Results

The results from the study by Ling & Hua (2009) quantitatively indicated that symbolic representation is more effective than alphanumeric encoding at alerting operators of changes to specific data-block (DB) fields. Furthermore, the more complex the DB (e.g. nine-field), the longer the exposure time required to perceive the information presented. Overall, the study demonstrated that training was effective up to a certain complexity and thereafter, salient visual features was advisable in improving operator performance.

Table 1: Detection Accuracy (%) for 6F-DB & 9F-DB
DB Type	6F-DB			9F-DB
Exposure Time (seconds)	0.5	1	3	0.5	1	3
Mean (%)	77	87.67	90.67	72.33	79	86.83

Mean derived from the sum of % for six training sessions divided by six.
Table 1 exhibits the relationship between the detection accuracy and exposure time for both DB types examined.
The difference between the exposure times of 3s and 1s is higher in the nine-field DB than six-field DB ; this suggests that the higher complexity of the 9F-DB required a longer exposure time for participants to detect changes.

Table 2: Task Performance Accuracy (%) Comparison for 6F-DB & 9F-DB
DB Type		6F-DB			9F-DB
Exposure Time (seconds)		0.5	1	3	0.5	1	3
Alert Sign	P	85	90	91	96	97	100
Call Sign	P	95	96	95	100	100	100
Planned Altitude	A	62	80	82	75	79	86
Vertical Status	P	95	93	96	100	84	95
Flight Speed	A	48	74	82	40	64	76
Heading Direction	A	48	74	82	34	54	78
Loss Separation	P				85	89	99
Reported Altitude	P				100	100	100
Aircraft Type	A				24	32	41
A denotes Alphanumeric field, P denotes Pattern field

Table 2 exhibits the relationship between alphanumeric versus pattern field task performance accuracy and exposure time for both DB types examined.
The alphanumeric fields had lower detection accuracies and bigger differences between the three exposure times than the pattern fields.
Overall performance accuracies of over 90% suggest that participants could process the salient visual features, that were used to encode changes in the pattern field, faster than in the alphanumeric field.

Methods

Research approach

The change detection task is one of the core cognitive responsibilities of air traffic controllers. The approach of this study was to determine the influence that the complexity of Datablock (DB) appearance and design had on the change detection task learning process and performance. The study focused on three areas:

Six-field versus nine-field DB Types
Pattern versus Alphanumeric DB Fields

Sample

10, male, University of Oklahoma students, aged 18-25 years, with minimum vision of 20/20 and normal colour vision.

Independent Variables

The variables for this study were:

Each of the six training sessions,
Three exposure times (0.5s, 1s, 3s), and,
The type of DB (six-field/nine-field)

Procedure

Participants were taught and examined with six-field (6F-DB) and nine-field (9F-DB) DBs.
The experiments were carried out on an Optiplex GX620 Dell computer and MATLAB was used to present the visual stimuli and record participant data.
Participants were shown DB samples for durations of 3s, 1s, or 0.5s, and then tested on whether any change was detected and in which of the fields did the change occur. The time between the presentation of the sample and the change/no change choice was recorded as the reaction time.

Data analysis

The MATLAB programme kept tabs on the accuracy score of each session
An analysis of variance (ANOVA) was carried out on the accuracy data collected, using the independent variables aforementioned.

Generalization potential

Although the participants were students, the study effectively demonstrates the benefits of time-on-task towards better performance.
The study is also applicable to real-world ATC situations because of the design of the experiments that mimicked the complexity of the data-block fields and the nature of aircraft movements across the controller’s radar screen.
The study further demonstrates how future DBs could take into consideration the cognitive ergonomics factors (symbols/colours) to improve change detection task performance.

References

Ling, C., & Hua, L. (2009) Effect of Datablock Complexity and Exposure Time on Performance of Change Detection Task. In D. Harris, (Ed.), Engineering Psychology and Cognitive Ergonomics (pp. 600-605). Oklahoma, USA: Springer Verlag.

Want to know more?

The Impact of Multi-layered Data-blocks on Controller Performance: An MIT Paper by Cummings, M.L., Tsonis, C.G., & Rader, A.A. (2007) that similarly analyses the influences of DB design complexity
Flight Tracking Strips and Data-Blocks: More information explaining how flight tracking strips and data-blocks are used in today’s ATC