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Measuring cognitive load [PDF]
Perspectives on Medical Education, 2018 None
John Sweller
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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
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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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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
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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
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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
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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.
Paul A. Kirschner +3 more
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Cognitive Load in Economic Decisions [PDF]
SSRN Electronic Journal, 2020 Intuitive decision making has a large and often negative impact in economic decisions, but its measurement and quantification remains challenging. Following research from psychology, behavioral economists have often attempted to causally manipulate the balance of intuition and deliberation by relying on experimental manipulations as cognitive load ...
Achtziger, Anja +2 more
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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 +3 more
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Brain Sciences, 2022 Cognitive load significantly influences learning effectiveness. All the three types of cognitive load—intrinsic, extraneous, and germane—are important for guiding teachers in preparing effective instructional designs for students. However, the techniques
Chao-Chih Wang +2 more
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