(H/F) Ph.D. student in Extended Reality in Collaborative Learning Applications

This project is in an emerging research area that lies at the intersection of education research, data science, human-computer interaction, virtual reality & augmented reality, and computer-supported cooperative work.
The PhD project will be carried out at LISN (Laboratoire Interdisciplinaire des Sciences du Numérique) in the VENISE (Virtual & augmented ENvIronments for Simulation & Experiments) team under the condition of obtaining a PhD grant.

Different advances in hardware and software have allowed the accelerated and widespread use of Extended Reality (XR), including Virtual Reality and Mixed Reality, in several fields, one of them for educational purposes. There are ample documentation and literature reviews on immersive learning using XR and case studies confirming its application and progress, generally with positive results, but there are also challenges and promising future work to be done. Using XR technologies, the success of teaching strategies can be decided through a supportive teaching and learning environment to foster students' psychological wellbeing and mindfulness by stimulating their interest in subjects and encouraging active participation and cooperative learning. Moreover, it is highly important to examine the negative effects of technology on students' learning capability such as addiction to technology or short attention spans, which affect in-depth learning due to lack of concentration, patience, and reflection.
In this project we focus on students' attention and engagement in immersive learning situations. Existing works have been done to measure these factors before. For instance, Allcoat and von Mühlenen (2018) study how learning using Virtual Reality (VR) can affect the students' engagement and emotions, or Ryan and Poole (2018) on their satisfaction, engagement, recall, and retention. Regarding attention, different elements have been considered such as visual attention detected by eye-tracking technology for learning performance in VR. Other methods have started to explore data provided by position and orientation of the head, hands and feet, Electrodermal Activity (EDA) and Electrocardiogram (ECG) signals. However, fundamental and experimental studies are still needed in this domain, especially to measure objectively the attention and engagement factor in real time during individual learning activities as well as collective ones on different XR platforms and contexts.