Cognitive Load Measurement in Perspective

Abstract

Cognitive load is a significant factor in various application areas such as human-computer interaction (HCI), adaptive automation and training, traffic control, performance prediction, driving safety, and military command and control. Consequently, the investigation of cognitive load factors and cognitive load measurement is essential in order to improve human’s wellbeing and safety at work. As indicated in Part I, an individual human has limited cognitive resources. Both theories and models have been proposed to understand and measure cognitive load. Cognitive load theory models the interaction between limited working memory and the relatively unlimited long term memory during the learning process. It distinguishes between three types of cognitive load: intrinsic load, extraneous load, and germane load. The first type is associated with the nature of learning material, while the latter two are influenced by instructional design. Techniques used for cognitive load measurement can be divided into the following categories: subjective rating, performance measures, behavioral measures and physiological measures. The physiological approaches for cognitive load measurement are based on the assumption that any changes in human cognitive functioning are reflected in the human physiology, and have attracted increasing attention. Popular physiological measures used in cognitive load studies include brain wave, eye activity, respiration, heart rate, skin conductance, and speech, etc. Response-based behavioral features for cognitive load measurement are those that can be extracted from any user activity that is predominantly related to deliberate/voluntary task completion. This book focuses on the use of the following modalities for cognitive load measurement: eye, skin conductance, digital pen, speech, linguistic, mouse activity as well as fusions thereof.