{"title":"检测考生对项目预知识的方法比较","authors":"Xi Wang, Yang Liu, F. Robin, Hongwen Guo","doi":"10.1080/15305058.2019.1610886","DOIUrl":null,"url":null,"abstract":"In an on-demand testing program, some items are repeatedly used across test administrations. This poses a risk to test security. In this study, we considered a scenario wherein a test was divided into two subsets: one consisting of secure items and the other consisting of possibly compromised items. In a simulation study of multistage adaptive testing, we used three methods to detect item preknowledge: a predictive checking method (PCM), a likelihood ratio test (LRT), and an adapted Kullback–Leibler divergence (KLD-A) test. We manipulated four factors: the proportion of compromised items, the stage of adaptive testing at which preknowledge was present, item-parameter estimation error, and the information contained in secure items. The type I error results indicated that the LRT and PCM methods are favored over the KLD-A method because the KLD-A can experience large inflated type I error in many conditions. In regard to power, the LRT and PCM methods displayed a wide range of results, generally from 0.2 to 0.8, depending on the amount of preknowledge and the stage of adaptive testing at which the preknowledge was present.","PeriodicalId":46615,"journal":{"name":"International Journal of Testing","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/15305058.2019.1610886","citationCount":"7","resultStr":"{\"title\":\"A Comparison of Methods for Detecting Examinee Preknowledge of Items\",\"authors\":\"Xi Wang, Yang Liu, F. Robin, Hongwen Guo\",\"doi\":\"10.1080/15305058.2019.1610886\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In an on-demand testing program, some items are repeatedly used across test administrations. This poses a risk to test security. In this study, we considered a scenario wherein a test was divided into two subsets: one consisting of secure items and the other consisting of possibly compromised items. In a simulation study of multistage adaptive testing, we used three methods to detect item preknowledge: a predictive checking method (PCM), a likelihood ratio test (LRT), and an adapted Kullback–Leibler divergence (KLD-A) test. We manipulated four factors: the proportion of compromised items, the stage of adaptive testing at which preknowledge was present, item-parameter estimation error, and the information contained in secure items. The type I error results indicated that the LRT and PCM methods are favored over the KLD-A method because the KLD-A can experience large inflated type I error in many conditions. In regard to power, the LRT and PCM methods displayed a wide range of results, generally from 0.2 to 0.8, depending on the amount of preknowledge and the stage of adaptive testing at which the preknowledge was present.\",\"PeriodicalId\":46615,\"journal\":{\"name\":\"International Journal of Testing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2019-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/15305058.2019.1610886\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Testing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/15305058.2019.1610886\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Testing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/15305058.2019.1610886","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
A Comparison of Methods for Detecting Examinee Preknowledge of Items
In an on-demand testing program, some items are repeatedly used across test administrations. This poses a risk to test security. In this study, we considered a scenario wherein a test was divided into two subsets: one consisting of secure items and the other consisting of possibly compromised items. In a simulation study of multistage adaptive testing, we used three methods to detect item preknowledge: a predictive checking method (PCM), a likelihood ratio test (LRT), and an adapted Kullback–Leibler divergence (KLD-A) test. We manipulated four factors: the proportion of compromised items, the stage of adaptive testing at which preknowledge was present, item-parameter estimation error, and the information contained in secure items. The type I error results indicated that the LRT and PCM methods are favored over the KLD-A method because the KLD-A can experience large inflated type I error in many conditions. In regard to power, the LRT and PCM methods displayed a wide range of results, generally from 0.2 to 0.8, depending on the amount of preknowledge and the stage of adaptive testing at which the preknowledge was present.