
Marco Frezzella
Press Officer
Haus G, Max-Planck-Ring 14
98693 Ilmenau
+ 49 3677 69-5003
marco.frezzella@tu-ilmenau.de
On September 1, TU Ilmenau will launch two innovative digital teaching projects funded by the Free State of Thuringia as part of the fellowship program for innovations in digital university teaching: One teaching project simulates a 3D substation in a virtual learning world, which is intended to make the energy supply of the future tangible for students. Another project uses experimental data to familiarize students with machine learning methods. In future, the results of the projects will also be made available to teachers at other universities as freely accessible and free teaching, learning and research resources.
The Thuringian Ministry of Education, Science and Culture and the Stifterverband, a funding network of companies, foundations, scientific organizations and private individuals, are supporting two innovative digital teaching projects at TU Ilmenau. The fellowship funding program aims to create incentives for the development and testing of digitally supported teaching and examination formats and to consolidate digital teaching at universities. For the funding period from September 1, 2025 to December 31, 2026, university lecturers will receive up to 50,000 euros for the development of digital teaching innovations. The materials or processes created in the funded projects are to be made available to other lecturers across universities as open educational resources.
AdobeStock/JackThe project "Virtual energy systems - 3D worlds for teaching sustainable energy systems", which Professor Dirk Westermann, Head of the Department of Electrical Power Supply, is launching in September, aims to deepen electrical engineering students' understanding of energy systems by using 3D models of substations and equipment. By enabling students to move independently in the virtual environment of a substation and explore the individual components, the digital models are intended to illustrate modern energy supply and make it comprehensible to them. The models also enable a detailed, realistic representation of equipment that is often difficult to access or dangerous in reality. The models are also used by teachers to explain certain functions of substations and modern energy supply processes. As the system is browser-based, users can access the learning content easily and flexibly from various end devices.
The special feature of the teaching project is the holistic integration of electrical energy systems into a virtual learning environment. In contrast to previous teaching methods, in which photos and videos are used, the 3D models enable an interactive and immersive learning experience. The use of such digital models should not only promote students' understanding of complex processes in energy systems, but also increase their motivation for a challenging course of study.
AdobeStock/AmalIn the project "Modelling Complex Systems with Machine Learning Methods (KoSyMo)" by Professor Christian Cierpka, Head of the Department of Technical Thermodynamics, and Dr Jan Heiland from the Department of Optimization-based Control, it is being demonstrated how digital, live measurement data from a technical experiment can be used for mathematical predictions. Similar setups and data play a role in weather observation, for example, and are used to make short and medium-term forecasts. Data-based mathematical methods at the interface to innovative measurement technology are needed in a variety of application areas in the modern world, as complex systems - such as ecosystems, the internet, the human nervous system or even urban traffic and economies - need to be understood and technologically controlled.
The sustainable and cost-effective technical setup designed by Prof. Cierpka and Dr. Heiland directly links experiment and data analysis: the practical physical experiment and the mathematical system theory. This enables students from a wide range of technical disciplines to recognize theoretical and technical difficulties straight away. In addition, data obtained in real time from an experiment gives them direct feedback on the success or failure of the mathematical modeling applied and the acquisition of measurement data - in a wide variety of interdisciplinary fields, such as data analysis, measurement technology, simulation and plant engineering. In this way, the new technology, embedded in a theoretical framework, creates innovative learning conditions for students that can achieve continuous learning success and a high level of satisfaction during their studies