Big data based research on the management system framework of ideological and political education in colleges and universities

2020 ◽  
pp. 1-10
Author(s):  
Yuejun Xia

Artificial intelligence model combined with data mining technology can mine useful data from college ideological and political education management, and conduct process evaluation and teaching management. Therefore, based on the superiority of data mining technology and artificial intelligence system, this paper improves the traditional algorithm and constructs a university ideological and political education management model based on big data artificial intelligence. Moreover, this study uses a local sensitive hash function to generate representative point sets and uses the generated representative point sets for clustering operations. In order to verify the performance of the algorithm model, a control experiment is designed to compare the algorithm of this paper with traditional data mining methods. It can be seen from the research results that the algorithm model constructed in this paper has good performance and can be applied to practice.

2020 ◽  
pp. 1-12
Author(s):  
Zheng Rong ◽  
Zheng Gang

The student’s political and ideological practices is a vital portion of education, and it is related to optimization of task based on fundamental scenario in establishing morality. In order to establish a scientific, reasonable and operable evaluation model for students’ ideological education, and evaluate the status of college students’ ideological education. In this paper, firstly, in view of the shortcomings of evaluation objectives, single evaluation methods, lack of pertinence of evaluation indicators and subjectivity of evaluation standards in the current evaluation system of university students’ ideological and political education, the basic principles for constructing evaluation models of university students’ ideological and political education are put forward. Secondly, in case to meet changing needs of the times, an artificial neural network algorithm based on artificial intelligence data mining and a traditional multi-layer fuzzy evaluation model are designed to evaluate the ideological and political education of college students. This newly proposed model integrates learning, association, recognition, self-adaptive and fuzzy information processing, and at the same time, it overcomes their respective shortcomings. Finally, an example analysis is carried out with a nearby university as an example. The evaluation results display that the evaluation model of students’ ideological education established in this paper is in good agreement with the previous evaluation results. It fully shows that the comprehensive evaluation model of fuzzy neural network for college students’ ideological and political education established in this paper is scientific and effective.


2020 ◽  
pp. 1-12
Author(s):  
Huang Xiaoyang ◽  
Zhao Junzhi ◽  
Fu Jingyuan ◽  
Zhang Xiuxia

Relying on the reform of the learning field curriculum system of ideological and political education courses in colleges and universities, the association rules between data mining and artificial intelligence technology are used to mine the association relationship between the software professional courses of the computer department, and the ideas and methods of optimizing the course setting are proposed. Discuss the reference value of the whole environment, multi-dimensional space-time, inter-subjectivity theory to the model construction from the theoretical level and the guiding significance of the Internet governance thought to the reform of ideological and political education in universities and colleges The survey results analyze the problems existing in the reform and construction of ideological and political education in colleges and universities, and propose improvements and optimization measures and the four systems of “systematic design outlined in the outline, teamwork coordination of team building, network expansion of environmental construction, and dual promotion of quality assurance". The countermeasures to improve the effectiveness of the ideological and political education in universities, experience summarization, theoretical analysis and empirical research, the idea of constructing a “three-stage full environment” network ideological and political education model for colleges and universities is proposed. Through in-depth understanding and analysis of the relevant knowledge of data mining artificial intelligence technology, the relevant methods of data mining artificial intelligence technology are used to solve the timeliness problems of ideological and political education reform in colleges and universities, so that relevant managers can timely learn relevant information in complex issues to provide solutions for further decision-making.


2021 ◽  
pp. 1-12
Author(s):  
Yuanmeng

Computational ideological and political education is the product of the high degree of integration of ideological and political education with computers, big data, artificial intelligence and other information technologies, and is a new paradigm of ideological and political education in the information age. Through intelligent data collection, data model construction, algorithm analysis, simulation and other links, ideological and political education can not only scientifically explain the various complex ideological and political education phenomena that have already occurred, but also accurately calculate and predict the future state of the ideological and political education system, so that the discipline of ideological and political education can be like natural science, engineering technology through data, model, calculation, simulation and other scientific means. Realize from empirical research to empirical research in order to achieve the political goal of ideological and political education in a more scientific, accurate and efficient way. However, there are still a series of conceptual, technical, data, legal and ethical problems in the construction of computational ideological and political education. Through efforts from various aspects, design practical and guiding program strategies, so as to make full use of big data as a carrier to implement the innovation of college students’ ideological and political education into practice, and enhance the effectiveness of college students’ ideological and political education in the era of big data as the ultimate goal.


2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.


Sign in / Sign up

Export Citation Format

Share Document