Research on the Teaching and Interaction Mode of Collaborative Development of Party Building and Civic and Political Education in Colleges and Universities Based on Artificial Intelligence

Abstract

Both ideological and political theory courses and student party building are the main channels of ideological and political education for students in colleges and universities in the new era, and they are important handles for cultivating builders and successors of socialism with Chinese characteristics. For this reason, after exploring the teaching strategy of AI-enabled synergistic development of party building and ideological and political education in colleges and universities, the article designs a Q&A interactive system based on the knowledge level of students' party building and ideological and political education. The system first improves the Bayesian knowledge tracking model and introduces the correlation degree between the knowledge points to realize the tracking of the knowledge level of students' Party building and Civic and political education, and on this basis, it combines the bi-directional threshold recurrent unit neural network and the attention mechanism to design a Q&A model based on the threshold recurrent unit. The article finally tests the teaching interaction effect of the model and finds that the highest adjusted residual value is writing-reading with a residual value of 0.663, which is mainly due to the small number of behaviors, which does not constitute significance. Therefore, the method of this paper can help to improve the interactive effect of Civics classroom teaching integrating party building knowledge.