Risk and resilience factors for primary-school dropout in Côte d’Ivoire

• In Event: Protective factors for children’s academic progress and outcomes in West Africa

Abstract

Introduction
In the West African country of Côte d’Ivoire (CIV) the primary school completion rate is just 56% (UNICEF, 2020). Risks associated with school dropout have been studied in West Africa, yet more research is needed to understand what protective factors can be associated with academic resilience (i.e., remaining in school despite facing adversity). To examine dropout and academic resilience, our study had two aims. First, we aimed to identify risk factors that predict primary school dropout in rural CIV and understand how cumulative risk (CR) across child-, family-, and school-levels contribute to dropout. Second, we aimed to identify protective factors that contribute to academic resilience.
We applied a risk and resilience framework along with Bronfenbrenner’s (2005) ecological systems model in which a child's individual characteristics interact with aspects of their family and school contexts to influence the likelihood of dropout. A greater understanding of both risk and protective factors can inform more evidence-based policies and produce better educational outcomes.
Methods
At the beginning of our longitudinal study in rural CIV, 1195 students were enrolled in CM1 (equivalent to fifth grade in North America). Characteristics related to the child (i.e., age-for-grade, gender, child labour, reading skill, and growth mindset), family (i.e., socioeconomic status, maternal literacy, home literacy environment), and school (i.e., teacher quality, school infrastructure, teaching materials, and learning environment) were collected from student and teacher measures. Two years later, 7% of students had dropped out.
To understand dropout risk, we conducted multilevel logistic regression models. We first examined child-, family-, and school-level variables distinctly. We then applied a CR framework (which dichotomizes risk exposure to understand multiple domains of risk; Evans et al., 2013) to examine child-, family-, and school-level CR and their interactions. To understand academic resilience, we used findings from our risk analysis to identify a “high-risk enrolled” subset of children and compared them to the children who dropped out.
Results
Children who dropped out of school were old for their grade, involved in more child labour, had poorer literacy, owned fewer books, and attended schools with poorer learning environments. Child-level CR was the strongest predictor of dropout (b=-.860, OR=.424); however, children with low child-level CR were more likely to drop out if they experienced high family-level CR (b=.227, OR=1.250). School characteristics (better infrastructure and teachers) were protective for children who were at high risk of dropout yet remained enrolled.
Discussion
Child-, family-, and school-level factors all contributed to increased dropout and these factors interact to affect dropout. Although child- and family-level factors contribute significantly to dropout, certain school factors may mitigate these risks and promote academic resilience. Higher quality schooling is needed to increase academic resilience. Studies focused on child-, family-, and school-factors and how they interact to predict educational outcomes in West Africa, and CIV specifically, are crucial to understanding and improving academic resilience in populations at greatest risk of dropout.

Authors

• Brooke Wortsman, University of Toronto
  Presenting Author

• Angela Capani

• Henry Brice

• Mary-Claire Ball, University of Toronto

• Benjamin Zinszer, Swarthmore College

• Sharon Wolf, University of Pennsylvania

• Kaja K Jasinska, University of Toronto