Why do they leave? Examining dropout behaviour in gender-atypical vocational education and training in Germany
Bibliographic Data
| ID | 6439342 |
|---|---|
| Authors | Janina Beckmann (0000-0001-6568-6523, Federal Institute for Vocational Education and Training, corresponding author) |
| Year | 2023 |
| Volume | 77 |
| Issue | 2 |
| Pages | 297-321 |
| Publication date | 2023-05-24 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Vocational Education and Training (JOURNAL) |
| Journal identifiers | ISSN: 1363-6820 • E-ISSN: 1747-5090 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/13636820.2023.2211546 |
| OpenAlex | W4378233786 |
| Language | EN |
| Citations received | 3 |
| References cited | 76 |
Germany's VET system is highly gender-segregated and marked by high dropout rates. This article investigates the dropout behaviour of apprentices in gender-atypical training occupations. First, we investigate whether gender-atypical apprentices drop out at a higher rate than their majority peers. Second, we examine differences in the self-reported reasons for dropping out among gender-typical and gender-atypical apprentices. Results show that gender-atypical apprentices, and particularly males in female-dominated occupations, are more likely to prematurely leave their apprenticeship. The self-reported reasons for dropping out differed by gender minority status: female minorities were more likely to drop out due to a lack of social integration, while male minorities were more likely to drop out due to unfulfilled aspirations in comparison to the gender majority. These results show that gender-specific perceptions and experiences are related to the higher dropout rates of gender-atypical apprentices
Apprenticeship · Demographic economics · Drop out · Dropout (neural networks · Geography · Pedagogy · Vocational education · Gender Diversity and Inequality · Labor market dynamics and wage inequality · Psychology · Youth Education and Societal Dynamics
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| Unique citing works | 3 |
|---|---|
| Citations per year | 1 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |