Research on Content Design and Intelligent Teaching Strategies of Civic and Political Education for Soil-based Engineering Students

Existing civil engineering professional civic education recommendation system is difficult to realize the accurate recommendation of civic resources in the process of practical application due to the lack of effective analysis of students. Taking this difficulty as the starting point, this paper improves the similarity calculation methods of user-based and content-based recommendation at the same time, and constructs an optimized hybrid recommendation algorithm. Subsequently, the effective integration of civil engineering specialty and Civic and political education under the recommendation algorithm of this paper is explored. The H value of this paper’s algorithm is in the range of 18.45-21.88, the M value is in the range of 1.85-2.01, and the D value is in the range of 4.40-4.85, which has high stability and high level of recommendation quality. Applying this paper’s recommendation algorithm to actual teaching, in which P=0.02<0.05 of the post-test test results of the values of the students in the experimental class and the control class show significant differences. It shows that the recommendation algorithm in this paper can realize the accurate recommendation of the Civics resources by combining the students’ characteristics.