{"title":"Monitoring Item Performance With CUSUM Statistics in Continuous Testing","authors":"Yi-Hsuan Lee, C. Lewis","doi":"10.3102/1076998621994563","DOIUrl":null,"url":null,"abstract":"In many educational assessments, items are reused in different administrations throughout the life of the assessments. Ideally, a reused item should perform relatively similarly over time. In reality, an item may become easier with exposure, especially when item preknowledge has occurred. This article presents a novel cumulative sum procedure for detecting item preknowledge in continuous testing where data for each reused item may be obtained from small and varying sample sizes across administrations. Its performance is evaluated with simulations and analytical work. The approach is effective in detecting item preknowledge quickly with group size at least 10 and is easy to implement with varying item parameters. In addition, it is robust to the ability estimation error introduced in the simulations.","PeriodicalId":48001,"journal":{"name":"Journal of Educational and Behavioral Statistics","volume":"46 1","pages":"611 - 648"},"PeriodicalIF":1.9000,"publicationDate":"2021-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Educational and Behavioral Statistics","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.3102/1076998621994563","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 3
Abstract
In many educational assessments, items are reused in different administrations throughout the life of the assessments. Ideally, a reused item should perform relatively similarly over time. In reality, an item may become easier with exposure, especially when item preknowledge has occurred. This article presents a novel cumulative sum procedure for detecting item preknowledge in continuous testing where data for each reused item may be obtained from small and varying sample sizes across administrations. Its performance is evaluated with simulations and analytical work. The approach is effective in detecting item preknowledge quickly with group size at least 10 and is easy to implement with varying item parameters. In addition, it is robust to the ability estimation error introduced in the simulations.
期刊介绍:
Journal of Educational and Behavioral Statistics, sponsored jointly by the American Educational Research Association and the American Statistical Association, publishes articles that are original and provide methods that are useful to those studying problems and issues in educational or behavioral research. Typical papers introduce new methods of analysis. Critical reviews of current practice, tutorial presentations of less well known methods, and novel applications of already-known methods are also of interest. Papers discussing statistical techniques without specific educational or behavioral interest or focusing on substantive results without developing new statistical methods or models or making novel use of existing methods have lower priority. Simulation studies, either to demonstrate properties of an existing method or to compare several existing methods (without providing a new method), also have low priority. The Journal of Educational and Behavioral Statistics provides an outlet for papers that are original and provide methods that are useful to those studying problems and issues in educational or behavioral research. Typical papers introduce new methods of analysis, provide properties of these methods, and an example of use in education or behavioral research. Critical reviews of current practice, tutorial presentations of less well known methods, and novel applications of already-known methods are also sometimes accepted. Papers discussing statistical techniques without specific educational or behavioral interest or focusing on substantive results without developing new statistical methods or models or making novel use of existing methods have lower priority. Simulation studies, either to demonstrate properties of an existing method or to compare several existing methods (without providing a new method), also have low priority.