On Comparative Study Between Two Diversified Educational Methodologies’ Academic Achievements (Artificial Neural Networks' Approach)

This presented piece of research addresses a comparative study of two applicable distinct educational methodologies in our children’s classrooms. Interestingly, the introduced educational comparative issue adopted two interdisciplinary realistic Artificial Neural Networks ANNs models. Which concerned with two different educational applied packages’ approaches (methodologies). Briefly, two diversified educational packages –which considers a specific math topic- have been applicable in our children’s fifth grade classrooms. Both diversified packages were characterized by two different educational methodologies. One has been originated from typical (teaching/ learning) classic approach. However, the other methodological package motivated by effective multisensory utilization (visual and auditory multimedia}. By more details, two selected (experimental & control) groups of children -with average age about 11 years- have been subjected to both suggested educational methodologies. Herein, the adopted math topic to be concerned with learning "How to solve long division problem?”. That has carried out by sequential processes: Divide, Multiply, Subtract, Bring Down, and repeat (if necessary). Nevertheless, the second is associated with the critical instructional issue of "how to teach/learn reading?" Both adopted modules have carefully designed in order to develop two multimedia educational packages to be applicable for both above adopted topics at children's classrooms interestingly, obtained results proved to have significant improved distinction for the applied multisensory methodology (experimental groups) versus the classical one (control groups). That
improvement has been clearly observed not only regarding average (mean) values of academic achievement, but also considering coefficient of variation which improvement results in more consistency of the statistical distribution of academic achievement's values. Furthermore, both multisensory designed modules proved to be in well agreement likewise the Artificial Neural Network (ANN) associative memories theory, cognitive multimedia, and classical conditioning.