Title: Improving college ideological and political education based on deep learning

Authors: Youwu Zhang; Yongquan Yan; R. Lakshmana Kumar; Sapna Juneja

Addresses: Ideological and Political Department, Shanxi Vocational College of Finance, Taiyuan, 030008, Shanxi, China; Institute of Marxism, Inner Mongolia University, Hohhot, 010020, Inner Mongolia, China ' School of Statistics, Shanxi University of Finance and Economics, Taiyuan, 020024, China ' Department of CSE, SNS College of Technology, Coimbatore – 641035, India ' IITM Group of Institutions, G.T. Karnal Road, Murthal, Sonipat, NCR-Delhi, Sonipat, Haryana, 131039, India

Abstract: The rapid development of information and technology results in the involvement of technology channels like communication devices, and simultaneously it acts as a vital part of life. It emerged as a significant concern in the student's educational progress both physically and mentally. It is essential to maintain the teaching quality in the teaching field, and more concentration is needed for the college ideological political education. For successive enhancement, a novel multimedia assisted ideological and political education system using deep learning techniques (MIPE-DLT) is introduced. The model analyses the characteristics and the capability of higher education students in gathering information and realising the effects of propagating novelties in ideological and political education. The proper flow of protocols has been executed in implementing multimedia techniques towards ideological and political education. It bridges the gap efficiently with a higher accuracy rate and processing rate. Compared with previous techniques, the MIPE-DLT achieves a high-order performance ratio with a minimal delay rate.

Keywords: multimedia; political; ideology; education; college learning; quality; teaching.

DOI: 10.1504/IJICT.2024.138778

International Journal of Information and Communication Technology, 2024 Vol.24 No.4, pp.431 - 447

Received: 31 Mar 2021
Accepted: 13 Sep 2021
Published online: 31 May 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article