Abstract:The objective of the project is to diagnose a child with learning disability and provide appropriate study material. The model will first classify a child as learning disabled or non- learning disabled based on certain assessment parameters. Once diagnosed with learning disability, the child is further classified into different types of learning disability like dyslexia, dysgraphia,dyscalculia and dysphasia. The model not only detects the type but also will identify the level of Learning Disability and provide the student with study material for improvement. The model is trained using the student’s history and parameters of curriculum-based test to determine the level of Learning Disability. Based on the level of Learning Disability the studying material will be provided to the children.
Introduction:
Learning Disability is a disorder that affects an individual’s ability to either understand what they see and hear, or to link information from different parts of the brain. Children with learning disability require a separate approach in order to be par with students who are non-learning disabled. Technology can play a significant role in this field. A model can provide learning materials for children with special needs based on the diverse characteristics of children. Learning Disability …show more content…
Several experimental runs demonstrated that SVN results were consistent independently of the size of the training data set. ANN by itself wasn't giving high accuracy in general. Hybrid techniques yield better results, but still were lacking some accuracy in diagnosing kids with LDs. Thus more research is needed to be done in this area to increase
Introduction:
Learning Disability is a disorder that affects an individual’s ability to either understand what they see and hear, or to link information from different parts of the brain. Children with learning disability require a separate approach in order to be par with students who are non-learning disabled. Technology can play a significant role in this field. A model can provide learning materials for children with special needs based on the diverse characteristics of children. Learning Disability …show more content…
Several experimental runs demonstrated that SVN results were consistent independently of the size of the training data set. ANN by itself wasn't giving high accuracy in general. Hybrid techniques yield better results, but still were lacking some accuracy in diagnosing kids with LDs. Thus more research is needed to be done in this area to increase