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|Department:||Department of Computing||en_US|
|Title:||Quiz Markup Language (QuizML)||en_US|
|Abstract:||This dissertation defines a new markup language namely Quiz Markup Language (QuizML). QuizML is an XML application for describing the semantics of quizzes and questions used in computerized training systems. It intends to facilitate the exchange and reuse of testing material by providing a standard file format for communication among different training tools. QuizML can be used to encode both traditional fixed-length testing and computerized adaptive testing (CAT). In fixed-length testing, all questions are selected beforehand and examinees are forced to answer each and every question. By contrast, CAT tailors itself to the ability of an individual examinee and selects questions according to the examinee's responses. This approach aims to minimize the test length in terms of the number of questions and time, and address the existing problems of fixed-length testing. In order to apply CAT in practice, the three-parameter IRT (Item Response Theory) model is employed in this dissertation. QuizML currently supports six different kinds of questions, including true/false, multiple-choice, poly-choice, fill-in-blank, image hotspot and matching. With the extensibility of QuizML, other kinds of questions can be easily included in the future. Besides, a web-based examination system, called QMS (QuizML Management System), is implemented to demonstrate how our works can ease the reuse of questions and assist users to prepare questions and adaptive tests through the Internet.||en_US|
|Pages:||vii, 84 leaves : ill. ; 30 cm||en_US|
|Subject:||XML (Document markup language)||en_US|
|Subject:||Hong Kong Polytechnic University -- Dissertations||en_US|
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