Suppr超能文献

来自古吉拉特邦艾哈迈达巴德市医学生评估的题目及测试分析,以识别高质量的多项选择题(MCQs)

Item and Test Analysis to Identify Quality Multiple Choice Questions (MCQs) from an Assessment of Medical Students of Ahmedabad, Gujarat.

作者信息

Gajjar Sanju, Sharma Rashmi, Kumar Pradeep, Rana Manish

机构信息

Department of Community Medicine, Gujarat Medical Education and Research Society Medical College, Sola, Ahemdabad, Gujarat, India.

出版信息

Indian J Community Med. 2014 Jan;39(1):17-20. doi: 10.4103/0970-0218.126347.

Abstract

BACKGROUND

Multiple choice questions (MCQs) are frequently used to assess students in different educational streams for their objectivity and wide reach of coverage in less time. However, the MCQs to be used must be of quality which depends upon its difficulty index (DIF I), discrimination index (DI) and distracter efficiency (DE).

OBJECTIVE

To evaluate MCQs or items and develop a pool of valid items by assessing with DIF I, DI and DE and also to revise/ store or discard items based on obtained results.

SETTINGS

Study was conducted in a medical school of Ahmedabad.

MATERIALS AND METHODS

An internal examination in Community Medicine was conducted after 40 hours teaching during 1(st) MBBS which was attended by 148 out of 150 students. Total 50 MCQs or items and 150 distractors were analyzed.

STATISTICAL ANALYSIS

Data was entered and analyzed in MS Excel 2007 and simple proportions, mean, standard deviations, coefficient of variation were calculated and unpaired t test was applied.

RESULTS

Out of 50 items, 24 had "good to excellent" DIF I (31 - 60%) and 15 had "good to excellent" DI (> 0.25). Mean DE was 88.6% considered as ideal/ acceptable and non functional distractors (NFD) were only 11.4%. Mean DI was 0.14. Poor DI (< 0.15) with negative DI in 10 items indicates poor preparedness of students and some issues with framing of at least some of the MCQs. Increased proportion of NFDs (incorrect alternatives selected by < 5% students) in an item decrease DE and makes it easier. There were 15 items with 17 NFDs, while rest items did not have any NFD with mean DE of 100%.

CONCLUSION

Study emphasizes the selection of quality MCQs which truly assess the knowledge and are able to differentiate the students of different abilities in correct manner.

摘要

背景

多项选择题(MCQs)常用于评估不同教育阶段的学生,因其具有客观性且能在较短时间内覆盖广泛内容。然而,所使用的多项选择题必须具备质量,这取决于其难度指数(DIF I)、区分指数(DI)和干扰项效率(DE)。

目的

通过评估DIF I、DI和DE来评估多项选择题或题目,并开发一批有效的题目,同时根据所得结果对题目进行修订、存储或舍弃。

地点

研究在艾哈迈达巴德的一所医学院进行。

材料与方法

在医学学士课程第一年40小时教学后,进行了社区医学内部考试,150名学生中有148名参加。共分析了50道多项选择题或题目以及150个干扰项。

统计分析

数据录入并在MS Excel 2007中进行分析,计算简单比例、均值、标准差、变异系数,并应用非配对t检验。

结果

在50道题目中,24道具有“良好至优秀”的DIF I(31%-60%),15道具有“良好至优秀”的DI(>0.25)。平均DE为88.6%,被认为是理想/可接受的,非功能性干扰项(NFD)仅为11.4%。平均DI为0.14。10道题目中DI较差(<0.15)且为负DI,表明学生准备不足,至少部分多项选择题的出题存在一些问题。一道题目中NFDs(被<5%的学生选择的错误选项)比例增加会降低DE并使其更容易。有15道题目有17个NFD,而其余题目没有任何NFD,平均DE为100%。

结论

研究强调选择高质量的多项选择题,这些题目能真正评估知识,并能以正确方式区分不同能力的学生。

相似文献

2
Item analysis of in use multiple choice questions in pharmacology.
Int J Appl Basic Med Res. 2016 Jul-Sep;6(3):170-3. doi: 10.4103/2229-516X.186965.
4
Item analysis of multiple choice questions: A quality assurance test for an assessment tool.
Med J Armed Forces India. 2021 Feb;77(Suppl 1):S85-S89. doi: 10.1016/j.mjafi.2020.11.007. Epub 2021 Feb 2.
7
Item Analysis of Single Best Response Type Multiple Choice Questions for Formative Assessment in Obstetrics and Gynaecology.
J Obstet Gynaecol India. 2024 Jun;74(3):256-264. doi: 10.1007/s13224-023-01904-2. Epub 2024 Feb 20.
10
Nonfunctional distractor analysis: An indicator for quality of Multiple choice questions.
Pak J Med Sci. 2020 Jul-Aug;36(5):982-986. doi: 10.12669/pjms.36.5.2439.

引用本文的文献

1
The Generation and Use of Medical MCQs: A Narrative Review.
Adv Med Educ Pract. 2025 Aug 5;16:1331-1340. doi: 10.2147/AMEP.S513119. eCollection 2025.
2
5
Item Analysis of Single Best Response Type Multiple Choice Questions for Formative Assessment in Obstetrics and Gynaecology.
J Obstet Gynaecol India. 2024 Jun;74(3):256-264. doi: 10.1007/s13224-023-01904-2. Epub 2024 Feb 20.
6
Comparing students' performance in self-directed and directed self-learning in College of Medicine, University of Bisha.
J Taibah Univ Med Sci. 2024 May 15;19(3):696-704. doi: 10.1016/j.jtumed.2024.05.003. eCollection 2024 Jun.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验