stAI
Act before it happens: Preventing and fighting Early Leaving from Education and Training with Artificial Intelligence
Nov.2023 – Oct.2026 | Erasmus+ | KA2 | Cooperation Partnership in school education | Project n. KA220-SCH-872D0211
AIM
According to CEDEFOP (2013), early leaving from education and training (ELET) constitutes 1.25% of the European GDP, with 10.6% of 18-24-year-olds in Europe being early leavers in 2018. Iceland has one of the highest rates at 20%, and countries like Portugal (25%), Romania (15.6%), and Italy (13.1%) exhibit concerning levels.
StAI Partners will cooperate to implement coordinated actions to prevent and, thus reduce ELET by monitoring and identifying – through the use of data science made accessible through an AI prompt-based system– the main factors influencing early leaving from education and training in their countries.
AIM
The stAI project aims to address the impact of ELET on students, emphasizing the critical role of teachers in intervention, as poor student-teacher relationships increase the likelihood of early leaving.
The initiative also targets the need to make research on ELET more accessible for teachers, implement supportive policies in schools, and provide decision-support tools for educational researchers and professionals.
Ultimately, the project seeks to improve policies, reduce early leaving, and enhance the transition from education to the next generation in Europe.
OBJECTIVES
The implementation of the stAI project aims to contribute to lowering the average percentage of early leavers by:
- Mapping the main risk factors that lead to ELET, thus recommending the most effective intervention strategies
- Outlining a complete picture of what systems based on knowledge-driven AI are, and how they can support decisions concerning ELET in education
- Improving decision support in education
- Advising policymakers to support the implementation of the education ecosystems at the local level
RESULTS
The results will be stemming from five Work Packages:
- WP1: Management
- WP2: Transnational Map of risk factors and recommendations about the most effective intervention strategies to prevent and combat ELET,
- WP3: Compendium of case studies displaying the potential, benefits, and concerns around the introduction of a prompt-based system based on knowledge-driven AI in education
- WP4: Technical design and implementation of an AI prompt-system prototype + usability kit
- WP5: Creation of stakeholders’ ecosystems
PARTNERSHIP
Coordinator:
P1 Haskoli Islands – School of Education – IS
Partners:
P2 Vrije Universiteit Brussel – BE
P3 CRES – Centro Ricerche e Studi Europei-future business – IT
P4 Scuolattiva Cooperativa Sociale Onlus – IT
P5 Colegiul National de Arta “Octav Bancila” – RO
P6 Escola Secundária Dr. José Afonso – PT
P7 A & A Emphasys Interactive Solutions Ltd – CY
WEBSITE:
http://stai-edu.eu/
PROJECT OUTCOMES
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The European Commission’s support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.