Digital media are increasingly used in formal teaching and learning contexts such as schools and universities. The explanation of to-be-learned phenomena within these media takes place by using combinations of different representation formats such as texts, pictures, animations or simulations. The research group is engaged in researching these multi-representational learning environments.
Multiple representations can be conducive to learning for various reasons, but their effectiveness depends on certain processes. In particular, learners must link essential information from text and image in memory (cognitive processes). Particularly during longer learning episodes, there is also a need for self-regulation of the learning process. Learners must develop a correct assessment of their current state of knowledge, which, among other things, allows them to control future learning activities in such a way that any gaps in knowledge that may still exist can be eliminated (metacognitive processes). Accordingly, a first goal of the research group is the empirical description of cognitive and metacognitive processes in learning with multiple representations.
Learners often have difficulties in carrying out these cognitive and metacognitive learning processes. Therefore, another objective is to develop support measures. On the one hand, these are based on an extension of classical teaching-learning scenarios by further multi-representational media (e.g. virtual experiments). On the other hand, specific features of digital media are used to develop support measures for learning with multiple representations (e.g. adaptive feedback based on process data). Research in this area is therefore concerned with the digital augmentation of teaching and learning scenarios.
