Technologies for automated analysis of co-located, real-life, physical learning spaces

Abstract

The motivation for this paper is derived from the fact that there has been increasing interest among researchers and practitioners in developing technologies that capture, model and analyze learning and teaching experiences that take place beyond computer-based learning environments. In this paper, we review case studies of tools and technologies developed to collect and analyze data in educational settings, quantify learning and teaching processes and support assessment of learning and teaching in an automated fashion. We focus on pipelines that leverage information and data harnessed from physical spaces and/or integrates collected data across physical and digital spaces. Our review reveals a promising field of physical classroom analysis. We describe some trends and suggest potential future directions. Specifically, more research should be geared towards a) deployable and sustainable data collection set-ups in physical learning environments, b) teacher assessment, c) developing feedback and visualization systems and d) promoting inclusivity and generalizability of models across populations.