An Approach for the Analysis of Perceptual and Gestural Performance During Critical Situations

  • Yannick Bourrier
  • Francis Jambon
  • Catherine Garbay
  • Vanda Luengo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10474)

Abstract

Our objective is the design of a Virtual Learning Environment to train a person performing a work activity, to acquire non-technical skills during the experience of a critical situation. While the person’s performance level is due to carefully acquired technical skills, how it is maintained in front of criticality depends on non-technical skills, such as decision-making, situation awareness or stress management. Following previous break downs of the domains ill-defined aspects, we focus in this paper on the design of an approach to evaluate the variation of a learner’s performance in front of learning situations showing varying degrees of criticality, in the domains of driving and midwifery.

Keywords

Ill-defined domains Non-technical skills Critical situations Neural networks 

References

  1. 1.
    Fletcher, G., Flin, R., McGeorge, P., Glavin, R., Maran, N., Patey, R.: Anaesthetists’ non-technical skills (ANTS): evaluation of a behavioural marker system. Br. J. Anaesth. 90(5), 580–588 (2003)CrossRefGoogle Scholar
  2. 2.
    Bourrier, Y., Jambon, F., Garbay, C., Luengo, V.: An approach to the TEL teaching of non-technical skills from the perspective of an ill-defined problem. In: Verbert, K., Sharples, M., Klobučar, T. (eds.) EC-TEL 2016. LNCS, vol. 9891, pp. 555–558. Springer, Cham (2016). doi:10.1007/978-3-319-45153-4_62 CrossRefGoogle Scholar
  3. 3.
    Lynch, C., Ashley, K., Aleven, V., Pinkwart, N.: Defining Ill-defined domains; a litera- ture survey. In: Proceedings of the Intelligent Tutoring Systems for Ill-Defined Domains Workshop, ITS 2006, pp. 1–10 (2006)Google Scholar
  4. 4.
    Fournier-Viger, P., Nkambou, R., Nguifo, E.M.: Building intelligent tutoring systems for ill-defined domains. In: Nkambou, R., Bourdeau, J., Mizoguchi, R. (eds.) Advances in Intelligent Tutoring Systems. Studies in Computational Intelligence, vol. 308, pp. 81–101. Springer, Heidelberg (2010). doi:10.1007/978-3-642-14363-2_5 CrossRefGoogle Scholar
  5. 5.
    Crundall, D., Chapman, P., Trawley, S., Collins, L., Van Loon, E., Andrews, B., Underwood, G.: Some hazards are more attractive than others: drivers of varying experience respond differently to different types of hazard. Accid. Anal. Prev. 45, 600–609 (2012)CrossRefGoogle Scholar
  6. 6.
    Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Trans. Knowl. Data Eng. 22(10), 1345–1359 (2010)CrossRefGoogle Scholar
  7. 7.
    Nair, V., Hinton, G.E.: Rectified linear units improve restricted boltzmann machines. In: Proceedings of the 27th International Conference on Machine Learning (ICML 2010), pp. 807–814 (2010)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Yannick Bourrier
    • 1
    • 2
  • Francis Jambon
    • 1
  • Catherine Garbay
    • 1
  • Vanda Luengo
    • 2
  1. 1.Univ. Grenoble Alpes, LIGGrenobleFrance
  2. 2.Univ. Pierre et Marie Curie, LIP6ParisFrance

Personalised recommendations