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An Overview on Classrooms' Academic Performance Considering: Non-Properly Prepared Instructors, Noisy Learning Environment, and Overcrowded Classes (Neural Networks' Approach)

Hassan. M. Mustafa 1 and Ayoub Al-Hamadi 2
1. Computer Eng. Department, Faculty of Engineering. Al-Baha University (K.S.A)
2. Institute for Electronics, Signal Processing and Communications (IESK), Otto-von-Guericke-University Magdeburg Germany
Abstract—This piece of research considers an interdisciplinary challenging educational phenomenon associated to students' academic performance at educational field practice (classrooms). By more details, it presents specifically an educational study regarding with three challenging phenomenal problems observed in classrooms. Firstly, problem faced by teachers' relation to accessible classroom activity. Such as the relation between value of learning rate parameter η and the Gaussian additive noise power σ to learning data submitted by a non-properly prepared instructor. Secondly, noisy data which considered as main cause of environmental annoyance and it negatively affects the quality of academic performance. That presented problem motivated by “Evans’ research reveals significant reading delays for children living near airports and exposed to airport noise". Finally, the problem deals with an auditory perception phenomenon, namely known as Cocktail Party Problem (CPP). This process practically experienced by the presence of overcrowded classroom noisy phenomenon considering only one speaker (instructor's speech).

Index Terms—artificial neural networks models, academic performance, noisy crowded environment, signal to noise ratio, cocktail party effect

Cite: Hassan. M. Mustafa and Ayoub Al-Hamadi, "An Overview on Classrooms' Academic Performance Considering: Non-Properly Prepared Instructors, Noisy Learning Environment, and Overcrowded Classes (Neural Networks' Approach)," International Journal of Learning and Teaching, Vol. 3, No. 1, pp. 38-45, March 2017. doi: 10.18178/ijlt.3.1.38-45
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