Our ambition is to contribute to lowering the average percentage of early school leavers. We will start with the country-specific risk maps, the benefits of applying AI-powered tools to support decision-making in education, and boldly go beyond to design and develop a knowledge-based AI prompt-system prototype to automate the extraction of actionable insight on the local factors influencing ELET and identify early school leavers. We will demonstrate to policymakers, stakeholders, and teachers that this system can result in a responsible use of AI to identify school leavers.
Partners
Haskoli Islands, Iceland
Vrije Universiteit Brussel, Belgium
CRES Centro di Ricerche e Studi Europei – future business, Italy
Scuolattiva Cooperativa Sociale Onlus, Italy
Colegiul National de Arta “Octav Bancila”, Romania
Escola Secundária Dr. José Afonso, Portugal
The project’s main intended impact is to monitor ELET by supporting schools in creating tools for them based on proven AI technology with three main purposes:
Descriptive: to better understand the factors leading to ELET in a specific, local context, to improve ELET-related policies.
Predictive: to provide teachers with an actionable and interpretable tool to identify at-risk students early on, adapted to the specific school context.
Prescriptive: supporting different stakeholders by suggesting interventions with the highest impact
We will also look into the following main topics:
Project Info
Start 01/01/2024
End 31/12/2026
Funding European Commission, Erasmus+
Members Prof. Dr. Johan Loeckx, Dr. Leticia Arco García, MSc. Laetitia D’Ornano
