A data portrait-based approach to precision education for medical students in China

With the rapid development of big data technology, smart campuses from medical universities of China have accumulated a large amount of student behavior data. How to extract hidden and valuable information from a large amount of data has become a problem faced by medical universities of China. This study constructed a framework for the portrait model of medical university students of China, which includes 5 dimensions: identity and organizational data, learning data, economic data, and health and interest data. These data are sourced from the smart campus information system of medical universities of China. Then, K-means clustering method is used to calculate these data, extract the characteristic attributes of students, and construct accurate student data portraits. This study uses big data profiling technology to accurately describe the digital characteristics of students, providing reference for the educational environment of medical universities.