文章基本信息

标题：MAXIMUM INFORMATION STRATIFICATION METHOD FOR CONTROLLING ITEM EXPOSURE IN COMPUTERIZED ADAPTIVE TESTING
本地全文：下载
作者：Juan Ramón Barrada ; Paloma Mazuela ; Julio Olea 等
期刊名称：Psicothema
印刷版ISSN：0214-9915
电子版ISSN：1886-144X
出版年度：2006
卷号：18
期号：1
页码：156-159
出版社：Cologio Oficial de Psicólogos del Principado
摘要：The proposal for increasing the security in Computerized Adaptive Tests that has received most attention in recent years is the a-stratified method (AS - Chang and Ying, 1999): at the beginning of the test only items with low discrimination parameters ( a ) can be administered, with the values of the a parameters increasing as the test goes on. With this method, distribution of the exposure rates of the items is less skewed, while efficiency is maintained in trait-level estimation. The pseudo-guessing parameter ( c ), present in the three-parameter logistic model, is considered irrelevant, and is not used in the AS method. The Maximum Information Stratified (MIS) model incorporates the c parameter in the stratification of the bank and in the item-selection rule, improving accuracy by comparison with the AS, for item banks with a and b parameters correlated and uncorrelated. For both kinds of banks, the blocking b methods (Chang, Qian and Ying, 2001) improve the security of the item bank.