Foundations of Human-Computer Interaction
Designing for Cognitive Alignment
- 1st Edition - May 1, 2026
- Latest edition
- Author: Robert Atkinson
- Language: English
Foundations of Human-Computer Interaction: Designing for Cognitive Alignment covers the fundamentals of human-computer interaction (HCI), usability, and user-centered design… Read more
Foundations of Human-Computer Interaction: Designing for Cognitive Alignment covers the fundamentals of human-computer interaction (HCI), usability, and user-centered design. It provides a holistic and engaging exploration of HCI by integrating historical perspectives, behavioral and cognitive insights, neuroscientific principles, and advanced technological tools. The book also discusses contemporary challenges such as dark patterns and surveillance capitalism, and offers an understanding of ethics and code of conduct to enable both students and practitioners to take their thinking and designs forward in a responsible way into the marketplace.
The book's pedagogy emphasizes interactive learning, critical thinking, and iterative design processes, making the content accessible and engaging for both novices and advanced learners.
The book's pedagogy emphasizes interactive learning, critical thinking, and iterative design processes, making the content accessible and engaging for both novices and advanced learners.
- Offers a mix of foundational theories, practical applications, and the latest advances in HCI, ensuring relevance to current and future technological landscapes
- Covers emerging trends, advanced tools, and practical applications, providing a richer, more integrated approach to learning and applying HCI principles
- Provides real-world examples and case studies, giving practical insights and demonstrating the impact of HCI in various industries
- Discusses the latest trends such as augmented intelligence, brain-computer interfaces, and explainable AI, preparing readers for the future landscape of HCI
- Includes a discussion on ethics to address contemporary challenges such as dark patterns and surveillance capitalism
- Incorporates hands-on design tools, user research techniques, and expert evaluation methodologies to foster practical skills and critical thinking
Graduate students and undergraduates in human-computer interaction, computer science, informatics, psychology, and related disciplines.
1. Foundations
1.1 Introduction
1.2 Major research areas in HCI
1.3 The evolution of HCI
1.4 Human-centered design
1.5 Usability vs. user experience
1.6 Real-world use cases
2. Behaviourist Perspective
2.1 Introduction and historical development
2.2 Key principles of behaviorism
2.3 Behaviorist techniques in HCI
2.4 Immediate feedback and gamification in HCI
2.5 General Design Principles
3. Cognitive Perspective
3.1 Introduction and historical development
3.2 Information Processing Theory and key cognitive processes
3.3 Human Processor Model
3.4 Cognitive Load Theory
3.5 Metacognition
3.6 General Design Principles
4. Cognitive Neuroscience Perspective
4.1 Two systems of thinking
4.2 Limbic reward pathway
4.3 Mirror neurons
4.4 Default Mode Network
4.5 Neuroplasticity
5. Models, Cycles, and Frameworks
5.1 Human-Action Cycle
5.2 ICAP Framework
5.3 Technology Acceptance Model (TAM)
5.4 Goals, Operators, Methods, Selection Rules (GOMS) Model
5.5 Keystroke-Level Model (KLM)
5.6 General Design Principles
6. Motivation and Emotional Design
6.1 Understanding motivation
6.2 Extrinsic and intrinsic motivation
6.3 Emotional design
6.4 Color and emotional impact
6.5 Social presence and scarcity
7. Design Thinking
7.1 Foundations and values
7.2 Design thinking phases
7.3 Prototyping and iteration
7.4 Common design processes
7.5 User research techniques
7.6 Ideation and conceptualization
8. Design Tools
8.1 Usability heuristics
8.2 Logical design decision
8.3 Interaction cost and load
8.4 Visual design guidelines
8.5 Color and typography
8.6 Form and button design
9. Expert Evaluations
9.1 Heuristic evaluation
9.2 Cognitive walkthrough
9.3 Consistency review
9.4 Standards inspection
9.5 Pluralist walkthrough
9.6 Formative evaluation
10. Research Tools
10.1 Usability testing
10.2 Scientific method
10.3 Experimental design
10.4 Hypothesis testing
10.5 Performance metrics
10.6 Self-report metrics
11. Usability Study
11.1 Purpose and process of usability studies
11.2 Key aspects
11.3 Planning a usability study
11.4 Conducting a usability study
11.5 Analyzing and reporting findings
11.6 Recognizing and addressing research bias
12. Data Analysis
12.1 Importance of data analysis
12.2 Descriptive statistics
12.3 Inferential statistics
12.4 Comparing means and medians
12.5 Relationship assessment
12.6 Categorical and proportional analysis
13. Advanced Tools
13.1 Advanced biometric tools
13.2 Eye tracking technology
13.3 Emotional analysis
13.4 Brain-Computer Interface
13.5 Multimodal laboratory
13.6 Closed-loop systems
14. Ethical Issues
14.1 Importance of ethics
14.2 Ethical principles
14.3 Professional codes of conduct
14.4 Challenges in AI-Infused systems
14.5 Dark patterns
14.6 Surveillance and limbic capitalism
15. Emerging Trends
15.1 Gartner’s Hype Cycle
15.2 Augmented intelligence
15.3 Brain-Computer Interfaces
15.4 Explanatory AI
15.5 Sequential pattern mining
15.6 Micro- and macro-user interactions
15.7 Smart wearables
15.8 Neurocognitive capitalism
1.1 Introduction
1.2 Major research areas in HCI
1.3 The evolution of HCI
1.4 Human-centered design
1.5 Usability vs. user experience
1.6 Real-world use cases
2. Behaviourist Perspective
2.1 Introduction and historical development
2.2 Key principles of behaviorism
2.3 Behaviorist techniques in HCI
2.4 Immediate feedback and gamification in HCI
2.5 General Design Principles
3. Cognitive Perspective
3.1 Introduction and historical development
3.2 Information Processing Theory and key cognitive processes
3.3 Human Processor Model
3.4 Cognitive Load Theory
3.5 Metacognition
3.6 General Design Principles
4. Cognitive Neuroscience Perspective
4.1 Two systems of thinking
4.2 Limbic reward pathway
4.3 Mirror neurons
4.4 Default Mode Network
4.5 Neuroplasticity
5. Models, Cycles, and Frameworks
5.1 Human-Action Cycle
5.2 ICAP Framework
5.3 Technology Acceptance Model (TAM)
5.4 Goals, Operators, Methods, Selection Rules (GOMS) Model
5.5 Keystroke-Level Model (KLM)
5.6 General Design Principles
6. Motivation and Emotional Design
6.1 Understanding motivation
6.2 Extrinsic and intrinsic motivation
6.3 Emotional design
6.4 Color and emotional impact
6.5 Social presence and scarcity
7. Design Thinking
7.1 Foundations and values
7.2 Design thinking phases
7.3 Prototyping and iteration
7.4 Common design processes
7.5 User research techniques
7.6 Ideation and conceptualization
8. Design Tools
8.1 Usability heuristics
8.2 Logical design decision
8.3 Interaction cost and load
8.4 Visual design guidelines
8.5 Color and typography
8.6 Form and button design
9. Expert Evaluations
9.1 Heuristic evaluation
9.2 Cognitive walkthrough
9.3 Consistency review
9.4 Standards inspection
9.5 Pluralist walkthrough
9.6 Formative evaluation
10. Research Tools
10.1 Usability testing
10.2 Scientific method
10.3 Experimental design
10.4 Hypothesis testing
10.5 Performance metrics
10.6 Self-report metrics
11. Usability Study
11.1 Purpose and process of usability studies
11.2 Key aspects
11.3 Planning a usability study
11.4 Conducting a usability study
11.5 Analyzing and reporting findings
11.6 Recognizing and addressing research bias
12. Data Analysis
12.1 Importance of data analysis
12.2 Descriptive statistics
12.3 Inferential statistics
12.4 Comparing means and medians
12.5 Relationship assessment
12.6 Categorical and proportional analysis
13. Advanced Tools
13.1 Advanced biometric tools
13.2 Eye tracking technology
13.3 Emotional analysis
13.4 Brain-Computer Interface
13.5 Multimodal laboratory
13.6 Closed-loop systems
14. Ethical Issues
14.1 Importance of ethics
14.2 Ethical principles
14.3 Professional codes of conduct
14.4 Challenges in AI-Infused systems
14.5 Dark patterns
14.6 Surveillance and limbic capitalism
15. Emerging Trends
15.1 Gartner’s Hype Cycle
15.2 Augmented intelligence
15.3 Brain-Computer Interfaces
15.4 Explanatory AI
15.5 Sequential pattern mining
15.6 Micro- and macro-user interactions
15.7 Smart wearables
15.8 Neurocognitive capitalism
- Edition: 1
- Latest edition
- Published: May 1, 2026
- Language: English
RA
Robert Atkinson
Dr Robert Atkinson is the Associate Professor of Computer Science in the School of Computing and Augmented Intelligence at Arizona State University, with a background in cognitive science, psychology, and neuroscience. His work focuses on the intersection of these fields with technology. He holds a PhD in Cognitive Science from the University of Wisconsin, and has published over 60 academic papers in peer-reviewed journals and conference proceedings across diverse fields, including computer science, psychology, data science, educational technology, human systems engineering, and informatics.
Affiliations and expertise
Arizona State University, Tempe, Arizona, USA