The knowledge or random guessing model for matching tests

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The knowledge or random guessing model for matching tests

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1992

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The knowledge or random guessing (KRG) model was applied to matching tests. A matching test typically consists of two lists of alternatives. The response alternatives in the first list might consist of several terms to be defined, and the question alternatives in the second list would then consist of the definitions. Examinees are instructed to match the question alternatives to the response alternatives. According to the KRG model, if an examinee knows the correct answer, the correct answer will be chosen; however, if the examinee does not know the correct match, he/she will select the question alternative by guessing at random. Reliability formulas for the number of correct matchings based on the KRG model are given by Zimmerman and Williams (1982). Before applying these formulas, an appropriate statistical test should be used to test whether the model holds. A goodness-of-fit test is developed that is especially sensitive to the assumption of random guessing. Moreover, a simplified version of the model is presented in which the alternatives are ordered according to a Guttman scale. Three examples are given in which the model is applied to real data. It appears that in many cases examinees use coping strategies that violate the assumption of random guessing. A suggestion is made for the development of a somewhat more complex model that takes into account examinee coping strategies and that can be considered an extension of the KRG model. Index terms: achievement testing, guessing in matching tests, knowledge or random guessing model, matching tests.

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Van der Ven, A. H & Gremmen, F. M. (1992). The knowledge or random guessing model for matching tests. Applied Psychological Measurement, 16, 177-194. doi:10.1177/014662169201600207

Suggested citation

Van der Ven, A. H. G. S.; Gremmen, F. M.. (1992). The knowledge or random guessing model for matching tests. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/115647.

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