During its first 18 months, LINEup has laid the groundwork for a comprehensive exploration of longitudinal data on students’ learning outcomes in Europe.
A first milestone was the systematic literature review, through which the consortium examined existing research based on longitudinal and repeated cross-sectional designs to study educational inequalities. The review identified 77 datasets, 54 analytical methods, and 70 variables, organized into a conceptual model with four clusters - student, family, teacher, school and education system. This model highlights the multiple and interrelated factors that shape educational inequalities.
On this basis, the consortium carried out a mapping of existing longitudinal datasets across 32 countries (the 27 EU Member States, three European Education Area associated countries – Iceland, Liechtenstein and Norway – plus Switzerland and the United Kingdom). More than 200 potential datasets were reviewed, of which 104 met the inclusion criteria and were included in the mapping. Each dataset was described in terms of its structure, scope and potential for analysing students’ educational outcomes and trajectories. The mapping revealed that strong data infrastructures are concentrated in Western and Northern Europe, while significant gaps remain in several Central and Eastern countries - underscoring the uneven coverage of longitudinal data in education.
In parallel, the project developed the Education Data Explorer, a user-friendly, open-access platform that visualizes the results of the mapping. The tool enables researchers and educational stakeholders to discover available data sources, explore their features, and assess their analytical potential. By making this information easily accessible, the Explorer represents a key step towards greater transparency and accessibility of longitudinal data in education.
Finally, the project launched a feasibility study on harmonization, assessing the extent to which the mapped datasets are comparable. Preliminary findings show both opportunities (e.g. shared variables on basic skills and background) and challenges (e.g. differences in test design, coding systems, and accessibility).
Together, these achievements significantly advance knowledge of what longitudinal data exist in Europe, how they can be used to study inequalities, and what steps are needed to move towards cross-country comparative research.
