Techniques utilising physiological data for supporting children with dyscalculia: A comprehensive review. - Nguyen, Thi Kieu Chinh; Le, Duc Duy; Nguyen, Thi Cam Huong; Le, Thanh Ha; Ngo, Thi Duyen (Technology & Disability, 2025)
Background: Dyscalculia is a specific learning disability that affects a person's ability to understand number-based information and arithmetic skills, particularly in children. Misconceptions about dyscalculia persist, but this disability has received significant attention from the research community, particularly in exploring techniques that utilise physiological data (eye tracking, electroencephalogram, electrocardiogram, etc.) to understand the underlying mechanisms of numerical processing. This interest highlights the need for a comprehensive review of this research direction. Objective: This paper aims to review the application of techniques with physiological data in children with dyscalculia. Methods: A thorough literature search was conducted using Web of Science, Scopus, Science Direct, and PubMed databases, adhering to PRISMA guidelines. After a rigorous selection process, 11 relevant articles were identified for this study. Results: Our findings revealed that researchers have long recognised the potential of these techniques, as demonstrated by their use in relevant studies over time. While the number of studies is limited and has focused primarily on eye tracking and electroencephalogram, the review provides detailed analyses that highlight the significant effectiveness of these techniques in assessing numerical performance in children with dyscalculia. Furthermore, we not only investigated the methodologies and results of these techniques but also discussed their limitations and the need for further research. These limitations may be due to small sample sizes or the absence of certain potential research directions that have emerged in studies of other developmental disorders, such as dyslexia and autism. Conclusions: This paper presents a clear direction for future research on utilising physiological data systems to support students struggling with mathematical learning disabilities.