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The "Nana Shilpa" is a mobile application system that is developed for screening and refinement of dyscalculia and dysgraphia learning disabilities in primary school students using the Localized languages. In the application, 4 variants of dyscalculia and 4 variants of dysgraphia disability conditions are considered. Using the medically consulted activities and results and processing the data using modern machine learning and deep learning techniques, the application predicts the possible risk of dyscalculia and dysgraphia learning disability condition in the students. All the results of screening tests and risk prediction history are stored in the report archive for the future reference of the user. If any student gets the prediction result of the possible risk of the disability condition considered in the application, it provides refinement activities in the multi-sensory environment to improve the condition. The application is built with attractive color combinations, animations and a multi-sensory environment which is suitable for primary school students to take the screening test and refinement activities without feeling distracted and pressured.
Nana Shilpa Team was created as the requirement to conduct the undergraduate final year project at the Sri Lanka Institute of information technology. The team consists of total 4 members which are Chamil Hewapathirana, Kalpani Abeysinghe, Maheshani Makalanda, Prabath Liyanage.