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Robert Gray

Course 2 teaches you how to distinguish between different methods for studying human error. You will also learn about human-centered design and usability, and how to compare and contrast different methodologies for evaluating the usability of products, technologies & systems.

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Syllabus

Course Introduction
In this course, you will gain the skills to distinguish between various research methods, understand their strengths and weaknesses, and explore human-centered design principles. By the end of Course 2, you will be well-equipped to conduct comprehensive research and evaluation to optimize human interactions within complex systems.
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what should give you pause
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Develops theoretical knowledge and practical skills for performing research studies in the field of human error
Builds a strong foundation for learners new to the topic of human error
Suitable for learners in various fields, including human factors, psychology, and engineering
Led by instructors with expertise in the field, providing valuable insights and practical knowledge
Part of a series of courses, offering a comprehensive understanding of human error
Covers fundamental concepts and advanced techniques for studying human error, providing a well-rounded understanding

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Reviews summary

Foundational course on human error and usability

According to learners, this course offers a solid foundation in understanding human error measurement and usability. Many found the modules on research methods particularly insightful and well-explained, making complex topics accessible. The course is often praised for its clear explanations and providing valuable foundational knowledge. However, some students with existing background in human factors found the content to lack depth and wished for more advanced techniques or real-world complex case studies. There's also a recurring desire for more hands-on exercises or labs to enhance practical application, as some felt it remained highly theoretical. While instructor knowledge is valued, a few reviewers noted that lecture delivery could be more engaging.
Instructors provide clear explanations, making complex topics accessible.
"I appreciated the practical examples and the instructor's clear explanations."
"The clarity of the explanations made complex topics accessible."
"The distinctions between different study methods for human error were very well explained."
Provides excellent foundational knowledge in human error and usability concepts.
"This course was absolutely fantastic for understanding the nuances of human error and how to approach its study."
"Good overview of human error measurement and usability, the course provides valuable foundational knowledge."
"Excellent course that delves into a critical area. The distinctions between different study methods for human error were very well explained."
"A gem for anyone interested in human performance and error. The deep dive into research methodologies was invaluable."
Content is strong, but some lectures could benefit from more dynamic delivery.
"Some lectures were a bit dry, but the readings compensated for it."
"The instructor was knowledgeable, but the delivery could be more engaging at times."
Reviewers often desire more hands-on activities and real-world examples.
"I wish there were more hands-on exercises or labs to solidify the concepts."
"It felt very theoretical with insufficient practical guidance. Needs more hands-on activities."
"I expected more real-world complex case studies."
"I would have liked more about real-world constraints in research."
Well-suited for beginners, but some advanced learners may find it introductory.
"It's a great starting point for beginners."
"I felt some parts of the course lacked depth, especially on advanced techniques."
"If you're an advanced professional, you might find it too basic."
"It felt like a rehash of basic concepts for me, having some background in human factors."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in How Can We Measure and Study Human Error? with these activities:
Read: Human Error by James Reason
Enhance understanding by reading a foundational text on human error analysis, expanding knowledge and providing a deeper perspective.
Show steps
  • Purchase or borrow the book
  • Read the book
  • Take notes and highlight key concepts
Complete Human Error Analysis Quizzes
Take frequent quizzes to test comprehension of key concepts and identify areas for further study.
Browse courses on Human Factors
Show steps
  • Access the Human Error Analysis quizzes
  • Complete a quiz
  • Review the answers and explanations
Attend a Human Factors Workshop
Advance knowledge by attending a workshop on human factors or usability, gaining insights from experts and engaging in hands-on activities.
Browse courses on Human Factors
Show steps
  • Research and find a relevant workshop
  • Register for the workshop
  • Attend the workshop and actively participate
Four other activities
Expand to see all activities and additional details
Show all seven activities
Explore UX Crash Course
Review a series of short videos on Coursera's UX Crash Course to reinforce the concepts of human-centered design, usability, and human error.
Browse courses on Human-Centered Design
Show steps
  • Sign up for the UX Crash Course on Coursera
  • Watch the entire 14-video series
Discuss Human Error Case Studies
Engage in a peer study group to discuss real-world examples of human error, offering diverse perspectives and enhancing understanding.
Browse courses on Case Studies
Show steps
  • Find a study partner or group
  • Select a case study of human error
  • Analyze the case study and identify contributing factors
  • Discuss your findings with your study group
Mentor Students in Human Error Analysis
Enhance subject mastery by mentoring students, reinforcing knowledge through teaching and providing support to others.
Browse courses on Mentoring
Show steps
  • Identify opportunities to mentor students
  • Prepare materials and resources
  • Meet with students regularly
Contribute to Human Error Analysis Tools
Gain practical experience by contributing to open-source human error analysis tools, deepening understanding and contributing to the community.
Browse courses on Tools
Show steps
  • Identify a relevant open-source project
  • Review the project's documentation and codebase
  • Make a contribution to the project
  • Submit your contribution for review

Career center

Learners who complete How Can We Measure and Study Human Error? will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in How Can We Measure and Study Human Error?.
This comprehensive handbook covers all aspects of human factors engineering and ergonomics. It is an essential reference for researchers and practitioners in the field.
Classic in the field of usability and provides a comprehensive overview of the principles of user-centered design. It must-read for anyone interested in learning more about how to design products that are both usable and effective.
Widely used textbook that provides a comprehensive introduction to the three major approaches to research design: qualitative, quantitative, and mixed methods. It is excellent for gaining a broad understanding and is often used as a foundational text in academic programs. The latest edition includes updates reflecting the 7th edition of the APA Publication Manual, making it a current and valuable reference.
Another highly regarded textbook for undergraduate students, this handbook offers comprehensive coverage of key areas in cognitive psychology, from perception to language and thinking. It emphasizes human cognition in context and includes updated research and case studies, making it a valuable resource for gaining a broad understanding and also for delving deeper into specific topics. It is commonly used as a textbook in academic institutions.
Classic guide to the research process, focusing on formulating research questions, developing arguments, and communicating findings effectively. It is highly recommended for students at all levels who are learning how to approach and structure a research project. It is particularly useful for solidifying an understanding of the fundamental principles of research.
A practical guide to coding qualitative data, this book provides detailed instructions and examples for various coding methods. It is an essential tool for anyone undertaking qualitative data analysis, from beginners to experienced researchers. It helps solidify understanding of a crucial step in qualitative research.
Teaches the fundamentals of UX design with a focus on usability and user-centered design. It is written in a clear and concise style, making it a great choice for beginners or those looking for a quick refresher.
This comprehensive book provides a detailed overview of the UX design process, from user research to evaluation. It valuable resource for UX designers of all levels, as it provides practical guidance and best practices.
This sourcebook detailed guide for analyzing qualitative data. It offers a wide range of methods and techniques, making it a valuable reference for students and researchers undertaking qualitative studies. The fourth edition includes new visual display models and updated content, ensuring its relevance for contemporary research.
First published in 1967, this seminal work is considered the first true textbook in cognitive psychology and played a crucial role in the cognitive revolution. It provides a comprehensive survey of the field as it existed then, covering perception, memory, and thought. It foundational classic and essential for understanding the origins of the discipline, though more valuable for historical context than current reference.
Classic in the field of usability engineering. It provides a comprehensive overview of the principles and practices of usability engineering, with a focus on quantitative methods for evaluating usability.
Considered a classic in the field, this book offers a deep dive into the theoretical underpinnings of hypothesis testing. It is highly rigorous and best suited for graduate students and researchers focusing on the mathematical theory of statistics. It serves as an invaluable reference for advanced topics.
This comprehensive textbook provides a broad overview of human factors engineering, covering topics such as human information processing, human error, and design for safety. It is an excellent resource for students and professionals alike.
A comprehensive guide to mixed methods research, this book covers the design, implementation, and analysis of studies that combine qualitative and quantitative approaches. It is essential for researchers interested in this growing area of research methodology and provides detailed guidance.
Dan Ariely explores the irrationality of human behavior and decision-making through engaging experiments. is excellent for gaining a deeper understanding of cognitive biases and how they influence our daily lives. It's highly accessible and relevant for both students and professionals interested in behavioral economics and cognitive psychology.
This online textbook and accompanying website provide a comprehensive overview of research methods concepts and procedures. It widely used resource for learning and teaching research methods, offering clear explanations and interactive exercises. It good resource for both foundational knowledge and review.
Delves into the science of learning and memory, drawing heavily on cognitive psychology research. It provides practical strategies for more effective learning and is highly relevant for students at all levels and for educators. It's excellent for deepening understanding of memory and learning processes and has high practical value.
Steven Pinker, a renowned cognitive scientist, provides a comprehensive overview of the human mind from an evolutionary perspective. is excellent for gaining a broad understanding of various cognitive functions and their potential origins. It popular and influential work in the field.
This textbook provides a solid introduction to cognitive psychology with a focus on connecting laboratory research to real-world phenomena. It's suitable for undergraduates and helps solidify understanding through practical examples and demonstrations. It's considered a comprehensive resource in the field.
Offers a concise yet comprehensive overview of statistical inference, including hypothesis testing, suitable for students in statistics, machine learning, and other quantitative fields. It moves quickly and covers a broad range of topics, making it excellent for those with a solid mathematical background seeking a fast-paced introduction or review.
This textbook provides a comprehensive overview of cognitive neuroscience, the field that bridges cognitive psychology and neuroscience. It's essential for understanding the neural basis of cognitive processes and is highly relevant for those looking to deepen their understanding and explore contemporary topics at the intersection of mind and brain. It commonly used textbook in cognitive neuroscience programs.
This recent textbook explores core cognitive psychology topics through the lens of real-world issues and contemporary challenges. It demonstrates the relevance of cognitive psychology in the 21st century, covering topics like creativity, problem-solving, and decision-making in modern contexts. It's ideal for exploring contemporary applications and seeing how the field is evolving.
Presents current topics and issues in cognitive psychology in a clear and engaging manner. It's accessible to students and helps readers understand the origin and evolution of theories through experimentation. It's a good resource for gaining a broad understanding and is often used as a textbook.
A definitive guide to conducting case study research, this book covers the design, collection, and analysis of case study data. It is essential for researchers utilizing this specific qualitative approach and provides in-depth knowledge for mastering the method.
Explores the role of emotion in design. It shows how emotions can influence our interactions with products and services, and provides guidance on how to design for emotional impact.
Bartlett's work on reconstructive memory, particularly his studies on the recall of complex material like stories, was a significant departure from earlier work on rote learning. This classic book introduced the concept of schemas and had a lasting impact on the study of memory. It is crucial for understanding the development of memory research in cognitive psychology.
Provides practical guidance on how to design for real-world constraints, such as budget, time, and technology. It great resource for designers who want to create products and services that are both useful and feasible.
Examines 15 influential classic studies in cognitive psychology, providing critical reflections on their impact and how they have shaped subsequent research. It's an excellent resource for understanding the historical development of the field and the foundational experiments. It's particularly useful for recognizing classic works and seeing their continued relevance.
Takes a naturalistic approach to decision-making, studying how people make decisions in real-world, high-stakes situations. It offers a different perspective than traditional lab-based research and is valuable for deepening understanding of applied cognitive processes. It's considered a modern classic and is relevant for professionals.
Explores the relationship between humans and technology. It provides insights into how human-centered design can be used to create products and services that are both useful and enjoyable to use.
These volumes are foundational to connectionism and the parallel distributed processing approach to cognition. They propose that the mind can be understood in terms of interconnected networks of simple units. This work has been highly influential in cognitive science and neuroscience. It's a classic for those interested in computational models of cognition and neural networks.
Provides practical guidance on conducting survey research, covering questionnaire design, sampling, data collection, and analysis. It valuable resource for those focusing on quantitative methods, particularly in social sciences and market research. It helps deepen understanding of a specific research methodology.
Provides a comprehensive overview of information architecture, the art and science of organizing and structuring information. It covers topics such as user research, content strategy, and navigation design.
A more advanced counterpart to 'Introduction to Statistical Learning,' this book covers a wide range of statistical learning methods, with relevant sections on inference and hypothesis testing. It is aimed at graduate students and researchers and key reference in the data science community. It provides a deeper theoretical understanding alongside practical algorithms.
Focuses on robust statistical methods, which are particularly relevant in contemporary data analysis when assumptions of traditional tests are not met. It covers robust approaches to hypothesis testing and is valuable for researchers and practitioners dealing with real-world data that may contain outliers or deviations from normality. The latest editions incorporate R.
Is highly relevant for those interested in applying hypothesis testing in a business context, specifically for online controlled experiments (A/B testing). It covers practical considerations and statistical nuances of hypothesis testing in this domain and is suitable for practitioners in data science, marketing, and product management.
Offers a step-by-step guide to conducting a research project, covering all stages from planning to writing up findings. It is particularly helpful for undergraduate and postgraduate students undertaking their first research project, providing practical advice and avoiding common mistakes.
Provides a modern introduction to statistics using R, covering data handling, visualization, and statistical inference, including hypothesis testing. It is suitable for students and practitioners who want to learn statistical concepts alongside practical implementation in R. It reflects contemporary approaches to data analysis.
Explores the importance of simplicity in design. It provides practical guidance on how to create simple and effective products and services.
Provides a concise overview of 100 principles of design, covering topics such as aesthetics, usability, and sustainability. It great resource for designers of all levels.
Explores the role of emotion in design. It provides practical guidance on how to design for emotional impact.

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