Digital Education

Artificial intelligence (AI) tools have evolved into important parts of everyday life, resulting in challenges for education. Generative AI tools can be used to effortlessly create texts, visualizations, and videos using prompts. This relative ease has several implications, such as placebo effects that lead AI users to overestimate their abilities. A major focus in this research area consists in the ethical issues surrounding AI-generated content in education and science. Read a current publication on the ethics of erroneous AI-generated visualizations in science by clicking the link below.

Virtually all forms of digital education result in at least some form of cognitive load. For instance, interactive simulations and serious games require learners to familiarize themselves with their controls, which are not directly related to the learning content. Influential theories of learning suggest that such demands would lead to diminished learning, while several studies indicate that (some) cognitive load does not necessarily lead to negative effects. The approach of cognitive load alignment holds that cognitive load in digital learning can be justified if the digital learning components are in alignment with the learning objective. The key publication on cognitive load alignment can be found under the following link.

Computer-generated visualizations, virtual reality, and augmented reality are becoming increasingly important components of education. A high level of visual detail does not necessarily help learners (and may even overwhelm them), yet simplified styles do not provide the optimal level of realism for all types of learning objectives. In this research area, learners' cognitive processing of realistic visualizations is studied and implications for design are drawn. To read a theoretical framework for learning with realistic visualizations, click on the link below.