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A systems approach to training aeronautical decision making: from identifying training needs to verifying training solutions

Published online by Cambridge University Press:  03 February 2016

W.-C. Li
Affiliation:
Graduate School of Psychology, National Defence University, Taipei, South Korea
D. Harris
Affiliation:
Department of Human Factors, School of Engineering Cranfield University, Bedford

Abstract

The human factors analysis and classification system (HFACS) was developed as an analytical framework for the investigation of the role of human error in aviation accidents. A total of 523 accidents in the Republic of China (ROC) Air Force between 1978 and 2002 were analysed using this framework. The results showed that in a great many cases, poor pilot decision making was implicated. Following a survey of flight instructors’ opinions, two of most promising mnemonic-based methods currently available to guide the decision making of pilots were identified (SHOR and DESIDE). These methods were developed into a short (four hour) aeronautical decision making training course. A total of 41 pilots from the Republic of China Tactical Training Wing then participated in a study to evaluate the effectiveness of this training course. Half of the participants received the short ADM training programme and half did not. Their decision making skill was evaluated in a series of emergency situations presented in a full-flight simulator. Furthermore, their decision making processes were examined in a series of pencil-and-paper based tests. The results clearly showed significant improvements in the quality of pilots’ situation assessment and risk management (underpinning processes in pilot decision making) although this was usually at the expense of speed of response. Pilots used the quicker to apply SHOR mnemonic in situations that which required a fast decision and the more comprehensive but slower to perform DESIDE method when there were fewer time pressures. The results do strongly suggest that ADM is trainable and the short programme devised was effective.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2007 

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References

1. Orasanu, J. and Connolly, T., The reinvention of decision making, 1993, Decision Making in Action: Models and Methods, Klein, G.A., Orasanu, J., Calderwood, R. and Zsambok, C.E. (Eds), pp 320, Ablex, Norwood, NJ, USA.Google Scholar
2. Branson, R.K., Rayner, G.T., Cox, J.L., Furman, J.P., King, F.J. and Hannum, W.H., Interservice procedures for instructional system development, 1975, Report N613.39-73-C-O150, Naval Education and Training Command, Florida, USA.Google Scholar
3. Patrick, J. Training, 2003, Principles and Practice of Aviation Psychology: Human Factors in Transportation, Tsang, P.S. and Vidulich, M.A. (Eds), pp 397434, Lawrence Erlbaum, New Jersey, USA.Google Scholar
4. Wiegmann, D.A. and Shappell, S.A., A Human Error Approach to Aviation Accident Analysis: The Human Factors Analysis and Classification System, 2003, Ashgate, Aldershot, UK.Google Scholar
5. Diehl, A., Human performance/system safety Issues in aircraft accident investigation and prevention, 1989, Fifth International Symposium on Aviation Psychology, pp 838847, Ohio State University, USA.Google Scholar
6. Feggetter, A.J., The development of an intelligent human factors data base as an aid for the investigation of aircraft accidents, 1991, Sixth International Symposium on Aviation Psychology, pp 324629, Ohio State University, USA.Google Scholar
7. Hollnagel, E., Cognitive Reliability and Error Analysis Method, 1998, Elsevier Science, Oxford, UK.Google Scholar
8. Hunter, D.R. and Baker, R.M., Reducing accidents among general aviation pilots through a national aviation safety program, 2000, Fourth Australian Aviation Psychology Symposium, Ashgate, Aldershot, UK.Google Scholar
9. Dekker, S., The Field Guide to Human Error Investigations, 2002, Ashgate, Aldershot, UK.Google Scholar
10. Reason, J., Human Error, 1990, Cam bridge University, New York, NY, USA.Google Scholar
11. Shappell, S.A. and Wiegmann, D.A., Applying reason: the human factors analysis and classification system (HFACS), Human Factors and Aerospace Safety, 2001, 1, (1), pp 5986.Google Scholar
12. Shappell, S.A. and Wiegmann, D.A., Report DOT/FAA/AM-03/4, 2003, Federal Aviation Administration, Washington, DC, USA.Google Scholar
13. Shappell, S.A. and Wiegmann, D.A., HFACS analysis of military and civilian aviation accidents: a North American comparison, 2004, pp 28, International Society of Air Safety Investigators, Queensland, Australia.Google Scholar
14. Wiegmann, D.A. and Shappell, S.A., Human factors analysis of postaccident data: applying theoretical taxonomies of human error, Int J of Aviation Psychology, 1997, 7, (1), pp 6781.Google Scholar
15. Wiegmann, D.A. and Shappell, S.A., Human error analysis of commerical aviation accidents: application of the human factors analysis and classification system, Aviation, Space, and Environmental Medicine, 2001, 72, (11), pp 10061016.Google Scholar
16. Wiegmann, D.A. and Shappell, S.A., Human error perspectives in aviation, Int J of Aviation Psychology, 2001, 11, (4), pp 341357.Google Scholar
17. Li, W.C., and Harris, D., HFACS analysis of ROC Air Force aviation accidents: reliability analysis and cross-cultural comparison, Int J of Applied Aviation Studies, 2005, 5, (1), pp 6581.Google Scholar
18. Jensen, R. and Hunter, D., General Aviation Aeronautical Decisionmaking, 2002, Federal Aviation Administration, Washington, DC, USA.Google Scholar
19. Li, W.C. and Harris, D., Pilot error and its relationship with higher organizational levels: HFACS analysis of 523 accidents, Aviation, Space and Environmental Medicine, 2006, 77, (10), pp 10561061.Google Scholar
20. Li, W.C, Harris, D. and Yu, C.S., Routes to failure: analysis of 41 civil aviation accidents from the Republic of China using the human factors analysis and classification system, Submitted to Accident Analysis and Prevention.Google Scholar
21. Buch, G., and Diehl, A., An investigation of the effectiveness of pilot judgment yraining, Human Factors, 1984, 26, (5), pp 557564.Google Scholar
22. Connolly, T.J., Blackwell, B.B. and Lester, L.F., A simulator-based approach to training in aeronautical decision making, Aviation, Space, and Environmental Medicine, 1989, 60, (1), pp 5052.Google Scholar
23. Diehl, A., A workshop on understanding and preventing aircrew error, 1991, Sixth International Symposium on Aviation Psychology, pp 2839, Ohio State University, USA.Google Scholar
24. Klein, G.A. and Woods, D.D., Conclusions: decision making in action, 1993, Decision Making in Action: Models and Methods, Klein, G.A., Orasanu, J., Calderwood, R. and Zsambok, C.E. (Eds), pp 404411, Ablex, Norwood, NJ, USA.Google Scholar
25. O’hare, D., Aeronautical decision making: metaphors, models and methods, 2003, Principles and Practice of Aviation Psychology: Human Factors in Transportation, Tsang, P.S. and Vidulich, M.A. (Eds), pp 201237, Lawrence Erlbaum, NJ, USA.Google Scholar
26. Prince, C. and Salas, E., Situation assessment for routine flight and decision making, Int J of Cognitive Ergonomics, 1997, 1, (4), pp 315324.Google Scholar
27. Jensen, R. and Benel, R., Judgment Evaluation and Instruction in Civil Pilot Training, 1977, Federal Aviation Administration, Washington, DC, USA.Google Scholar
29. Cohen, M.S., Three paradigm for viewing decision biases, 1993, Decision Making in Action: Models and Methods, Klein, G.A., Orasanu, J., Calderwood, R. and Zsambok, C.E. (Eds), pp 3650, Ablex, Norwood, NJ, USA.Google Scholar
29. Endsley, M.R., Measurement of situation awareness in dynamic systems, Human Factors, 1995, 37, (1), pp 6584.Google Scholar
30. Drillings, M. and Serfaty, D., Naturalistic decision making in command and control, 1997, Naturalistic Decision Making, Zsambok, C.E. and Klein, G. (Eds), pp 7180, Lawrence Erlbaum, Mahwah.Google Scholar
31. Klein, G.A., A recognition-primed decision (RPD) model of rapid decision making, 1993, Decision Making in Action: Models and Methods, Klein, G.A., Orasanu, J., Calderwood, R. and Zsambok, C.E. (Eds), pp 138147, Ablex, Norwood, NJ, USA.Google Scholar
32. Orasanu, J. and Fischer, U., Finding decisions in natural environments: the view from the cockpit, 1997, Naturalistic Decision Making, Zsambok, C.E. and Klein, G. (Eds), pp 343358, Lawrence Erlbaum, Mahwah.Google Scholar
33. Waag, W.L. and Bell, H.H., Situation assessment and decision making in skilled fighter pilots, 1997, Zsambok, C.E. and Klein, G. (Eds), Naturalistic Decision Making pp 247256, Lawrence Erlbaum, Mahwah.Google Scholar
34. Orasanu, J. Decision making in the cockpit, 1993, Cockpit Resource Management, Wiener, E.L., Kanki, B.G. and Helmreich, R.L. (Eds), pp 137172, Academic Press, San Diego, CA, USA.Google Scholar
35. Wohl, J.G., Force management decision requirements for air force tactical command and control, 1981, IEEE Transactions on Systems, Mans, and Cybernetics, SMC-11, pp 618639.Google Scholar
36. Maher, J., Beyond CRM to decisional heuristics: an airline generated model to examine accidents and incidents caused by crew errors in deciding, 1989, Fifth International Symposium on Aviation Psychology, pp 439444, Ohio State University, USA.Google Scholar
37. Oldaker, I., Pilot decision making — an alternative to judgement training, 1996, Technical Soaring, 20, (2), pp 3641.Google Scholar
38. Hormann, H.J., FOR-DEC: a perspective model for aeronautical decision making, 1995, Fuller, R., Johnston, R. and Mcdonald, N. (Eds), Human Factors in Aviation Operations, pp 1723, Ashgate Publishing, Aldershot, UK.Google Scholar
39. Murray, S.R., Deliberate decision making by aircraft pilots: a simple reminder to avoid decision making under panic, 1997, Int J of Aviation Psychology, 7, (1), pp 83100.Google Scholar
40. Janis, I.L. and Mann, L., Decision making: a psychological analysis of conflict, choice, and commitment, 1977, Free Press, New York, NY, USA.Google Scholar
41. Li, W.C. and Harris, D., Aeronautical decision-making mnemonics: instructor-pilots evaluation of five alternative methods, Aviation, Space and Environmental Medicine, 2005, 76, (12), pp 11561161.Google Scholar
42. Report No Advisory Circular 120-51A, 1993, Federal Aviation Administration, US Department of Transport, Washington, DC, USA.Google Scholar
43. Noble, D., A model to support development of situation assessment aids, 1993, Klein, G.A., Orasanu, J., Calderwood, R. and Zsambok, C.E. (Eds), Decision Making in Action: Models and Methods, pp 287305), Ablex, Norwood, NJ, USA.Google Scholar
44. Endsley, M.R. and Bolstad, C.A., Individual differences in pilot situation awareness, International J of Aviation Psychology, 1994, 4, (3), pp 241264.Google Scholar
45. Fischer, U., Orasanu, J. and Wich, M., Expert pilots’ perceptions of problem situations, 1995, Eighth International Symposium on Aviation Psychology, pp 777782, Ohio State University, USA.Google Scholar
46. Jensen, R.S., Guilke, J. and Tigner, R., Understanding expert aviator judgment, 1997, Decision Making Under Stress: Emerging Themes and Applications, Flin, R., Salas, E., Strub, M. and Martin, L. (Eds), (pp 233242, Ashgate, Aldershot, UK.Google Scholar
47. Orasanu, J., Davison, J. and Fischer, U., The role of risk in aviation decision making: how pilots perceive and manage flight risks, 2001, Proceedings of the Human Factors and Ergonomics Society 45th Annual Meeting, pp 5862, Santa Monica, USA.Google Scholar
48. Payne, J.W., Bettman, J.R. and Johnson, E.J., Adaptive strategy selection in decision-making, J of Experimental Psychology: Learning, Memory and Cognition, 1988, 14, pp 534552.Google Scholar
49. Kaempf, G.L. and Orasanu, J., Current and future applications of naturalistic decision making, 1997, Naturalistic Decision Making, Zsambok, C.E. and Klein, G. (Eds), pp 8190, Lawrence Erlbaum, Mahwah.Google Scholar
50. Patrick, J., Training: Research and Practice, 1992, Academic Press, London, UK.Google Scholar
51. Kirkpatrick, D.L., Evaluation of training, 1976, Training and Development Handbook, Craig, R.L. and Bittel, L.R. (Eds), pp 18.118.27, McGraw Hill, New York, NY, USA.Google Scholar