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

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

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

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

Situation awareness Perceive, comprehend, predict

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

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)

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

Trainees versus qualified controllers

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

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

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

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

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

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

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

CONTACT DETAILS PROF. FIONA DONALD DEPARTMENT OF PSYCHOLOGY UNIV. OF THE WITWATERSRAND, PRIVATE BAG 3, WITS, 2050 TEL: +27 11 717 4507 / 4503 EMAIL: Fiona.Donald@wits.ac.za