Student Achievement Trajectories in Ontario: Creating and validating a province-wide, multi-cohort and longitudinal database

IntroductionLongitudinal data that tracks student achievement over many years are crucial for understanding children's learning and guiding effective policies interventions. Despite being Canada's most populous province, Ontario lacks such large-scale longitudinal on learning. Linking datasets across cohorts requires rigorous linkage protocols, flexible handling of complex cohort structures, methods to validate linked datasets, viable organizational partnerships. We administrative early child development educational merged two characteristics students' neighborhoods schools. developed a protocol validated how the resulting database could be generalized Ontario's population. Methods analysisTwo main individual-level sources were linked: 1) Early Development Instrument (EDI), school readiness assessment all public kindergartners is administered in three-year cycles, 2) Educational Quality Assessment Office's (EQAO) math reading assessments grades 3, 6, 9, 10. To compensate their lack common personal identification number, deterministic process was using several variables. A school-level neighborhood-level dataset also later linked. examined differences between unlinked cases Results implicationsWe successfully 50% EDI's 374,239 cases, 86,778 which contained five datapoints, creating tracking multiple from kindergarten through grade 10, with covariates development, demographics, affect, neighborhoods, Analyses revealed only negligible demographic measures, while small detected neighborhood socioeconomic index some measures development. In conclusion, we recommend filling key voids sustainable research capacity by representative protocols verification.