Research on Digital Resource Construction and Intelligent Recommendation Strategy for Civic and Political Education in Colleges and Universities

As an inevitable product of the combination of curriculum ideology education and educational informatisation, curriculum ideology digital resources play an important role in the construction of curriculum ideology. At present, there are problems such as insufficient quantity, low quality, poor match with professional construction goals, and lack of systematization of the curriculum for civic and political resources, which affect the educational effectiveness. This paper builds a Civics course resource network, mines learners’ learning behaviours and interests, adopts collaborative filtering algorithms, calculates the similarity between learners’ learning behaviours and resource usage preferences, establishes a personalized recommendation collection of Civics course resources, and realizes the personalized recommendation of the Civics course resources in colleges and universities by collaborative filtering. Fusion of the resource content algorithm and proposed improvements to collaborative filtering to form a hybrid recommendation algorithm. Based on the recommendation algorithm evaluation index, the recall and accuracy of the algorithm are evaluated, and the precision and recall of this paper’s algorithm are 89% and 89.96%, respectively, which are higher than the remaining two comparative algorithms, indicating that it can achieve a better-recommending effect under the actual recommending scenario. This paper’s algorithm has the largest number of resource recommendations, and the recommendations for the fourth year of college are 1310.52036 and 1334.27602, respectively. At the same time, the students are able to maintain more than 42 minutes of listening time for these recommended resources, which means this paper’s algorithm has a better recommendation effect.