Sensor Data-Driven Emotion Perception in Physical Learning Spaces-A Review and Prospect

Abstract

Learning spaces are gradually developing for supporting self-regulated learning. The availability of learning and movement data in classroom teaching, outdoor learning and campus environments has been enhanced, owing to the emergence of wearable technologies. Consequently, the learning analytics technology for the physical spaces is emerging at the right moment. Learning spaces are facing profound transformations under the educational development of human-technology co-evolution, the learning support services in physical spaces thus need to be reshaped urgently. In recent years, researchers have focused on using sensor technology to collect learners' physiological and behavioral data, combining learning analytics to infer their emotional states, and adopting appropriate intervention mechanisms to improve the positive emotional arousal and academic success. First, this paper introduces some concepts related to the perception of academic emotions in physical spaces. Then the main methods and typical cases are pointed out. Specifically, our aim was to reveal the research status and development trend of emotion perception in physical spaces under the learning analytics fields and to provide a novel insight for the future reshaping of the physical learning spaces.