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Improving Ability Estimation Accuracy for Automated Item Generated Forms under Multistage Testing

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Bibliographic Details
Title: Improving Ability Estimation Accuracy for Automated Item Generated Forms under Multistage Testing
Language: English
Authors: Stella Y. Kim, Won-Chan Lee
Source: Journal of Educational Measurement. 2026 63(1).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 22
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Automation, Test Items, Accuracy, Ability, Adaptive Testing, Computer Assisted Testing, Computation
DOI: 10.1111/jedm.70027
ISSN: 0022-0655
1745-3984
Abstract: The emergence of automated item generation (AIG) techniques has intensified discussions around their application in assessment development. Some testing companies have already begun developing software to construct exams using AIG. However, the current literature offers limited insights into the characteristics of items generated through AIG, particularly in the realm of multistage testing (MST). This study proposes a novel approach for adjusting template item parameters to enhance ability estimation accuracy under the MST context. A simulation study was conducted using two MST designs with varying numbers of stages and modules. Results demonstrated that the proposed method significantly improved the accuracy of person parameter estimates compared to a more practical, yet less precise, approach that assumes all item clones share identical parameters.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1501398
Database: ERIC
FullText Text:
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: 22
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  Data: <searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Items%22">Test Items</searchLink><br /><searchLink fieldCode="DE" term="%22Accuracy%22">Accuracy</searchLink><br /><searchLink fieldCode="DE" term="%22Ability%22">Ability</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+Testing%22">Adaptive Testing</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Assisted+Testing%22">Computer Assisted Testing</searchLink><br /><searchLink fieldCode="DE" term="%22Computation%22">Computation</searchLink>
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  Data: 0022-0655<br />1745-3984
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  Data: The emergence of automated item generation (AIG) techniques has intensified discussions around their application in assessment development. Some testing companies have already begun developing software to construct exams using AIG. However, the current literature offers limited insights into the characteristics of items generated through AIG, particularly in the realm of multistage testing (MST). This study proposes a novel approach for adjusting template item parameters to enhance ability estimation accuracy under the MST context. A simulation study was conducted using two MST designs with varying numbers of stages and modules. Results demonstrated that the proposed method significantly improved the accuracy of person parameter estimates compared to a more practical, yet less precise, approach that assumes all item clones share identical parameters.
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  Data: 2026
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  Data: EJ1501398
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      – Text: English
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        PageCount: 22
    Subjects:
      – SubjectFull: Automation
        Type: general
      – SubjectFull: Test Items
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      – SubjectFull: Accuracy
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      – SubjectFull: Ability
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