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

TL;DR

This study demonstrates that WiFi association logs can be used to infer student collocation patterns and their significant correlation with academic performance, offering a privacy-preserving and cost-effective alternative to traditional location tracking methods.

Contribution

The paper introduces a novel approach to analyze student collocation using WiFi logs and establishes its relationship with academic success, surpassing traditional metrics like attendance.

Findings

WiFi logs can effectively approximate student collocation.

Collocation behaviors correlate with academic performance (r=0.24).

WiFi-based analysis outperforms peer feedback and attendance metrics.

Abstract

A comprehensive understanding of collocation can help understand performance outcomes. For university cohorts, this needs data that describes large groups over a long period. Harnessing user devices to infer this, while tempting, is challenged by privacy concerns, power consumption, and maintenance issues. Alternatively, embedding new sensors in the environment is limited by the expense of covering the entire campus. We investigate the feasibility of 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) over 14 weeks. After describing how we determine collocation with the WiFi logs, we present a study to analyze how collocation within groups relates to a student's final score. We find collocation behaviors show a significant correlation (Pearson's r = 0.24) with performance -- better than both peer feedback or individual behaviors like attendance. Finally, we discuss how repurposing WiFi logs can facilitate applications for domains like mental wellbeing and physical health.