ABOUT THE PROJECT

Short Description

Objective and focus

The stAI project is dedicated to reducing the average percentage of early leavers in education through a multifaceted approach. This involves identifying key risk factors contributing to early leaving, recommending effective intervention strategies, leveraging knowledge-driven AI systems in decision-making, enhancing decision support mechanisms, and advising policymakers on implementing education ecosystem improvements at the local level.

Short Description

Implementation activities

The project’s implementation encompasses various activities. These include creating a transnational early leavers risk map, compiling a comprehensive compendium of best practices, guidelines, ethics principles, and national governance initiatives. Additionally, the project involves developing an AI prompt-system prototype with multilingual support to assist in decision-making processes.

Short Description

Anticipated results

The expected outcomes of the stAI project include a transnational risk map highlighting intervention recommendations, a compendium featuring case studies and insights into knowledge-driven AI systems, and the technical implementation of an AI prompt system prototype. Furthermore, the project aims to establish stakeholders’ ecosystems through targeted activities across different work packages.

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Significance and impact

By achieving its objectives and delivering on its anticipated results, the stAI project seeks to make significant strides in reducing early leaving in education. Through the identification of risk factors, recommendation of interventions, and leveraging AI-driven decision-making tools, the project aims to create a more supportive and effective educational environment, ultimately benefiting students, educators, policymakers, and society as a whole.