Teaching Design Model of Media Courses Based on Artificial Intelligence

Abstract

Under the background of information technology, in order to promote the smooth development of teaching design of media courses, we must adhere to the basic principle of taking students as the center and reasonably create teaching situations. Insert high-flying wings for the production and dissemination of intelligent media content in the AI era, making content production faster and more efficient, realizing scene and experience of content terminals, and making information dissemination more intelligent and personalized. This topic launches the teaching design of media courses based on AI (artificial intelligence). The teaching scheduling model of media courses and the teaching recommendation algorithm of media courses based on AI are established. By introducing LSTM (Long Short-Term Memory) to embed the multi-feature information of users and courses into the model, users’ interests and preferences can be fully understood, and satisfactory recommendation results can be given. The results show that the accuracy of CF(collaborative filtering) recommendation based on clustering is higher than that of this recommendation algorithm. The accuracy and recall of this recommendation algorithm can reach 91.4619% and 87.7128% respectively. On the one hand, the cold start problem of CF algorithm is improved, on the other hand, compared with the content-based recommendation algorithm, the effect is significantly improved, and the expected effect is achieved.

Keywords

• Artificial intelligence
• media courses
• teaching design
• recommendation algorithm