Deep Reinforcement Learning-Based Ideological and Political Course Resource Recommendation

With the rapid development of information technology, digital transformation in education has become an important way to improve the quality and effect of education. Especially in the ideological and political course teaching, how to use intelligent technology to improve the personalized recommendation effect of teaching resources has become a hot research topic. In this paper, we first describe the concepts related to deep reinforcement learning. Secondly, an improved algorithm of ideological and political course resource recommendation based on deep reinforcement learning is extracted. Finally, the effectiveness of the proposed system in improving recommendation accuracy and personalization is verified through experiments. This paper not only provides theoretical basis for intelligent recommendation of ideological and political education resources, but also provides practical reference for personalized learning in education field.