One of the key difficulties confronting universities today is how to use the current technology to raise educational standards and support educational reform. This is due to the ongoing growth of network technology. This study primarily explores the collaborative filtering recommendation algorithm-based recommendation model for college civics teaching materials. Analyzed are both the functional and non-functional demands for collegiate civic and political science teaching materials. For these requirements, the collaborative filtering recommendation algorithm is put out, and it is enhanced so that it may be applied in real-world settings. In order to execute the model, the system architecture and process are established, and the impacts of teaching interventions are used to examine the outcomes of the suggested practical teaching of civic and political science teaching materials in colleges and universities. The findings revealed that the p-values of the significance probabilities were, respectively, 0.056, 0.007, and 0.235 for the entrance exam and the first semester final examination, the entrance examination and the second semester final examination, and the first semester final examination and the second semester final examination. The collaborative filtering recommendation algorithm-based recommendation model for teaching resources recommendation of university thinking and politics proposed in this paper is effective in enhancing students’ learning autonomy and promoting the exchange of ideas. It has a certain effect.