Item-Writing Practice and Evidence

Rodriguez, Michael C.

doi:10.1007/978-1-4419-9356-4_11

Cited by 9 publications

(7 citation statements)

References 23 publications

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“…Item-writing guides suggested avoiding this response option ( Haladyna and Rodriguez, 2013 ; Oermann and Gaberson, 2013 ), the work of DiBattista et al (2014) revealed that using NOTA as a distractor does not change item difficulty compared with that of standard-format items that do not include NOTA. Moreover, Rodriguez (2011) and Caldwell and Pate (2013) showed that items containing NOTA as the correct alternative increased item difficulty but not discrimination power.…”

Section: Introductionmentioning

confidence: 99%

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

2018

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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.

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Section: Introductionmentioning

confidence: 99%

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

2018

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“…We want to avoid distractions and unnecessary words for students who generally are poor readers and have a history of poor test performances. By having fewer answer choices and emphasizing the attraction aspect of distractors, item reliability and test score validity can be improved for all students, not just those with disabilities (Rodriguez, 2009(Rodriguez, , 2011.…”

Section: Item Accessibilitymentioning

confidence: 99%

Distractor Functioning in Modified Items for Test Accessibility

2014

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Effective distractors in multiple-choice items should attract lower ability students, those with misconceptions or limited knowledge and skills, because they are based on common misconceptions or errors in logic. A large, multi-state data set collected for a quasi-experimental study on test modifications was analyzed to measure the impact on distractor functioning. The key modification of interest was the removal of the weakest of three distractors, from 39 items in reading and 39 items in mathematics. Distractor functioning was neither systematically improved nor systematically weakened through the modification process. However, more than 70% of the distractors became more discriminating. A moderate correlation between distractor selection rate and distractor discrimination, in mathematics, may have indicated that the modified items were being missed by the appropriate students. Implications of these findings for test developers are discussed.

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“…In other words, the primary role of formative assessment is diagnostic -to inform the instructor what each student knows or does not know over some area of content. While there are numerous ways to assess students' knowledge, multiple-choice tests are the most widely used assessments in K-16 as they can be the most efficient to administer while simultaneously being quick and objective to grade (Rodriguez, 2011;Haladyna & Rodriguez, 2013). We use a typical College Algebra item to contextualize multiple-choice item terminology in mathematics.…”

Section: Introductionmentioning

confidence: 99%

Creating Diagnostic Assessments

Chamberlain

Jeter

2020

JAHE

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The goal of this paper is to propose a new method to generate multiple-choice items that can make creating quality assessments faster and more efficient, solving a practical issue that many instructors face. There are currently no systematic, efficient methods available to generate quality distractors (plausible but incorrect options that students choose), which are necessary for multiple-choice assessments that accurately assess students' knowledge. We propose two methods to use technology to generate quality multiplechoice assessments: (1) manipulating the mathematical problem to emulate common student misconceptions or errors and (2) disguising options to protect the integrity of multiple-choice tests. By linking options to common student misconceptions and errors, instructors can potentially use multiple-choice assessments as personalized diagnostic tools that can target and modify underlying misconceptions. Moreover, using technology to generate these quality distractors would allow for assessments to be developed efficiently, in terms of both time and resources. The method to disguise the options generated would have the added benefit of preventing students from working backwards from options to solution and thus would protect the integrity of the assessment. Preliminary results are included to exhibit the effectiveness of the proposed methods.

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Item-Writing Practice and Evidence

Cited by 9 publications

References 23 publications

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

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

Distractor Functioning in Modified Items for Test Accessibility

Creating Diagnostic Assessments

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