Human Factors in Simulation and Training: Theory and Methods_Team-IRA

✍ Scribed by Dennis A. Vincenzi (editor), Mustapha Moloua (editor), Peter A Hancock (editor), James A. Pharmer (editor), James C. Ferraro (editor)

• Publisher: CRC Press
• Year: 2023
• Tongue: English
• Leaves: 351
• Edition: 2
• Category: Library

✦ Synopsis

Human Factors in Simulation and Training: Theory and Methods covers theoretical concepts on human factors principles as they apply to the fields of simulation and training in the real world.

This book discusses traditional and nontraditional aspects of simulation and training. Topics covered include simulation fidelity, transfer of training, limits of simulation and training, virtual reality in the training environment, simulation-based situation awareness training, automated performance measures, performance assessment in simulation, adaptive simulation-based training, and scoring simulations with artificial intelligence

This book will be a valuable resource for professionals and graduate students in the fields of ergonomics, human factors, computer engineering, aerospace engineering and occupational health and safety.

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Editors
Contributors
Chapter 1 Human Factors in Simulation and Training: An Overview
Introduction
Simulation: The Perfect Storm
Human Factors in Simulation and Training: A Brief History
Why Simulate?
Simulation versus Modeling
The Modeling and Simulation Process: Verification, Validation, and Accreditation
Advantages and Disadvantages of Simulation
Advantages
Cost-Effectiveness
Availability
Safety
Surrogate Value
Reduced Environmental Impact
Improved Training Environment
Standardized Training Environments
Provide Data
Lack of Realism
Disadvantages of Simulation
Does Not Necessarily Reflect Real-World Performance
Surrogate Value
User Acceptance
A Sampling of Progress in Simulation
War-Gaming
Online Gaming
Aviation
Extended Reality: Augmented Reality, Virtual Reality, and Mixed Reality
Introduction to XR
Historical VR Devices
XR Applications in Training
VR in Medical Training
AR in Medical Training
AR in DoD Tactical Combat Casualty Care
VR Flight Training Devices
MR Flight Training Device
AR Trainer for H-60R Preflight Procedures
XR Applications in Operational Support
AR in Army Tactical Operations
VR in Operational Medicine
AR in Operational Medicine
AR for Aircraft Maintainers
Future Directions
XR HMD Enhancements
AR for Red Air
VR for Spatial Disorientation Training
Pilot Training Next (PTN) and Naval Aviation Training Next (NATN)
Challenges to the Adoption of XR Technology
XR Device Visual Fidelity
User Fatigue
Integration
User Resistance
Safety
Regulations
XR Is Not Always the Optimal Training Solution
Augmented Reality in Decision-Making
The Perfect Storm Revisited: The Future of Human Factors in Simulation and Training
Technological Trends
Computation Power
Innovations in Education and Training
The Changing Nature of Education
Acceptance of Simulation/Gaming
Acknowledgments
Disclaimer
References
Chapter 2 Justification for Use of Simulation
Introduction
Purposes
Training
Systems Engineering Evaluation
Research
Recreation
Domains of Application
Aviation
Military
Medical
Driving
Emergency Response
Education and STEM
Entertainment
Maintenance
Achievable Outcomes
Cost Benefit
Safety
Data
Intervention
Flexibility and Availability
Realism
Conclusion
References
Chapter 3 Simulation Fidelity
Introduction
Definition of Fidelity
Physical Fidelity
Visual–Audio Fidelity
Equipment Fidelity
Motion Fidelity
Psychological–Cognitive Fidelity
Other Fidelity
Measuring Fidelity
The Mathematical Model
Subjective Methods
Fidelity Evaluation Frameworks
Fidelity and Transfer of Training
Summary
References
Chapter 4 Transfer of Training
Introduction
Transfer of Training: Terms and Concepts
Positive Transfer
Negative Transfer
Near Transfer
Far Transfer
A Model of Factors Affecting the Transfer of Training
Training Input Factors
Training Outputs
Conditions of Transfer
Dynamic Models of Training Transfer
Research Methods
Transfer of Training Performance Measurement
Objective Measures
Subjective Measures
Selecting Performance Measures
Using Performance Measures to Indicate Transfer
Experimental Design
Forward Transfer Study
Backward Transfer Study
Quasi-Experimental Study
Curve-Fitting Method
Summary
References
Chapter 5 Simulation-Based Training for Decision-Making: Providing a Guide to Develop Training Based on Decision-Making Theories
Theoretical Background of Decision-Making
Normative Decision Models
Decision Models: New Perspectives
Naturalistic Decision-Making (NDM) Framework and Recognition-Primed Decision (RPD) Model
Biases in Decision-Making
Confirmation
Over- and Under-Confidence
Framing
Probability Perception (Gambler’s Fallacy)
Sunk Costs
Decision Theory Applied to Training
Steps in Developing Simulations to Train Decision-Making
Conduct a Needs Assessment
Identify Learning Objectives
Set the Simulation Context
Establish KSAs
Create Events to Elicit KSAs
Establish an Assessment Plan
Conclusion
References
Chapter 6 Almost Like the Real Thing – The Hidden Limits in Flight Simulation and Training
Introduction
Introduction to Simulator Motion
How Do Humans Perceive Motion Drive?
Let Them Eat Humble Pie—Or Not?
Same, Same But Different
Fiddling with Fidelity While Missing the Story
A Perfect Tool or a Tool That Can Be Perfected?
Summary
Acknowledgment
References
Chapter 7 Cybersickness in Immersive Training Environments
Introduction
Cybersickness Background
Individual Susceptibility and Stimulus Intensity
Quantifying Immersive Stimulus Intensity
Usage Protocol
Conclusions
Acknowledgments
References
Chapter 8 Distributed Debriefing for Simulation-Based Training
Introduction
Issues to Consider in Providing Distributed Debriefing for Simulation-Based Training
The Rest of This Chapter
Debriefing Functions and Methods
Functions of Debriefs
Methods of Debriefs
Challenges of Distributed Debriefs
Performance Diagnosis
Performance Recall, Comparison, and Extrapolation
Assessment and Display of Competence
Requirements for Distributed Debriefs
Communication
Collaboration
Automated Data Capture
Data Presentation
Data Selection
Replay Perspective
Expert Models of Performance
Flexible Delivery Style
Post-Exercise Review
Store Lessons Learned
Scalable
Ease of Use
Current Techniques for Debriefing Distributed Teams
State of the Art in Distributed Debriefing
Large-Scale Distributed Simulation Training Exercises
Small-Scale Distributed Simulation Training Exercises
Summary
Acknowledgments
References
Chapter 9 Performance Assessment in Simulation
Subjective Methods of Performance Measurement
Purpose of Performance Measures
Special Properties of Performance Measures in Simulators
Defining and Assessing Reliability
Data Requirements
Qualitative versus Quantitative
A Qualitative Index
Quantitative Indices
Special Problems with Simulators
The Gouge
Instructor Attitudes
Objective Methods of Performance Measurement
Automated Data Collection Systems
Flight Technical Error
Deviation-Based Metrics
Root Mean Square Error (RMSE)
Number of Deviations and Time-Outside Standard
Time within FAA Practical Test Standard
Non-FTE Measures
Rates of Change
Control Input
Summary
Note
References
Chapter 10 Performance Measurement Issues and Guidelines for Adaptive, Simulation-Based Training
Introduction
Research Advances
Adaptive SBT Implementation
A Confirmatory Performance Measurement Framework for Adaptive SBT
Dimensions and Essential Characteristics of Performance Measures
Validity
Criterion Relevance
Reliability
Measure Invariance
Objectivity and Intrusiveness
Diagnosticity
Measurement Principles for Adaptive Training
Principle 1: Ensure that Performance Measure Development Is Guided by Sound Theory
Principle 2: Consider and Exploit Measurement Affordances
Principle 3: Ensure Usefulness of Measures for Evaluating Training Effectiveness
Summary and Conclusions
References
Chapter 11 Scoring Simulations with Artificial Intelligence
Artificial Intelligence and Reproducing Expert Ratings
Traditional Approach to Scoring Open-Ended Content: Rater Training
The Architecture
The Data
Output
Other Considerations
Scoring Actions in Simulated Environments
Traditional Approaches to Scoring Simulations
Data Representations for Modeling Simulations
Machine Learning Methods for Scoring Simulations
Static Methods Using Summarized Representations
Time Series Methods
Applications
Trainee Feedback
Early Prediction
Real-Time Feedback
Adaptive Simulations
Conclusion
References
Chapter 12 Dissecting the Neurodynamics of the Pauses and Uncertainties of Healthcare Teams
Introduction
The Significance of Structure in EEG Amplitudes
Neurodynamic Correlates of Uncertainty
Estimating the Frequency Magnitude and Duration of Uncertainty
Augmenting Debriefings with Neurodynamics
Using Neurodynamic Analyses to Train the Trainers
Early Novices
Later Novices
Evolving the Technology
Summary
References
Chapter 13 The Future of Simulation
Proem
The Fundamental and Practical Reasons for Simulation
Simulations in the Past
On Predicting the Future
The Practicalities of Simulation
Simulation and Training
Discourse between Two Worlds
Hybrid Simulation Worlds
Assessing the Progress of Simulation Technologies
The Turing Test of Simulation
Supersimulation
The Moral Dimension of Simulation
A Philosophical Valediction
Summary and Conclusion
Acknowledgments
References
Appendix A: Glossary of Modeling Terms
Appendix B: Glossary of Simulation Terms
Appendix C: Glossary of Verification, Validation, and Accreditation Terms
Index