Objective
Where the available research data on ESL only explains isolated aspects of the evolution towards ESL, the RESL.eu project analyses ESL from a holistic perspective. By framing the complex and often subtle interplay of factors influencing ESL on macro/meso/micro level; and by deconstructing these configurations of influencing factors in the specific contexts where they occur, we expect to uncover specific combinations of variables and contexts influencing the processes related to ESL. This allows us to formulate conceptual models useful for the development and implementation of policies and specific measures to influence ESL, making the project not only relevant to academics, but also to policy makers, school staff and civil society.
RESL.eu aims to provide insights into the mechanisms and processes influencing a pupil’s decision to leave school/training early; as well as into the decision of ESLers to enroll in alternative learning arenas unrelated to a regular school - but wherein specific creative or innovative methods of knowledge and skill transfer are used. Additionally, RESL.eu focuses on the vulnerable group of youngsters that left education or training early and are identified as NEET (Not in Education, Employment or Training). RESL.eu also aims to identify and analyze the intervention and compensation measures that succeeded in transferring knowledge and in keeping pupils in education/training, although they showed high (theoretical) risk of ESL.
In order to be able to compare the data gathered in 7 partner countries, RESL.eu will develop and refine the theoretical framework on ESL, formulating a workable yet nuanced definition of ESL. Through a mixed-method design, a total of 28140 surveys and 1176 interviews/FGD will be conducted, generating in-depth data while allowing systematic comparisons and quantitative generalizations. Results are targeted at different audiences/stakeholders: EU- & national policy makers, school staff, academics and civil society.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- social sciencessociologysocial issuessocial inequalities
- social sciencespolitical sciencespolitical policiescivil society
- social scienceseconomics and businessbusiness and managementemployment
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Call for proposal
FP7-SSH-2012-1
See other projects for this call
Funding Scheme
CP-IP - Large-scale integrating projectCoordinator
2000 Antwerpen
Belgium