DocumentCode :
2090457
Title :
System for Online Detection of Aberrant Responses in E-Testing
Author :
Ueno, Maomi ; Okamoto, Toshio
Author_Institution :
Grad. Sch. of Inf. Syst., Univ. of Electro-Commun.
fYear :
2008
fDate :
1-5 July 2008
Firstpage :
824
Lastpage :
828
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.
Keywords :
Bayes methods; educational administrative data processing; statistical testing; Bayesian predictive distribution; e-testing; online examinee aberrant response detection; outlier detection; outlier statistics; statistical test; Bayesian methods; Data models; Delay; History; Information systems; Internet; Psychometric testing; Statistical analysis; Statistical distributions; Statistics; aberrant responses; data mining; e-testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Learning Technologies, 2008. ICALT '08. Eighth IEEE International Conference on
Conference_Location :
Santander, Cantabria
Print_ISBN :
978-0-7695-3167-0
Type :
conf
DOI :
10.1109/ICALT.2008.171
Filename :
4561843
Link To Document :
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