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
Wilcox, Rand R. (1981). Solving measurement problems with an answer-until-correct scoring procedure. Applied Psychological Measurement, 5, 399-414. doi:10.1177/014662168100500313
Wilcox, Rand R..
Solving measurement problems with an answer-until-correct scoring procedure.
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