Long COVID for Public Schools: Chronic Absenteeism before and after the Pandemic
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| Title: | Long COVID for Public Schools: Chronic Absenteeism before and after the Pandemic |
|---|---|
| Language: | English |
| Authors: | Nat Malkus, American Enterprise Institute (AEI) |
| Source: | American Enterprise Institute. 2024. |
| Availability: | American Enterprise Institute. 1150 Seventeenth Street NW, Washington, DC 20036. Tel: 202-862-5800; Fax: 202-862-7177; Web site: http://www.aei.org |
| Peer Reviewed: | N |
| Page Count: | 23 |
| Publication Date: | 2024 |
| Document Type: | Reports - Research |
| Descriptors: | Attendance, COVID-19, Pandemics, Geographic Location, Racial Differences, Ethnicity, School Districts, Academic Achievement, Academic Failure, Trend Analysis, Poverty, Rural Urban Differences, School District Size, One Parent Family, Distance Education, Rural Schools, Urban Schools, Suburban Schools |
| Abstract: | This report documents chronic absenteeism over the COVID-19 pandemic. Drawing on the American Enterprise Institute's Return to Learn Tracker Chronic Absenteeism Data Collection, it shows that increases in chronic absenteeism were widespread during the pandemic. More worrisome, using the most recent data for the 2022-2023 school year, even after the pandemic subsided drastically, the elevated rates of chronic absenteeism fell very little. The report also uses district-level data to report variable rates of chronic absenteeism by district characteristics including pre-pandemic achievement, poverty, size, and the duration of remote instruction in the 2021 school year. Of particular concern, the percentage-point increases in chronic absenteeism were larger in districts and among groups that already had higher chronic absenteeism rates before the pandemic. The author concludes by discussing the findings and suggesting policy responses, given the potential for these rates of chronic absenteeism to hamper urgently needed recovery from pandemic learning loss and its negative association with school culture. |
| Abstractor: | ERIC |
| Entry Date: | 2025 |
| Accession Number: | ED674001 |
| Database: | ERIC |
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