A Web-based Multimedia Computerized Adaptive Testing System--Online Pretest Samples Collecting and Simulating Comparison of Four Ability Estimation Methods
| Autor: | Chia-Chi Mao, 毛家驥 |
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| Rok vydání: | 2005 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 93 This study will explore how to enhance a web-based multimedia computerized adaptive testing (CAT) system. The enhancements of the multimedia CAT system include: 1. Online pretest samples collecting: Besides online pretest samples collecting, an offline pretest samples accumulation is accomplished by the files exporting and importing of CAT pretest samples. Whenever the count of some CAT pretest samples exceeds the system default, the online calibration of IRT items parameters might be manually enabled. 2. Simulating comparison of four IRT ability estimator engines: There is a system built-in functionality simulating real CAT sessions operating. It is implemented with ASP programs. The ability estimator engines are designed according to four IRT ability methods (OWEN、EAP、MLE and WLE ). The first step of the simulating study of four IRT ability estimators is to feed same specific response patterns to each of the four engines. Unlike an ordinary CAT system, maximum test length (e.g. 20、25 or 30, etc) is no longer served as one of test termination rules. For four IRT ability estimators, individual test length (could be the size of items bank) and estimated ability of each response pattern are of interest of this study. The conclusion of this study is as follows: 1. After enhancing, the online multimedia CAT system pretest samples collecting feature avoids the drawback of huge examinees attendance and expensive cost caused by a conventional paper and pencil style pretest samples collecting task. 2. Bayesian ability methods, OWEN and EAP, would generate an outcome of slow convergence or running out of the items bank for some response patterns. On the contrary, maximum likelihood ability methods, MLE and WLE, would be typically convergent for these same response patterns. 3. To overcome the issue of contradiction between ability estimation accuracy and CAT efficiency caused by a specific response pattern for OWEN and EAP methods, it is suggested that a CAT system driven by a single ability estimation engine (e.g. EAP) is transformed into the multiple CAT ability estimation engines (e.g. EAP+MLE) scheme. Whenever the system detects a response pattern which could cause default engine to be slowly convergent, the mechanism of the multiple ability estimation engines would automatically switch to another engine to estimate ability again for the same response pattern. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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