Identifying Dyscalculia Symptoms Related to Magnocellular Reasoning Using Smartphones

This paper presents a study that has developed a mobile software application for assisting diagnosis of learning disabilities in mathematics, called dyscalculia, and measuring correlations between dyscalculia symptoms and magnocellular reasoning. Usually, software aids for dyscalculic individuals are focused on both assisting diagnosis and teaching the material. The software developed in this study however maintains a specific focus on the former, and in the process attempts to capture alleged correlations between dyscalculia symptoms and possible underlying causes of the condition. Classification of symptoms is performed by k-Nearest Neighbor algorithm classifying five parameters evaluating user's skills, returning calculated performance in each category as well as correlation strength between detected symptoms and magnocellular reasoning abilities. Expert evaluations has found the application to be appropriate and productive for its intended purpose, proving that mobile software is a suitable and valuable tool for assisting dyscalculia diagnosis and identifying root causes of developing the condition.