E72 Embodiment in Action: Multimodal Analyses of the Dynamics Between Movement and Cognition (Short paper) learning by distributing cognitive load, enhancing meaning-making through action, and integrating social and spatial cues (Castro-Alonso et al., 2024; Zhong et al., 2023). Despite the growing body of work, most studies have focused on conceptual domains such as mathematics and physics focusing mainly on self-reports or performance outcomes. Much less is known about how embodiment supports procedural learning in professional contexts. Moreover, evidence for direct coupling between bodily engagement and cognitive processes remains limited. Previous studies often rely on performance outcomes or self-reports, while fewer examine real-time physiological and behavioral indices of cognitive effort (Lyu & Deng, 2024; Skulmowski & Rey, 2018). To address this need, the present study integrates multimodal measures that include motion tracking, eye tracking, and electrodermal activity (EDA). Using these synchronized data streams, we investigate how bodily engagement during a VR based learning within nursing professional context. This approach expands embodied learning research into procedural domains and highlights mechanisms through which movement may support cognitive processing. Research question How does bodily engagement during procedural learning impact the cognitive process, as evidenced by blink rate and EDA peaks? Methods Research design and procedure This study examined bodily and cognitive engagement during a VR simulation for nursing students. The simulation was designed to teach the medication administration process in a VR hospital environment. Students moved through the scenario, interacted with objects, and completed medication-related tasks independently. The present analysis focuses specifically on the procedural learning phase of the simulation, where students practiced actions such as drug preparation and administration. This phase demands real-time coordination of motor activity, attention, and decision-making.(Adler et al., 2025; Anderson, 2015). Participants and instruments A total of 37 sophomore nursing students enrolled in a four-year Bachelor of Nursing program at an Israeli university voluntarily participated in the study. Ethical approval was obtained from the university’s ethics committee (#0001776-7). All participants completed the learning session individually, and each student underwent the VR simulation once. To assess students’ cognitive dynamics, eye-tracking metrics, electrodermal activity (EDA), and real-time motion data were collected using the MediaPipe framework. Eye movement data were recorded using the Smart Eye Aurora eye-tracking system, integrated with the iMotions 10.1 biometric research platform to create a unified data collection environment. During the learning session, continuous gaze recordings were processed to identify blink rate, a physiological indicator used to reflect variations in cognitive load (Holland & Tarlow, 1972). The electrodermal activity (EDA) signal was continuously recorded using the Shimmer 3 wristband to capture both the skin conductance level and the rapidly changing phasic response
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