The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Improving the fairness of multiple-choice questions: a literature review
Abstract
The ubiquity of multiple-choice questions (MCQs) results from their efficiency and hence reliability. Cognitive knowledge assessed by MCQ predicts and correlates well with overall competence and performance but examinees and examiners alike frequently perceive MCQ-based testing as 'unfair'. Fairness is akin to defensibility and is an increasingly important concept in testing. It is dependent on psychometric adequacy, diligence of construction, attention to consequential validity and appropriate standard setting. There is a wealth of evidence that extended matching questions are the fairest format but MCQs should always be combined with practical assessments, as written testing emphasizes learning from written sources.
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Cites
Education and thinking: The role of knowledge.
Glaser, R. (1984) · American Psychologist · doi:10.1037/0003-066x.39.2.93 · Cited by 1,272 · cited 1×
“However, decades of research into reasoning and thinking have unequivocally shown that knowledge of a domain is the single best determinant of expertize (Glaser, 1984).”
BackgroundThe assessment of professional competence: Developments, research and practical implications
Van Der Vleuten, C. P. M. (1996) · Advances in Health Sciences Education · doi:10.1007/bf00596229 · Cited by 1,247
Snyder, B. R. (1973) · The MIT Press eBooks · Cited by 691
The real test bias: Influences of testing on teaching and learning.
Frederiksen, N. (1984) · American Psychologist · doi:10.1037//0003-066x.39.3.193 · Cited by 531
The effect of assessments and examinations on the learning of medical students
NEWBLE, D. I., & JAEGER, K. (1983) · Medical Education · doi:10.1111/j.1365-2923.1983.tb00657.x · Cited by 490
Making Doctors : An Institutional Apprenticeship
(1997) · Bloomsbury Academic eBooks · doi:10.5040/9781474215107 · Cited by 326
A Consumer's Guide to Setting Performance Standards on Criterion-Referenced Tests
Berk, R. A. (1986) · Review of Educational Research · doi:10.2307/1170289 · Cited by 230
Standard setting in medical education
Cusimano, M. D. (1996) · Academic Medicine · doi:10.1097/00001888-199610000-00062 · Cited by 175
AMEE Guide No. 18: Standard setting in student assessment
Ben-David, M. F. (2000) · Medical Teacher · doi:10.1080/01421590078526 · Cited by 174
Extended‐matching items: A practical alternative to free‐response questions
Case, S. M., & Swanson, D. B. (1993) · Teaching and Learning in Medicine · doi:10.1080/10401339309539601 · Cited by 167
Cited by
Item analysis of multiple choice questions: A quality assurance test for an assessment tool
Kumar, D., Jaipurkar, R., Shekhar, A., Sikri, G., & Srinivas, V. (2021) · Medical Journal Armed Forces India · doi:10.1016/j.mjafi.2020.11.007 · Cited by 109
Bottomley, S., & Denny, P. (2011) · Biochemistry and Molecular Biology Education · doi:10.1002/bmb.20526 · Cited by 102
Meo, S. A., Al-Masri, A. A., Alotaibi, M., Meo, M. Z. S., & Meo, M. O. S. (2023) · Healthcare · doi:10.3390/healthcare11142046 · Cited by 74
Generating Multiple Choice Questions for Computing Courses Using Large Language Models
Tran, A., Angelikas, K., Rama, E., Okechukwu, C., Smith, D. H., & MacNeil, S. (2023) · 2023 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie58773.2023.10342898 · Cited by 60
Barriers and facilitators to writing quality items for medical school assessments – a scoping review
Karthikeyan, S., O’Connor, E., & Hu, W. (2019) · BMC Medical Education · doi:10.1186/s12909-019-1544-8 · Cited by 41
Metadata
- Authors
- McCoubrie, P.
- Venue
- Medical Teacher
- Publisher
- Informa UK Limited
- Published
- 2004-12
- Volume
- 26
- Issue
- 8
- Pages
- 709-712
- ISSN
- 0142-159X (ISSN-L)
- 1466-187X
- OpenAlex
- W2077630385
- Cited by
- 313
- References
- 24
- FWCI
- 4.15
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
