Validity, in the context of testing and assessment, refers to the extent to which a test measures what it is supposed to measure. Establishing validity is crucial for ensuring that test results are meaningful and can be used to make informed decisions. The basic principles of validity are typically represented by different types of evidence. These evidences provide a comprehensive picture of a test's validity.
Here are the five key sources of validity evidence:
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Evidence Based on Test Content: This refers to how well the content of the test represents the domain it is intended to cover. It involves examining the test items to ensure they are relevant to the construct being measured and that they cover all important aspects of that construct. A panel of experts often reviews the test content to determine its appropriateness and comprehensiveness.
- Example: A mathematics test designed to assess algebra skills should include questions that cover all key algebra topics, such as solving equations, graphing functions, and working with polynomials.
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Evidence Based on Response Processes: This examines the cognitive processes that test-takers use when responding to the test questions. It's important to ensure that test-takers are engaging in the intended cognitive processes, rather than relying on irrelevant strategies or factors. Methods for gathering this evidence include think-aloud protocols, interviews, and observations.
- Example: If a reading comprehension test is designed to assess deep understanding, evidence should indicate that test-takers are actively analyzing and interpreting the text, rather than simply identifying keywords or guessing.
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Evidence Based on Internal Structure: This evaluates the relationships among the test items themselves. Statistical techniques like factor analysis are used to determine whether the test items group together in a way that aligns with the theoretical construct being measured. A high degree of internal consistency suggests that the items are measuring a single, unified construct.
- Example: If a test is designed to measure anxiety, the items should be highly correlated with each other, indicating that they are all measuring different facets of the same underlying construct.
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Evidence Based on Relations to Other Variables: This examines the relationship between the test scores and other variables that are theoretically related to the construct being measured. This can include correlations with other tests, measures of performance, or demographic variables. Types of evidence include:
- Convergent validity: The test should correlate highly with other tests that measure the same or similar constructs.
- Discriminant validity: The test should not correlate highly with tests that measure unrelated constructs.
- Concurrent validity: The test should correlate with a criterion measure administered at the same time.
- Predictive validity: The test should predict future performance on a related criterion.
- Example: A new test of job satisfaction should correlate positively with existing measures of job satisfaction (convergent validity) and negatively with measures of burnout (discriminant validity). It should also predict future job performance (predictive validity).
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Evidence Based on Consequences of Testing: This explores the intended and unintended consequences of using the test. It's important to consider the potential impact of the test on individuals, groups, and institutions, and to ensure that the benefits of using the test outweigh any potential negative consequences.
- Example: If a high-stakes test is used to determine college admissions, it's important to consider whether the test is fair to all demographic groups and whether it leads to unintended consequences such as narrowing the curriculum or increasing test anxiety.
In summary, validity is not a single property of a test but rather an ongoing process of gathering evidence to support the interpretations and uses of test scores. By considering evidence from these five sources, test developers and users can build a strong case for the validity of their assessments.
