A research paper exploring real-time cognitive load assessment using wearable devices has been withdrawn. The study aimed to analyze electroencephalogram (EEG) and heart rate variability (HRV) data to evaluate cognitive load in secondary vocational students. A random forest model achieved 97% accuracy in classifying cognitive load levels, and demonstrated cross-task transferability in a subsequent experiment. Despite its potential theoretical and practical significance for education, the paper was ultimately withdrawn by its author. AI
IMPACT This withdrawn research highlights the potential of AI in analyzing physiological signals for cognitive load assessment, though its impact is now limited.
RANK_REASON The cluster contains a withdrawn academic paper. [lever_c_demoted from research: ic=1 ai=1.0]
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