Uncovering the mechanisms of virtual reality (VR)-enhanced neuroscience education: the role of eye tracking and facial expression recognition

Virtual reality (VR) has demonstrated substantial advantages in neuroscience education, consistently outperforming traditional instructional approaches in enhancing spatial understanding, knowledge retention, and learner engagement. However, despite this robust evidence of effectiveness, most existing studies remain primarily outcome-oriented, focusing on what learners achieve over how learning processes occur within immersive VR environments. Consequently, the cognitive and affective mechanisms that mediate VR-enhanced learning outcomes remain underexplored. This mini-review synthesizes current evidence on the integration of biometric sensing technologies—specifically eye tracking and facial expression recognition—in VR-based neuroscience education to elucidate the cognitive and affective processes. We examine how eye tracking provides objective indicators of visual attention and cognitive load, while facial expression analysis captures affective states such as curiosity and frustration. The integration of this multimodal data offers a holistic framework to understand the interplay between immersion, attention, and emotion in knowledge acquisition. Furthermore, we discuss significant technical and ethical challenges, including data synchronization, privacy, and measurement reliability. Finally, we outline future directions, emphasizing the potential for artificial intelligence (AI) to create adaptive VR learning systems that respond in real-time to learner biomarkers. This approach lays the groundwork for more mechanism-informed and evidence-aligned design of adaptive XR learning environments.”