Exploring homophily in demographics and academic performance using spatial-temporal student networks

Network analysis in educational research has primarily relied on self-reported relationships or connections inferred from online learning environments, such as discussion forums. However, a large part of students’ social connections through day-to-day on-campus encounters has remained underexplored. The paper examines spatial-temporal student networks using campus WiFi log data throughout a semester, and their relations to the student demographics and academic performance. A tie in the spatial-temporal network was inferred when two individuals connected to the same WiFi access point at the same time intervals at the ‘beyond chance’ frequency. Our findings revealed that students were more likely to co-locate with the individuals of similar gender, ethnic group identity, family income, and grades. Analysis of homophily over the semester showed that students of the same gender were more likely to co-locate as the semester progressed. However, co-location of the students similar on ethnic minority identity, family income, and grades remained consistent throughout the semester. Mixed-effect regression models demonstrated that features derived from spatial-temporal networks, such as degree, the grade of the most frequently co-located peer, and average grade of five most frequently co-located peers were positively associated with academic performance. This study offers a unique exploration of the potential use of WiFi log data in understanding of student relationships integral to the quality of college experience.