Research and application of behavior analysis of college students based on smart campus

The country strongly supports the transformation of education towards intelligence, the normalization of online learning, and the development of smart campuses based on advanced information technology. With the support of smart campuses, it is possible to better, faster, and more accurately grasp the behavior of college students, thus making more favorable suggestions and decisions. Firstly, a definition of smart campus was provided, and the behavior of college students was scientifically classified and summarized. K-means clustering method and Apriori algorithm were introduced. Subsequently, a literature review will be conducted. Finally, establish a research model, collect data from different modules of the smart campus system, clean the data, use K-means clustering method to transform the data, and finally use Apriori algorithm to derive the correlation rule between college student behavior and grades, and propose relevant suggestions.