Can School Failure Be Prevented? Using National Longitudinal Data to Improve an "Early Alert" System

• In Event: Advances and New Considerations in On-Track Indicator Systems

Abstract

In 2016, Uruguay put in place an “early alert” system and started gathering longitudinal student data to improve educational trajectories. Working in collaboration with national educational authorities, we conducted two-level hierarchical and cross-classified logistic regression analyses to understand which features of Uruguayan students’ primary school trajectories, their individual, family, primary and secondary school characteristics are related with students’ success or failure in their first year of secondary school. All considered prior-schooling factors and some secondary school characteristics significantly affect chances of success (with higher odds for success in low-SES secondary schools suggesting a frog-pond effect). Nevertheless, results warn against using predictive models without testing their sensitivity and their false positive rates, particularly for planning interventions with scarce resources.

Authors

• Jennifer Vinas-Forcade, Ghent University

• Cindy Mels, Universidad Católica del Uruguay

• Martin M. Valcke, Ghent University

• Ilse Derluyn, Ghent University