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Chronic Absence Patterns and Prediction during COVID-19: Insights from Connecticut

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Title: Chronic Absence Patterns and Prediction during COVID-19: Insights from Connecticut
Language: English
Authors: Chang, Hedy N., Gee, Kevin, Hennessy, Briana, Alexandro, David, Gopalakrishnan, Ajit, Attendance Works, Connecticut State Department of Education (CSDE)
Source: Attendance Works. 2021.
Availability: Attendance Works. 200 Granville Way, San Francisco, CA 94127. e-mail: info@attendanceworks.org; Web site: http://www.attendanceworks.org/
Peer Reviewed: N
Page Count: 11
Publication Date: 2021
Document Type: Reports - Evaluative
Education Level: Elementary Education
Junior High Schools
Middle Schools
Secondary Education
High Schools
Descriptors: Attendance, COVID-19, Pandemics, Data Collection, Distance Education, Online Courses, Blended Learning, Conventional Instruction, Incidence, Elementary School Students, Middle School Students, High School Students, Age Differences, Socioeconomic Status, Racial Differences, Ethnicity, Students with Disabilities, Gender Differences, Teaching Methods, Predictor Variables
Geographic Terms: Connecticut
Abstract: This report describes how Connecticut took steps to collect consistent attendance data by learning mode -- remote, in-person and hybrid -- and publicly released data in a timely manner during the pandemic. For example, the Connecticut State Department of Education (CSDE) agreed upon a standard definition of attendance -- showing up to school for half of a day -- to ensure consistency with prior year data and across learning modes. CSDE also invested in frequent collection and public reporting of attendance and chronic absence data throughout the 2020-21 school year. As a result, Connecticut is uniquely positioned to analyze how patterns of chronic absence differ across learning modes, grades and student groups. The report offers eight key findings from the analysis of Connecticut's chronic absence data that can inform COVID-19 educational recovery efforts and attendance initiatives. It shares lessons learned from Connecticut and recommends steps that other states can take to improve their data systems and ensure actionable data for the next school year.
Abstractor: As Provided
Entry Date: 2021
Access URL: https://www.attendanceworks.org/wp-content/uploads/2019/06/Chronic_Absence_in_CT_062421.pdf
Accession Number: ED613690
Database: ERIC
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  Data: Chronic Absence Patterns and Prediction during COVID-19: Insights from Connecticut
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  Data: <searchLink fieldCode="AR" term="%22Chang%2C+Hedy+N%2E%22">Chang, Hedy N.</searchLink><br /><searchLink fieldCode="AR" term="%22Gee%2C+Kevin%22">Gee, Kevin</searchLink><br /><searchLink fieldCode="AR" term="%22Hennessy%2C+Briana%22">Hennessy, Briana</searchLink><br /><searchLink fieldCode="AR" term="%22Alexandro%2C+David%22">Alexandro, David</searchLink><br /><searchLink fieldCode="AR" term="%22Gopalakrishnan%2C+Ajit%22">Gopalakrishnan, Ajit</searchLink><br /><searchLink fieldCode="AR" term="%22Attendance+Works%22">Attendance Works</searchLink><br /><searchLink fieldCode="AR" term="%22Connecticut+State+Department+of+Education+%28CSDE%29%22">Connecticut State Department of Education (CSDE)</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Attendance+Works%22"><i>Attendance Works</i></searchLink>. 2021.
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  Data: Attendance Works. 200 Granville Way, San Francisco, CA 94127. e-mail: info@attendanceworks.org; Web site: http://www.attendanceworks.org/
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  Data: N
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  Data: 11
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  Data: 2021
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  Data: <searchLink fieldCode="EL" term="%22Elementary+Education%22">Elementary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Junior+High+Schools%22">Junior High Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Middle+Schools%22">Middle Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Secondary+Education%22">Secondary Education</searchLink><br /><searchLink fieldCode="EL" term="%22High+Schools%22">High Schools</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Attendance%22">Attendance</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Pandemics%22">Pandemics</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Collection%22">Data Collection</searchLink><br /><searchLink fieldCode="DE" term="%22Distance+Education%22">Distance Education</searchLink><br /><searchLink fieldCode="DE" term="%22Online+Courses%22">Online Courses</searchLink><br /><searchLink fieldCode="DE" term="%22Blended+Learning%22">Blended Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Conventional+Instruction%22">Conventional Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Incidence%22">Incidence</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+School+Students%22">Elementary School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Middle+School+Students%22">Middle School Students</searchLink><br /><searchLink fieldCode="DE" term="%22High+School+Students%22">High School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Age+Differences%22">Age Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+Status%22">Socioeconomic Status</searchLink><br /><searchLink fieldCode="DE" term="%22Racial+Differences%22">Racial Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Ethnicity%22">Ethnicity</searchLink><br /><searchLink fieldCode="DE" term="%22Students+with+Disabilities%22">Students with Disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Connecticut%22">Connecticut</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: This report describes how Connecticut took steps to collect consistent attendance data by learning mode -- remote, in-person and hybrid -- and publicly released data in a timely manner during the pandemic. For example, the Connecticut State Department of Education (CSDE) agreed upon a standard definition of attendance -- showing up to school for half of a day -- to ensure consistency with prior year data and across learning modes. CSDE also invested in frequent collection and public reporting of attendance and chronic absence data throughout the 2020-21 school year. As a result, Connecticut is uniquely positioned to analyze how patterns of chronic absence differ across learning modes, grades and student groups. The report offers eight key findings from the analysis of Connecticut's chronic absence data that can inform COVID-19 educational recovery efforts and attendance initiatives. It shares lessons learned from Connecticut and recommends steps that other states can take to improve their data systems and ensure actionable data for the next school year.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2021
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  Data: <link linkTarget="URL" linkTerm="https://www.attendanceworks.org/wp-content/uploads/2019/06/Chronic_Absence_in_CT_062421.pdf" linkWindow="_blank">https://www.attendanceworks.org/wp-content/uploads/2019/06/Chronic_Absence_in_CT_062421.pdf</link>
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
    Subjects:
      – SubjectFull: Attendance
        Type: general
      – SubjectFull: COVID-19
        Type: general
      – SubjectFull: Pandemics
        Type: general
      – SubjectFull: Data Collection
        Type: general
      – SubjectFull: Distance Education
        Type: general
      – SubjectFull: Online Courses
        Type: general
      – SubjectFull: Blended Learning
        Type: general
      – SubjectFull: Conventional Instruction
        Type: general
      – SubjectFull: Incidence
        Type: general
      – SubjectFull: Elementary School Students
        Type: general
      – SubjectFull: Middle School Students
        Type: general
      – SubjectFull: High School Students
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      – SubjectFull: Age Differences
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      – SubjectFull: Socioeconomic Status
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      – SubjectFull: Racial Differences
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      – SubjectFull: Ethnicity
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      – SubjectFull: Students with Disabilities
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      – SubjectFull: Gender Differences
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      – SubjectFull: Teaching Methods
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      – SubjectFull: Predictor Variables
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      – SubjectFull: Connecticut
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      – TitleFull: Chronic Absence Patterns and Prediction during COVID-19: Insights from Connecticut
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