Predicting Collaborative Learning Quality through Physiological Synchrony Recorded by Wearable Biosensors

Abstract

AbstractInterpersonal physiological synchrony has been consistently found during collaborative tasks. However, few studies have applied synchrony to predict collaborative learning quality in real classroom. This study collected electrodermal activity (EDA) and heart rate (HR) in naturalistic class sessions, and compared the physiological synchrony between independent task and group discussion task. Since each student learn differently and not everyone prefers collaborative learning, participants were sorted into collaboration and independent dyads based on collaborative behaviors before data analysis. The result showed that during groups discussions, high collaboration pairs produced significantly higher synchrony than low collaboration dyads (p = 0.010). Given the equivalent engagement level during independent and collaborative tasks, the difference of physiological synchrony between high and low collaboration dyads was triggered by collaboration quality. Building upon this result, the classification analysis was conducted, indicating that EDA synchrony can predict collaboration quality (AUC = 0.767, p = 0.015).