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A comprehensive understanding of collocation can help understand performanceoutcomes. For university cohorts, this needs data that describes large groupsover a long period. Harnessing user devices to infer this, while tempting, ischallenged by privacy concerns, power consumption, and maintenance issues.Alternatively, embedding new sensors in the environment is limited by theexpense of covering the entire campus. We investigate the feasibility ofleveraging WiFi association logs for this purpose. While these provide coarseapproximations of location, these are easily obtainable and depict multipleusers on campus over a semester. We explore how these coarse collocations arerelated to individual performance. Specifically, we inspect the associationbetween individual performance and the collocation behaviors of project groupmembers. We study 163 students (in 54 project groups) over 14 weeks. Afterdescribing how we determine collocation with the WiFi logs, we present a studyto analyze how collocation within groups relates to a student's final score. Wefind collocation behaviors show a significant correlation (Pearson's r = 0.24)with performance -- better than both peer feedback or individual behaviors likeattendance. Finally, we discuss how repurposing WiFi logs can facilitateapplications for domains like mental wellbeing and physical health.

Leveraging WiFi Network Logs to Infer Student Collocation and its Relationship with Academic Performance