Cargando…

Introduction to the LIVECAT web-based computerized adaptive testing platform

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 LIVECA...

Descripción completa

Detalles Bibliográficos
Autores principales: Seo, Dong Gi, Choi, Jeongwook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Health Personnel Licensing Examination Institute 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657939/
https://www.ncbi.nlm.nih.gov/pubmed/33401349
http://dx.doi.org/10.3352/jeehp.2020.17.27
_version_ 1783608576667811840
author Seo, Dong Gi
Choi, Jeongwook
author_facet Seo, Dong Gi
Choi, Jeongwook
author_sort Seo, Dong Gi
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7657939
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Korea Health Personnel Licensing Examination Institute
record_format MEDLINE/PubMed
spelling pubmed-76579392020-11-18 Introduction to the LIVECAT web-based computerized adaptive testing platform Seo, Dong Gi Choi, Jeongwook J Educ Eval Health Prof Software Report 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. Korea Health Personnel Licensing Examination Institute 2020-09-29 /pmc/articles/PMC7657939/ /pubmed/33401349 http://dx.doi.org/10.3352/jeehp.2020.17.27 Text en © 2020, Korea Health Personnel Licensing Examination Institute This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Report
Seo, Dong Gi
Choi, Jeongwook
Introduction to the LIVECAT web-based computerized adaptive testing platform
title Introduction to the LIVECAT web-based computerized adaptive testing platform
title_full Introduction to the LIVECAT web-based computerized adaptive testing platform
title_fullStr Introduction to the LIVECAT web-based computerized adaptive testing platform
title_full_unstemmed Introduction to the LIVECAT web-based computerized adaptive testing platform
title_short Introduction to the LIVECAT web-based computerized adaptive testing platform
title_sort introduction to the livecat web-based computerized adaptive testing platform
topic Software Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657939/
https://www.ncbi.nlm.nih.gov/pubmed/33401349
http://dx.doi.org/10.3352/jeehp.2020.17.27
work_keys_str_mv AT seodonggi introductiontothelivecatwebbasedcomputerizedadaptivetestingplatform
AT choijeongwook introductiontothelivecatwebbasedcomputerizedadaptivetestingplatform