Construction of Ideological and Political Education in Universities Based on Intelligent Digital Education

Given the current state of ideological education in colleges and universities, we propose leveraging image recognition technology to foster innovation and digital advancement in this mode of education. The weighted average method is used to greyscale the video images of students’ classrooms, and after binarizing the images using the OTSU algorithm, interference factors are avoided by denoising and angle correction. We combine the motion history image (MHI) and HOG features to create a new feature that depicts Civics classroom behavior. The SVM classifier then performs the classification of classroom behavior, ultimately constructing the Civics classroom behavior recognition model based on HOC+MHII+SVM. This paper’s model and research data are combined to conduct an example analysis of Civics education in colleges and universities. It can be concluded from the analysis that, in the case of simultaneously adopting SVM for recognition and classification, it is found that HOC+MHI feature fusion has a more significant effect on classroom behavior recognition than FPN+Multi-layer CBAM, and the difference of its various indexes is maintained within the range of 0.01~0.08. In addition, the experimental group has a significant difference relationship in the four dimensions of demonstrating the concept of honor and shame, the concept of national development, the value of development, and the value of society, P<0.05. This study provides theoretical references for research on the innovation of the ideological and political education model and is conducive to the promotion of cultivating the formation of students’ socialist core values.

Research on Building a New Mode of Civic and Political Education by Image Recognition Technology for Popularizing Socialist Core Values

Liu

2024

Content Innovation and Strategy Dynamic Adjustment of College Students’ Civic and Political Education Based on the Empowerment of Intelligent Algorithm

2024

Students’ ideology is mainly developed in the college period, so the ideological and political education work in colleges and universities should be strengthened in order to help students improve their ideological and moral qualities. In this paper, after the introduction of data mining, through the comparison of two algorithms of COBWEB clustering and K-means clustering based on the model method, we chose to use the K-means clustering method to carry out the learning characteristics mining clustering for the students of logistics management majoring in the school of management of a university in Zhengzhou City, Henan Province, and 220 students were selected as the research object. The students were divided into four categories for integration from six dimensions: learning foundation, learning interest, independent learning ability, collaborative learning ability, beginning of Civics learning, and advanced Civics learning. and. then, the purpose of students’ learning Civics education was studied in terms of learning motivation. In all dimensions, students in the first category did well, and 135 students in each category aimed to improve their academic qualifications while learning Civics courses. The innovative path for the content of Civic and Political Education is proposed based on the learning characteristics of the students. 180 students were selected as examples of logistics management class students, divided into experimental and comparison groups, and explored in terms of cultural self-confidence level, academic level, and motivation for learning using the difference analysis method. It was found that after applying the proposed content to the Civic and Political Education classroom, the experimental group and the comparison group showed significant improvement in all dimensions except for learning motivation. It indicates that the content innovation strategy of Civic and Political Education proposed in this paper has a better impact on the teaching effect.

Exploring the path of deep integration of traditional culture and ideological and political education based on virtual reality technology

Tang,

2024

The continuous development of the information age promotes the transformation of teaching methods, and the forms of students’ learning and receiving knowledge are also constantly updated. In this paper, virtual reality technology is used to realize the deep integration of traditional culture and ideological and political education from the three aspects of the course: teaching objectives, teaching content and teaching process, and design of a three-dimensional animation classroom. The particle swarm algorithm is used to optimize the acquisition of teaching resources and integrate the best ideological and political education resources that incorporate traditional culture. Through empirical analysis, it was found that 66% of the learners of the teaching resources acquired by the algorithm believed that it stimulated their interest in learning the course, and 68% of the learners believed that it strengthened their understanding and mastery of the knowledge points. Compared with the traditional teaching mode of 3D animation classroom teaching mode based on virtual reality technology, the effect of improving students’ performance in traditional culture and Civics education under the former mode is higher than that of the traditional teaching mode. The teaching experiment demonstrates that the teaching design of this paper is capable of effectively integrating traditional culture with ideological and political education.