Exploring Patterns of Absenteeism from PreK through Elementary School and Their Associations with Academic Outcomes

• In Event: Unpacking School Absenteeism across the PreKindergarten and Elementary School Years

Abstract

During the early years of schooling, children often exhibit the highest levels of absenteeism in preK (e.g., Dubay & Holla, 2015; Ehrlich et al., 2018; MA DESE, 2019). Moreover, high levels of absenteeism during preK have been associated with worse school readiness skills by the end of the year and predictive of worse academic outcomes and higher absenteeism levels during elementary school (Ansari & Purtell, 2018; Dubay & Holla, 2016; Ehrlich et al., 2018; Rhoad-Drogalis & Justice, 2018). These findings highlight how the preK year may be an optimal time for intervention before longer-term patterns of absenteeism may develop. At the same time, there is less understanding regarding how absenteeism remains stable or changes following the preK year, how these longer-term patterns matter for child outcomes (e.g., do children who are frequently absent in preK but seldomly absent in subsequent years also exhibit poor outcomes?), and under what contexts these patterns may matter most. The present study addresses these gaps through the following aims: (1) describe children’s absenteeism patterns from preK to Grade 4; (2) examine whether absenteeism patterns predict children’s Grade 4 English language arts (ELA) and math achievement outcomes; and (3) test whether differences vary based on child- and school-level poverty.

To address these questions, I leveraged administrative data from Massachusetts and focused on 25,063 children who were enrolled in public preK between 2011 and 2014 and remained in the public schools through Grade 4. Latent class growth analysis (LCGA), a person-centered approach, was used to identify absenteeism patterns from preK to Grade 4. Regression analyses were then used to examine whether absenteeism patterns predicted Grade 4 academic outcomes and test for moderation by child- and school-level poverty. All regression analyses accounted for the nesting of children in the school of their Grade 4 enrollment and a host of child- and school-level covariates.

LCGA analyses revealed four absenteeism patterns among sample children (see Figure 1). Most children (76%) exhibited low levels of absenteeism across all observed years observed (i.e., “always low”). A substantial proportion of children (20%) exhibited levels of absenteeism typically considered at-risk for chronic absenteeism (i.e., “always at-risk”). The remaining 4% of children fell into two patterns: “always high” (2%) and “declining” (2%).

Differences in ELA and math outcomes by absenteeism trajectory were also detected (see Figure 2). On average, “always low” absenteeism children scored the highest on ELA and math, “always high” absenteeism children scored the lowest, and “always at-risk” and “declining” absenteeism children scored in between these two groups. No evidence for moderation by child-level economic disadvantage was detected, but moderation by school-level economic disadvantage was found for math achievement (“Always at-risk”: b = -0.04, SE = 0.02, p = .04; “Always high”: b = -0.11, SE = 0.05, p = .04), with larger differences between children in different patterns in schools with higher levels of economic disadvantage. These analyses shed light on the importance of considering the overall pattern of children’s absenteeism. Additional policy and practice implications will be discussed during the presentation.

Author

• Wendy Wei, SRCD Pre-doctoral State Policy Fellow, Massachusetts Department of Early Education and Care (EEC), Harvard University
  Presenting Author