Measuring Cognitive Load Using Linguistic Features: Implications for Usability Evaluation and Adaptive Interaction Design

Abstract

An intelligent adaptable system, aware of a user’s experienced cognitive load, may help improve performance in complex, time-critical situations by dynamically deploying more appropriate output strategies to reduce cognitive load. However, measuring a user’s cognitive load robustly, in real-time is not a trivial task. Many research studies have attempted to assess users’ cognitive load using different measurements, but these are often unsuitable for deployment in real-life applications due to high intrusiveness. Relatively novel linguistic behavioral features as potential indices of user’s cognitive load is proposed. These features may be collected implicitly and nonintrusively supporting real-time assessment of users’ cognitive load and accordingly allowing adaptive usability evaluation and interaction. Results from a laboratory experiment show significantly different linguistic patterns under different task complexities and cognitive load levels. Implications of the research for adaptive interaction are also discussed, that is, how the cognitive load measurement-based approach could be used for user interface evaluation and interaction design improvement.

Additional information

Notes on contributors

M. Asif Khawaja

M. Asif Khawaja has a PhD in Computer Science from University of New South Wales (UNSW), Sydney, Australia. He was working as a researcher in human–computer interaction at NICTA in Sydney. He specializes in human–computer interaction, cognitive load assessment, trust assessment, behavioral analysis, and software engineering. Currently he is working in the software industry as a technical architect.

Fang Chen

Fang Chen is research group manager at NICTA and holds Conjoint Professor and Honorary Associate positions with UNSW and University of Sydney. Her research interests are human–computer interaction, especially in multimodal systems, cognitive load modelling, speech and language processing, and user interface design. She has more than 100 refereed publications and 25 patents.

Nadine Marcus

Nadine Marcus is a senior lecturer in human–computer interaction, School of Computer Science and Engineering, UNSW. Inspired by cognitive load theory, her research focuses on design of multimedia educational technology to improve learning and interface design, including animation and transient information effects and speech-based measures of mental load.