The lecture series ‘Virtual Education, Real Worlds?’ will continue in the 2026/27 winter semester. This semester will again feature fascinating talks on the use of XR in university teaching, as well as reports on selected research priorities.
Dr. Miriam Mulders (20.10.2026)
Teaching in Immersive Futures: AI-powered XR dialogues for professional scenarios
This presentation provides an insight into current developments at the intersection of Artificial Intelligence (AI), Extended Reality (XR) and higher education. The focus is on immersive training and dialogue scenarios in which learners can test their skills in complex communicative situations. Drawing on current research and practical examples, the presentation discusses the educational potential, empirical findings and challenges of such environments. The presentation also serves as a public launch for the fellowship and opens up perspectives on future forms of professional skills training in higher education and schools.
Prof. Dr. Oliver Bodensiek (10.11.2026)
From XR applications to effective immersive learning environments – layered scaffolding and adaptive learning support
Immersive technologies do not influence learning solely through their technological features. Their potential is realised through psychological affordances such as presence and agency, as well as through cognitive-affective processes such as motivation, self-efficacy, cognitive load and self-regulation. However, these processes are shaped not only by the XR application itself, but also by its didactic integration and the design of the learning support. The presentation therefore explores the question of how individual XR applications can be developed into effective immersive learning environments. These are understood as didactically orchestrated learning arrangements in which preparatory, immersive, practical and reflective phases fulfil different functions. Drawing on findings regarding cognitive load, multimedia learning and scaffolding, the presentation examines how learners can be supported within and between these phases.
The focus is on the principle of multi-layered scaffolding: support measures are understood not as isolated functions, but as interrelated spatial, process-related, cognitive and reflective design elements. They can be built up, adapted and gradually phased out throughout the learning process. Building on this, the paper discusses how learning support can be better tailored to specific situations and individual needs. Process and interaction data, eye-tracking and psychophysiological markers can provide insights into cognitive-affective states, but must be interpreted in a multimodal and context-specific manner. Using examples from scientific, technical and vocational learning contexts, the potential and limitations of didactically embedded and adaptively supported immersive learning environments are highlighted.
Hendrik Peeters (08.12.2026)
Between Observation and Model: Augmented Reality in Chemistry Experiments
Although chemical phenomena are observed at the macroscopic level, explaining them requires the use of models at the submicroscopic level. Students often have difficulty linking these levels of representation. Augmented Reality (AR) offers particular potential here: Submicroscopic models can be superimposed directly onto the real experiment in both space and time, thereby bridging the gap between observation and model-based interpretation.
This paper provides insight into a doctoral project that investigates how AR influences this connection during experiments in chemistry classes. To this end, the AR app CLEAR (Chemical Laboratory Experiments with Augmented Reality) was developed, which displays submicroscopic models in parallel with selected experiments. In an initial comparative intervention study with high school students, the effect of this approach on the development of subject knowledge and cognitive load was examined. Supplementary analyses of the explanations created by the students focus on how macroscopic observations and submicroscopic models were linked in the explanatory processes. Building on this, a second study with middle school students examined the extent to which the AR-supported learning environment can be didactically enriched through targeted prompts in the form of supportive hints.
In the lecture, based on both studies, we will discuss the extent to which AR can bridge the representation levels in chemical experimentation. In addition to the empirical studies, the CLEAR app will be presented as a concrete AR learning environment and discussed in terms of its design as well as its opportunities and challenges for use in chemistry instruction.
Prof. Dr. Julia Waldeyer & Dorian Thomsen (12.01.2027)
Cognitive Load and its Impact on Learning in Extended Reality: Different Measures, Same Load?