User Research Canon
A set of fundamental principles and guidelines that inform and shape user research practices. Crucial for maintaining consistency and ensuring high-quality user insights.
143 topics found for:
“field research”
Grounded Theory
A research method that involves forming a theory based on data systematically gathered and analyzed. Useful for developing design theories and solutions that are directly grounded in user research and data.
Deductive Research
A research approach that starts with a theory or hypothesis and uses data to test it, often moving from general to specific. Essential for validating theories and making informed decisions based on data.
Ethnographic Research
A qualitative research method that studies people in their natural environments to understand their behaviors, cultures, and experiences. Crucial for gaining deep insights into user behaviors and contexts.
Observer Bias
A type of bias that occurs when the observer's expectations or beliefs influence their interpretation of what they are observing, including experimental outcomes. Essential for ensuring the accuracy and reliability of research and data collection.
Experimenter Bias
A bias that occurs when researchers' expectations influence the outcome of a study. Crucial for designing research methods that ensure objectivity and reliability.
Contextual Design
A user-centered design process that involves understanding users' needs and workflows through field research and applying these insights to design. Essential for creating designs that are deeply informed by user contexts and behaviors.
Longitudinal Study
A research method that involves repeated observations of the same variables over a period of time. Crucial for understanding changes and developments over time.
Contextual Inquiry
A field research method where researchers observe and interview users in their natural environment to understand their tasks and challenges. Crucial for gaining authentic insights into user behavior and needs.
CIT
Critical Incident Technique (CIT) is a method used to gather and analyze specific incidents that significantly contribute to an activity or outcome. This method is important for identifying key factors that influence performance and user satisfaction.
Naturalistic Observation
A research method that involves observing subjects in their natural environment. Crucial for gathering authentic data and insights into real-world behaviors and interactions.
Field Study
Research conducted in natural settings to collect data on how people interact with products or environments in real-world conditions. Crucial for gaining authentic insights into user behaviors and contexts.
Selection Bias
A bias that occurs when the sample chosen for a study or survey is not representative of the population being studied, affecting the validity of the results. Important for ensuring the accuracy and reliability of research findings and avoiding skewed data.
Social Desirability Bias
The tendency for individuals to present themselves in a favorable light by overreporting good behavior and underreporting bad behavior in surveys or research. Crucial for designing research methods that mitigate biases and obtain accurate data.
Repeated Measures Design
A research design where the same participants are used in all conditions of an experiment, allowing for the comparison of different conditions within the same group. Essential for reducing variability and improving the reliability of experimental results.
Matched Pairs Design
An experimental design where subjects are paired based on certain characteristics, and then one is assigned to the treatment and the other to the control group. Important for reducing variability and improving the accuracy of experimental results.
Response Bias
A tendency for respondents to answer questions in a manner that is not truthful or accurate, often influenced by social desirability or survey design. Important for understanding and mitigating biases in survey and research data.
Look Elsewhere Effect
A statistical phenomenon where a large number of hypotheses are tested, increasing the chance of a rare event being observed. Crucial for understanding and avoiding false positives in data analysis.
Factor Analysis
A statistical method used to identify underlying relationships between variables by grouping them into factors. Crucial for simplifying data and identifying key variables in research.
Context Mapping
A research technique that explores the context in which users interact with a product, service, or environment to understand their needs and behaviors. Crucial for gaining deep insights into user contexts and designing more relevant solutions.
Extension Neglect
A cognitive bias where people ignore the relevance of sample size in making judgments, often leading to erroneous conclusions. Crucial for designers to account for appropriate sample sizes in research and analysis.
Normal Distribution
A statistical distribution where most occurrences take place near the mean, and fewer occurrences happen as you move further from the mean, forming a bell curve. Crucial for data analysis and understanding variability in user behavior and responses.
Association Fallacy
A logical fallacy in which it is assumed that qualities of one thing are inherently qualities of another, due to an irrelevant association. Important for avoiding incorrect associations in user research and data interpretation.
Delphi Method
A structured communication technique originally developed as a systematic, interactive forecasting method which relies on a panel of experts. Important for gathering expert opinions and making informed decisions.
Needs Assessment
A systematic process for determining and addressing needs or gaps between current conditions and desired outcomes. Important for identifying user requirements and guiding the development of digital products that meet those needs.
Quantitative Research
A research method that focuses on collecting and analyzing numerical data to identify patterns, relationships, and trends, often using surveys or experiments. Essential for making data-driven decisions and validating hypotheses with statistical evidence.
Qualitative Research
A research method that focuses on understanding phenomena through in-depth exploration of human behavior, opinions, and experiences, often using interviews or observations. Essential for gaining deep insights into user needs and behaviors to inform design and development.
ASI
Artificial Superintelligence (ASI) is a hypothetical AI that surpasses human intelligence and capability in all areas. Important for understanding the potential future impacts and ethical considerations of AI development.
Content Validity
The extent to which a measure represents all facets of a given construct, ensuring the content covers all relevant aspects. Important for ensuring that assessments and content accurately reflect the intended subject matter.
Fallacy of Composition
A logical fallacy that occurs when one assumes that what is true for a part is also true for the whole. Important for avoiding incorrect assumptions in design and decision-making.
Survivorship Bias
A cognitive bias that occurs when conclusions are drawn from a non-representative sample, focusing only on successful cases and ignoring failures. Crucial for making accurate assessments and designing systems that consider both successes and failures.
RLHF
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human input to guide the training of AI models. Essential for improving the alignment and performance of AI systems in real-world applications.
Representativeness
Representativeness is a heuristic in decision-making where individuals judge the probability of an event based on how much it resembles a typical case. Crucial for understanding biases in human judgment and improving decision-making processes.
UX
User Experience (UX) refers to the overall experience of a person using a product, system, or service, encompassing all aspects of the end-user's interaction. Crucial for creating products that are not only functional but also enjoyable, efficient, and satisfying to use.
Confidence Interval
A range of values, derived from sample statistics, that is likely to contain the value of an unknown population parameter. Essential for making inferences about population parameters and understanding the precision of estimates in product design analysis.
Turing Test
A test proposed by Alan Turing to determine if a machine's behavior is indistinguishable from that of a human. Important for evaluating the intelligence of AI systems.
Transformer
A type of model architecture primarily used in natural language processing tasks, known for its efficiency and scalability. Essential for state-of-the-art NLP applications.
InfoVis
Information Visualization (InfoVis) is the study and practice of visual representations of abstract data to reinforce human cognition. Crucial for transforming complex data into intuitive visual formats, enabling faster insights and better decision-making.
Think-Aloud Protocol
A usability testing method where participants verbalize their thoughts while interacting with a product. Essential for understanding user thought processes and identifying usability issues.
Chaos Theory
The study of dynamic systems that are highly sensitive to initial conditions, leading to unpredictable behavior. Important for recognizing and managing unpredictable elements in design and development processes.
HCI
Human-Computer Interaction (HCI) is the study of designing interfaces and interactions between humans and computers. It ensures that digital products are user-friendly, efficient, and satisfying.
Grit
The perseverance and passion for long-term goals, often seen as a key trait for success. Important for understanding and fostering resilience and persistence in design and product development.
Neuroaesthetics
The study of how the brain perceives and responds to art and design, exploring the neural basis for aesthetic experiences. Important for understanding the neurological underpinnings of aesthetic preferences and enhancing design impact.
Environmental Psychology
The study of the interplay between individuals and their surroundings, including built environments and natural settings. Essential for designing spaces that enhance well-being and productivity.
Behavioral Insights
Practical applications of behavioral science to understand and influence human behavior in various contexts. Crucial for applying scientific insights to design and improve user experiences and outcomes.
Behavioral Game Theory
The study of strategic decision making, incorporating psychological insights into traditional game theory models. Useful for understanding complex user interactions and designing systems that account for strategic behavior.
Behavioral Finance
The study of how psychological influences affect financial behaviors and decision-making. Essential for understanding and influencing financial decision-making and behavior.
Decision Theory
The study of how individuals make choices among alternatives and the principles that guide these choices. Important for designing decision-making processes and interfaces that help users make informed choices.
Data Science
An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Essential for driving data-informed decision making, predicting trends, and uncovering valuable insights in digital product design and development.
XAI
Explainable AI (XAI) are AI systems that provide clear and understandable explanations for their decisions and actions. This transparency is crucial for building trust and confidence in AI applications across various domains.
Intertemporal Choice
The study of how people make choices about what and how much to do at various points in time, often involving trade-offs between costs and benefits occurring at different times. Crucial for designing systems that account for delayed gratification and long-term planning.
Communication Theory
The study of how information is transmitted and received, including the processes and methods that facilitate communication. Important for designing effective communication strategies and user interfaces.
Innovation Theory
The study of how new ideas, products, and processes are developed and brought to market. Essential for fostering creativity and ensuring the continuous improvement and relevance of products.
Theory of Reasoned Action
A psychological theory that predicts an individual's behavior based on their intention, which is influenced by their attitudes and subjective norms. Important for understanding and predicting user behavior and designing interventions to influence actions.
Centre-Stage Effect
The tendency for people to pay more attention to items placed in the center of a visual field. Crucial for designing layouts that maximize visibility and impact of key elements.
Omission Bias
A cognitive bias where people judge harmful actions as worse, or less moral, than equally harmful omissions (inactions). Important for understanding user decision-making and designing systems that mitigate this bias.
CBR
Case-Based Reasoning (CBR) is an AI method that solves new problems based on the solutions of similar past problems. This approach is essential for developing intelligent systems that learn from past experiences to improve problem-solving capabilities.
Subadditivity Effect
A cognitive bias where the total probability assigned to a set of events is less than the sum of the probabilities assigned to each event individually. Important for understanding how users estimate probabilities and make decisions under uncertainty.
Nielsen’s Heuristics
A set of ten general principles for user interface design created by Jakob Nielsen to improve usability. Essential for evaluating and improving user interface designs.
Spotted Pattern
A reading pattern where users focus on individual elements or "spots" of interest on a page, rather than following a linear path. Crucial for designing engaging and attention-grabbing content layouts.