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Experienced mental workload, perception of usability, their interaction and impact on task performance.
Luca Longo1,2
1School of Computing, College of health and sciences, Dublin Institute of Technology, Dublin, Ireland.
Plos One
|August 2, 2018
Summary
This study reveals that usability and mental workload are distinct factors that, when combined, significantly enhance the prediction of human performance in interactive systems. Understanding this relationship is key for better system design.
Area of Science:
- Human-Computer Interaction (HCI)
- Cognitive Psychology
- Human Factors Engineering
Background:
- Existing usability assessment methods often overlook user characteristics, context, and task specifics.
- Human Mental Workload is a critical factor in predicting human performance, yet its relationship with usability remains underexplored.
Purpose of the Study:
- To investigate the relationship between usability and mental workload.
- To examine the combined impact of usability and mental workload on human performance in information-seeking tasks.
Main Methods:
- A user study involving participants performing information-seeking tasks on three popular websites.
- Correlation analysis to explore the relationship between usability and mental workload across tasks, users, and performance levels.
- Supervised Machine Learning techniques to build predictive models of task performance.
Main Results:
- Usability and mental workload were found to be non-overlapping constructs.
- Both constructs significantly contribute to predicting human performance.
Conclusions:
- Usability and mental workload are distinct but complementary factors in HCI.
- Integrating assessments of both usability and mental workload can substantially improve the prediction of user performance.
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