DS4AA - Understanding the drivers of academic achievement for Portugal’s high school system, 2018

DS4AA - Understanding the drivers of academic achievement for Portugal’s high school system

The DS4AA project examines factors influencing academic achievement across public high schools in Portugal. School dropout rates, currently at 14%—above the European average—represent a significant hurdle for economic and social progress, as underscored by the European Commission. This project aims to explore the key antecedents of academic success at a national scale, aligning with the European Strategy 2020 objective to reduce dropout rates below 10% and increase higher education attainment.

Drawing from the comprehensive data available in Portugal, the project uses a large set of historical student records provided by the Directorate-General for Education and Science Statistics (DGEEC). By applying advanced data science and artificial intelligence (AI) techniques, DS4AA develops predictive models to identify critical factors influencing academic achievement, helping policymakers and educators design targeted interventions.

This project was coordinated by NOVA IMS in partnership with the Directorate-General for Education and Science Statistics (DGEEC).

As the coordinator of the DS4AA project, NOVA IMS led the strategic and technical execution of this initiative, utilizing its expertise in data science and AI to transform educational data into actionable insights. NOVA IMS spearheaded the application of sophisticated supervised AI methods to build predictive models that illuminate the primary factors influencing student performance, from demographic characteristics to school-level variables.

In collaboration with DGEEC, NOVA IMS efficiently leveraged existing large-scale datasets to develop regression and classification analyses, which form the foundation of the predictive tools now available for early-year forecasts of individual student performance. These tools empower public authorities, schools, and educators to make data-driven decisions, aligning educational practices with national and EU objectives and enhancing the effectiveness of public decision-making processes.

• Funding Programme: FCT, I.P. - Scientific Research and Technological Development Projects in Data Science and Artificial Intelligence in Public Administration
• Funding to NOVA IMS: 157 737,50 € 
• Duration: 2019 - 2022
• Website: https://ds4aa.pt/