Identifying at-risk students at an early stage is a challenging task for colleges and universities. In this paper, we use students' oncampus network traffic volume to construct several useful features in predicting their first semester GPA. In particular, we build proxies for their attendance, class engagement, and out-of-class study hours based…

In an age of assessment and accountability, academic libraries feel much pressure to prove their value according to new university measurements of student success. This study describes a methodology for how libraries may examine student interactions with services to assess whether library usage impacts student grade point averages (GPAs) and…