Investigating the Effects of Desktop Computer Simulation Training on Situation Awareness (SA) and Adaptive Decision-Making Skills

2009 ◽  
Author(s):  
Vanessa Johnson ◽  
Robert J. Pleban ◽  
Jennifer S. Tucker
Keyword(s):  
Decision Making ◽  
Computer Simulation ◽  
Situation Awareness ◽  
Simulation Training ◽  
Desktop Computer ◽  
Adaptive Decision Making

Training Situation Awareness and Adaptive Decision-Making Skills Using a Desktop Computer Simulation

2009 ◽  
Author(s):  
Robert J. Pleban ◽  
Jennifer S. Tucker ◽  
Vanessa Johnson Katie /Gunther ◽  
Thomas R. Graves
Keyword(s):  
Decision Making ◽  
Computer Simulation ◽  
Situation Awareness ◽  
Desktop Computer ◽  
Adaptive Decision Making

Training Situation Awareness and Adaptive Decision-Making Skills Using a Desktop Computer Simulation

2009 ◽  
Author(s):  
Robert J. Pleban ◽  
Jennifer S. Tucker ◽  
Vanessa Johnson ◽  
Katie Gunther ◽  
Thomas R. Graves
Keyword(s):  
Decision Making ◽  
Computer Simulation ◽  
Situation Awareness ◽  
Desktop Computer ◽  
Adaptive Decision Making

scholarly journals Short 2-H in Situ Trauma Team Simulation Training Effectively Improves Non-Technical Skills of Hospital Trauma Teams

2018 ◽  
Vol 108 (2) ◽  
pp. 117-123 ◽  
Author(s):  
E. Rosqvist ◽  
S. Lauritsalo ◽  
J. Paloneva
Keyword(s):  
Decision Making ◽  
Situation Awareness ◽  
Simulation Training ◽  
Trauma Team ◽  
Technical Skills ◽  
Coping With Stress ◽  
Training Course ◽  
Resuscitation Guidelines ◽  
Trauma Teams

Background and Aims: As conducting the regular trauma team simulation training is expensive and time-consuming, its effects must be explored. The objective was to evaluate the efficacy of a structured 2-h in situ multiprofessional trauma team simulation training course on non-technical skills. Materials and Methods: This prospective study comprised 90 trauma teams with 430 participants. The structured, 2-h course consisted of an introductory lecture and two different simulations with debriefings. Data were collected using a pre–post self-assessment questionnaire. In addition, the expert raters used the T-NOTECHS scale. Results: The following non-technical skills improved significantly among both medical doctors and nurses: knowledge of the trauma resuscitation guidelines, problem identification, decision making, situation awareness/coping with stress, communication and interaction, time management, being under authority, and confidence in one’s role in a team. The teams improved significantly in leadership, cooperation and resource management, communication and interaction, assessment and decision making, and situation awareness/coping with stress. Conclusion: A short, structured 2-h in situ trauma team simulation training course is effective in improving non-technical skills.

Models of decision support in socio-cyber-physical systems

2019 ◽  
pp. 55-70 ◽  
Author(s):  
A. V. Smirnov ◽  
T. V. Levashova
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Situation Awareness ◽  
Cyber Physical Systems ◽  
Emergent Behavior ◽  
Emergent Properties ◽  
Decision Making Process ◽  
Physical Systems ◽  
Decision Support Models ◽  
Common Goals

Introduction: Socio-cyber-physical systems are complex non-linear systems. Such systems display emergent properties. Involvement of humans, as a part of these systems, in the decision-making process contributes to overcoming the consequences of the emergent system behavior, since people can use their experience and intuition, not just the programmed rules and procedures.Purpose: Development of models for decision support in socio-cyber-physical systems.Results: A scheme of decision making in socio-cyber-physical systems, a conceptual framework of decision support in these systems, and stepwise decision support models have been developed. The decision-making scheme is that cybernetic components make their decisions first, and if they cannot do this, they ask humans for help. The stepwise models support the decisions made by components of socio-cyber-physical systems at the conventional stages of the decision-making process: situation awareness, problem identification, development of alternatives, choice of a preferred alternative, and decision implementation. The application of the developed models is illustrated through a scenario for planning the execution of a common task for robots.Practical relevance: The developed models enable you to design plans on solving tasks common for system components or on achievement of common goals, and to implement these plans. The models contribute to overcoming the consequences of the emergent behavior of socio-cyber-physical systems, and to the research on machine learning and mobile robot control.

The Emergence of Adaptive Decision Making in Children

1997 ◽  
Vol 24 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jennifer Gregan‐Paxton ◽  
Deborah Roedder John
Keyword(s):  
Decision Making ◽  
Adaptive Decision Making
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