"I spent 14 hours debugging just one assignment": Toward Computer-Mediated Personal Informatics for Computer Science Student Mental Health

Anxiety and depression rates in Computer Science (CS) students are double those of other undergraduates and 5-10 times higher than the general population. However, factors contributing to the elevated mental health issues in CS students remain unknown. To bridge this gap, we conducted need-finding interviews (N=20), which revealed that the complexity of debugging, along with imposter syndrome, are key contributors to stress and burnout. Participants expressed openness toward and feature preferences in a computer-based Personal Informatics (PI) tool to facilitate self-reflection. In response, we developed EmotionStream, an algorithm-assisted PI tool that provides both contextual and emotional insights based on individual behaviors. We found that participants rated their experience with the tool highly. Post-hoc analysis revealed that emotional states, augmented with contextual cues, show promise of predicting realtime stress. Based on our findings, we provide design implications for future PI tools to support CS student mental well-being.

• Human-centered computing → Empirical studies in HCI ; • Applied computing → Health informatics.