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Simultaneous Detection of Compromised Items and Examinees with Item Preknowledge in Online Assessments Using Response Time Data

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Bibliographic Details
Title: Simultaneous Detection of Compromised Items and Examinees with Item Preknowledge in Online Assessments Using Response Time Data
Language: English
Authors: Cengiz Zopluoglu (ORCID 0000-0002-9397-0262)
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: 23
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Test Items, Computer Assisted Testing, Cheating, Reaction Time, Identification
DOI: 10.1111/jedm.70030
ISSN: 0022-0655
1745-3984
Abstract: The rapid transition from traditional paper-and-pencil tests to computer-based testing systems has significantly altered the educational landscape, particularly during the COVID-19 pandemic. While online assessments offer numerous advantages, they also present unique challenges, with test security being paramount. This article addresses the critical issue of test fraud in digital assessments, specifically focusing on item preknowledge, where examinees have prior access to test items. Using response-time data, we propose a statistical framework for simultaneously identifying compromised items and examinees with item preknowledge in a single-step analysis. Unlike existing methods, our model does not require prior knowledge about the compromised status of items. Using a large-scale online certification exam dataset, we demonstrate the model's application in detecting significant signals in response times, identifying potentially compromised items, and examinees with potential item preknowledge.
Abstractor: As Provided
Notes: https://github.com/czopluoglu/duolingo_dglnrt
Entry Date: 2026
Accession Number: EJ1501284
Database: ERIC
FullText Text:
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  Data: Simultaneous Detection of Compromised Items and Examinees with Item Preknowledge in Online Assessments Using Response Time Data
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  Data: <searchLink fieldCode="AR" term="%22Cengiz+Zopluoglu%22">Cengiz Zopluoglu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9397-0262">0000-0002-9397-0262</externalLink>)
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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: <searchLink fieldCode="DE" term="%22Test+Items%22">Test Items</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Assisted+Testing%22">Computer Assisted Testing</searchLink><br /><searchLink fieldCode="DE" term="%22Cheating%22">Cheating</searchLink><br /><searchLink fieldCode="DE" term="%22Reaction+Time%22">Reaction Time</searchLink><br /><searchLink fieldCode="DE" term="%22Identification%22">Identification</searchLink>
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  Data: The rapid transition from traditional paper-and-pencil tests to computer-based testing systems has significantly altered the educational landscape, particularly during the COVID-19 pandemic. While online assessments offer numerous advantages, they also present unique challenges, with test security being paramount. This article addresses the critical issue of test fraud in digital assessments, specifically focusing on item preknowledge, where examinees have prior access to test items. Using response-time data, we propose a statistical framework for simultaneously identifying compromised items and examinees with item preknowledge in a single-step analysis. Unlike existing methods, our model does not require prior knowledge about the compromised status of items. Using a large-scale online certification exam dataset, we demonstrate the model's application in detecting significant signals in response times, identifying potentially compromised items, and examinees with potential item preknowledge.
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  Data: As Provided
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  Data: https://github.com/czopluoglu/duolingo_dglnrt
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  Data: 2026
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  Data: EJ1501284
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