Understanding aviation performance with eye tracking

Aviation has mastered the analysis of outcomes. Procedures are documented, deviations are tracked, and events are dissected with precision. 

Seeing the “why” behind outcomes 

What is less visible is the layer beneath the outcome: how attention shifted in the moment and how mental demand influenced performance. 

In 2024, IATA reported that manual handling and flight
control errors contributed to 39% of accidents. These events are rarely about knowledge gaps. More often, they reflect how scan discipline, prioritization, and workload interact under operational pressure. 

The next frontier for aviation performance is not more standards. It is better visibility into the precursors that shape those outcomes. 

This goes beyond traditional heat maps. Wearable eye tracking now enables real-time analysis of attention in operational environments. That insight supports not only individual performance and instruction, but also how training programs are designed and improved over time.

Making attention visible 

Objective visibility into attention changes the quality of performance discussions. 

Traditional debriefs focus on procedural outcomes measured against optimal standards. Instructors note deviations or reference concepts such as loss of situational awareness. What is not directly observed, however, is the pilot’s cognitive state at the moment of execution. 

Wearable eye tracking makes attention observable. Scan discipline becomes measurable rather than assumed. Verification becomes confirmable rather than inferred. 

In one applied study, eye tracking was used to observe air traffic controllers in a live control room. Instead of relying on post-event reports, teams replayed exactly how information was gathered and acted on.  The issue wasn’t training. It was a mode error in the interface. 

The fix was not retraining. It was redesign. 

When attention becomes measurable, design decisions become more grounded. 

Understanding workload in context 

Attention alone does not explain performance. Workload completes the picture. 

Cognitive load reflects the mental effort required at a given moment. In aviation, that demand fluctuates constantly. A stable phase can shift quickly into high-demand processing. 

How workload degradation unfolds: 

That progression is rarely captured in traditional reports. 

Eye-based indicators such as fixation behavior, scan patterns, and pupil response can signal when workload is approaching saturation. When layered with cognitive
analytics built on wearable systems — including platforms that integrate Tobii eye tracking data — organizations gain a clearer picture of when performance is beginning to shift. 

• Not seen 

• Seen but not processed 

• Seen and deprioritized 

On paper, these appear identical. In reality, they require different interventions. 

Captain Parker adds that objective workload measurement also has implications beyond the individual: 

Traditional evaluation captures outcomes. Attention and workload data capture precursors. 

Application across roles 

This visibility is not role-specific. 

In training, instructors gain a firmer basis for debrief. Interpretation gaps narrow and coaching becomes more consistent. 

In maintenance and inspection, leaders can examine whether interruptions or task transitions are driving overload rather than defaulting to retraining. 

In manufacturing, workflow design can be refined before small attention bottlenecks scale into systemic inefficiencies. 

Across domains, the value is not added oversight. It is better alignment between task design and human capability.

What this means for aviation teams today 

For aviation organizations focused on improving training effectiveness, operational safety, and system design, the opportunity is clear: make attention and workload visible as part of everyday evaluation. 

This is not a new layer of data for the sake of measurement. It is a way to understand how performance actually unfolds in real environments, and where it begins to break down. 

With that visibility, teams can: 

• Strengthen debriefs with objective insight into what operators actually saw and processed  

• Identify breakdowns in attention before they surface as performance errors  

• Improve system and interface design by uncovering sources of cognitive friction  

• Align training programs with how people perform under real-world conditions  

Aviation already measures what happened with rigor. The next step is understanding why it happened, and using that insight to improve performance before it falters.