Prediction of learning disabilities in school age children using decision tree

Abstract

The aim of this paper is to predict the Learning Disabilities (LD) of school-age children using decision tree. Decision trees are powerful and popular tool for classification and prediction in Data mining. Different rules extracted from the decision tree are used for prediction of learning disabilities. LDs affect about 10 percent of all children enrolled in schools. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. This paper highlights the data mining technique - decision tree, used for classification and extraction of rules for prediction of learning disabilities. As per the formulated rules, LD in any child can be identified. © 2010 Springer-Verlag Berlin Heidelberg.