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.
Authors: Ogut, Burhan1 bogut@air.org, Circi, Ruhan1 rcirci@air.org, Huo, Huade1 hhuo@air.org, Hicks, Juanita1 hhicks@air.org, Yin, Michelle2 michelle.yin@northwestern.edu
Source: International Electronic Journal of Elementary Education. Mar2025, Vol. 17 Issue 2, p253-266. 14p.
Subject Terms: *Limited English-proficient students, *Behavioral assessment, *Eighth grade (Education), *Educational equalization, *Students with disabilities
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. [ABSTRACT FROM AUTHOR]
Copyright of International Electronic Journal of Elementary Education is the property of International Electronic Journal of Elementary Education and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: <searchLink fieldCode="JN" term="%22International+Electronic+Journal+of+Elementary+Education%22">International Electronic Journal of Elementary Education</searchLink>. Mar2025, Vol. 17 Issue 2, p253-266. 14p.
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  Data: *<searchLink fieldCode="DE" term="%22Limited+English-proficient+students%22">Limited English-proficient students</searchLink><br />*<searchLink fieldCode="DE" term="%22Behavioral+assessment%22">Behavioral assessment</searchLink><br />*<searchLink fieldCode="DE" term="%22Eighth+grade+%28Education%29%22">Eighth grade (Education)</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+equalization%22">Educational equalization</searchLink><br />*<searchLink fieldCode="DE" term="%22Students+with+disabilities%22">Students with disabilities</searchLink>
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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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Electronic Journal of Elementary Education is the property of International Electronic Journal of Elementary Education and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.26822/iejee.2025.376
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      – Code: eng
        Text: English
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      – SubjectFull: Limited English-proficient students
        Type: general
      – SubjectFull: Behavioral assessment
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      – SubjectFull: Eighth grade (Education)
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      – SubjectFull: Educational equalization
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      – SubjectFull: Students with disabilities
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      – TitleFull: Running Out of Time: Leveraging Process Data to Identify Students Who May Benefit from Extended Time.
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              Text: Mar2025
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