A multi-layered architecture for analysis of non-technical-skills in critical situations
In most technical domains, it is a worker’s technical expertise which determines how they assess and respond to situations. However, their performance is also influenced by meta-cognitive abilities, such as situation awareness and decision-making or personal resources skills such as stress and fatigue management. These expertise are commonly described as non-technical skills. Studies have shown that while these skills almost always complement technical activity, they are most influential during critical situations, where usual technical procedures cannot be successfully applied. The MacCoy-Critical project will Intelligent Learning Environment, able to diagnose a learner’s non-technical skills in critical situations inside of a virtual environment, in the domains of driving and delivery handling by midwives. This diagnosis should in turn allow the architecture to generate adapted immediate feedback, as well as providing new learning critical situations adapted to the learner’s skills. As part of the project, this article focuses on the challenges raised by the diagnosis of non-technical skills inside a virtual environment. We propose a general architecture which aims to extract information concerning the influence of non-technical skills from learners’ activity, assuming the technical skills are already acquired. This article presents the conceptual un-derpinnings behind the proposed architecture.
Artificial Intelligence In Education https://hal.archives-ouvertes.fr/hal-01517152 Artificial Intelligence In Education, Jun 2017, Wuhan, China. 2017, AIED 2017ARRAY(0x7fe6a73905e8) 2017-06-29