## 3 Data Analysis
### Two-Factor ANOVA on Controller Situational Awareness Related Indicators
#### 3.2.1 Analysis of Controllers' Eye Movement Characteristics
The impact of fatigue conditions on the TFT parameter was significant. The data indicate that when the tiredness levels of distant tower controllers varied, both seasoned and novice controllers showed a decline in fixation time. For both tiredness state (F = 19.856, \(p\) = 0.00) and controller qualifications (F = 38.992, \(p\) = 0.00), a two-way ANOVA showed that there were significant main effects for average fixation times (AFT). The two factors did not significantly interact for AFT (F = 0.006, \(p\) = 0.941). The qualities of the controller have a considerable impact on AFT. The statistics illustrate that both experienced and trainee controllers exhibited a declining trend in average fixation time as their tiredness levels varied. A two-way ANOVA on total saccade times (TST) revealed a significant main effect for the tiredness state (F = 10.468, \(p\) = 0.004), although the impact of qualifications was not significant (F = 1.649, \(p\) = 0.241). The tiredness state and qualifications for TST did not significantly interact (F = 0.657, \(p\) = 0.427). The condition of weariness markedly affected the TST parameter. Data indicate that while the tiredness levels of distant tower controllers fluctuated, both seasoned and novice controllers exhibited a decline in saccade length. The examination of average saccade count (ASC) revealed that neither tiredness state (F = 2.192, \(p\) = 0.154) nor qualifications (F = 0.906, \(p\) = 0.353) significantly influenced the ASC parameter. We detected a significant interaction between tiredness state and controller qualifications (F = 4.690, \(p\) = 0.043). The interplay between fatigue levels and qualifications significantly influenced ASC parameters. The data indicate that while the tiredness levels of distant tower controllers varied, the average saccade counts of experienced controllers decreased, whereas those of trainee controllers escalated. A two-way ANOVA revealed a significant main impact of the tiredness state on the average pupil diameter (APD) (F = 142.717, \(p\) < 0.00), although the influence of qualifications was not significant (F = 0.867, \(p\) = 0.363). We observed no significant interaction between tiredness state and qualifications for APD (F = 0.841, \(p\) = 0.370). The impact of controller qualifications on the APD parameter was significant. The data indicate that while the tiredness levels of distant tower controllers fluctuated, both seasoned and novice controllers had a diminishing trend in average pupil diameter. The study of each eye movement metric may be examined in conjunction with the aforementioned data and post-experimental interviews. Under typical circumstances, the frequency of blinking correlates with psychological states. Blink rates often increase under stressful situations and decrease while concentrating on a job. Figure 3a demonstrates that experienced controllers typically displayed greater blink counts than trainee controllers in both fatigued and non-fatigued conditions, possibly due to trainee controllers allocating more attention to their tasks, leading to a reduction in blinks relative to their experienced peers. Fixation points denote the spatial places that controllers concentrate on during a designated time period, with the quantity of fixation points correlating to the amount of information requiring processing. The quantity of fixation points rises when controllers engage with regions of interest [30]. Figure 3b illustrates that experienced controllers exhibited marginally fewer fixation locations compared to trainee controllers. The superior experience of seasoned controllers, who may promptly concentrate on pertinent information upon receiving directives, may account for this gap, while trainee controllers may process information at a slower pace, leading to an increased number of fixation points.