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Measuring cognitive load [PDF]

Perspectives on Medical Education, 2018
None
John Sweller
doaj   +3 more sources

Cognitive Load in Pediatric Critical Care Medicine: Tsunamis and a Thousand Cuts [PDF]

Critical Care Explorations
IMPORTANCE:. Excessive cognitive load impairs task performance and contributes to burnout, but studies of cognitive load in pediatric critical care medicine (PCCM) settings are limited. OBJECTIVES:. To better understand cognitive load in an academic PCCM
Daniel E. Ehrmann, MD, MS, FABP, Sara N. Gallant, PhD, Sunkyung Yu, MS, Danny Eytan, MD, PhD, Elaine Gilfoyle, MD, FRCPC, Azadeh Assadi, PhD, Seth Gray, MD, FABP, Oshri Zaulan, MD, FRCPC, Mjaye Mazwi, MBChB, FABP   +8 more
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Examining the Size of the Latent Space of Convolutional Variational Autoencoders Trained With Spectral Topographic Maps of EEG Frequency Bands

IEEE Access, 2022
Dimensionality reduction and the automatic learning of key features from electroencephalographic (EEG) signals have always been challenging tasks. Variational autoencoders (VAEs) have been used for EEG data generation and augmentation, denoising, and ...
Taufique Ahmed, Luca Longo
doaj   +1 more source

Explaining Deep Q-Learning Experience Replay with SHapley Additive exPlanations

Machine Learning and Knowledge Extraction, 2023
Reinforcement Learning (RL) has shown promise in optimizing complex control and decision-making processes but Deep Reinforcement Learning (DRL) lacks interpretability, limiting its adoption in regulated sectors like manufacturing, finance, and healthcare.
Robert S. Sullivan, Luca Longo
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Interpreting Disentangled Representations of Person-Specific Convolutional Variational Autoencoders of Spatially Preserving EEG Topographic Maps via Clustering and Visual Plausibility

Information, 2023
Dimensionality reduction and producing simple representations of electroencephalography (EEG) signals are challenging problems. Variational autoencoders (VAEs) have been employed for EEG data creation, augmentation, and automatic feature extraction.
Taufique Ahmed, Luca Longo
doaj   +1 more source

On the Dimensionality and Utility of Convolutional Autoencoder’s Latent Space Trained with Topology-Preserving Spectral EEG Head-Maps

Machine Learning and Knowledge Extraction, 2022
Electroencephalography (EEG) signals can be analyzed in the temporal, spatial, or frequency domains. Noise and artifacts during the data acquisition phase contaminate these signals adding difficulties in their analysis.
Arjun Vinayak Chikkankod, Luca Longo
doaj   +1 more source

Modeling Cognitive Load as a Self-Supervised Brain Rate with Electroencephalography and Deep Learning

Brain Sciences, 2022
The principal reason for measuring mental workload is to quantify the cognitive cost of performing tasks to predict human performance. Unfortunately, a method for assessing mental workload that has general applicability does not exist yet. This is due to
Luca Longo
doaj   +1 more source

From Cognitive Load Theory to Collaborative Cognitive Load Theory [PDF]

International Journal of Computer-Supported Collaborative Learning, 2018
Cognitive load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, particularly the relations between working memory and long-term memory, the theory has been used to generate a variety of instructional effects.
Kirschner, Paul A., Sweller, John, Kirschner, Femke, Zambrano, Jimmy R.   +3 more
openaire   +4 more sources

Cognitive load promotes honesty

Psychological Research, 2022
AbstractIn three experiments, we examined the cognitive underpinnings of self-serving dishonesty by manipulating cognitive load under different incentive structures. Participants could increase a financial bonus by misreporting outcomes of private die rolls without any risk of detection.
Moritz Reis, Roland Pfister, Anna Foerster   +2 more
openaire   +3 more sources

Human Mental Workload: A Survey and a Novel Inclusive Definition

Frontiers in Psychology, 2022
Human mental workload is arguably the most invoked multidimensional construct in Human Factors and Ergonomics, getting momentum also in Neuroscience and Neuroergonomics.
Luca Longo, Christopher D. Wickens, Gabriella Hancock, P. A. Hancock   +3 more
doaj   +1 more source