Solving measurement problems with an answer-until-correct scoring procedure

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Solving measurement problems with an answer-until-correct scoring procedure

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1981

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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

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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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