Reverse Engineering Attendance: An Exploration of Schools Beating the Absenteeism Odds

• In Event: Exploring Tensions in Research on Chronic Absenteeism

Abstract

In the aftermath of the COVID-19 pandemic, chronic absenteeism has become an even more urgent educational equity issue. The rates at which students miss 10% or more of the school year have skyrocketed (D.C. Policy Center, 2023; Dee, 2024; Fuller et al., 2023). There are longstanding disparities in who is absent from school with students of color and students with disabilities more likely to be chronically absent (Lala et al., 2018; Patnode et al., 2018). Districts nationwide are searching for ways to reduce chronic absenteeism. Yet in the quest for solutions to myriad disparities in education, few studies have applied an asset-based approach to educational equity phenomenon such as chronic absenteeism (Welsh et al., 2023). In this study, we replicate and extend the approach of Welsh et al. (2023) to identify and describe “inclusive absenteeism” schools, schools that are beating the chronic absenteeism odds in terms of overall prevalence and racial disparity. The following research question guides our analyses:
In what ways do school characteristics differ between schools with low, average and high rates and disparities in chronic absenteeism?

Data and Methods

We use student-level data (N=496,085) and a robust set of school-level covariates (2017-2022) from an urban-emergent Southeastern district in tandem with descriptive methods to explore the nature of student and school characteristics in inclusive absenteeism schools. Similar to Welsh et al. (2023), schools were stratified into three categories based on absenteeism metrics (both prevalence and disparities). Schools identified as inclusive absenteeism schools (IAS) were those that fell within the bottom tercile across all metrics. On the opposite end of the absence spectrum were high absenteeism schools (HAS), operationalized as those in the top tercile for the same metrics. The remaining schools, falling between these two extremes, were classified as median absenteeism schools (MAS). We used multinomial logistic regression to analyze how school characteristics predict whether schools are IAS or HAS relative to MAS.

Preliminary Results

We find that inclusive absenteeism schools (IAS) are not commonplace, confirming the rigor of the criteria to identify schools beating the absenteeism odds. IAS show lower overall, Black, and Hispanic absenteeism rates relative to MAS and HAS but similar White absenteeism rates. In IAS, the White absenteeism rates are higher than the Black and Hispanic absenteeism rates. Almost all of the IAS are elementary and middle schools and a notable proportion are charter schools. No IAS were identified in the post-COVID school years underscoring the challenge of chronic absenteeism since the onset of pandemic.

School-level multinomial regressions results indicate that schools with a higher proportion of Black students are less likely to be IAS. Schools with a higher proportion of economically disadvantaged students and students with disabilities are more likely to be HAS. Schools with more positive school climate, as rated by higher ratings of belonging in schools, are less likely to be HAS. Overall, we find that student demographics and school climate matter. This suggests that investment in school climate is beneficial for reducing chronic absenteeism, particularly increasing students’ belonging in schools.

Authors

• Richard O. Welsh, Vanderbilt University

• Changhee Lee, Vanderbilt University