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On optimality of teaching quality for a mathematical topic using Neural Networks (with a case study)

This paper addresses an interdisciplinary approach integrating evaluation of an educational issue with Artificial Neural Network (ANN) modeling. Specifically, it is concerned with ANN modeling of two Computer Assisted Learning (CAL) packages/modules using various learning rate values. Both packages are considered for teaching a mathematical topic: “How to solve long division problem?”. They have been submitted at the fifth grade classroom level in elementary schools (as a case study with or without associated teacher's voice). Furthermore, after the application of the suggested CAL packages, practical findings have been compared with classical learning obtained results. Interestingly, all findings are shown to be in agreement with simulation results after running the introduced realistic ANN model. Finally, this work investigated well how measured mathematical teaching quality could be fairly improved via assessment of two learning parameters' performance (achievement level & response time).