Mental workload and cognitive task automaticity: an evaluation of subjective and time estimation metrics

Area of Science:

• Human-Computer Interaction
• Cognitive Psychology
• Systems Engineering

Background:

• Evaluating mental workload is crucial for effective system design and analysis.
• Understanding workload is key to optimizing human-system interactions.
• Previous research highlights the need for robust mental workload assessment methods.

Purpose of the Study:

• To investigate the structure and assessment of mental workload.
• To compare subjective assessment and time estimation as workload measures.
• To examine workload in decision and monitoring tasks under varying conditions.

Main Methods:

• Participants performed customer assignment tasks in manual (decision) and automatic (monitoring) modes.
• Time pressure was manipulated (fast vs. slow conditions).
• Subjective workload and time estimation intervals were recorded.

Main Results:

• Mental workload demonstrated a multi-dimensional structure.
• Subjective workload was more influenced by participatory mode (manual vs. automatic) than task speed.
• Time estimation was sensitive to perceptual/cognitive demands, not automated responses.

Conclusions:

• Subjective workload assessment is multi-step and influenced by user involvement.
• Time estimation can effectively gauge cognitive load in complex tasks.
• Findings inform the design of systems that better manage user mental workload.