Multiple-Choice Item Distractor Development Using Topic Modeling Approaches.

ABSTRACT: Writing a high-quality, multiple-choice test item is a complex process. Creating plausible but incorrect options for each item poses significant challenges for the content specialist because this task is often undertaken without implementing a systematic method. In the current study, we describe and demonstrate a systematic method for creating plausible but incorrect options, also called distractors, based on students' misconceptions. These misconceptions are extracted from the labeled written responses. One thousand five hundred and fifteen written responses from an existing constructed-response item in Biology from Grade 10 students were used to demonstrate the method. Using a topic modeling procedure commonly used with machine learning and natural language processing called latent diric

SUBMITTER: Shin J 

PROVIDER: S-EPMC6524712 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature