HORIZON EUROPE FRAMEWORK PROGRAMME┋Mapping of longitudinal data and assessment of inequalities in education, training and learning achievements

Expected Outcome

Projects should contribute to all of the following expected outcomes:

• Map and collect existing regional or national longitudinal data allowing to follow individual cohorts of students over time and allowing to analyse their learning outcomes, and trends in educational inequalities.
• Provide policymakers with an analysis of the available literature and a selection of techniques used to assess inequalities in education, training and learning achievements over time.
• Identify the interventions that compensate inequalities in learning outcomes over time based on the analysis of longitudinal data.

Scope

Long-standing educational inequalities have been pervasive across the European Union and the disruptions related to the COVID-19 pandemic have further aggravated inequalities within and between countries. Despite the richness of analysis, existing initiatives and recommendations, longitudinal studies of individual student cohorts are rare, and it is difficult to follow students, assess their learning outcomes over time and identify trends in education inequalities. It is even more difficult to examine any causal link between educational policies and inequalities in education achievements. Proposals should map and collect surveys with a longitudinal design, following the learning progress of students over time, and linking with information for example on students’ achievement scores, socio-economic background, language spoken at home, migration history, the school they attend, or whether they have attended early care and childhood education. Close cooperation with authorities and/or other institutions owning the data is essential and should be ensured. Proposals should enhance the knowledge base of what shapes the educational outcomes over time, how to best support the learning of all students and reduce education inequalities in the short, medium and long-term. Clustering and cooperation with other selected projects under this call and other relevant projects are strongly encouraged.