Exploring the Effects of Multi-Sensory Extraneous Load on Attention and Task Performance for Training Contexts in Virtual Reality

Abstract

Virtual reality (VR) is increasingly being used in training contexts and for understanding cognitive performance. These environments require multi-sensory interactions that can overload cognitive processing and may unintentionally include elements that disrupt attention. Combined with the use of modern EEGs (electroencephalograms), HMDs (head-mounted devices) can be used to understand the thresholds of cognitive load in these multi-sensory virtual environments. Current research in this field suggests cognitive load is affected by the amount of information being processed at a given time and will increase as different types of stimuli are processed simultaneously, like in VR (Albus, Vogt, & Seufert, 2021; Antonenko, et. al, 2010; Baceviciute et. al, 2020; Hebb & Donderi, 2013; Jerald, 2015; Mayer, 2005; Mayer, 2014; Mayer & Fiorella, 2014; Sanei & Chambers, 2013). However, it is still unclear the nuances of cognitive load when distracted by different features of auditory and visual stimuli. The goal of this research is to establish a cognitive-motor dual-task paradigm for understanding cognitive load in VR based on four distractor types: pitch, speed, amplitude, and proximity. These features are analyzed using objective (EEG) and subjective (questionnaires) measures to separate types of cognitive load. The methods employed in this research aim to provide a novel way of analyzing this type of multi-sensory information and inform designers of specific features that may unknowingly increase extraneous cognitive load in virtual training and learning contexts.