Significance of the Institutional Context for Drop-Out and Long-Term Studies

Research question/goal: 

As part of the joint project "Significance of the Institutional Context for Drop-Out and Long-Term Studies", the sub-project "Institutional Context at the State and University Level" is being carried out at the MZES. Cooperation partners are the German Centre for Higher Education Research and Science Studies (DZHW), whose scientific director Prof. Monika Jungbauer-Gans coordinates the project , and the University of Hanover, represented by the project directors Prof. Christoph Hönnige (Political Science) and Prof. Volker Epping (Law; President of the University of Hanover). The joint project is funded by the Federal Ministry of Education and Research (BMBF) in the research field of "prevention and intervention measures in higher education to reduce drop-out".

The joint project investigates the effect of the study-related institutional context on the course of study, intention to drop out, long-term study and drop-out. The sub-studies "Institutional Context", "Duration of Studies and Drop-Out", and "Intention to Drop Out" examine the aforementioned effects on the basis of data from official statistics and surveys. The characteristics of the institutional context for three levels (state, university, degree programme) are determined by the partners at the University of Hanover and the MZES. Our sub-study uses a quantitative text analysis to measure the contextual feature space on a common theoretical basis. This allows for scaling, reproducing and validating the institutional context.

The focal questions in the project are:

  • Does the institutional context, i.e. the state laws regulating higher education and the general examination regulations of higher education institutions that are relevant to the course of study, have an effect on the frequency of dropping out?
  • Do these regulations correlate with the occurrence of long-term students—as a group at risk of dropping out?
Current stage: 

The Mannheim subproject team has developed an elaborate coding scheme to capture the level of flexibility in examination regulations. The manual coding is underway and will be used for algorithms to measure the character of other texts. We are currently also setting up a “Shiny Server” application on a virtual machine at the MZES to make the corpus, the coding, and the results of the machine learning available.

Fact sheet

2021 to 2022
Data Sources: 
Laws and regulations at the state and university level
Geographic Space: 
German Bundesländer