Who's Absent from School? A Two-State Examination of Trends in Absenteeism before and after COVID-19
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| Title: | Who's Absent from School? A Two-State Examination of Trends in Absenteeism before and after COVID-19 |
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| Language: | English |
| Authors: | Morgan Polikoff, Nicolas Pardo, American Enterprise Institute (AEI) |
| Source: | American Enterprise Institute. 2025. |
| 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: | 35 |
| Publication Date: | 2025 |
| Document Type: | Reports - Research Numerical/Quantitative Data |
| Descriptors: | Attendance, COVID-19, Pandemics, Student Characteristics, Age Differences, Instructional Program Divisions, Academic Achievement, Racial Differences, Socioeconomic Status, Poverty, English Learners, Predictor Variables, Gender Differences, Students with Disabilities, Academically Gifted, Ethnicity, Student Mobility |
| Geographic Terms: | Virginia, North Carolina |
| Abstract: | This report examines descriptive patterns in student absenteeism before and after the COVID-19 pandemic in Virginia and North Carolina. The authors asks four questions: (1) How do absence rates vary across student demographic groups and years?; (2) What student characteristics (grade, achievement, race, poverty, status as an English language learner, limited English proficiency, etc.) and school or district characteristics (level, student demographics, etc.) most strongly predict student absenteeism?; (3) To what extent have the demographic predictors of absenteeism changed from before to after COVID?; and (4) How sensitive are the results to the chosen measure of absenteeism? To answer these questions, the authors examine descriptive statistics and conduct a series of ordinary least squares and logistic regressions. Because absenteeism has increased across the board and especially for low-income students, the authors conclude that policymakers must take broad-based approaches to bring students back to school. The results shed light on the groups that may be most at risk and in need of intervention post-COVID. |
| Abstractor: | ERIC |
| Entry Date: | 2026 |
| Accession Number: | ED677931 |
| Database: | ERIC |
| Abstract: | This report examines descriptive patterns in student absenteeism before and after the COVID-19 pandemic in Virginia and North Carolina. The authors asks four questions: (1) How do absence rates vary across student demographic groups and years?; (2) What student characteristics (grade, achievement, race, poverty, status as an English language learner, limited English proficiency, etc.) and school or district characteristics (level, student demographics, etc.) most strongly predict student absenteeism?; (3) To what extent have the demographic predictors of absenteeism changed from before to after COVID?; and (4) How sensitive are the results to the chosen measure of absenteeism? To answer these questions, the authors examine descriptive statistics and conduct a series of ordinary least squares and logistic regressions. Because absenteeism has increased across the board and especially for low-income students, the authors conclude that policymakers must take broad-based approaches to bring students back to school. The results shed light on the groups that may be most at risk and in need of intervention post-COVID. |
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