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Distractor Efficiency in an Item Pool for a Statistics Classroom Exam: Assessing Its Relation With Item Cognitive Level Classified According to Bloom’s Taxonomy

Authors: Silvia Testa; Anna Toscano; Anna Toscano; Rosalba Rosato;

Distractor Efficiency in an Item Pool for a Statistics Classroom Exam: Assessing Its Relation With Item Cognitive Level Classified According to Bloom’s Taxonomy

Abstract

Multiple-choice items are one of the most commonly used tools for evaluating students' knowledge and skills. A key aspect of this type of assessment is the presence of functioning distractors, i.e., incorrect alternatives intended to be plausible for students with lower achievement. To our knowledge, no work has investigated the relationship between distractor performance and the complexity of the cognitive task required to give the correct answer. The aim of this study was to investigate this relation, employing the first three levels of Bloom's taxonomy (Knowledge, Comprehension, and Application). Specifically, it was hypothesized that items classified into a higher level of Bloom's classification would show a greater number of functioning distractors. The study involved 174 items administered to a sample of 848 undergraduate psychology students during their statistics exam. Each student received 30 items randomly selected from the 174-item pool. The bivariate results mainly supported the authors' hypothesis: the highest percentage of functioning distractors was observed among the items classified into the Application category (η2 = 0.024 and Phi = 0.25 for the dichotomized measure). When the analysis controlled for other item features, it lost statistical significance, partly because of the confounding effect of item difficulty.

Country
Italy
Keywords

multiple-choice items, distractors, item analysis, Psychology, Rasch model, General Psychology, Bloom’s taxonomy, BF1-990

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
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Top 10%
Top 10%
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