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The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.
Test validity, validity in educational and psychological testing; Face validity, the property of a test intended to measure something; Construct validity, refers to whether a scale measures or correlates with the theorized psychological construct it measures; Content validity, the extent to which a measure represents all facets of a given construct
Test validity is the extent to which a test (such as a chemical, physical, or scholastic test) accurately measures what it is supposed to measure.In the fields of psychological testing and educational testing, "validity refers to the degree to which evidence and theory support the interpretations of test scores entailed by proposed uses of tests". [1]
The validity of an argument can be tested, proved or disproved, and depends on its logical form. [3] Arguments. Argument terminology used in logic.
Wikipedia allows anonymous editing; contributors (known as "editors") are not required to provide any identification or an email address. A 2009 study of Dartmouth College in the English Wikipedia noted that, contrary to usual social expectations, anonymous editors were some of Wikipedia's most productive contributors of valid content. [32]
Convergent validity refers to the degree to which two measures of constructs that theoretically should be related, are in fact related. In contrast, discriminant validity tests whether concepts or measurements that are supposed to be unrelated are, in fact, unrelated. [19] Take, for example, a construct of general happiness.
Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.
Internal validity, therefore, is more a matter of degree than of either-or, and that is exactly why research designs other than true experiments may also yield results with a high degree of internal validity. In order to allow for inferences with a high degree of internal validity, precautions may be taken during the design of the study.