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Running out of Time: Leveraging Process Data to Identify Students Who May Benefit from Extended Time

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Title: Running out of Time: Leveraging Process Data to Identify Students Who May Benefit from Extended Time
Language: English
Authors: Burhan Ogut (ORCID 0000-0003-1729-1396), Ruhan Circi (ORCID 0000-0003-3854-1796), Huade Huo (ORCID 0009-0004-5014-646X), Juanita Hicks (ORCID 0000-0002-4906-3083), Michelle Yin (ORCID 0000-0001-9333-1535)
Source: International Electronic Journal of Elementary Education. 2025 17(2):253-266.
Availability: International Electronic Journal of Elementary Education. T&K Akademic Rosendalsvein 45, Oslo 1166, Norway. e-mail: iejee@iejee.com; Web site: https://www.iejee.com/index.php/IEJEE/index
Peer Reviewed: Y
Page Count: 14
Publication Date: 2025
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R324P210002
Document Type: Journal Articles
Reports - Research
Descriptors: Identification, Testing Accommodations, National Competency Tests, Equal Education, Students with Disabilities, Time Factors (Learning), Computer Assisted Testing, Student Evaluation, Timed Tests
Assessment and Survey Identifiers: National Assessment of Educational Progress
ISSN: 1307-9298
Abstract: This study explored the effectiveness of extended time (ET) accommodations in the 2017 NAEP Grade 8 Mathematics assessment to enhance educational equity. Analyzing NAEP process data through an XGBoost model, we examined if early interactions with assessment items could predict students' likelihood of requiring ET by identifying those who received a timeout message. The findings revealed that 72% of students with disabilities (SWDs) granted ET did not use it fully, while about 24% of students lacking ET were still actively engaged when timed out, indicating a considerable unmet need for ET. The model demonstrated high accuracy and recall in predicting the necessity for ET based on early test behaviors, with minimal influence from background variables such as eligibility for free lunch, English Language Learner (ELL) status, and disability status. These results underscore the potential of utilizing early assessment behaviors as reliable predictors for ET needs, advocating for the integration of predictive models into digital testing systems. Such an approach could enable real-time analysis and adjustments, thereby promoting a fairer assessment process where all students have the opportunity to fully demonstrate their knowledge.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2025
Accession Number: EJ1468386
Database: ERIC
FullText Links:
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  Data: <searchLink fieldCode="AR" term="%22Burhan+Ogut%22">Burhan Ogut</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1729-1396">0000-0003-1729-1396</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ruhan+Circi%22">Ruhan Circi</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3854-1796">0000-0003-3854-1796</externalLink>)<br /><searchLink fieldCode="AR" term="%22Huade+Huo%22">Huade Huo</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0004-5014-646X">0009-0004-5014-646X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Juanita+Hicks%22">Juanita Hicks</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4906-3083">0000-0002-4906-3083</externalLink>)<br /><searchLink fieldCode="AR" term="%22Michelle+Yin%22">Michelle Yin</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-9333-1535">0000-0001-9333-1535</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22International+Electronic+Journal+of+Elementary+Education%22"><i>International Electronic Journal of Elementary Education</i></searchLink>. 2025 17(2):253-266.
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  Data: International Electronic Journal of Elementary Education. T&K Akademic Rosendalsvein 45, Oslo 1166, Norway. e-mail: iejee@iejee.com; Web site: https://www.iejee.com/index.php/IEJEE/index
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  Data: This study explored the effectiveness of extended time (ET) accommodations in the 2017 NAEP Grade 8 Mathematics assessment to enhance educational equity. Analyzing NAEP process data through an XGBoost model, we examined if early interactions with assessment items could predict students' likelihood of requiring ET by identifying those who received a timeout message. The findings revealed that 72% of students with disabilities (SWDs) granted ET did not use it fully, while about 24% of students lacking ET were still actively engaged when timed out, indicating a considerable unmet need for ET. The model demonstrated high accuracy and recall in predicting the necessity for ET based on early test behaviors, with minimal influence from background variables such as eligibility for free lunch, English Language Learner (ELL) status, and disability status. These results underscore the potential of utilizing early assessment behaviors as reliable predictors for ET needs, advocating for the integration of predictive models into digital testing systems. Such an approach could enable real-time analysis and adjustments, thereby promoting a fairer assessment process where all students have the opportunity to fully demonstrate their knowledge.
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 253
    Subjects:
      – SubjectFull: Identification
        Type: general
      – SubjectFull: Testing Accommodations
        Type: general
      – SubjectFull: National Competency Tests
        Type: general
      – SubjectFull: Equal Education
        Type: general
      – SubjectFull: Students with Disabilities
        Type: general
      – SubjectFull: Time Factors (Learning)
        Type: general
      – SubjectFull: Computer Assisted Testing
        Type: general
      – SubjectFull: Student Evaluation
        Type: general
      – SubjectFull: Timed Tests
        Type: general
      – SubjectFull: National Assessment of Educational Progress
        Type: general
    Titles:
      – TitleFull: Running out of Time: Leveraging Process Data to Identify Students Who May Benefit from Extended Time
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