Applied Attention Theory

Applied Attention Theory, Second Edition provides details concerning the relevance of all aspects of attention to the world beyond the laboratory. Topic application areas include the design of warning systems to capture attention; attention distractions in the workplace; failures of dividing attention while driving; and the measurement of mental workload while flying.This new edition discusses the implications of virtual reality and augmented reality for human attention. It also covers the treatment of attention-based pedagogical methods used to enhance learning, and presents attentional issues in interacting with automation and AI. New chapters include applications of attention to healthcare, education pedagogy, highway safety, cybersecurity, and human interaction with autonomous vehicles and other AI systems.The readership for this book is the professional, the researcher, and the student. Cover Half Title Title Copyright Contents Preface Authors Chapter 1 Introduction 1.1 Varieties of Attention 1.2 Relation to Other Applied Domains 1.3 Scaling Up Basic to Applied Research 1.3.1 The Role of Models 1.4 Outline of the Book Chapter 2 Single-Channel Theory and Automaticity 2.1 Single-Channel Theory and the Psychological Refractory Period 2.2 Applications of Single-Channel Theory to Workload Prediction 2.3 Dichotic Listening: Early versus Late Selection 2.4 Automaticity 2.5 Conclusion Chapter 3 Attention Control 3.1 Inattentional and Change Blindness 3.2 Covert versus Overt Attention 3.3 The Spotlight of Visual Attention 3.4 Posner’s Cuing Paradigm 3.5 Central versus Peripheral Cuing 3.6 Auditory and Cross-Modal Cuing 3.7 Alarms and Attention Guidance 3.8 Alert Salience 3.9 Alert Reliability 3.10 Level of Unaided Human Performance: Discrimination Difficulty 3.11 The Nature of Automation Errors: Misses versus False Alerts 3.12 Base-Rate Effects 3.13 Solutions 3.14 Conclusion Chapter 4 Visual Attention, Scanning, and Information Sampling 4.1 Sources of Attention Motivation 4.2 Eye Movement Measures 4.3 Limits of Visual Scanning as a Measure of Attention 4.4 Influences on Visual Information Access 4.4.1 Habit 4.4.2 Salience 4.4.3 Information Content: Bandwidth 4.4.4 Information Content: Context 4.4.5 Information Value 4.4.6 Information Access Effort 4.5 The SEEV Tradeoff Model 4.5.1 Applications of the SEEV Model 4.6 Adapting SEEV to Predict Noticing 4.7 Novice–Expert Differences in Scanning 4.8 Conclusion Chapter 5 Visual Search 5.1 A Model of Applied Visual Search 5.2 The Standard Search Models 5.3 Preattentive and Attentive Processing 5.4 Search Guidance 5.4.1 Bottom-Up Guidance: Visual Salience 5.4.2 Top-Down Guidance: Feature Activation 5.4.3 Top-Down Guidance: Context 5.5 The Functional Visual Field (FVF) and Oculomotor Scan Patterns 5.6 Stopping Policy and Missed Targets 5.6.1 The Target Prevalence Effect 5.6.2 Satisfaction of Search 5.7 Collaborative Search 5.8 Summary: Enabling Better Search 5.9 Conclusion Chapter 6 Spatial Attention and Displays 6.1 Space-Based Attention Theory 6.2 Object-Based Attention Theory 6.3 The Proximity Compatibility Principle 6.4 Task Proximity 6.4.1 Display Proximity 6.4.1.1 Sensory/Perceptual Similarities 6.4.1.2 Object Integration 6.4.1.2.1 Connections and Abutment 6.4.1.2.2 Heterogeneous versus Homogeneous Featured Objects 6.4.1.3 Close Proximity by Emergent Features 6.4.2 Costs of Focused Attention: Is There a Free Lunch? 6.4.3 Overlaying Imagery: Maps, HUDS, HMDs, and Augmented Reality 6.4.4 Applications to Graph Design 6.4.5 Ecological Interfaces, Navigation, and Supervisory Displays 6.4.5.1 EID and Emergent Features 6.4.6 Integration Over Space and Time 6.4.7 Visual Momentum and Navigation 6.5 Conclusion Chapter 7 Resources and Effort 7.1 Effort in Single-Task Choice 7.2 Effort in the Choice to Stop Search or Limit Sampling 7.3 Effort in the Choice to Behave Safely 7.4 Effort in the Choice Between Decision Strategies 7.5 Effort in the Choice of a Feature to Use: Implications for System Design 7.6 Effort in Information Integration: The Proximity Compatibility Principle 7.7 Effort Depletion and Expansion: The Vigilance Decrement 7.8 Effort as Resources: Dual-Task Performance 7.8.1 The Performance Resource Function and the Performance Operating Characteristic 7.9 Relevance of Effort to Mental Workload 7.10 Measuring Effort and Mental Workload 7.11 Analysis of Primary Task Demands 7.11.1 Analysis of Secondary Task Performance 7.11.2 Subjective Measurement 7.11.3 Physiological/Neuroergonomic Measures 7.12 Conclusion Chapter 8 Concurrent Task Performance: Time-Sharing and Multiple Resources 8.1 Multiple-Resource Theory 8.2 History and Origins 8.3 The 4-Dimensional Multiple-Resource Model 8.3.1 Stages 8.3.2 Perceptual Modalities 8.3.2.1 Visual Scanning 8.3.2.2 Auditory Preemption 8.3.2.3 Compatibility 8.3.2.4 Redundancy Gain 8.3.3 Visual Channels 8.3.4 Processing Codes 8.4 The Multiple-Resource Model Revisited 8.5 A Computational Model of Multiple-Resource Interference 8.6 Other Sources of Interference: Preemption, Cooperation, and Confusion 8.6.1 Auditory Preemption 8.6.2 Cooperation 8.6.3 Confusion 8.7 Conclusion Chapter 9 Sequential Multitasking: Attention Switching, Interruptions, and Task Management 9.1 Task Switching 9.2 Interruption Management 9.2.1 Properties of the OT 9.2.1.1 Engagement 9.2.1.2 Subgoal Completion and Memory Load 9.2.1.3 Importance and Priority of the OT 9.2.2 Properties of the IT 9.2.2.1 Importance 9.2.2.2 Salience 9.2.3 OT Properties Influencing Task Return and Reengagement 9.2.3.1 Strategies Carried Out at Switch 1 9.2.3.2 Delay in Return 9.2.3.3 Difficulty of the IT 9.2.3.4 Visibility of the OT 9.2.3.5 IT–OT Similarity 9.3 Task and Workload Management 9.3.1 Priority 9.3.2 Interest 9.3.3 Salience 9.3.4 Difficulty 9.4 Individual Differences in Attention-Switching and Multitasking Success 9.4.1 Categories of Individual Differences 9.4.1.1 Switching Speed 9.4.1.2 Switching Frequency 9.4.2 Correlates of Individual Differences in Switching 9.4.2.1 Working Memory 9.4.2.2 Executive Control 9.4.2.3 Fluid Intelligence and the General Time-Sharing Ability 9.4.3 The Tangled Web 9.5 Conclusion Chapter 10 Attention and Human Interaction with Automation and AI 10.1 Visual Monitoring of Automation: Alarms and Alerts 10.2 Attention Cuing 10.3 Attention and Effort: Level of Engagement 10.4 Automation, Workload, and HAI Team Productivity 10.5 Adaptive Automation, Attention, and Workload 10.6 Conclusion Chapter 11 Applications (with Tobias Grundgeiger and Yusuke Yamani) 11.1 Aviation 11.1.1 Chapter 2. Single-Channel Theory and Automaticity 11.1.2 Chapter 3: Alarms and Alerts 11.1.3 Chapter 4. Supervisory Control 11.1.4 Chapter 5. Visual Search 11.1.5 Chapter 6: Attention in Space 11.1.6 Chapter 7. Resources and Effort 11.1.7 Chapter 8. Multiple Resources 11.1.8 Chapter 9. Interruption and Task Management 11.2 Driving (with Yusuke Yamani) 11.2.1 Driving Experience and Visual Scanning 11.2.2 Multitasking and Driver Distraction 11.2.3 Automated Driving 11.3 Acute Health Care (with Tobias Grundgeiger) 11.3.1 Medical Simulation Environments 11.3.2 Work Experience 11.3.3 “Good” Attention Distribution 11.3.4 Cognitive Aids 11.3.5 Interruptions and Task Management 11.4 Learning and Training 11.4.1 Expertise and Attention 11.4.1.1 Training Expertise in Time-Sharing Skills 11.4.2 Attention and Effort in Studying and Learning 11.4.2.1 Study Strategies 11.4.2.2 Instructional Materials 11.5 Cybersecurity 11.5.1 Challenge: Situation Awareness 11.5.2 Challenge: Attention Overload 11.5.3 Challenge: Display Design 11.5.4 Challenge: Degree of Automation 11.6 Conclusion References Author Index Subject Index Applied Attention Theory, Second Edition provides details concerning the relevance of all aspects of attention to the world beyond the laboratory. Topic application areas include the design of warning systems to capture attention; attention distractions in the workplace; failures of dividing attention while driving; and the measurement of mental workload while flying. This new edition discusses the implications of VR and AR for human attention. It also covers the treatment of attention-based pedagogical methods used to enhance learning and presents attentional issues in interacting with automation and AI. New chapters include applications of attention to healthcare, education pedagogy, highway safety, and human interaction with autonomous vehicles and other AI systems. The readership for this book is the professional, the researcher, and the student. "The book discusses the implications of VR and AR for human attention, covers treatment of attention-based pedagogical methods to enhance learning, presents attentional issues in interacting with automation and AI, explores research in applied human factors journals, and offers new chapters on applications of attention to health care, education & pedagogy, highway safety and human-interaction with autonomous vehicles, and other AI systems"-- Provided by publisher This book provides details concerning the relevance of all aspects of attention. Topic application areas run from the design of warning systems to capture attention, to the attention distractions in the workplace, to the failures of dividing attention while driving, to the measurement of mental workload while flying.