Ideological and Political Education Reform Using Mobile Phones as a Carrier in the Context of Artificial Intelligence

Author:

Sun Qian1ORCID

Affiliation:

1. School of Marxism, Shaanxi Xueqian Normal University, Xi’an, 710100 Shaanxi, China

Abstract

With the rapid development and transformation of the current society, reform in the education system has reached new heights of development. Also, the evaluation of ideological and political education reform using mobile phones as a carrier for artificial intelligence has become increasingly popular and essential. However, there are some problems in the reform process, though it has many advantages overstanding in a row. The concept of mobile phones as a carrier in artificial intelligence- (AI-) based mobile learning includes a complete teaching and learning process through mobile Internet devices. These Internet of Things (IoT) devices can be tablets, smartphones, and e-readers. In the present scenario, learning on a smartphone is still relatively marginal, while learning on computers and tablets is the subject of many experiments and projects in recent years. Many benefits are regularly put forward to promote mobile Internet technology in education, like more interactivity to enrich the learning, like discussion forums, blog spots, e-classrooms, chatrooms, and learning apps. Reading on mobile phones and in the traditional education system (reading books) improves brain activity. As a result, the concept of mobile phones as a carrier in AI (mobile learning) has more advantages than the traditional educational systems. The present research proposes a set of hypotheses that show mobile learning is way more advantageous than the conventional education system. In this research, remote supervision algorithms with wireless communication technology are proposed to perform the reformation of ideological and political education using mobile phones. The proposed algorithm focuses on the accurate delivery of the online courses, and the algorithm is compared with the existing hybrid K-means method, which has provided 5.03% less accuracy than the proposed method.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

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