Results 11 to 20 of about 182,780 (313)
An Item Response Modeling Approach to Cognitive Load Measurement
Frontiers in Education, 2021 The accurate measurement of the cognitive load a learner encounters in a given task is critical to the understanding and application of Cognitive Load Theory (CLT).
John Fitzgerald Ehrich +3 more
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Measuring cognitive load [PDF]
Perspectives on Medical Education, 2018 None
John Sweller
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Cognitive-Load Theory: Methods to Manage Working Memory Load in the Learning of Complex Tasks
Current Directions in Psychological Science, 2020 Cognitive-load researchers attempt to engineer the instructional control of cognitive load by designing methods that substitute productive for unproductive cognitive load.
Fred Paas, Jeroen J G Van Merrienboer
exaly +1 more source
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
doaj +1 more source
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
openaire +3 more sources