Publications

The article focuses on students with health impairments that have adverse effects on their studies, within the German higher education system. Using data from “The student survey in Germany: best: Studying with health impairments” we present current results on the composition of this group, on their drop-out intention and experienced discrimination during their studies. There exist notable differences within this group according to the type and severity of impairment.

The COVID-19 pandemic accelerated the digitalisation of higher education, presenting both opportunities and challenges. It acted as a universal catalyst for digitalization. This (forced) boost of digitalisation creates both: Possibilities for increased inclusion of underrepresented student groups in higher education on the one hand, and challenges with regards to an inflexible overreliance on digital formats for other student groups on the other hand. This report examines the interplay between institutional services, student needs, and study modes, aiming to understand their impact on satisfaction and success in higher education.

Early-life environments can have long-lasting effects on individuals’ later life courses. Interestingly, research on the effects of school reforms has hardly adopted this perspective. Therefore, we investigate a staggered school reform that reduced the number of school years and increased weekly instructional time for secondary school students in most German federal states. We analyze this quasi-experiment in a difference-in-differences framework using nationally representative large-scale survey data on 69,513 students who attended university between 1998 and 2016. Using both TWFE and weighted-group ATT estimators, we find negative effects of reform exposure on hours spent attending classes and on self-study.

This work proposes using the feature of large language models (LLMs) to learn about the "data bias" injected by diverse SDG classifications into bibliometric data by exploring five SDGs. We build a LLM that is fine-tuned in parallel by the diverse SDG classifications inscribed into the databases' SDG classifications. Our results show high sensitivity in model architecture, classified publications, fine-tuning process and natural language generation. The wide arbitrariness at different levels raises concerns about using LLM in research practice.

Nacaps, the National Academics Panel Study, is a new longitudinal study of doctoral candidates and doctorate holders in Germany funded by the Federal Ministry of Education and Research (BMBF). The project aims at providing nationwide cross-sectional and longitudinal data on doctoral candidates and doctorate holders in Germany regarding their study conditions as well as their career trajectories within and outside of academia. The Nacaps study series apply a panel design to multiple cohorts. Nacaps 2018 is the first cohort in this series of studies. In 2019, all doctoral candidates registered at 53 higher education institutions [...] Full Abstract: https://doi.org/10.21249/DZHW:nac2018:2.0.0