This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…

Chronic absenteeism is a critical issue that has been linked to many adverse student outcomes. The current study focuses on improving a key system already in place in many school districts--early warning systems (EWSs)--in order to decrease chronic absenteeism in students' earliest schooling years. Using a demographically diverse population of…

Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…

This book presents how to keep working on education in contexts of crisis, such as emergencies, zones of conflict, wars and health pandemics such as COVID-19. Specifically, this work shows a number of strategies to support global learning and teaching in online settings. Particularly, it first presents how to facilitate knowledge sharing and…

This guide aims to help parents understand the flexibility provided to States and school districts in the "Every Student Succeeds Act" (ESSA), which amended the "Elementary and Secondary Education Act," a landmark Federal education law. Parents are the most important advocates for their children. Because States and school…