Identification of Mechanisms and Biomarkers of Learning Efficiency Based on Multimodal Data

In today’s rapidly evolving world, the ability to efficiently learn and process new information is increasingly crucial. This study aims to identify mechanisms and biomarkers of learning efficiency using multimodal data. We designed and conducted a neurophysiological experiment simulating educational activities over two days with 26 participants aged 18 to 30. Behavioral data such as memory time-the interval from stimulus presentation to participant response-were analyzed to understand cognitive processes during learning. Participants underwent the Multidimensional Fatigue Inventory (MFI-20) test to assess their psychophysiological state before and after the experiment. Our findings reveal a statistically significant decrease in performance $50-60$ minutes after presenting new information, aligning with Ebbinghaus’s forgetting curve. This suggests that unfamiliar information not properly assimilated within this time frame does not enter long-term memory. The results underscore the importance of reviewing new information shortly after learning to enhance retention. By identifying key behavioral markers and understanding their impact on learning efficiency, this study contributes to the development of intelligent expert systems that optimize educational activities based on individual psychophysiological characteristics.