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LIVECAT 网络版计算机化自适应测试平台简介。

Introduction to the LIVECAT web-based computerized adaptive testing platform.

机构信息

Department of Psychology, College of Social Sciences & Hallym Applied Psychology Institute, Hallym University, Chuncheon, Korea.

The CAT Korea Company, Seoul, Korea.

出版信息

J Educ Eval Health Prof. 2020;17:27. doi: 10.3352/jeehp.2020.17.27. Epub 2020 Sep 29.

Abstract

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.

摘要

本研究介绍了 LIVECAT,一个基于网络的计算机化自适应测试平台。该平台提供了许多功能,包括编写项目内容、管理项目库、创建和管理测试、报告测试结果,以及提供测试和考生信息。LIVECAT 为考试管理员提供了一个编写和管理考试的简单灵活的环境。它可以在 http://www.thecatkorea.com/ 上使用。为了编程 LIVECAT,使用了以下几种工具:操作系统,Amazon Linux;Web 服务器,nginx 1.18;WAS,Apache Tomcat 8.5;数据库,Amazon RDMS-Maria DB;以及语言,JAVA8、HTML5/CSS、Javascript 和 jQuery。LIVECAT 平台可用于实现几种项目反应理论(IRT)模型,如 Rasch 模型和 1-、2-、3-参数逻辑模型。管理员可以在 LIVECAT 中选择特定的测试构建模型。可以将多媒体数据(如图像、音频文件和电影)上传到 LIVECAT 中的项目。LIVECAT 中有两种评分方法(最大似然估计和后验期望),并且在 LIVECAT 中的每个 IRT 模型中都应用了最大 Fisher 信息项目选择方法。LIVECAT 平台的表现与传统测试平台相当或更好。LIVECAT 平台使用户无需心理计量学专业知识即可在其机构中轻松实现和执行计算机化自适应测试。最新的 LIVECAT 版本仅提供二项式项目反应模型和 CAT 的基本组件。不久,LIVECAT 将包括高级功能,如多项式项目反应模型、加权似然估计方法和内容平衡方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9df9/7657939/e534b59c6a44/jeehp-17-27f1.jpg

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