Application of collaborative serious gaming for the elicitation of expert knowledge and towards creating Situation Awareness in the field of infrastructure resilience

Author(s):  
Rebecca Wehrle ◽  
Marcus Wiens ◽  
Frank Schultmann
1997 ◽  
Vol 25 (4) ◽  
pp. 373-407 ◽  
Author(s):  
Charles W. Gerson

The majority of the literature on situation awareness is focused on its perceptual definition and modeling. In contrast, this presentation focuses on the importance of training simulation systems in increasing the potential for good situation awareness. Situation awareness is defined as an evaluative product based on expert performance criteria. A conventional information processing model is used to represent situation awareness as a generalized concept and modified for specific applications. Three salient factors affecting quality situation awareness are discussed: 1) high fidelity procedural training, 2) expert knowledge and experience, and 3) the strong indeterminates of attitude and emotional state. Additional issues are discussed, including: a developmental verses a gestalt framework for the perceptual process; information processing capacities; automaticity skills; traditional verses transactional training; the novice/expert relationship; expert and novice decision making; training device fidelity and ethnographic concerns; the dimension of unpredictability; inherent psychological abilities; and workload.


2021 ◽  
Author(s):  
Amy Irwin ◽  
Ilinca-Ruxandra Tone ◽  
Nejc Sedlar

Objective: Non-technical skills, the social and cognitive skills thought necessary for safe and effective working, have been studied within the farming context over the past six years. However, these skills are not yet taught as part of a safety curriculum for farmers, due, in part, to a lack of defined framework and assessment system. The current paper describes the development of the FLINTS behavioural marker system for discussion, observation, evaluation and feedback on non-technical skills for farmers.Method: The development of the behavioural marker system proceeded through three key stages. First, the current research knowledge on non-technical skills was synthesised to compile a list of non-technical skill categories and elements. Second, a series of discussion groups with subject matter experts was conducted to develop behavioural markers for each element. Lastly, refinement and review of the system was undertaken by academics and experts.Results: The FLINTS taxonomy containing five non-technical skill categories and 16 elements was produced. The non-technical skill categories comprised situation awareness, teamwork & communication, leadership, task management and decision-making each with specific elements and behavioural markers.Conclusion: FLINTS represents the first behavioural marker system for farmer non-technical skills, constructed through expert knowledge and advice via discussion and review groups, combined with underpinning research findings. This represents the first step towards the development of non-technical training and assessment for farmers. The FLINTS system was produced as a handbook and is freely available to all potential users (https://research.abdn.ac.uk/nts-farming/flints/).


2004 ◽  
Author(s):  
Parsa Mirhaji ◽  
S. Lillibridge ◽  
R. Richesson ◽  
J. Zhang ◽  
J. Smith

2004 ◽  
Author(s):  
Cheryl A. Bolstad ◽  
◽  
Cleotilde Gonzalez ◽  
John Graham

2014 ◽  
Author(s):  
Dan Chiappe ◽  
Thomas Strybel ◽  
Kim-Phuong Vu ◽  
Lindsay Sturre

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