Physiological responses in individual and cooperative learning using VR

Aim: Virtual reality (VR) is increasingly being utilized in nursing education, but previous studies often report subjective evaluations based on individual learning. While cooperative learning is gaining attention as one form of active learning, the learning effects of VR have not been clearly established. Therefore, this study aims to explore differences between individual and cooperative learning using VR through composite indicators, including physiological responses.
Method: Thirteen nursing students were assigned to either an individual learning group (n=5) or a cooperative learning group (n=8; divided into two groups of four, with one student in each group performing physiological data measurements). Using immersive VR educational materials (theme: “The Lives of Elderly in the Community”), measurements were taken across four phases: rest, VR viewing, individual work, and group work. Changes in electroencephalogram (F3 and F4, β percentage normalized to open-eye rest) and electrocardiogram (LF/HF, sympathovagal balance from heart rate variability) patterns at four phases were compared between the individual learning group and the collaborative learning group. The SSQ scores were calculated as the overall score. Descriptive data from worksheets were recorded during both individual and group work and subjected to content analysis.
Result: The β increased in both groups during VR viewing, and was particularly high in the individual learning group. The LF/HF tended to fluctuate across phases within the cooperative learning group. The SSQ scores were mild for nearly all participants. In the worksheets, descriptions of learning from a broader perspective were more common in the cooperative learning groups than in the individual learning groups.
Conclusion: This exploratory data suggests that VR learning and subsequent group work may promote brain activation, and that cognitive load and emotional responses may differ between individual and cooperative learning. While these results cannot be generalized, examining multiple indicators together may help clarify learning outcomes.

Mami Fukushige is an assistant professor at the Faculty of Life Sciences, Kumamoto University. She has approximately 10 years of clinical experience in healthcare settings and has since been engaged in education and research at educational institutions. She completed a master's program in nursing education and a doctoral program in public health.