PASSt - Predictive Analytics Services for Study Success Management

In a modern and increasingly diverse knowledge society, it is essential for universities to be able to respond to the individual starting conditions and needs of students in a targeted and effective manner. For this purpose, it is necessary to analyze the challenges of student cohorts and to take into account different socio-demographic and private conditions (social background, employment, care obligations, etc.) in order to create an information base on which measures can be taken in the future to increase studyability.

The aim of the project is to develop, test and validate data-based planning and forecasting tools for optimizing teaching and study processes, in particular also study success and examination activity, and finally to make them available to all Austrian universities. Specifically, the model approach combines regressions, machine learning, and simulations to achieve the most accurate result possible.

The project PASSt is carried out by the TU Wien under the direction of Dr. Shabnam Tauböck and in cooperation with the WU Wien and the JKU Linz.

For more information on the project, please visit the project's public coLAB space, opens an external URL in a new window.