Project info

  • Reducing Early Leaving in VET

    Reducing Early Leaving in VET

  • 2018-1-RO01-KA202-049334

  • 01/10/2018 - 30/09/2020

Project info

  • erasmusplus

  • Action ka202

  • Call 2018

  • CEN

Project Description:

Early leaving from education and training (ELET) is a serious issue in many EU countries and has attracted the attention of many researchers, policy-makers and educators. Although the situation varies across countries and the underlying reasons for students leaving early are highly individual, the process leading up to it includes a number of common elements: learning difficulties, socio-economic problems, or a lack of motivation, guidance or support.

Early leaving is highly challenging, not only for young people, but also for societies. For many, Early Leaving Education or Training will lead to reduced opportunities in the labour market and an increased likelihood of unemployment, poverty, health problems and reduced participation in political, social and cultural activities. Furthermore, these negative consequences have an impact on the next generation and may perpetuate the occurrence of early leaving. Youth unemployment in the EU is currently running at 20% and ELET contributes directly to it as employability depends strongly on the level of qualification achieved.

In order to understand why young people leave education and training early, it is moreover important to see ELET not only as a status or educational outcome but as a process of disengagement that occurs over time (Lyche, 2010). Chronic absenteeism and exclusion from school can be among the symptoms, or may even be the cause of students leaving early (Neild et al., 2007). However, there are more signs which indicate that students may be at risk. Warning signs may occur as early as in primary school and may be related to individual factors (e.g. educational performance, behaviour, attitudes) or to factors within individuals’ families, their schools, and communities . Understanding early leaving from education and training as a complex process, detecting early signals and identifying students who are at risk of leaving education and training early is therefore a prerequisite for developing targeted and effective measures to prevent it.