Review Gold Open Access 2022

Dropout from initial vocational training – A meta-synthesis of reasons from the apprentice's point of view

Educational Research Review
Journal · Vol. 35 · Art. 100414
Abstract

Internationally, vocational education and training (VET) faces some major challenges, one of them certainly constituting the number of premature terminations of contract. A large part of former research within this context has concentrated on the identification and analysis of dropout reasons from the apprentice's point of view. Due to differing foci within previous studies, gaining a comprehensive overview of reasons for premature termination of contract has been impeded. Hence, it was the aim of this paper to summarize central cross-study and cross-sector findings within this context. Therefore, the present state of research was systematically reviewed and meta-synthesized: 70 studies were extracted, including 666 potential dropout variables that were aggregated based on 68 categories. As a result, a collection of empirically retrieved factors was developed and integrated within a framework model of premature termination of contract. Results indicate that former research has mainly focused on dropout drivers within the individual. Simultaneously, there has been far less focus on the learning environment in the workplaces. In addition, only for a small number of dropout categories are the findings consistent. Results of quantitative studies indicate that the dropout probability increases with a low training wage, a training occupation not representing the apprentice's dream job, an apprentice's low educational level, a poor performance level within training, a learning disability, increasing age and a migration background. Finally, studies find significant differences concerning the respective training occupation. © 2021 The Authors

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Author Affiliations
Universität Mannheim, Mannheim, Baden-Wurttemberg, Germany
Funding & Acknowledgements
Deutsche Forschungsgemeinschaft, DFG
Grant: KL 3076/2-1
This research study was funded by the German Research Foundation (DFG) under Grant No. KL 3076/2-1 .
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