Learning is hard work. We know this only too well from our own experience. Our research in the field of cognitive load deals with factors that are particularly strenuous and investigates how this effort can be continuously monitored in learning situations. In addition to performance measures, behavioral parameters and physiological indicators, we also use cognitive modeling approaches, in particular related to the cognitive architecture ACT-R.
Redundant information in learning material unnecessarily strains the cognitive resources of learners. Therefore, a continuously decreasing instructional support with increasing expertise is beneficial. However, a look at the current educational literature shows that structured and formalized metrics are still missing. To develop these, we use different task settings, for example, the construction of LEGO robots.
In our digital age, information is present everywhere. This often distracts us from our actual goals and interrupts our ongoing activities. In the learning context, this has tremendously negative effects. Hence, in addition to investigating interrupting characteristics of learning materials, we are developing approaches to strengthen attention control. We further explore beneficial resumption strategies and how they can be taught.
In 2015, the member states of the UN adopted the Agenda 2030 for sustainable development, which among other things stipulates the protection and restoration of our ecosystem. In this context, digital media can help to raise awareness of environmentally friendly actions and bring about sustainable changes in behavior.
In our project "BeeLife", we are developing an intelligent app for schools that demonstrates the importance of wild bees for our ecosystem. The project is sponsored by the German Federal Environmental Foundation.
Technical devices can be used most effectively to support learning processes if they take into account that different people use them in different ways. We are therefore investigating the ways in which factors such as age, gender, affinity for technology or cognitive limitations influence this and incorporate these findings into the design of technology.
Artificial intelligence is part of our everyday life, a component of technical innovations and increasingly becoming part of education. Intelligent systems are often assumed to make objective decisions, but numerous examples demonstrate how such systems take over our conscious and unconscious stereotypes and biases. By initiating processes of reflection, we strive to sensitize people to societal implications of these stereotypes and biases in intelligent systems.