Design and Application of Based Feed Forward Deep Neural Network Ideological and Political Education Assistance System

The teaching system refers to conventional Ideological and Political teaching (IPT) method pays attention to students' complex role in learning. The public teaching course is a humble important course in regular schools for nonpedagogical students. Efficient education must be estimated through the most effective as well as developing advancements. Thus, this research proposes the Deep Learning (DL) approach of Feed Forward Deep Neural Network (FFDNN) for the Ideological and Political educational assistance system. The proposed approach introduces a teaching error feedback mechanism integrated through knowledge sources and audio and video source data from classroom produced in teaching procedure. A proposed approach generates the reports of teaching irregularities through correlating subjective data by empirical data. The experimental results demonstrates that the proposed FFDNN approach attains the Students Political Evaluation Ratio of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{8 9. 1 3 \%}$</tex> and Students efficiency ratio of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 5. 5 7 \%}$</tex> respectively. This research resulted in strengthening teacher instructional approaches, learning approaches as well as teacher management modes.