Abstract
Asynchronous virtual clinical simulations have emerged as a scalable component of modern nursing education, yet the absence of real-time instructor debriefing often leads to elevated extraneous cognitive load and sub-optimal clinical decision-making. This randomized controlled trial evaluated the efficacy of an automated multimodal feedback system designed to optimize cognitive load and improve performance during asynchronous virtual clinical simulations. A total of 124 undergraduate baccalaureate nursing students were randomly assigned to either an experimental group receiving real-time, automated multimodal feedback (integrated visual overlays, dynamic auditory prompts, and physiological telemetry cues) or a control group receiving standard end-of-simulation written text reports. Cognitive load was assessed immediately following the simulation using the Paas Cognitive Load Scale and the NASA-TLX instrument, while clinical performance was evaluated using a validated 25-point clinical decision-making rubric. The experimental group exhibited a statistically significant reduction in overall cognitive load (M = 4.12, SD = 0.88) compared to the control group (M = 6.45, SD = 1.02; p < .001, d = 2.44), driven primarily by reductions in extraneous load and frustration subscales. Concurrently, students receiving multimodal feedback achieved significantly higher clinical performance scores (M = 21.80, SD = 2.10) than control participants (M = 16.40, SD = 3.20; p < .001, d = 1.98). These findings demonstrate that automated, real-time multimodal scaffolding successfully mitigates extraneous cognitive friction in self-directed digital learning environments, thereby fostering germane processing and enhancing clinical competency acquisition.
