Social Origin and Students' Trajectory Patterns at German Universities. A Sequence-Analytical Approach
Bibliographic Data
| ID | 3940907 |
|---|---|
| Authors | Christina Haas (0000-0002-9972-4759, corresponding author) |
| Year | 2023 |
| Volume | 74 |
| Issue | 3 |
| Pages | 431-465 |
| Publication date | 2023-01-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Soziale Welt (JOURNAL) |
| Journal identifiers | ISSN: 0038-6073 |
| Publisher | Nomos Verlag (PUBLISHER) |
| DOI | 10.5771/0038-6073-2023-3-431 |
| OpenAlex | W4387066356 |
| Language | EN |
| Citations received | 2 |
While the relationship between the transition to higher education and social origin has been widely investigated, much less is known about study trajectories, that is, the study patterns between enrolment and graduation (or terminal dropout). This paper fills this gap by responding to the question: 'How do students of different social origin progress through their bachelor's studies at German univer- sities?' Based on explanations of how academic-cultural and economic resources are related to social origin, opposing hypotheses regarding students' social origin and their experience of linear, as opposed to less linear, higher education trajectories are developed. The analysis is based on a panel study with bachelor students at German universities (National Educational Panel Study, NEPS). Trajectories are reconstructed using sequence analysis, yielding six different higher education trajectory types. The results of the multinomial logistic regression models reveal that students with low educated parents are at greater risk of following incomplete and more complex study trajectories. Compared with those students who experience a linear trajectory, the divergence in paths is partly explained with reference to differences in academic achievement, but also, to some degree, with reference to other resource differences
Bachelor · Divergence (linguistics) · Economic growth · Economics · Geography · German · Graduation (instrument) · Higher education · Mathematics education · Multinomial logistic regression · Political science · Socioeconomic status · Sociology · Statistics · Trajectory · Advanced Causal Inference Techniques · Demography · Intergenerational and Educational Inequality Studies · Mathematics · Psychology · Spatial and Panel Data Analysis
| Citations per year | 1 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |