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The Call Is Coming from inside the School! How Well Does Cell Phone Data Predict Whether K12 School Buildings Were Open during the Pandemic? Working Paper No. 309-1124

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Title: The Call Is Coming from inside the School! How Well Does Cell Phone Data Predict Whether K12 School Buildings Were Open during the Pandemic? Working Paper No. 309-1124
Language: English
Authors: Dan Goldhaber, Nick Huntington-Klein, Nate Brown, Scott Imberman, Katharine O. Strunk, National Center for Analysis of Longitudinal Data in Education Research (CALDER) at American Institutes for Research (AIR)
Source: National Center for Analysis of Longitudinal Data in Education Research (CALDER). 2024.
Availability: National Center for Analysis of Longitudinal Data in Education Research. American Institutes for Research, 1000 Thomas Jefferson Street NW, Washington, DC 20007. Tel: 202-403-5796; Fax: 202-403-6783; e-mail: info@caldercenter.org; Web site: https://caldercenter.org
Peer Reviewed: N
Page Count: 64
Publication Date: 2024
Document Type: Reports - Research
Education Level: Elementary Education
Secondary Education
Descriptors: Handheld Devices, Telecommunications, COVID-19, Pandemics, Data Use, Predictor Variables, Elementary Schools, Secondary Schools, Measurement Techniques, School Closing
Geographic Terms: Michigan, Washington
Abstract: The COVID-19 pandemic forced widespread school closures and a shift to remote learning. A growing body of research has examined the effects of remote learning on student outcomes. But the accuracy of the school modality measures used in these studies is questionable. The most common measures--based on self-reports or district website information--are often inconsistent and lack nationwide coverage. Some studies have used cell phone mobility data to identify school modalities, but there is no consensus yet on how to translate device pings into modality measures. This paper contributes to the literature on modality measurement by examining the relationship between mobile device signals and school modality prior to the pandemic and applies those findings to the pandemic period in Michigan and Washington. We compare our results to state-provided closure data and other nationwide sources, including the Return to Learn Tracker and the COVID-19 School Data Hub. Our findings indicate that cell phone mobility data can accurately predict school modality under normal conditions, but the accuracy drops during the pandemic. These results have implications for future research on educational and health outcomes during both pandemic and non-pandemic-related school closures.
Abstractor: As Provided
Entry Date: 2024
Accession Number: ED662864
Database: ERIC
FullText Text:
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  Data: National Center for Analysis of Longitudinal Data in Education Research. American Institutes for Research, 1000 Thomas Jefferson Street NW, Washington, DC 20007. Tel: 202-403-5796; Fax: 202-403-6783; e-mail: info@caldercenter.org; Web site: https://caldercenter.org
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  Data: <searchLink fieldCode="DE" term="%22Michigan%22">Michigan</searchLink><br /><searchLink fieldCode="DE" term="%22Washington%22">Washington</searchLink>
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  Data: The COVID-19 pandemic forced widespread school closures and a shift to remote learning. A growing body of research has examined the effects of remote learning on student outcomes. But the accuracy of the school modality measures used in these studies is questionable. The most common measures--based on self-reports or district website information--are often inconsistent and lack nationwide coverage. Some studies have used cell phone mobility data to identify school modalities, but there is no consensus yet on how to translate device pings into modality measures. This paper contributes to the literature on modality measurement by examining the relationship between mobile device signals and school modality prior to the pandemic and applies those findings to the pandemic period in Michigan and Washington. We compare our results to state-provided closure data and other nationwide sources, including the Return to Learn Tracker and the COVID-19 School Data Hub. Our findings indicate that cell phone mobility data can accurately predict school modality under normal conditions, but the accuracy drops during the pandemic. These results have implications for future research on educational and health outcomes during both pandemic and non-pandemic-related school closures.
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  Data: 2024
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  Data: ED662864
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=ED662864
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      – Text: English
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      Pagination:
        PageCount: 64
    Subjects:
      – SubjectFull: Handheld Devices
        Type: general
      – SubjectFull: Telecommunications
        Type: general
      – SubjectFull: COVID-19
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      – SubjectFull: Pandemics
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      – SubjectFull: Data Use
        Type: general
      – SubjectFull: Predictor Variables
        Type: general
      – SubjectFull: Elementary Schools
        Type: general
      – SubjectFull: Secondary Schools
        Type: general
      – SubjectFull: Measurement Techniques
        Type: general
      – SubjectFull: School Closing
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      – SubjectFull: Michigan
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      – SubjectFull: Washington
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      – TitleFull: The Call Is Coming from inside the School! How Well Does Cell Phone Data Predict Whether K12 School Buildings Were Open during the Pandemic? Working Paper No. 309-1124
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