Real Time EEG Based Measurements of Cognitive Load Indicates Mental States During Learning

Abstract

One of the recommended approaches in instructional design methods is to optimize the value of working memory capacity and avoid cognitive overload. Educational neuroscience offers innovative processes and methodologies to analyze cognitive load based on physiological measures. Observing psychophysiological changes when they occur in response to the course of a learning session allows adjustments in the learning session based on the individual learner's capabilities. The availability of non-invasive electroencephalogram (EEG)-based devices and advanced near-real-time analysis techniques have improved our understanding of the underlying mechanisms and have impacted the way we design instructional methods and adapt them to the current learner's cognitive load and valence states. We review Cognitive Load Theory, how cognitive load may be measured, and how analysis of EEG data can be applied to enhance learning through real-time measurements of the learner's cognitive load. We show an experiment that provides a proof of concept of real-time measures based on EEG indicators and of mental states during learning.