10th International
Conference on
Teaching Statistics
8 – 13 July 2018
Kyoto, Japan
Contributed paper list


Contributed Paper C179

 

Examining Distractors in Multiple-Choice Questions for Classroom Assessments: Learning from Psychometrics


Authors

Yan Liu (The University of British Columbia, Canada)
Amery Wu (The University of British Columbia, Canada)
Minjeong Park (The University of British Columbia, Canada)
Ernest Kwan (Carleton University, Canada)

Presenter

Yan Liu (Canada)

Abstract

Psychometric research mainly involves the construction of tests/assessments and the development of techniques to ensure the quality of measurement. However, this field has been focusing more on large-scale tests/assessments. There has been less attention and efforts on classroom assessments. The present study is scoped in a broader goal of bridging psychometric research and classroom assessments. More specifically, we will introduce some psychometric techniques for instructors to examine the distractors in multiple-choice questions, including the most commonly used distractor analysis strategies, including a particular technique, differential option functioning (DOF) based on multinomial logistic regression. DOF is a versatile tool that can help to better understand students’ misconceptions and learning gaps. A demonstration will be provided using an introductory course assessment.