This paper explores the relationship between college students’ consumption views and their consumption views under Civic Education in the context of multiple datasets. Secondly, a multi-agent, multi-source heterogeneous data collection model is used to collect data on consumption view and Civic Education. A CNN model is designed to study the correlation between consumption view and Civic Education. The CNN and LSTM multi-grain data classification models are used to fuse the features of consumer outlook and Civic Education, respectively. Then, build an online learning platform for college students’ consumerism. Finally, the platform’s fusion effect and learning results for college students were analyzed and studied. The average JS index of data fusion was 93.32%, and the fusion effect was good. The total score of students’ pre and post-test consumerism scores increased from 86 to 100, and the effect of college students’ consumerism education was positive.