37 questions · 21 sources · 0 syntheses
Cognitive Science
The interdisciplinary study of mind and mental processes.
Source-derived questions
Questions extracted from the papers in this topic, excluding the curated questions above.
- How can connecting instructional design patterns with software architecture patterns reduce friction between learning content and its delivery system?
- How can deep neural network models serve as testable, end-to-end trainable implementations of cognitive theories?
- How can eye-tracking parameters be used to distinguish intrinsic, extraneous, and germane cognitive load as separate, continuous measures rather than a single total load signal?
- How can intrinsic and extraneous cognitive load be estimated from transcripts of real-world AI-assisted knowledge work?
- How can item-response theory be used to derive difficulty parameters that serve as a proxy for intrinsic cognitive load?
- How did Simon's work span economics, psychology, and cognitive science at once?
- How did leaning left or right on a Wii balance board affect participants' numerical estimates?
- How do removal and clustering, as two distinct abstraction operations over irrelevant details in symbolic explanations, differ in their effects on human understanding versus cognitive effort?
- How do subjects typically react when told they missed the gorilla in the video?
- How do the computational requirements that different tasks place on neural networks parallel cognitive load in human learners?
- How does AI-generated content usage compensate for cognitive load, and why is this compensation only partial?
- How does a learner's executive function capacity moderate whether they benefit from interleaved versus blocked instructional sequencing?
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- How does professional expertise moderate the relationship between cognitive load and performance benefits from AI assistance?
- How does the forgetting-reconstructive hypothesis explain the memory benefits of interleaved practice over blocked practice?
- How does the frontal cortex actively project face-like templates onto ambiguous visual noise?
- How does working memory capacity, measured via an operation span task, relate to eye movement patterns during learning under varying cognitive load conditions?
- How might personalized LLM tutoring affect cognitive load management for different student populations?
- How was ground-truth cognitive load established in the CLARE experiments, and how did the MATB-II task vary workload complexity across sessions?
- In what sense did Newell and Simon argue human problem-solving and computation are the same activity?
- What brain mechanism might explain why looking at a beautiful painting reduces pain intensity?
- What does scaling from principles and circuit models to complex end-to-end trainable systems reveal about how the brain manages information processing demands?
- What does the finding that clustering improves understanding while removal reduces cognitive effort imply for designing human-centered explanations from symbolic AI systems?
- What does the twin study suggest about how facial distinctiveness underpins recognizing your own face?
- What evidence links item difficulty values to existing theories of intrinsic versus extraneous cognitive load?
- What experimental methodology was used to measure participants' reasoning performance and extraneous cognitive load when classifying stimuli using ASP-derived explanations?
- What is inattentional blindness, and what does the gorilla study demonstrate about it?
- What is inhibitory spillover, and how does it explain the bladder-decision-making link?
- What is the physical symbol system hypothesis, and what does it claim about intelligence?
- What physiological and behavioral modalities does the CLARE dataset combine to capture real-time cognitive load, and why use multiple signal types together?
- What problem did Crick turn to studying after his work on DNA, in his later years at the Salk Institute?
- What was the setup of Simons and Chabris's invisible gorilla experiment?
- Why are self-report measures of cognitive load considered problematic, and what alternative does item difficulty offer?
- Why do CNN-based deep learning models outperform other approaches for binary cognitive load classification on this multimodal dataset?
- Why does having learners generate explanations for their reasoning improve learning outcomes, and how does this generation effect relate to germane cognitive load?
- Why does the eye get drawn to highlighted passages even when the highlighting is misplaced?
- Why has this finding faced replication difficulties in later studies?
- Why might studying a skill with no practical use reveal something about how the brain is architected?
Sources
- A Patterns Based Approach for Design of Educational Technologies
- CLARE: Cognitive Load Assessment in REaltime with Multimodal Data
- Deep Learning for Cognitive Neuroscience
- Difficulty as a Proxy for Measuring Intrinsic Cognitive Load Item
- Precision Proactivity: Measuring Cognitive Load in Real-World AI-Assisted Work
- The Dual Role of Abstracting over the Irrelevant in Symbolic Explanations: Cognitive Effort vs. Understanding
- The Life Cycle of Large Language Models: A Review of Biases in Education
- The Role of Executive Function in Interleaved vs Blocked Learning of Science Concepts
- Use of Eye-Tracking Technology to Investigate Cognitive Load Theory
- Using Large Language Models to Provide Explanatory Feedback to Human Tutors
- ACM A.M. Turing Award
- Death of Francis Crick