Journal of Educational Evaluation for Health Professions

Software report

Introduction to the LIVECAT web-based computerized adaptive testing platform: Dong Gi Seo, Jeongwook Choi; J Educ Eval Health Prof. 2020;17:27. Published online September 29, 2020; DOI: https://doi.org/10.3352/jeehp.2020.17.27

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This study introduces LIVECAT, a web-based computerized adaptive testing platform. This platform provides many functions, including writing item content, managing an item bank, creating and administering a test, reporting test results, and providing information about a test and examinees. The LIVECAT provides examination administrators with an easy and flexible environment for composing and managing examinations. It is available at http://www.thecatkorea.com/. Several tools were used to program LIVECAT, as follows: operating system, Amazon Linux; web server, nginx 1.18; WAS, Apache Tomcat 8.5; database, Amazon RDMS—Maria DB; and languages, JAVA8, HTML5/CSS, Javascript, and jQuery. The LIVECAT platform can be used to implement several item response theory (IRT) models such as the Rasch and 1-, 2-, 3-parameter logistic models. The administrator can choose a specific model of test construction in LIVECAT. Multimedia data such as images, audio files, and movies can be uploaded to items in LIVECAT. Two scoring methods (maximum likelihood estimation and expected a posteriori) are available in LIVECAT and the maximum Fisher information item selection method is applied to every IRT model in LIVECAT. The LIVECAT platform showed equal or better performance compared with a conventional test platform. The LIVECAT platform enables users without psychometric expertise to easily implement and perform computerized adaptive testing at their institutions. The most recent LIVECAT version only provides a dichotomous item response model and the basic components of CAT. Shortly, LIVECAT will include advanced functions, such as polytomous item response models, weighted likelihood estimation method, and content balancing method.

Citations

Citations to this article as recorded by

Presidential address: improving item validity and adopting computer-based testing, clinical skills assessments, artificial intelligence, and virtual reality in health professions licensing examinations in Korea
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Review

Components of the item selection algorithm in computerized adaptive testing: Kyung (Chris) Tyek Han; J Educ Eval Health Prof. 2018;15:7. Published online March 24, 2018; DOI: https://doi.org/10.3352/jeehp.2018.15.7

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Abstract PDF Supplementary Material

Computerized adaptive testing (CAT) greatly improves measurement efficiency in high-stakes testing operations through the selection and administration of test items with the difficulty level that is most relevant to each individual test taker. This paper explains the 3 components of a conventional CAT item selection algorithm: test content balancing, the item selection criterion, and item exposure control. Several noteworthy methodologies underlie each component. The test script method and constrained CAT method are used for test content balancing. Item selection criteria include the maximized Fisher information criterion, the b-matching method, the astratification method, the weighted likelihood information criterion, the efficiency balanced information criterion, and the KullbackLeibler information criterion. The randomesque method, the Sympson-Hetter method, the unconditional and conditional multinomial methods, and the fade-away method are used for item exposure control. Several holistic approaches to CAT use automated test assembly methods, such as the shadow test approach and the weighted deviation model. Item usage and exposure count vary depending on the item selection criterion and exposure control method. Finally, other important factors to consider when determining an appropriate CAT design are the computer resources requirement, the size of item pools, and the test length. The logic of CAT is now being adopted in the field of adaptive learning, which integrates the learning aspect and the (formative) assessment aspect of education into a continuous, individualized learning experience. Therefore, the algorithms and technologies described in this review may be able to help medical health educators and high-stakes test developers to adopt CAT more actively and efficiently.

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Research Article

Estimation of an Examinee's Ability in the Web-Based Computerized Adaptive Testing Program IRT-CAT: Yoon-Hwan Lee, Jung-Ho Park, In-Yong Park; J Educ Eval Health Prof. 2006;3:4. Published online November 22, 2006; DOI: https://doi.org/10.3352/jeehp.2006.3.4

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Abstract PDF

We developed a program to estimate an examinee's ability in order to provide freely available access to a web-based computerized adaptive testing (CAT) program. We used PHP and Java Script as the program languages, PostgresSQL as the database management system on an Apache web server and Linux as the operating system. A system which allows for user input and searching within inputted items and creates tests was constructed. We performed an ability estimation on each test based on a Rasch model and 2- or 3-parametric logistic models. Our system provides an algorithm for a web-based CAT, replacing previous personal computer-based ones, and makes it possible to estimate an examinee?占퐏 ability immediately at the end of test.

Citations

Citations to this article as recorded by

Analysis on Validity and Academic Competency of Mock Test for Korean Medicine National Licensing Examination Using Item Response Theory
Han Chae, Eunbyul Cho, SeonKyoung Kim, DaHye Choi, Seul Lee
Keimyung Medical Journal.2023; 42(1): 7. CrossRef
Accuracy and Efficiency of Web-based Assessment Platform (LIVECAT) for Computerized Adaptive Testing
Do-Gyeong Kim, Dong-Gi Seo
The Journal of Korean Institute of Information Technology.2020; 18(4): 77. CrossRef
Computer‐Based Testing and Construction of an Item Bank Database for Medical Education in Korea
Sun Huh
Korean Medical Education Review.2014; 16(1): 11. CrossRef
Can computerized tests be introduced to the Korean Medical Licensing Examination?
Sun Huh
Journal of the Korean Medical Association.2012; 55(2): 124. CrossRef
Application of Computerized Adaptive Testing in Medical Education
Sun Huh
Korean Journal of Medical Education.2009; 21(2): 97. CrossRef

Original Articles

Correlations between the scores of computerized adaptive testing, paper and pencil tests, and the Korean Medical Licensing Examination: Mee Young Kim, Yoon Hwan Lee, Sun Huh; J Educ Eval Health Prof. 2005;2(1):113-118. Published online June 30, 2005; DOI: https://doi.org/10.3352/jeehp.2005.2.1.113

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Abstract PDF

To evaluate the usefulness of computerized adaptive testing (CAT) in medical school, the General Examination for senior medical students was administered as a paper and pencil test (P&P) and using CAT. The General Examination is a graduate examination, which is also a preliminary examination for the Korean Medical Licensing Examination (KMLE). The correlations between the results of the CAT and P&P and KMLE were analyzed. The correlation between the CAT and P&P was 0.8013 (p=0.000); that between the CAT and P&P was 0.7861 (p=0.000); and that between the CAT and KMLE was 0.6436 (p=0.000). Six out of 12 students with an ability estimate below 0.52 failed the KMLE. The results showed that CAT could replace P&P in medical school. The ability of CAT to predict whether students would pass the KMLE was 0.5 when the criterion of the theta value was set at -0.52 that was chosen arbitrarily for the prediction of pass or failure.

Citations

Citations to this article as recorded by

Analysis on Validity and Academic Competency of Mock Test for Korean Medicine National Licensing Examination Using Item Response Theory
Han Chae, Eunbyul Cho, SeonKyoung Kim, DaHye Choi, Seul Lee
Keimyung Medical Journal.2023; 42(1): 7. CrossRef
Application of Computerized Adaptive Testing in Medical Education
Sun Huh
Korean Journal of Medical Education.2009; 21(2): 97. CrossRef
Estimation of an Examinee's Ability in the Web-Based Computerized Adaptive Testing Program IRT-CAT
Yoon-Hwan Lee, Jung-Ho Park, In-Yong Park
Journal of Educational Evaluation for Health Professions.2006; 3: 4. CrossRef

Students' Attitude toward and Acceptability of Computerized Adaptive Testing in Medical School and their Effect on the Examinees' Ability: Mee Young Kim, Sun Huh; J Educ Eval Health Prof. 2005;2(1):105-111. Published online June 30, 2005; DOI: https://doi.org/10.3352/jeehp.2005.2.1.105

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Abstract PDF

An examinee's ability can be evaluated precisely using computerized adaptive testing (CAT), which is shorter than written tests and more efficient in terms of the duration of the examination. We used CAT for the second General Examination of 98 senior students in medical college on November 27, 2004. We prepared 1,050 pre-calibrated test items according to item response theory, which had been used for the General Examination administered to senior students in 2003. The computer was programmed to pose questions until the standard error of the ability estimate was smaller than 0.01. To determine the students' attitude toward and evaluation of CAT, we conducted surveys before and after the examination, via the Web. The mean of the students' ability estimates was 0.3513 and its standard deviation was 0.9097 (range -2.4680 to +2.5310). There was no significant difference in the ability estimates according to the responses of students to items concerning their experience with CAT, their ability to use a computer, or their anxiety before and after the examination (p>0.05). Many students were unhappy that they could not recheck their responses (49%), and some stated that there were too few examination items (24%). Of the students, 79 % had no complaints concerning using a computer and 63% wanted to expand the use of CAT. These results indicate that CAT can be implemented in medical schools without causing difficulties for users.

Citations

Citations to this article as recorded by

Computer‐Based Testing and Construction of an Item Bank Database for Medical Education in Korea
Sun Huh
Korean Medical Education Review.2014; 16(1): 11. CrossRef
Can computerized tests be introduced to the Korean Medical Licensing Examination?
Sun Huh
Journal of the Korean Medical Association.2012; 55(2): 124. CrossRef
Application of Computerized Adaptive Testing in Medical Education
Sun Huh
Korean Journal of Medical Education.2009; 21(2): 97. CrossRef

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