Identifying Dyslexic Students by Using Artificial Neural Networks
Tangirala Venkateswara Prasad · 2010
Abstract— There are millions of children suffering from dyslexia across the globe. Due to its implicit characteristics, the identification or the diagnosis of students with this learning disability has long been a difficult issue. In fact there is a little consensus about what is the best procedure to identify a child suffering from dyslexia. In some developed countries there are set procedures and adequate awareness for identification of this disorder. This paper proposes a systematic approach for identification of dyslexia and to classify or analyze potential cases more accurately and easily by use of ANN. The preliminary results obtained using test data were satisfactory and can be used as an effective tool to identify dyslexic child and obtaining adequate information before rushing to a specialist. Many efforts are required to make the model more accurate.