Learning disability diagnosis and classification - A soft computing approach

The objective of this study is to diagnose a child with learning disability. The model is designed by implementing a soft computing technique called Learning Vector Quantization. The model classifies a child as learning disabled or non- learning disabled. Once diagnosed with learning disability, rule based approach is used further to classify them into types of learning disability that is dyslexia, dysgraphia and dyscalculia. The model is trained using the parameters of curriculum-based test. The paper proposes a methodology of not only detecting learning disability but also the type of learning disability.