Evaluating Functional and Non-Functional Distractors and Their Relationship with Difficulty and Discrimination Indices in Four-Option Multiple-Choice Questions
-
Published:2022-12-27
Issue:4
Volume:14
Page:55-62
-
ISSN:2180-1932
-
Container-title:Education in Medicine Journal
-
language:
-
Short-container-title:EIMJ
Author:
Shakurnia Abdolhussein, ,Ghafourian Mehri,Khodadadi Ali,Ghadiri Ata,Amari Afshin,Shariffat Moosa, , , , ,
Abstract
Multiple-choice questions-one best answer (MCQ-OBA) is the most frequently accepted assessment tool in Iran’s medical universities. Writing functional distractors (FDs) is an important aspect of framing MCQ-OBA. This study aimed to assess FDs and non-functional distractors (NFDs) in MCQ-OBA and the association of distractor efficiency with difficulty and discrimination indices. This cross-sectional study was conducted at the Department of Immunology, the Ahvaz Jundishapur University of Medical Sciences. A total of 734 MCQ-OBA were reviewed, including 2,936 options (2,202 distractors and 734 correct responses). NFDs were defined as options chosen by <5% of examinees. Of the 734 MCQ-OBAs, 265 (36.1%) had 0 NFDs, 231 (31.5%) had 1 NFD, 146 (19.9%) had 2 NFDs, and 92 (12.5%) had 3 NFDs. The Pearson’s correlation showed a significant relationship between the difficulty index and the number of NFDs (r = 0.453; P < 0.0001). However, the correlation between the discrimination index and the number of NFDs was insignificant (r = 0.055; P = 0.135). The findings revealed that NFDs inversely affected the test quality of items. Items with more NFDs were easier and had poorer discriminatory power. The distractor function analysis and revision of NFDs serve as an important method to improve the quality of MCQ-OBA.
Publisher
Penerbit Universiti Sains Malaysia
Subject
Nursing (miscellaneous),Health Professions (miscellaneous),Education,Medicine (miscellaneous)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Q-GENius: A GPT Based Modified MCQ Generator for Identifying Learner Deficiency;Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky;2023