Act before it happens: Preventing and fighting Early Leaving from Education and Training with Artificial Intelligence

<< Objectives >>The implementation of stAI project aims to contribute to lower 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 decision w.r.t. ELET in education-Improving decision support in education -Advising policy makers to support the implementation of the education ecosystems at local level.<< Implementation >>stAI activities:-Transnational ELET risk map (60 teachers,30 policy makers)-Elaboration of a Compendium incl:-Collection of good pract. about opportunities and concern to introduce knowledge-driven AI systems in education-Guidelines and ethics principles -National governance initiatives related to ELET-Exec.Summary of the Compendium in EN+7languages-Development of an AI prompt-system prototype in EN and video tutorial in 7 languages-Recom. for policy makers in EN+7languages<< Results >>The results will be stemming from 4 main WPs: -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, benefit, 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