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D293 Section 4

Assessment an Learning Analytics Section 4 "Bias & Accessibility"

PromptAnswer
Why Should We Mitigate Bias? It Ensures Accurate Measurement, Promotes Equity, Provides Valid Data
Construct Validity Bias Inaccuracy in how an assessment measures what it is intended to. Does it accurately measure knowledge or skills? How we construct "build" our assessments.
Content Validity Bias Failure of an assessment to fully represent its subject matter. {Content that was not taught} Example: World History Questions on a US History Test
Item Selection Bias Biased Test Item choices that favor or disadvantage certain groups. Example: Math Word Problems with Football Jargon.
Predictive Validity Bias Inaccuracy in forecasting future outcomes across different groups. Does it accurately predict future abilities? Example: Using a written test instead of a Driving Exam to predict driving skill.
Irrelevant Knowledge Any uncommon information that is unrelated to the assessments targeted learning objectives and goals.
Cognitive Load Overwhelming the working memory's limited capacity handle only a few bits of information at a time.
Define: UDL Universal Design for Learning
P.O.U.R. Principles Perceivable, Operable, Understandable, Robust
P-Perceivable Information and UI components must be presented to users in way they can perceive using their 5 senses. Example: Make it accessible to learners who are hard of hearing or color blind
O-Operable UI components and navigation must be usable. Example if there is a drag and drop, have an alternative method for those who cant use a mouse. Another Example: Text-To-Speech
U-Understandable Information and UI navigation must be understandable, clear, easy to navigate, and use language at the appropriate grade level.
R-Robust Content must be able to be accessed across multiple platforms and devices.
Created by: rebeccan
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