On Simulation of e-Learning Convergence Time Using Artificial Neural Networks

This paper addresses a challenging and critical issue of how to evaluate dynamically e-Learners' performance. That is by considering their learning response (convergence) time to reach desired output answer. More precisely, this piece of research aims to investigate realistically performance of eeducational phenomenon associated with e-learners' brain response time. Moreover, presented work integrates neuronal sciences and computer technology into e-educational environment as an interdisciplinary research direction to study realistically e-learning performance issue. Accordingly, Artificial Neural Networks (ANN) models are suggested for realistic performance evaluation of timely dependant response till reaching learning process convergence. So, response time is adopted as an appropriate candidate parameter for e-learning systems' evaluation. Herein, analysis of response time parameter considers individual learners' differences while performing learning process. Additionally, evaluated effect of contributing neurons on e-learning processes performance is presented. Finally, after running of suggested realistic simulation programs, some interesting results are introduced.