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.
23 topics found for:
“assessment accuracy”
Dunning-Kruger Effect
A cognitive bias where individuals with low ability at a task overestimate their ability, while experts underestimate their competence. Crucial for designers to create educational content and user interfaces that accommodate varying levels of user expertise.
Overconfidence Effect
A cognitive bias where a person's subjective confidence in their judgments is greater than their objective accuracy. Crucial for understanding user decision-making and designing systems that account for overconfidence.
Illusory Superiority
A cognitive bias where individuals overestimate their own abilities, qualities, or performance relative to others. Important for understanding user self-perception and designing systems that account for inflated self-assessments.
A/A Testing
A method of testing two identical versions of a webpage or app to ensure the accuracy of the testing tool. Important for validating the effectiveness of A/B testing tools and processes.
Base Rate Fallacy
A cognitive bias where people ignore general statistical information in favor of specific information. Critical for designers to use general statistical information to improve decision-making accuracy and avoid bias.
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.
Illusion of Validity
A cognitive bias where individuals overestimate the accuracy of their judgments, especially when they have a lot of information. Important for understanding and mitigating overconfidence in user decision-making.
Certainty Effect
A cognitive bias where people give greater weight to outcomes that are certain compared to those that are merely probable. Important for designers to consider how users weigh certain outcomes more heavily in their decision-making.
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.
Surrogation
The process by which a measure or metric comes to replace the underlying objective it is intended to represent, leading to distorted decision-making. Important for ensuring that metrics accurately reflect true objectives and designing systems that prevent metric manipulation.
Requirements Gathering
The process of collecting and documenting the needs and expectations of stakeholders for a new or modified product or system. Essential for ensuring that the final product meets user needs and business objectives.
Ratio Bias
A cognitive bias where people judge the likelihood of an event based on its relative size rather than absolute probability. Important for understanding user decision-making biases and designing systems that present information accurately.
Empirical Rule
Also known as the 68-95-99.7 Rule, it states that for a normal distribution, nearly all data will fall within three standard deviations of the mean. Important for understanding the distribution of data and making predictions about data behavior in digital product design.
Category Size Bias
A cognitive bias where people judge the likelihood of an event based on the size of its category rather than its actual probability. Crucial for designers to understand how category size influences user perception and decision-making processes.
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.
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.
ROI
Return on Investment (ROI) is a performance measure used to evaluate the efficiency or profitability of an investment or compare the efficiency of different investments. Crucial for assessing the financial effectiveness of business decisions, projects, or initiatives.
Open Rate
The percentage of email recipients who open a given email. Important for measuring the effectiveness of email marketing campaigns.
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.
Regressive Bias
A cognitive bias where individuals overestimate the likelihood of extreme events regressing to the mean. Crucial for understanding decision-making and judgment under uncertainty.
Pessimism Bias
A cognitive bias that causes people to overestimate the likelihood of negative outcomes. Important for understanding user risk perception and designing systems that address irrational pessimism.
PAR
Performance and Accountability Reporting (PAR) is a comprehensive document that outlines an organization's performance in achieving its goals and its accountability in managing resources. This report is essential for transparency, governance, and continuous improvement.