Using Past and Present Indicators of Human Workload to Explain Variance in Human Performance

Area of Science:

• Cognitive psychology
• Human-computer interaction
• Neuroscience

Background:

• Cognitive workload is theorized to affect performance via resource competition.
• Empirical evidence directly linking intra-individual workload fluctuations to performance changes is limited.

Purpose of the Study:

• To investigate the real-time relationship between cognitive workload and performance within individuals.
• To determine if workload fluctuations independent of task demands predict performance variations.

Main Methods:

• A multiple object-tracking task was used to collect performance data.
• Real-time cognitive workload was objectively measured using a modified detection response task.
• A multi-level Bayesian model controlled for task difficulty and prior performance.

Main Results:

• Higher cognitive workload, both during and preceding a trial, predicted poorer performance.
• This negative workload-performance relationship was consistent across participants.
• Workload fluctuations independent of task demands significantly explained performance variations.

Conclusions:

• Cognitive workload has a direct and pervasive influence on human performance.
• Findings support the development of adaptive systems to mitigate performance decrements in real-time.
• Understanding workload dynamics is crucial for optimizing human performance in various contexts.