Solving measurement problems with an answer-until-correct scoring procedure
1981
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Solving measurement problems with an answer-until-correct scoring procedure
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1981
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Abstract
Answer-until-correct (AUC) tests have been in use
for some time. Pressey (1950) pointed to their advantages
in enhancing learning, and Brown (1965)
proposed a scoring procedure for AUC tests that
appears to increase reliability (Gilman & Ferry,
1972; Hanna, 1975). This paper describes a new
scoring procedure for AUC tests that (1) makes it
possible to determine whether guessing is at random,
(2) gives a measure of how "far away" guessing
is from being random, (3) corrects observed test
scores for partial information, and (4) yields a measure
of how well an item reveals whether an examinee
knows or does not know the correct response.
In addition, the paper derives the optimal
linear estimate (under squared-error loss) of true
score that is corrected for partial information, as
well as another formula score under the assumption
that the Dirichlet-multinomial model holds. Once
certain parameters are estimated, the latter formula
score makes it possible to correct for partial information
using only the examinee’s usual number-correct
observed score. The importance of this formula
score is discussed. Finally, various statistical
techniques are described that can be used to check
the assumptions underlying the proposed scoring
procedure.
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Wilcox, Rand R. (1981). Solving measurement problems with an answer-until-correct scoring procedure. Applied Psychological Measurement, 5, 399-414. doi:10.1177/014662168100500313
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doi:10.1177/014662168100500313
Suggested citation
Wilcox, Rand R.. (1981). Solving measurement problems with an answer-until-correct scoring procedure. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/100416.
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