Automated Item Generation: impact of item variants on performance and standard setting
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Published version
Author(s)
Type
Journal Article
Abstract
Background
Automated Item Generation (AIG) uses computer software to create multiple items from a single question model. There is currently a lack of data looking at whether item variants to a single question result in differences in student performance or human-derived standard setting. The purpose of this study was to use 50 Multiple Choice Questions (MCQs) as models to create four distinct tests which would be standard set and given to final year UK medical students, and then to compare the performance and standard setting data for each.
Methods
Pre-existing questions from the UK Medical Schools Council (MSC) Assessment Alliance item bank, created using traditional item writing techniques, were used to generate four ‘isomorphic’ 50-item MCQ tests using AIG software. Isomorphic questions use the same question template with minor alterations to test the same learning outcome. All UK medical schools were invited to deliver one of the four papers as an online formative assessment for their final year students. Each test was standard set using a modified Angoff method. Thematic analysis was conducted for item variants with high and low levels of variance in facility (for student performance) and average scores (for standard setting).
Results
Two thousand two hundred eighteen students from 12 UK medical schools participated, with each school using one of the four papers. The average facility of the four papers ranged from 0.55–0.61, and the cut score ranged from 0.58–0.61. Twenty item models had a facility difference > 0.15 and 10 item models had a difference in standard setting of > 0.1. Variation in parameters that could alter clinical reasoning strategies had the greatest impact on item facility.
Conclusions
Item facility varied to a greater extent than the standard set. This difference may relate to variants causing greater disruption of clinical reasoning strategies in novice learners compared to experts, but is confounded by the possibility that the performance differences may be explained at school level and therefore warrants further study.
Automated Item Generation (AIG) uses computer software to create multiple items from a single question model. There is currently a lack of data looking at whether item variants to a single question result in differences in student performance or human-derived standard setting. The purpose of this study was to use 50 Multiple Choice Questions (MCQs) as models to create four distinct tests which would be standard set and given to final year UK medical students, and then to compare the performance and standard setting data for each.
Methods
Pre-existing questions from the UK Medical Schools Council (MSC) Assessment Alliance item bank, created using traditional item writing techniques, were used to generate four ‘isomorphic’ 50-item MCQ tests using AIG software. Isomorphic questions use the same question template with minor alterations to test the same learning outcome. All UK medical schools were invited to deliver one of the four papers as an online formative assessment for their final year students. Each test was standard set using a modified Angoff method. Thematic analysis was conducted for item variants with high and low levels of variance in facility (for student performance) and average scores (for standard setting).
Results
Two thousand two hundred eighteen students from 12 UK medical schools participated, with each school using one of the four papers. The average facility of the four papers ranged from 0.55–0.61, and the cut score ranged from 0.58–0.61. Twenty item models had a facility difference > 0.15 and 10 item models had a difference in standard setting of > 0.1. Variation in parameters that could alter clinical reasoning strategies had the greatest impact on item facility.
Conclusions
Item facility varied to a greater extent than the standard set. This difference may relate to variants causing greater disruption of clinical reasoning strategies in novice learners compared to experts, but is confounded by the possibility that the performance differences may be explained at school level and therefore warrants further study.
Date Issued
2023-09-11
Date Acceptance
2023-06-15
Citation
BMC Medical Education, 2023, 23
ISSN
1472-6920
Publisher
BMC
Journal / Book Title
BMC Medical Education
Volume
23
Copyright Statement
© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or
other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this
licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco
mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or
other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this
licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco
mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
License URL
Identifier
https://link.springer.com/article/10.1186/s12909-023-04457-0
Publication Status
Published
Article Number
659
Date Publish Online
2023-09-11