Design of an Intelligent Virtual Classroom Platform for Ideological and Political Education Based on the Mobile Terminal APP Mode of the Internet of Things
Author(s) -
Xilin Zhang,
Xiaohan Gao,
Honglian Yi,
Zhe Li
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/9914790
Subject(s) - ideology , computer science , the internet , android (operating system) , virtuality (gaming) , multimedia , mathematics education , politics , world wide web , artificial intelligence , psychology , political science , law , operating system
This article uses a software architecture model that combines two architectures, based on the traditional Android environment. Through comparative research on network technology today, Java technology has been selected as a tool for developing network education systems for future research and maintenance upgrades. The underlying network education technology relies on APP to enable education between teachers and students. This technology can not only give play to the advantages of computers in network data transmission, but also embody a new teaching model with teachers and students as the main body. It can solve various practical problems in teacher and student education and educate teachers and students by simulating the actual educational environment of the classroom and educational process using a variety of practical education management strategies. The experimental results prove that with the help of this virtual classroom platform for ideological and political education, it can provide students with more ideological and political learning resources, increase students' interest and time in learning, and promote the diversification of ideological and political learning methods. The quality of teaching is more conducive to the learning of knowledge points for students. At the same time, the system is operating in good condition. Switching between different interfaces is maintained at about 0.1 seconds. The system performance is also perfect. The overall analysis function is basically designed. It is a better learning platform.
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