基于数据挖掘的大学生思想政治评价模型研究

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS
Linting
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引用次数: 0

摘要

在我国整个教育体系中,思想政治教育是一个重要的组成部分,包含着非常丰富的内容。随着时代的发展,各种新的信息技术手段被积极应用到思想政治实践教学中。目前,随着互联网的快速发展,大学生群体正在成长。“95后”网络“原住民”的思想政治教育评价主体发生了巨大变化。思想政治教育评价的传统价值取向逐渐解构,新的多元价值取向渗透到主体行为的方方面面,必须建立符合时代特征的主体评价体系,评价要“接地气”,易于操作,而不是流于形式。本文从实际情况出发,分析了数据挖掘技术与大学生思想政治教育评价的密切关系,然后重点研究了基于数据的大学生思想政治教育评价模型的相关问题
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the model of college students’ ideological and political evaluation based on data mining
In the whole educational system of our country, ideological and political education is an important component, and contains very rich content. With the development of the times, a variety of new information technology methods have been actively applied to the ideological and political practical teaching. At present, the group of college students is growing up with the rapid development of Internet. The “95 after generation” network “indigenous people” has undergone great changes in the evaluation body of Ideological and political education. Evaluation of Ideological and political education of the traditional value orientation gradually deconstructed, a new multi value orientation to penetrate into the body of all aspects of the behavior, must be established in accordance with the characteristics of the times subject evaluation system, the evaluation of “down to earth” and easy to be operated, rather than a mere formality. Based on the actual situation, this paper analyzes the close relationship between data mining technology and the evaluation of College Students’ Ideological and political education, and then focuses on the related problems of College Students’ Ideological and political evaluation model based on data
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
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