Classroom Analytics: Telling Stories About Learning Spaces Using Sensor Data

Abstract

The increasing use of interactive devices and networked technologies is blurring the boundaries of the physical classroom by enabling learners and teachers to connect with digital content, systems and people located elsewhere. An underexplored opportunity enabled by emerging sensors and classroom technologies is that multimodal data traces of physical classroom activity can be automatically captured and rendered visible with the purpose of supporting teaching and learning. Positioning and proximity sensor data can be used (1) to generate a deeper understanding of embodied aspects of learning and spatial aspects of instruction, and (2) to provide evidence that enable assessment of effectiveness of the design of physical spaces in education. This chapter presents three data stories that illustrate potential emerging contributions of multimodal classroom analytics to enable new ways to study the teaching and learning processes that unfold in physical learning spaces. Through these stories, we illustrate how analytics for classroom proxemics can enable: (1) the creation of interfaces that provide feedback to learners and educators about activity in the physical classroom; (2) new ways to assess pedagogical activity in learning spaces to inform space re-design or co-configuration; and (3) new approaches to speed up analysis cycles that currently depend on classroom observations.