{"title":"电子测试异常响应在线检测系统","authors":"M. Ueno, Toshio Okamoto","doi":"10.1109/ICALT.2008.171","DOIUrl":null,"url":null,"abstract":"We have developed a method for online detection of examinees' aberrant responses. This method uses response time data in e-testing. Unique features of this method are: 1. It includes an outlier detection method using Bayesian predictive distribution. 2. It can be used with small-sample sets. 3. It provides a unified statistical test method of various statistical tests by changing hyper-parameters and provides more accurate test results than commonly used methods. 4. Outlier statistics are estimated by considering both examinee abilities and the difficulty level of items. We evaluated this system, and results of our evaluation show that it is effective.","PeriodicalId":128089,"journal":{"name":"2008 Eighth IEEE International Conference on Advanced Learning Technologies","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"System for Online Detection of Aberrant Responses in E-Testing\",\"authors\":\"M. Ueno, Toshio Okamoto\",\"doi\":\"10.1109/ICALT.2008.171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have developed a method for online detection of examinees' aberrant responses. This method uses response time data in e-testing. Unique features of this method are: 1. It includes an outlier detection method using Bayesian predictive distribution. 2. It can be used with small-sample sets. 3. It provides a unified statistical test method of various statistical tests by changing hyper-parameters and provides more accurate test results than commonly used methods. 4. Outlier statistics are estimated by considering both examinee abilities and the difficulty level of items. We evaluated this system, and results of our evaluation show that it is effective.\",\"PeriodicalId\":128089,\"journal\":{\"name\":\"2008 Eighth IEEE International Conference on Advanced Learning Technologies\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Eighth IEEE International Conference on Advanced Learning Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICALT.2008.171\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Eighth IEEE International Conference on Advanced Learning Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALT.2008.171","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
System for Online Detection of Aberrant Responses in E-Testing
We have developed a method for online detection of examinees' aberrant responses. This method uses response time data in e-testing. Unique features of this method are: 1. It includes an outlier detection method using Bayesian predictive distribution. 2. It can be used with small-sample sets. 3. It provides a unified statistical test method of various statistical tests by changing hyper-parameters and provides more accurate test results than commonly used methods. 4. Outlier statistics are estimated by considering both examinee abilities and the difficulty level of items. We evaluated this system, and results of our evaluation show that it is effective.
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