathematical learning in a variable ADHD group, resulting in administration of suboptimal interventions.

The primary goal of our project is to assess the performance of children aged 6-12 years with suspected ADHD on a set of tasks measuring various aspects of mathematical ability, and assess their associations with performance on a range of cognitive tasks measuring aspects such as memory and attention. In doing so, this project can offer new insight on the underlying challenges faced by children with ADHD in mathematical learning and facilitate novel theoretical perspectives of our understanding of the associations between learning and cognition. The second objective of the project aims to investigate whether the data of children with ADHD who show a similar set of cognitive and/or mathematical difficulties can be grouped together. This cluster grouping analysis will inform whether tailored interventions optimally suited to the needs of a child with ADHD could be investigated in future research.

Awarded: Carnegie-Caledonian PhD Scholarship

Field: Education

University: University of Edinburgh

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