Intelligent Model to Predict the Subject of Study for Inclusion Student Based on Histories Background

Abstract

Inclusive education for young disabled people is a trends, issues and big challenges. Young disabled people have fewer chances to get a properly job as they are more likely to drop out after the first year and to have erratic and longer pathways within the University education. Hence, the aim of the project is to deliver an intelligent model for the university management to easy guide the candidates of disable students in selecting the best subject of their study. The project will be begun with literature reviews and then will be concentrated on the early survey (questionnaire) of the student histories. The information will be analyzed and classified to serve as references in determining of the academic factors. The next step is developing the database of background histories as input system and academic performance as output of the system. The back propagation Neural network (BPNN) will be trained to build the complex relationship between input and output system. Finally, the system will deliver a NN tool to select the best of subject of study based on grade performance and histories background.