“Understanding a concept is the beginning of understanding science. Without conceptual understanding, you cannot bring the idea of what you are aiming to achieve to a wider audience. Without interesting a wider audience, you will never inspire the next generation of scientists and researchers on whom future science will rely.”
Stefan Rossegger, CERN Switzerland

In the system-oriented natural sciences students should achieve sufficient scientific competence to be able to work independently in their chosen field. For that they must be able to form appropriate mental models of the complex systems they study, and of the key processes driving them. They also need to develop their skills in problem solving.

It is difficult by conventional teaching to stimulate the cognitive processes needed to form useful mental models. Hence we have developed tools for visual modeling to help students integrate inputs/information in the form of an evolving mental model. As a result students should be able to appreciate how system complexity builds on simple processes and process interaction, and build hypotheses about how processes relate to observed data.

We support mental model building using both basic and advanced visual models:

Basic model building

For example by (what-if) scenario visualization – Fundamentals EVOs

Advanced model building

Parameterization of dynamic visual models – Modeling EVOs