Before revision:  This paper investigates one such approach by leveraging WiFi association logs archived by a managed campus network. In their raw form, access point logs can approximate a student's location but with low spatio-temporal resolution. This paper first demonstrates that processing these logs can infer the collocation of 46 students in 34 lectures over 3 months, with a precision of 0.89 and a recall of 0.75. Next, we investigate how this WiFi-based coarse collocation reflects signals of social interaction. With 163 students  in 54 project groups , we find that member performance shows a correlation of 0.75 with performance determined from collocation of groups through 14 weeks.
After revision:  This paper investigates one such approach by leveraging WiFi association logs for this purpose. While these provide coarse approximations of location, these are easily obtainable and depict multiple users on campus over a semester. We explore how these coarse collocations are related to individual performance. Specifically, we inspect the association between individual performance and the collocation behaviors of project group members. We study 163 students in 54 project groups , we find that member performance shows a correlation of 0.75 with performance determined from collocation of groups through 14 weeks.