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 |
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| 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 |
| 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. |
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