Teaching quality evaluation of college civic and political science courses based on BP neural algorithm

IF 0.5 Q4 ENGINEERING, MULTIDISCIPLINARY
Chen Wang
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引用次数: 0

Abstract

Constructing the evaluation system of ideological and political education of new media in colleges is both beneficial to evaluate the established ideological and political education work and an important guide to improve the corresponding work. At present, promoting ideological and political education work with high integration of information technology has become an important way of ideological and political education work in colleges. However, the theoretical circles are still not focused enough on how to evaluate the ideological and political education work in colleges. Based on the characteristics of the information age, this paper establishes the teaching quality evaluation system of ideological and political education courses in colleges, introduces BP neural network evaluation method, and obtains strong empirical support through simulation experiments, so as to build a feasible teaching quality evaluation model of ideological and political courses in colleges. At the same time, the corresponding optimization suggestions are put forward, including improving the relevance of ideological and political education work, dynamically grasping students’ ideological and political information and doing a good job of data processing, and improving the professional information literacy of the ideological and political work team, in order to provide some reference for the efficient development of ideological and political education work in colleges.
基于BP神经算法的高校思政课教学质量评价
构建高校新媒体思想政治教育评价体系,既有利于对已开展的思想政治教育工作进行评价,也是改进相应工作的重要指导。当前,推进与信息技术高度融合的思想政治教育工作已成为高校思想政治教育工作的重要途径。然而,理论界对于如何评价高校思想政治教育工作还不够重视。本文基于信息时代的特点,建立了高校思想政治教育课程教学质量评价体系,引入BP神经网络评价方法,并通过仿真实验获得了有力的实证支持,从而构建了可行的高校思想政治课程教学质量评价模型。同时,提出了相应的优化建议,包括提高思想政治教育工作的针对性、动态掌握学生思想政治信息并做好数据处理、提高思想政治工作队伍的专业信息素养等,以期为高校思想政治教育工作的高效开展提供一定的参考。
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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
152
期刊介绍: The major goal of the Journal of Computational Methods in Sciences and Engineering (JCMSE) is the publication of new research results on computational methods in sciences and engineering. Common experience had taught us that computational methods originally developed in a given basic science, e.g. physics, can be of paramount importance to other neighboring sciences, e.g. chemistry, as well as to engineering or technology and, in turn, to society as a whole. This undoubtedly beneficial practice of interdisciplinary interactions will be continuously and systematically encouraged by the JCMSE.
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