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Cannavò, Rosario; Conti, Daniela; Di Nuovo, Alessandro (2015)
Publisher: Elsevier
Journal: Applied Computing and Informatics
Languages: English
Types: Article
Subjects: Attention assessment, Software validation, Information technology, T58.5-58.64, Aviation pilot selection and training, Computer assisted performance evaluation
Attention has a key role in the flight performance of the aviation pilot, therefore it is among human factors commonly used in the evaluation of candidate pilots. In this context, our work aims to define a single integrated instrument able to measure all the distinctive attention factors and to assist the assessment and the training of aviation pilots.\ud \ud In this paper, we present a battery of seven computerized tests, encompassing classical and innovative solutions inspired by the literature in the field, for the integrated measurement of the attention factors of aviation pilots. The computer software is validated by means of an experimental trial with 50 experienced aviation pilots and 50 untrained people as controls. Statistical analyses confirm that the instrument can effectively classify aviation pilots, and identify a subset of distinctive attention factors that could be used for monitoring their duty.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] A. Baddeley, Working memory, Science 255 (1992) 556-559.
    • [2] D. Bartram, Validation of the MICROPAT Battery, Int. J. Select. Assess. 3 (2) (1995) 84-95.
    • [3] L.C. Boer, Taskomat: evaluation of a computerized test battery, Int. J. Select. Assess. 3 (2) (1995) 105-114.
    • [4] T.R. Carretta, Pilot candidate selection method, Aviat. Psychol. Appl. Human Fact. 1 (1) (2011) 3-8.
    • [5] K. Conzelmann, D. Keye, Which aspects of a semistructured interview, besides cognitive ability tests, contribute incrementally to predicting the training success of air traffic controller trainees?, Int J. Select. Assess. 22 (3) (2014) 240-252.
    • [6] A.G. Di Nuovo, R.B. Cannavo, S. Di Nuovo, An agent-based infrastructure for monitoring aviation pilot's situation awareness, in: IEEE Symposium on Intelligent Agent (IA), IEEE, 2011, pp. 1-7.
    • [7] A.G. Di Nuovo, R.B. Cannavo` , S. Di Nuovo, An intelligent infrastructure for in-flight situation awareness of aviation pilots, in: Foundations of Augmented Cognition. Directing the Future of Adaptive Systems, Springer Berlin Heidelberg, 2011, pp. 598-607.
    • [8] M.R. Endsley, Theoretical underpinnings of situation awareness: a critical review, Situation Awareness Anal. Meas. (2000) 3-32
    • [9] M.R. Endsley, D.J. Garland, Pilot situation awareness training in general aviation, in: H. Factors, E. Society (Eds.), Human Factors and Ergonomics Society Annual Meeting Proceedings, Proceedings 2 - Training, 2000, pp. pp. 357-360.
    • [10] D. Gopher, M. Well, T. Bareket, Transfer of skill from a computer game trainer to flight, Hum. Factors: J. Hum. Factors Ergon. Soc. 36 (1994) 387-405.
    • [11] R.E. King, T.R. Carretta, P. Retzlaff, E. Barto, M.J. Ree, M.S. Teachout, Standard cognitive psychological tests predict military pilot training outcomes, Aviat. Psychol. Appl. Human Factors 3 (1) (2013) 28.
    • [12] E.I. Knudsen, Fundamental components of attention, Annu. Rev. Neurosci. 30 (2007) 57-78.
    • [13] M.W Matlin, Cognition, eighth ed., Wiley, 2012, p. 640.
    • [14] A.T. Schriver, D.G. Morrow, C.D. Wickens, D.A. Talleur, Expertise differences in attentional strategies related to pilot decision making, Hum. Factors: J. Hum. Factors Ergon. Soc. 50 (6) (2008) 864-878.
    • [15] H. Strasburger, I. Rentschler, M. Juttner, Peripheral vision and pattern recognition: a review, J. Vision 11 (2011) 13.
    • [16] K. Sulistyawati, Y.P. Chui, Y.M. Tham, Y.K. Wee, Evaluation of process tracing technique to assess pilot situation awareness in air combat missions, in: Proceedings of the 7th International Conference on Engineering Psychology and Cognitive Ergonomics, Springer-Verlag, Berlin, Heidelberg, 2007, pp. 824-833.
    • [17] E. Toulouse, H. Pieron, Prueba perceptiva y de atenci o´n, TEA Ediciones SA, Madrid, 1986.
    • [18] C.D. Wickens, J.S. McCarley, A.L. Alexander, L.C. Thomas, M. Ambinder, S. Zheng, Attention-situation awareness (A-SA) model of pilot error, in: David C. Foyle, Becky L. Hooey (Eds.), Human Performance Modeling in Aviation, 2008, pp. 213-239.
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