Disentangling the role of income in the academic achievement of migrant children Academic Article uri icon

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abstract

  • Poverty has a well-established association with poor developmental outcomes in children but is often found to be a weak predictor of outcomes for migrant children. Building on theory focused on the developmental competencies of minority children, the current study used a systematic and novel analytic approach to disentangle the relationship between income and developmental outcomes for different groups of migrant children. Utilizing a population-based cohort of children in British Columbia, Canada (N = 23,154), the study examined whether income differently predicted the kindergarten to Grade 7 (K-7) literacy and numeracy trajectories of migrant children (economic, family, and refugee groups), in comparison to non-migrants. By applying Group-Based Trajectory Modeling (GBTM), the study found that lower income was generally associated with lower K-7 literacy and numeracy achievement trajectories. The relationship between income and achievement did not differ for migrant children in comparison to non-migrant children, with the exception of one sub-group of high-achieving economic class migrant children, which appeared to be less impacted by low income levels. Follow-up binomial logistic regression analysis found that parental education levels at migration and English language ability predicted which migrant children would be high literacy and numeracy achievers despite low income. The results suggest that basic associations between poverty and the outcomes of migrant children mask an underlying complexity: For most migrant children, poverty was just as predictive of detrimental academic outcomes as it was for non-migrant children and being in the exceptional sub-group of high-achieving, low-income migrant children was partly accounted for by other protective factors.

authors

  • Gagné, Monique
  • Janus, Magdalena
  • Muhajarine, Nazeem
  • Gadermann, Anne
  • Duku, Eric
  • Milbrath, Constance
  • Minh, Anita
  • Forer, Barry
  • Magee, Carly
  • Guhn, Martin

publication date

  • January 2020

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