Study on Machine Learning Applications in Ideological and Political Education under the Background of Big Data

Author:

Li Yanjie1,Mao He2ORCID

Affiliation:

1. Xi’an Siyuan University, Xi’an, Shaanxi 330022, China

2. Suzhou University of Science and Technology, Suzhou, Jiangsu 215000, China

Abstract

With the development of big data and data mining technology, machine learning has been applied in many fields. However, there are a large number of difficulties for students who majored in ideological and political education. It is very necessary for those students to integrate machine learning technology into ideological and political education courses. In this paper, we introduced how to integrate machine learning into ideological and political education courses in class. Firstly, we explained what teachers should do before/in/after class for teaching machine learning courses and what students should prepare. Secondly, we took the introduction section of machine learning courses as an example to connect each content with ideological and political education and illustrate them in the way of ideological and political education. Thirdly, we took the decision tree algorithm that belongs to machine learning as an example to explore the ideological and political education philosophy in the decision tree algorithm. Finally, we make a questionnaire from the perspective of learning attitude, learning influence, and learning effect to investigate the outcomes of students with our teaching way. Our results presented valuable meaningful information for students who majored in not only computer science but also ideological and political education, thus promoting the progress of interdisciplinary and making machine learning courses understood more easily in the class of ideological and political education.

Publisher

Hindawi Limited

Subject

Computer Science Applications,Software

Reference29 articles.

1. Big data for development: challenges and opportunitise;E. Letouze,2012

2. A Handler for Big Data

3. Big data:Science in the petabyte era;M. Minnesota;Nature,2008

4. Big data:the next frontier for innovation, Competition,and productivity;J. Manyika,2011-05-21

5. The World’s Technological Capacity to Store, Communicate, and Compute Information

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