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Introduction to the LIVECAT web-based computerized adaptive testing platform
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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
- 5,346 View
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- 3 Web of Science
- 3 Crossref
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Abstract
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Supplementary Material - 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.
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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
Hyunjoo Pai
Journal of Educational Evaluation for Health Professions.2023; 20: 8. CrossRef - Patient-reported outcome measures in cancer care: Integration with computerized adaptive testing
Minyu Liang, Zengjie Ye
Asia-Pacific Journal of Oncology Nursing.2023; 10(12): 100323. CrossRef - Development of a character qualities test for medical students in Korea using polytomous item response theory and factor analysis: a preliminary scale development study
Yera Hur, Dong Gi Seo
Journal of Educational Evaluation for Health Professions.2023; 20: 20. CrossRef
- 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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