On Analysis and Evaluation of Non-Properly Prepared Teachers' Implication on Students Considering Optical Character Recognition (OCR) (Neural Networks' Modeling Approach)
Hassan M. H. Mustafa · 2015
This paper addresses an interdisciplinary, interesting, and critical educational phenomenal issue. Adopted phenomenon related directly to clearness of educational environment affecting enhancement and enlightening of learning/teaching performance. Specifically, it describes the serious problematic issue associated with implication of non-properly prepared teachers' on students' learning performance (achievement) in classrooms. Herein, the undesired level of improperness mapped into well-known communication term named signal to noise ratio. In the context of communication technology this term abbreviated as SNR or S/N which measures the clarity of the received desired signal through transmission channel. Suggested Artificial Neural Network (ANN) model adopts feed forward (FF) structure which obeys Kohonen learning law while bits training to recognize three figures having (T, H, and L) shapes via (3X3) retina. Interesting findings have been obtained after running of a realistic simulation program suggested herein. Such as the relation between value of learning rate parameter