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

Abstract

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.

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

“…Universities can leverage this particular characteristic of big data to develop specialized data and information platforms that can track progress in the field of political and ideological education [ 18 ]. Teachers will be able to fully create individual teaching qualities, stay current on students' views and ideological dynamics, and increase the relevance of education in politics and ideology after evaluating the vast amounts of data [ 19 , 20 ]. In this study, we will conduct a thorough analysis and discussion of big data, as well as the difficulties and potential paths for innovation faced by universities.…”

Study on Document Measurement and Visual Analysis of Big Data Education Evaluation

“…The main research content of this category is to apply different clustering algorithms to analyze learners' learning ability and professional skills, match industrial needs [6], conduct learning analysis [7], and realize the clustering and visualization of interactive education network resources [12]. Research related to AI technology includes monitoring and early warning of students' online learning performance [14], or evaluating the quality of education management of a discipline to help the discipline achieve intelligent teaching [5,9,20,21].…”

Improving online ideological and political precision education in universities based on knowledge mapping

“…There are many methods for estimating parameters in item response theory, including the great likelihood estimation, EM algorithm, Bayesian algorithm, etc. This paper will use the great likelihood estimation method for the parameter estimation process [18][19]. The specific parameter estimation method is as follows:…”