International student mobility (ISM) prepares young people for the challenges of global and multicultural environments. However, disadvantaged students have lower participation rates in mobility schemes and, hence, benefit less from their positive impacts on career progression. Therefore, policymakers aim to make mobility programs more inclusive. Nevertheless, it is far from clear how policy design can achieve this aim. This study investigates factors driving inequality in international student mobility uptake. The study’s novelty is twofold: first, in contrast to most existing studies it does not only investigate individual but also university characteristics as possible drivers of unequal uptake. This is possible due to the use of rich graduate survey and administrative data merged with university-level ETER data. Second, the study compares results across four European countries. Results show that the socio-economic mobility gap remains still sizable even when taking university characteristics into account. However, universities matter considerably and especially student compositions in terms of socio-economic background and ability contribute to unequal ISM uptake. As a consequence, intergovernmental policies should aim to distribute grants and mobility opportunities more equally across all universities, independent of their student composition.
ETER User Trainings
ETER Introductory User Training
The training addresses first-time and entry-level ETER users (e.g. policy analysts, institutional managers at HEIs,…). The main goal is to enable users to navigate through the ETER data interface, select the data of interest (variables, countries, years) and extract data according to their needs. A practical demonstration of a simple use case will prepare users to perform basic analysis with ETER data.
Using ETER Data to Compare Institutions
The training will focus on the usage of ETER to identify institutions with similar profile as the focal one, and on which data and indicators can be used for comparing them. It will be therefore of interest for institutional managers and data analysts.
Clean and Prepare ETER Data for Analysis with Stata
The training will provide an overview on the ETER data structure, different options of importing ETER data into Stata, data preparation and examples from the ETER project using Stata.