Workload Assessment: How to Diagnose Workload Issues and Enhance Performance

Workload assessment can be important wherever people perform under high levels of task demands, such as multi-tasking and time pressure. This accessible guide sets out a comprehensive, systematic approach to evaluating workload measures and to designing studies to maximize the value obtained from the measures. No single volume in the current literature deals exclusively with workload assessments. In this book, you’ll find

  • Basic concepts in both workload theory and applications in a variety of domains
  • A comprehensive survey of leading self-report, performance-based, and psychophysiological measures
  • A checklist to ensure assessment quality
  • Two detailed workload examples to illustrate practical applications.

Workload Assessment has been written to be accessible to a wide audience and generally requires little specific background knowledge. This book will help guide researchers toward best practices in the use of workload measures to test theory-driven hypotheses in studies of cognitive psychology and cognitive neuroscience. Practitioners in domains such as surface transportation, aerospace, industrial ergonomics, the military, cybersecurity, system design, education, and health care will be able to choose the most appropriate workload measures for applied problems, and use workload data in efforts to mitigate performance issues. Workload Assessment is essential reading for graduate students in human factors and applied cognitive psychology, as well as supplementary reading for undergraduate students in these topics.

Workload Assessment is an excellent example of scientific scholarship at its very best. The authors show a firm grasp of the literature and effectively encapsulate that literature, which spans decades. Abundant references point readers to the key papers and to publications that go into depth about particular topics and applications. This is commendable.
- Robert R. Hoffman, Research Scientist, Institute for Human and Machine Cognition