Empirical Estimates of Intercorrelations among the Components of Scores on Multiple-Choice Tests

1966 ◽  
Vol 19 (2) ◽  
pp. 651-654 ◽  
Author(s):  
Donald W. Zimmerman ◽  
Richard H. Williams ◽  
Hubert H. Rehm ◽  
William Elmore

College students were instructed to indicate on various multiple-choice tests whether they “knew the answer” or “guessed” each item, and the results were treated as estimated true and error components of scores. The values of the intercorrelations of these components were similar to those given by a computer program described previously. The values found for all tests were consistent with the assumption that test scores consist of both independent and non-independent components of error and that the non-independent error component is relatively large.

Author(s):  
David DiBattista ◽  
Laura Kurzawa

Because multiple-choice testing is so widespread in higher education, we assessed the quality of items used on classroom tests by carrying out a statistical item analysis. We examined undergraduates’ responses to 1198 multiple-choice items on sixteen classroom tests in various disciplines. The mean item discrimination coefficient was +0.25, with more than 30% of items having unsatisfactory coefficients less than +0.20. Of the 3819 distractors, 45% were flawed either because less than 5% of examinees selected them or because their selection was positively rather than negatively correlated with test scores. In three tests, more than 40% of the items had an unsatisfactory discrimination coefficient, and in six tests, more than half of the distractors were flawed. Discriminatory power suffered dramatically when the selection of one or more distractors was positively correlated with test scores, but it was only minimally affected by the presence of distractors that were selected by less than 5% of examinees. Our findings indicate that there is considerable room for improvement in the quality of many multiple-choice tests. We suggest that instructors consider improving the quality of their multiple-choice tests by conducting an item analysis and by modifying distractors that impair the discriminatory power of items. Étant donné que les examens à choix multiple sont tellement généralisés dans l’enseignement supérieur, nous avons effectué une analyse statistique des items utilisés dans les examens en classe afin d’en évaluer la qualité. Nous avons analysé les réponses des étudiants de premier cycle à 1198 questions à choix multiples dans 16 examens effectués en classe dans diverses disciplines. Le coefficient moyen de discrimination de l’item était +0.25. Plus de 30 % des items avaient des coefficients insatisfaisants inférieurs à + 0.20. Sur les 3819 distracteurs, 45 % étaient imparfaits parce que moins de 5 % des étudiants les ont choisis ou à cause d’une corrélation négative plutôt que positive avec les résultats des examens. Dans trois examens, le coefficient de discrimination de plus de 40 % des items était insatisfaisant et dans six examens, plus de la moitié des distracteurs était imparfaits. Le pouvoir de discrimination était considérablement affecté en cas de corrélation positive entre un distracteur ou plus et les résultatsde l’examen, mais la présence de distracteurs choisis par moins de 5 % des étudiants avait une influence minime sur ce pouvoir. Nos résultats indiquent que les examens à choix multiple peuvent être considérablement améliorés. Nous suggérons que les enseignants procèdent à une analyse des items et modifient les distracteurs qui compromettent le pouvoir de discrimination des items.


1982 ◽  
Vol 51 (2) ◽  
pp. 523-527 ◽  
Author(s):  
Lillian M. Range ◽  
Howard N. Anderson ◽  
Andrea L. Wesley

On multiple-choice tests, 52 anxious college students changed answers significantly more often than nonanxious students. Nondepressed students, and those who held a positive view of the nature of man, were more successful in changing answers. Student's who made B's were more successful than C students in changing answers.


2010 ◽  
Vol 26 (4) ◽  
pp. 302-308 ◽  
Author(s):  
Klaus D. Kubinger ◽  
Christine Wolfsbauer

Test authors may think about adding the response options “I don’t know the solution” and “none of the other options is correct” in order to reduce a high guessing probability for multiple-choice items. However, in this paper it was expected that different types of personality would use these response options differently, as a consequence of which they would do more or less guessing and, therefore, achieve higher or lower test scores, on average. An experiment was performed based on randomizing participants into two groups, one of them being warned that it is better to admit being unable to solve the item, and the participants were classified according to their personality scores into high-, medium-, and low-scoring. Multivariate analyses of variance (195 pupils between 14 and 19 years) disclosed that only Openness to Experience showed any (moderate) effect, and even this only for a single subtest (Cattell’s culture fair test).


2015 ◽  
Vol 166 (2) ◽  
pp. 278-306 ◽  
Author(s):  
Henrik Gyllstad ◽  
Laura Vilkaitė ◽  
Norbert Schmitt

In most tests of vocabulary size, knowledge is assessed through multiple-choice formats. Despite advantages such as ease of scoring, multiple-choice tests (MCT) are accompanied with problems. One of the more central issues has to do with guessing and the presence of other construct-irrelevant strategies that can lead to overestimation of scores. A further challenge when designing vocabulary size tests is that of sampling rate. How many words constitute a representative sample of the underlying population of words that the test is intended to measure? This paper addresses these two issues through a case study based on data from a recent and increasingly used MCT of vocabulary size: the Vocabulary Size Test. Using a criterion-related validity approach, our results show that for multiple-choice items sampled from this test, there is a discrepancy between the test scores and the scores obtained from the criterion measure, and that a higher sampling rate would be needed in order to better represent knowledge of the underlying population of words. We offer two main interpretations of these results, and discuss their implications for the construction and use of vocabulary size tests.


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