Exploring the Path of Enhancing Ideological and Political Education in Universities in the Era of Big Data

Author:

Shao Nana12,Hu He32ORCID

Affiliation:

1. School of Marxism, Hainan Medical University, Hainan, Haikou 571199, China

2. Hainan Integrated Moral Education Research Base for College, Middle School and Children, Hainan, Haikou 570204, China

3. School of Marxism, Qiongtai Normal University, Hainan, Haikou 570204, China

Abstract

The emergence of the big data era has drastically altered people’s lives and perceptions. One needs a thorough understanding of the topic to effectively apply big data’s benefits to the ideological and political education work that colleges and universities carry out. By doing so, the advantages of big data can be better exploited and integrated into the educational process, enhancing the work’s overall quality. To enhance the path of ideological and political education in colleges and universities, it is necessary to change according to the matter, advance according to the time, and make new changes according to the situation, and therefore, it is important to actively explore the path of ideological and political education in colleges and universities under the times. In this study, we research and analyze the opportunities and challenges facing the ideological and political education of universities in the era of big data, reexamine the subjective and objective environment in which the ideological and political education of universities is located, and explore the innovative development path of the ideological and political education of universities in the new environment. We will also encourage the innovative growth of ideological and political work in four areas, such as cultivating big data thinking innovation, working method innovation, working carrier innovation, and ideological work team construction, and conduct a ranking analysis on the significance of the exploration variables to improve the path of ideological work. The importance score measures the value of features in the construction of the ascending decision in the model, so the XGBoost algorithm is used to sort and analyze the significance of exploring variables to enhance the political and ideological work trajectory. The analysis of the experimental results shows that the innovation of working methods has greatly enhanced the conditions for carrying out ideological and political education in the new environment and has far-reaching implications and important significance for the innovation of ideological and political education in universities.

Funder

Ministry of Education of the People's Republic of China

Publisher

Hindawi Limited

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

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