Evaluation of College Students' Ideological and Political Education Management Based on Wireless Network and Artificial Intelligence with Big Data Technology

Evaluation of College Students' Ideological and Political Education Management Based on Wireless Network and Artificial Intelligence with Big Data Technology

Artificial intelligence

Big data

Convolution

Education computing

Information management

Petroleum reservoir evaluation

Students

Wireless networks

The construction of a correct worldview, outlook on life, and values for students is linked to the development and breakthrough in the management of ideological as well as political education of students. At the same time, college students must be encouraged to follow well-rounded education and struggle to be well-prepared for the challenges of the new era. In order to raise students' understanding of the critical role that political and ideological education plays in their academic success, it is authoritative that efforts to integrate these two spheres of learning be extended and new encounters made. That's what prompted this study, which is focused on assessing college students' level of ideological and political education administration, and it uses a mixture of big data technologies as well as artificial intelligence (AI) to do it. The accuracy of the traditional ideological as well as political education management quality assessment algorithm is not high, feature information extracted by the single-scale neural network (NN) is not rich enough, and the multiscale convolutional network (CN) fusion cannot consider the different values and importance for each scale. In this paper, the convolution kernel of the two-dimensional CN is changed to a one-dimensional convolution kernel, and the multiscale feature fusion CN model MCNN is first designed. The model is optimized and improved, the attention mechanism is integrated, and the MACNN model for the management evaluation of ideological as well as political education is proposed. Besides, this work organizes the network model in a wireless network environment that users can contact and operate at any time. 2022 Junnan Qin et al.

2022

Qin, Junnan

Wang, Yihan

Zhao, Qing

Tan, Liheng

Luo, Yaqi

Security and Communication Networks

2022

journalArticle

19390114

10.1155/2022/5802525

http://dx.doi.org/10.1155/2022/5802525