Simulation of Improved Academic Achievement for a Mathematical Topic Using Neural Networks Modeling

This paper is inspired by the simulation of Artificial Neural Networks (ANNs) applied recently for evaluation of phonics methodology to teach the children “how to read?” Nevertheless, in this paper, a novel approach is presented aiming to improve the academic achievement in learning children as an adopted mathematical topic namely long division problem. That's by comparative study of practical application results at educational field (a children classroom); for two computer aided learning (CAL) packages versus classical learning (case study). Presented study highly recommends the novel application of interdisciplinary teaching trends as a measure for learning performance evaluation. It is based on ANNs modeling, memory association, behaviorism, and individual’s learning styles. Interestingly, observed and obtained practical findings after the field application, proved the superiority of the package associated with teacher's voice over both without voice, and classical learning / teaching as well.