PhD Cognitive Load in a Digital 3D Learning Environment (1.0 FTE)

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University , the various disciplines collaborate intensively towards major societal themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Sustainability.

The Faculty of Veterinary Medicine has a unique position in the Netherlands. Not only is this the only institution where Veterinarians are trained, but is is also where Researchers are working together on innovative scientific research. In addition, the faculty provides specialist clinical care in the largest academic veterinary hospital in Europe. Thanks to this position, the Faculty of Veterinary Medicine is a point of contact for all veterinary matters, both nationally and increasingly internationally. The faculty employs approximately 900 Veterinarians, Scientists and support staff and counts 1,500 students.

Digital 3-dimensional (3D) environments are increasingly used for learning in higher education. Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR) and eXtended Reality (XR) are examples of these environments. They offer the opportunity to better align competence development and learning by allowing to study complex 3D relationships in a full 3D context. In addition, they offer excellent opportunities for active, collaborative and experimental learning. However, new learning technologies often involve new cognitive mechanisms that can influence learning efficacy.

At the Utrecht University Veterinary Faculty, in close collaboration with the Leiden University Medical Center, we are investigating the use of new learning technologies in our curricula. Previous research in the context of learning 3D Anatomy with AR technology (Microsoft HoloLens) revealed that the students’ cognitive profiles affect their learning efficacy in a 3D digital learning environment. The project aims to identify the role of cognitive load in that process. Methods will be developed to monitor various aspects of cognitive loads in real time during the 3D learning process. Currently we focus on biometric measurements like pupil diameter/eye tracking and mobile electric encephalography (EEG).