From movement to learning: Leveraging VR behavioral metrics to evaluate cognitive load and curiosity

Virtual Reality (VR) is increasingly used in education due to its immersive and interactive capabilities, but its impact on cognitive load and curiosity remains underexplored, particularly regarding real-time behavioral indicators of cognitive load and curiosity. This study investigates how VR behavioral metrics, specifically hand and head movement patterns, can serve as objective, synchronous indicators of cognitive engagement and intrinsic motivation. A controlled experiment was conducted with 125 medical students, who engaged in a neuroanatomy learning task within a VR environment featuring varying levels of interactivity. Behavioral data, including movement entropy, exploration patterns, and gesture dynamics, were analyzed in relation to self-reported measures of cognitive load, motivation, and engagement. Results indicate that while greater hand movement was associated with lower intrinsic motivation, higher head movement correlated positively with germane cognitive load and intrinsic motivation, implying deeper cognitive engagement. Additionally, movement entropy emerged as a predictor of curiosity-driven learning, suggesting its potential as an indicator of learning behaviors in VR environments. These findings contribute to a better understanding of how behavioral data can complement traditional assessments of learning experiences in VR. They also highlight the need for further research into integrating movement-based metrics with instructional design to support engagement and learning.