doi: 10.7763/IJIET.2016.V6.817
On Comparative Analogy of Academic Performance Quality Regarding Noisy Learning Environment versus Non-properly Prepared Teachers Using Neural Networks' Modeling
Abstract
This piece of research presents analytical evaluation of comparative analogy between two educational phenomena considering academic performance (achievement) observed inside our classrooms. These two phenomena are: the effect of noisy learning environment on educational field academic achievement quality. In addition to the impact of interactive teaching by non-properly prepared teachers on academic performance. The comparative analogy investigated herein, is presented systematically via adopting Artificial Neural Networks' (ANNs) modeling. By more details: noisy data considered as the main cause of environmental annoyance which negatively affects the quality of academic performance. Furthermore, considering student's learning ability problem faced by non-properly prepared teachers during their academic tutoring performance inside classrooms. On the basis of the adopted supervised learning ANN model, two basic neural networks' parameters have been explicitly considered. That's while running of presented simulation program, both parameters are: learning rate value (η) and gain factor value (λ).
Keywords
- Artificial neural networks models
- academic performance
- signal to noise ratio
How to Cite
Hassan M. Mustafa and Ayoub Al-Hamadi, "On Comparative Analogy of Academic Performance Quality Regarding Noisy Learning Environment versus Non-properly Prepared Teachers Using Neural Networks' Modeling," International Journal of Information and Education Technology, vol. 6, no. 12, pp. 917-922, 2016. https://doi.org/10.7763/IJIET.2016.V6.817
Copyright & License
Copyright © 2016 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).