Measuring Cognitive Load and Insight: A Methodology Exemplified in a Virtual Reality Learning Context

Recent improvements of Virtual Reality (VR) technology have enabled researchers to investigate the benefits VR may provide for various domains such as health, entertainment, training, and education. A significant proportion of VR system evaluations rely on perception-based measures such as user pre-and post-questionnaires and interviews. While these self-reports provide valuable insights into users' perceptions of VR environments, recent developments in digital sensors and data collection techniques afford researchers access to measures of physiological response. This work explores the merits of physiological measures in the evaluation of emotional responses in virtual environments (ERVE). We include and place at the center of our ERVE methodology emotional response data by way of electrodermal activity and heart-rate detection which are analyzed in conjunction with event-driven data to derive further measures. In this paper, we present our ERVE methodology together with a case study within the context of VR-based learning in which we derive measures of cognitive load and moments of insight. We discuss our methodology, and its potential for use in many other application and research domains to provide more in-depth and objective analyses of experiences within VR.