1. Visual analysis as a predictor of performance in air traffic control (ATC) trainees.
Prof Fiona Donald (University of the Witwatersrand) Dr Craig Donald (Leaderware, Edith Cowan University, Australia) Ms Megan Gould (Former Master’s student) ESSA2017, ASHFAS2017, ErgoAfrica2017

2. SAFETY ATC keeps aircraft separated in the air & on the ground

3. VISUAL ANALYSIS
‘... the active, goal-directed and effortful scrutiny of visual scenes in order to identify differences, discrepancies and patterns in objects, behaviours and events’ (Donald, 2011).
Looking does not guarantee ‘seeing,’ or understanding

4. Relevance of visual analysis?
Increasingly able to ‘see’ things we can’t see with eyes
ATCO: Large portion of job uses visual attention
Selection & training

6. Situation awareness Perceive, comprehend, predict

7. AIM
Does visual analysis predict success in trainees and air traffic controllers?
Trainees (54 on Core Content course)
Qualified controllers (25 from 4 airports)

8. SAMPLE PROFILE Voluntary participation
Trainees a pre-screened sample (assessed after selection process) – reduces strength of results
Successful vs Not successful trainees (45 vs 9 on Core Content course because this was the largest sample)

9. VISUAL ANALYSIS MEASURES - LEADERWARE
ScreenX
4, 6 and 8s detection
Reaction time
False alarms
SAMAE
Scanning - Division of Attention
4 and 15s detection 4s detection
Reaction time Reaction time
False alarms False alarms

10. Trainees versus qualified controllers

11. CORE CONTENT COURSE: COMPLETED VS WITHDREW ScreenX 8s, Scanning 4, 15s & RT significant

12. VISUAL ANALYSIS AND PERFORMANCE ON CORE CONTENT COURSE
3 out of 13 subjects had no significant correlations with visual analysis:
ATC Theory & Procedures Section A
Search & Rescue
Safety Management & Human Factors

13. CORE CONTENT COURSE: SUMMARY OF VISUAL ANALYSIS AND COURSE RESULTS
VA measure
ICAO
ATC Th & Proc B
Aircraft ID & perf.
Prin-ciples of flight
Meteor-ology
Avionics
Instru-ments & app-roach
ATM/ CNS
Aviation legisla-tion
Aero. Mess-aging
Ave
Screen4s
Screen6s
Screen8s
Scan4s
Scan RT
ScanFA
Div4s
DivRT
DivFA
KEY:
.2 to .29
. 3 to .39
.4 to .49
.5 to .59

14. CORE CONTENT COURSE: SUMMARY OF VISUAL ANALYSIS AND COURSE RESULTS
VA measure
ICAO
ATC Th & Proc B
Aircraft ID & perf.
Prin-ciples of flight
Meteor-ology
Avionics
Instru-ments & appr.
ATM/ CNS
Aviation legisla-tion
Aero. Mess-aging
Ave
Screen4s
.34
.30
Screen6s
.31
.37
.38
.35
.29
.38**
.39**
.36
Screen8s
.33
.32
.43**
.37**
.40**
Scan4s
.41
0.32
0.44*
0.51
Scan RT
-.37**
-0.36
-0.35
-0.49
-0.46
ScanFA
-0.31
Div4s
.48**
DivRT
-.35
-0.32
DivFA
-.39**
0.3
KEY:
.2 to .29
.3 to .39
.4 to .49
.5 to .59
All significant

15. MAIN FINDINGS SUMMARY
Withdrawals performed consistently worse on Visual Analysis exercises (Core Content course)
Visual analysis exercises together predict 10 subjects and average (Core Content course)
Works for all language groups, but stronger predictions for English and Afrikaans first language speakers
Possibilities of combining measures and exercises – better prediction
Controllers get better visual analysis scores than trainees

16. THE WAY FORWARD Performance measures for qualified controllers
Results from subsequent courses
Additional assessments of trainees & current controllers to
build more confidence
Incorporate visual analysis in selection?
Validation of other instruments used in the past
Impact of other competencies – also relative to visual analysis

17. ACKNOWLEDGEMENTS Thanks to
The ANSP for allowing and facilitating the study
Managers at airports
Everyone who participated and assisted
THANK YOU

18. CONTACT DETAILS
PROF. FIONA DONALD DEPARTMENT OF PSYCHOLOGY UNIV. OF THE WITWATERSRAND, PRIVATE BAG 3, WITS, 2050 TEL: /