PASSt – which stands for "Predictive Analytics Services for Student Success Management" – is one of the projects that is being funded as part of the tender for "Digital and social transformation in higher education, opens an external URL in a new window" by the Federal Ministry for Education, Science and Research. Led by TU Wien in conjunction with its partners JKU Linz, University of Graz and WU Wien, the project team is developing digital planning and forecasting tools to improve teaching and study processes.
Navigation system for study success
Using current analytics methods and technologies, the university's wealth of data should be used to acquire useful knowledge about student behaviour and study success. Digital tools for different target groups are emerging within the project. The focus is naturally on the students, whose study progress and success needs to be more transparent. This will thus enable specific measures to be offered to become more successful through study – the vision is for a navigation system for study success.
Naturally, the processing of personal data for study success is a central issue to be considered from the outset with regard to data protection and ethical considerations. This issue is thus already one of the project's first work packages, with the aim not only of complying with legal standards but also of developing a generally applicable code of practice that enables students to have the best possible transparency for the processing of their data.
Visualised information for university management
It is not just individual students who should benefit. Assessment activity, i.e. the number of students who pass each academic year with at least 16 ECTS credits, is also a significant influencing factor in university financing. As well as other key performance indicators for university management, PASSt should also develop forecasting models that can be used to gain a better estimate of this number of assessment activities – and thus indirectly of future budgets. Information about study success should be prepared and presented clearly (through "dashboards"). It should be possible to derive measures to improve the study setup easily. In future, these dashboards should also support academic authorities, such as academic deans and academic commissions, with well-prepared data.
Project launched in summer
The project began in June 2020 and will continue until mid-2023. The inter-university project team is already working hard on its first work package, which concerns the review of university data models and specification of model variables for the forecasting models.