Journal of Data Processing Kai Shen, Xinyi Yuan 14 4 2024 https://doi.org/10.6025/jdp/2024/14/4/133-139 https://www.dline.info/jdp/fulltext/v14n4/jdpv14n4_1.pdf With the continuous development of technology, big data analysis techniques have been widely applied in various fields. In traditional management approaches, administrators rely on manual data analysis and processing, which not only lacks efficiency but is also prone to errors. On the contrary, analysis methods based on clustering algorithms can provide effective support for management tasks. In this article, we will use the K-Means clustering algorithm to extract useful information, thereby effectively improving the performance of college students on campus. We carefully preprocess this information, remove redundant content, and then categorize it, leading to a significant enhancement in college students’ performance.