This project focuses on promotive and protective factors in the context of reading and math difficulties. The project aims to understand two types of resilience: (1) educational engagement and attainment during secondary education despite learning difficulties, and (2) resolution of reading and math difficulties over time. The goal is to integrate information regarding child-, parent-, and school-related factors in order to identify the promotive and protective factors contributing to the two types of resilience. This will be achieved by: (1) using longitudinal datasets spanning from early childhood to adulthood, (2) including a variety of cognitive, parental, motivational, and school-related factors, and (3) using advanced statistical methods. Data from two Finnish longitudinal studies will be used; the Jyvaskyla Longitudinal Study of Dyslexia (JLD) and the First Steps Study/School Path.
The findings add knowledge on the protective mechanisms in the development of reading and math and inform the development of evidence-based curricula, the development of targeted support systems, and intervention programs for children and youth facing difficulties in reading and math.
Psyridou, M., Prezja, F., Torppa, M., Lerkkanen, M.-K., Poikkeus, A.-M., Vasalampi, K. (2024). Machine learning predicts upper secondary education dropout as early as the end of primary school. (arXiv:2403.14663) https://doi.org/10.48550/arXiv.2403.14663