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 multiple-choice 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.
The Journal of Assessment in Higher Education
Scholarly Commons Citation
Chamberlain, D., & Jeter, R. (2020). Creating Diagnostic Assessments: Automated Distractor Generation with Integrity. The Journal of Assessment in Higher Education, 1(1). https://doi.org/10.32473/jahe.v1i1.116892