StudentLife

TLDR

Student stress and strain are largely hidden. The study uses a continuous sensing app on Android phones to evaluate how workload affects stress, sleep, activity, mood, sociability, mental well‑being, and academic performance over a 10‑week term among 48 Dartmouth students. The study employed the app and made the resulting dataset publicly available online. Results show significant correlations between smartphone sensor data and mental health and educational outcomes, revealing a term lifecycle where students start with high positive affect, low stress, healthy sleep and activity, but as workload increases, stress rises and positive affect, sleep, conversation, and activity decline.

Abstract

Much of the stress and strain of student life remains hidden. The StudentLife continuous sensing app assesses the day-to-day and week-by-week impact of workload on stress, sleep, activity, mood, sociability, mental well-being and academic performance of a single class of 48 students across a 10 week term at Dartmouth College using Android phones. Results from the StudentLife study show a number of significant correlations between the automatic objective sensor data from smartphones and mental health and educational outcomes of the student body. We also identify a Dartmouth term lifecycle in the data that shows students start the term with high positive affect and conversation levels, low stress, and healthy sleep and daily activity patterns. As the term progresses and the workload increases, stress appreciably rises while positive affect, sleep, conversation and activity drops off. The StudentLife dataset is publicly available on the web.