Multimedia Delivery and Teaching Innovation of Civic Value in Art Education in the Digital Media Era

The rapid development of information technology and multimedia education in today’s world has led to important changes in the delivery of ideological values in the process of art education. In this paper, according to the form of multimedia presentation of knowledge, a multimedia learning cognitive model is used to study the process of multimedia transmission of Civic and political values. A diverse and efficient recommendation algorithm is proposed, and a recommendation system for Civics and Politics courses is constructed based on the algorithm. The method mines the set of high-efficiency items related to the relationship between courses and categories through a conceptual hierarchical tree and introduces a diversity upper bound function to optimize the mining process. Thus, rules are efficiently generated in the efficiently used generalized itemsets. A collaborative filtering algorithm between users and course types is used to find the neighbors that best match the target users. The results show that the four indicators of this paper’s recommender system are better than other recommender methods. The F-measure of this paper’s system is 0.45, which indicates that this paper’s method can produce the best recommendation effect of the Civics courses. The students in the process of art education can get the Civics course recommendation that is more suitable for them, which improves the efficiency of the Civics value transmission among students.